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African Journal of
Business Management
Volume 5 Number 17 4 September 2011
ISSN 1993-8233

ABOUT AJBM
The African Journal of Business Management (AJBM) is published weekly (one volume per year) by Academic
Journals.
African Journal of Business Management (AJBM) is an open access journal that publish research analysis and
inquiry into issues of importance to the business community. Articles in AJBM examine emerging trends and
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Editors
Prof. Wilfred Isioma Ukpere
Department of Industrial Psychology and People
Management,
Faculty of Management,
University of Johannesburg,
South Africa.
Prof. Gazi Mahabubul Alam
Department of Educational Management,
Planning and Policy,
Faculty of Education Building,
University of Malaya, 50603 Kuala Lumpur,
Malaysia.
Dr. Olawale Olufunso Fatoki
University of Fort Hare
Department of Business Management,
University of Fort Hare, x1314, Alice, 5700, Eastern
Cape, South Africa
Dr. Amran Awang
Faculty of Business Management, 02600 Arau,
Perlis, Malaysia
Dr. Giurca Vasilescu Laura
University of Craiova, Romania
13, A.I. Cuza, 200585, Craiova, Dolj,
Romania.
Prof. Himanshu Tandon
VIT Business School,
VIT University,
Vellore 632014 (India)
Dr. Ilse Botha
University of Johannesburg
APK Campus PO Box 524 Aucklandpark 2006
South Africa.
Dr. Howard Qi
Michigan Technological University
1400 Townsend Dr., Houghton, MI 49931,
U.S.A.
Dr. Aktham AlMaghaireh
United Arab Emirates University
Department of Economics & Finance
United Arab Emirates.
Dr. Haretsebe Manwa
University of Botswana
Faculty of Business
University of Botswana
P.O. Box UB 70478
Gaborone Botswana.
Dr. Reza Gharoie Ahangar
Islamic Azad University of Babol,
Iran
Dr. Sérgio Dominique Ferreira
Polytechnic Institute of Cavado and Ave
Campus IPCA, Lugar do Aldão, 4750-810. Vila
Frescainha,
Portugal.
Dr. Ravinder Rena
Polytechnic of Namibia,
Private Bag:13388 Harold Pupkewitz Graduate School
of Business; Windhoek,
Namibia.
Dr. Shun-Chung Lee
Taiwan Institute of Economic Research
No. 16-8, Dehuei Street, Jhongshan District, Taipei
City 104,
Taiwan.
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National Taipei University of Nursing and Health
Sciences No. 365, Min-Te Road, Taipei,
Taiwan.
Dr. Gregory J. Davids
University of the Western Cape
Private Bag x17, Bellville 7535,
South Africa.
Prof. Victor Dragotă
Bucharest Academy of Economic Studies, Department
of Finance
Bucharest, Sector 1, Piata Romana no. 6, Room 1104,
Romania
Dr. Ling-Yun HE
College of Economics and Management,
China Agricultural University
(East Campus), Qinghua Donglu street, Haidian
district,
Beijing 100083, China
Dr. Maurice Oscar Dassah
School of Management, IT and Governance
University of KwaZulu-Natal
Post Office Box X54001
Durban
4000
South Africa.

Editorial Board
Dr. Peide Liu
Business Administration School,
Shandong Economic University, China
Dr. Marwan Mustafa Shammot
King Saud University, P.O.Box 28095 ,
Riyadh 11437
Kingdom of Saudi Arabia.
Dr. Hela Miniaoui
University of Wollongong in Dubai,
Knowledge Village, Block 15 PoBox 20183,Dubai
UAE
Dr. Suhanya Aravamudhan
6965 Cumberland Gap Pkwy, Harrogate, TN
USA
Dr. Hooman Attar
Amirkabir University of Technology
Iran
Prof. Luis Antonio Fonseca Mendes
University of Beira Interior –
Business and Economics Department -
Estrada do Sineiro – Polo IV – 6200-209 Covilhã
Portugal
Dr. Wu, Hung-Yi
Department of Business Administration
Graduate Institute of Business Administration
National Chiayi University No.580, Xinmin Rd., Chiayi City
60054, Taiwan (R.O.C.)
Dr. Shu-Fang Luo
No.28, Da-Ye S. Road, Lin-Hai Industrial Park,
Hsiao-Kang, 812, Kaohsiung City
Taiwan
Dr. Ahmad.M.A.Ahmad Zamil
King Saud University, P.O.Box 28095 ,
Riyadh 11437
Kingdom of Saudi Arabia
Dr. Paloma Bernal Turnes
Universidad Rey Juan Carlos
Dpto. Economía de la Empresa
Pº de los Artilleros s/n
Edif. Departamental, Desp. 2101
28032 Madrid, España
Dr. Mario Javier Donate-Manzanares
Facultad de Derecho y Ciencias Sociales Ronda de Toledo,
s/n 13071 Ciudad Real
Spain
Dr. Mohamed Abd El Naby Mohamed Sallam
Faculty of Commerce -
University of Kafr El-Sheikh
Egypt
Dr. Guowei Hua
NO. 3 Shangyuancun, Haidian District, Beijing 100044,
School of Economics and Management, Beijing Jiaotong
University,
China.
Dr. Mehdi Toloo
No. 136, Forsate Shirazi st., Islamic Azad University, Central
Tehran Branch, Tehran, P. O. Box 13185.768.
Iran.
Dr. Surendar Singh
Department of Management Studies, Invertis University
Invertis village, Bareilly - Lucknow Highway,
N.H.-24, Bareilly (U.P.) 243 123
India.
Dr. Nebojsa Pavlovic
High school “Djura Jaksic”
Trska bb, 34210 Raca,
Serbia.
Dr. Colin J. Butler
University of Greenwich
Business School, University of Greenwich, Greenwich, SE10
9LS,
London, UK.
Prof. Dev Tewari
School of Economics and Finance
Westville Campus
University of Kwa-Zulu Natal (UKZN)
Durban, 4001
South Africa.
Dr. Olof Wahlberg
Mid Sweden University,
851 70 Sundsvall
Sweden

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African Journal of Business Management
International Journal of Medicine and Medical Sciences
Table of Contents: Volume 5 Number 17 4 September, 2011
ences
Review
ARTICLES
A logistic study of the Brazilian airport model and its employment at the
Tancredo Neves International Airport 7165
Tadeu Hugo Ferreira Braga and Silva Jersone Tasso Moreira
Understanding and approaching the cultural gap between First World
leaders and their Third World workforce: An African focus 7171
Chuen Tse Kuah and Kuan Yew Wong
TQM, role stressors and counterproductive behaviour: A proposed
framework on strain reduction 7179
Julian Hong-Leong Teh and Shwu-Shing Ng
A survey of empirical studies on management ownership 7188
Mahdi Salehi and Bahram Baezegar
Research Articles
The commercialisation process of patents by universities 7198
Kamariah Ismail, Wan Zaidi Wan Omar and Izaidin Abdul Majid
A note on “A mixed integer programming formulation for multi floor
layout”[African Journal of Business Management 3 (2009) 616-620] 7209
Krishna k. Krishnan and Amir Ardestani Jaafari

Table of Contents: Volume 5 Number 17 4 September, 2011
ences
ARTICLES
A phenomenographic study investigating consumers’ conceptions of
marketing in Taiwan 7216
Hung-Ming Lin
Diffusion of Internet Protocol Television (IPTV) service demands: An
empirical study in the Serbian market 7224
Valentina Radojicic, Bojan Bakmaz and Goran Markovic
Cause-related marketing and consumer behaviour in the greater e
Thekweni area 7232
Karen M. Corbishley and Roger B. Mason
Supply chain management: success factors from the Malaysian
manufacturer’s perspective 7240
Ai Chin Thoo, Hon Tat Huam, Rosman Md Yusoff, Amran Md Rasli,
Abu Bakar Abd Hamid
Dimensions of information technology infrastructure flexibility in
improving management efficacy of construction industry perspective:
A conceptual study 7248
Nurshuhada Zainon and Hafez Salleh
Locus of control and readiness to conjure and believe in mystical powers
among small business operators in Entebbe, Uganda: A multilevel
rasch rating scale model analysis 7258
Aloyce R. Kaliba, Robert Isabalija, Victor W. Mbarika, Mathieu K.
Kourouma, Carlos Thomas, Moya M. Bukoma, Wilson M. Mande,
Mohammed Ndifuna and Akodo Robinah

Table of Contents: Volume 5 Number 17 4 September, 2011
ences
ARTICLES
An evaluation of the investors overreaction to the past financial
function criteria: Iranian evidence 7284
Mehdi Moradi, Mahdi Salehi and Afshin Hasanzadehnamaghi
Optimal pricing for internet service providers: Fuzzy geometric
programming model 7291
S. J. Sadjadi, A. Yousefli and R. Ghezelsoflou
Perceptual gap and anatomy of investment risk decisions 7296
Nidhi Walia and Ravi Kiran
Earnings management and the auditing value in China 7306
Yi-Pei Liu and Yu-Shu Cheng
Impact of organizational commitment on job satisfaction and employee
retention in pharmaceutical industry 7316
Atif Anis, Kashif-ur-Rehman, Ijaz-Ur-Rehman, Muhammad Asif Khan and
Asad Afzal Humayoun
Optimal order quantity under advance sales and permissible delays in
payments 7325
Mei-Liang Chen and Mei-Chuan Cheng
The students’ degree of preference for residence hall facilities and
amenities, study of a developing country 7335
Fatemeh Khozaei, Ahmad Sanusi Hassan and T Ramayah
An empirical study on factors that affect the transition time between
capability maturity model integration (CMMI) levels in Saudi Arabia 7342
Fahad H. Alshammari and Rodina Ahmad

Table of Contents: Volume 5 Number 17 4 September, 2011
ences
ARTICLES
On the exchange rates behavior by PPP: A test on Malaysian ringgit and
US dollar 7350
Farhad Pourkalbassi, Alireza Bahiraie, Aishah Hamzah and Lee Chin
The Effect of tourism web page design on browser's attitude and visit
intention 7357
Yu-Shan Lin
Evaluation of corporate social responsibility performance standards 7367
Grigoris Giannarakis, and Nikolaos Litinas, Nikolaos Sariannidis
Integrating codesign into new product innovation: Consumer-driven
online game optiomization design 7375
Chi-Shun Liao
Measuring the impact of multiplier, to determine the Keynesian model
of income, in open economy, in the context of Pakistan 7385
Naveed Iqbal Syed, Muhammad Sohail Tahir and Shamim A. Sahibzada
Transformational leadership, employee engagement and performance:
Mediating effect of psychological ownership 7391
Azka Ghafoor, Tahir Masood Qureshi, M. Aslam Khan and Syed Tahir Hijazi
Financial competitiveness evaluation on sporting goods listed enterprises:
A China study 7404
Feng Ran and Xiaoling Zhang
A (data envelopment analysis) DEA-based systematic approach for
selection of strategic alliance candidates: Case by the biotechnology
industry 7410
Chia-Nan Wang and Chih-Hong Wang

Table of Contents: Volume 5 Number 17 4 September, 2011
ences
ARTICLES
Technology portfolio modeling in hybrid environment 7420
Sattari Ardabili, Farzad
Analyzing performance of investment companies listed in the Tehran
stock exchange by selected ratios and measures 7428
Reza Tehrani, Hamed Ahmadinia and Amaneh Hasbaei
To the promotion of work life quality using the paradigm of managerial
coaching: The role of managerial coaching on the quality of work life 7340
Seyed Ali Akbar Ahmadi , Najmeh Jalalian, Yashar Salamzadeh,
Mohammadreza daraei and Azam Tadayon
The effects of Iranian consumers’ buying tendencies on utilitarian and
hedonic shopping value 7349
Neda Irani and Kambiz Heidarzadeh Hanzaee
The perceived service quality, satisfaction and behavioural intent towards
cellphone network service providers: A generational perspective 7361
D. J. Petzer and C. F. De Meyer
Value at risk: Evidence from Pakistan Stock Exchange 7474
Faisal Nawaz and Muhammad Afzal
Entrepreneurial motivation as a determinant of South American firm
consolidation 7481
Agustin Álvarez-Herranz and Pilar Valencia-De Lara
An empirical study on the causes of business failure in Iranian context 7488
Zahra Arasti

Table of Contents: Volume 5 Number 17 4 September, 2011
ences
ARTICLES
Using greedy clustering method to solve capacitated location-routing
problem 7499
Ali Nadizadeh, Rashed Sahraeian, Ali Sabzevari Zadeh and Seyed
Mahdi Homayouni
The relationship between cultural intelligence and group effectiveness
in Mobarakeh steel company 7507
A. Khani, A. Etebarian and M. Abzari
Factors of cross-buying intention - bancassurance evidence 7511
Chiang Ku Fan, Li-Tze Lee, Yu-Chieh Tang and Yu Hsuang Lee
Ownership structure and dividend policy: Evidence from Iran 7516
Sasan Mehrani, Mohammad Moradi and Hoda Eskandar
Exploring the efficiency of international tourism development in an
emerging market 7526
Meng-Chun Kao, Che-Yang Lin, Mei-Chi Lai and Hao-Chen Huang
Is Moral Intensity Applicable to Natural Environment Issues? 7533
Chieh-Wen Sheng and Ming-Chia Chen
Impact of locus of control, changes in work load and career prospects on
organizational commitment of employees of life insurance companies
during merger and acquisition 7542
Chiewei Hung and Ker-Tah Hsu
Improving supply chain performance: The strategic integration of lean
and agile supply chain 7557
Seyyed Ali Banihashemi

Why firms do not adopt SaaS
Table of Contents: Volume 5 Number 17 4 September, 2011
ences
ARTICLES
Does proactive green logistics management improve business
performance? A case of Chinese logistics enterprises 7564
Yongrok Choi and Ning Zhang
The influence of the emotional intelligence on self monitoring 7575
Sandhya Rani C., R. G. Priyadharshini and T. Kannadasan
Applying the extended theory of planned behavior to predict the
intention of visiting a green hotel 7579
Kun-Shan, Wu and Yi-Man Teng
Role of rural production cooperatives in developing non-oil exports of
West Azerbaijan province, Iran 7588
Farhad Lashgarara and Nina Shaddeli
Behavioral approach to portfolio selection: The case of Tehran Stock
Exchange as emerging market 7593
Farshad Heybati, Freydoon Rahnamay Roodposhti and Seyed Reza Moosavi
The functional relationship between mentoring relationship, employee
development and organisational success 7603
Jan Visagie and Gideon J. Kruger
Consumers’ attitudes towards different product category of private labels 7616
Shih Jung Wang and Lily Shui-Lien Chen
The determinants of board size and composition: Evidence from Taiwan
banks 7622
Pi-Hui Ting

Table of Contents: Volume 5 Number 17 4 September, 2011
ences
ARTICLES
Monetary union for the development process in the East African
community: Business cycle synchronization approach 7632
Kamaludin Ahmed Sheikh, Mohammad Nurul Azam, Talukder Golam Rabby,
Gazi Mahabubul Alam, and Issa Khan
Open business models: A case study of system-on-a-chip (SoC) design
foundry in the integrated circuit (IC) industry 7642
Po-Young Chu and Wan-Chen Chen
Firm characteristics and voluntary disclosure of graphs in annual reports
of Turkish listed companies 7651
Ali Uyar
How after-sales service quality dimensions affect customer satisfaction 7658
Alireza Fazlzadeh, Fatemeh Bagherzadeh and Pegah Mohamadi
An empirical investigation into the extent of customer satisfaction and
customer loyalty at big retail stores in King William’s Town, South Africa 7665
Tafadzwa Machirori and Olawale Fatoki
Identifying the challenges related to policymaking institutions for
entrepreneurship formal education in Iran 7674
Mohammad Hossein Rahmati, Hossein Khanifar, and Seyed Mohammad
Moghimi
Understanding the mediating effect of cognitive and emotional satisfaction
on customer loyalty 7683
Maznah Wan Omar, Mohd Rizaimy Shaharudin, Kamaruzaman Jusoff, and
Mohd Noor Mohd Ali,

African Journal of Business Management Vol. 5(17), pp. 7165-7170, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM10.291
ISSN 1993-8233 ©2011 Academic Journals
Review
A logistic study of the Brazilian airport model and its
employment at the Tancredo Neves International
Airport
Tadeu Hugo Ferreira Braga 1 and Silva Jersone Tasso Moreira 2 *
1 Pontifícia Universidade Católica de Minas Gerais, Avenida Dom José Gaspar, 500, Prédio 03, Sala 114, Coração
Eucarístico, Belo Horizonte, Minas Gerais, Brazil, 30.535-091.
2 Universidade FUMEC, Avenida Afonso Penna, 3880, 1º Andar, Bairro Cruzeiro, Belo Horizonte, Minas Gerais, Brazil,
30.130-190.
Accepted 12 July, 2010
The objective of this article is the logistic study about the Brazilian Airport Model, justifying its
importance and the impediments to the segment’s development, especially with regards to the cargo
movement. As development, it is possible to evaluate the differences between the concepts of an
industrial airport and the airport-cities, as complementary requirements to the national development. As
a case study, the Tancredo Neves International Airport (TNIA) in Belo Horizonte, in the State of Minas
Gerais, is presented as an example for the development of the sector and its conceptual evolution, with
proposals for its operations.
Key words: Brazilian Airport Model, industrial airport, airport-cities, economic development.
INTRODUCTION
The aviation sector and the Brazilian economy demand
higher flights. The growth of air cargo is estimated at
6.1% a year for the two next decades, which will consume
more aircrafts and will demand an adequate
infrastructure for the airport terminal segment.
According to the studies that were carried out by the
Operation Studies Nucleus, of the “Escola de Governo
Professor Paulo Neves de Carvalho”, and of the
“Fundação João Pinheiro”, using the Anac’s data (2009),
the airfreight sector transports 40% of the economic value
of cargos in the world, which represents 8% of its total
weight. This means that products with high aggre-gated
value are transported in this sector.
Despite the merchandise’s distribution in Brazil, the international
commerce is centralized on the sea transport
modal, with 92% of the cargo’s activities going through
ports; would this be the future of the transport sector? It is
possible to observe this with the production tendency in
adopting the flow of technology, instead of following
*Corresponding author. E-mail: tasso@fumec.br. Tel: (55) (31)
3269-5230. Fax: (55) (31) 3269-5231.
the low aggregated value industrial model.
It is possible to say that the world is going towards
logistic models, with the production accomplished according
to the consumer’s demands, adopting sophisticated
sale’s prediction methods, which confirms the existence
of a new supply chain model (Tadeu, 2008). An example
would be the productive capacity of the technology
companies, from the moment that material resources’
purchase is confirmed in any part of the world. Starting at
this stage, it is possible to verify the existence of stocks
for production, usually put available by the suppliers. You
cannot justify storage of high value resources, to avoid
losses and diminish risks (Bowersox, 2001).
However, these companies’ production is decentralized
and globalized, in order to take advantage of free trade
areas; this is allied to the good economical performance
around the world and the outsourcing aspects.
In this scenario, the airport is fundamental. The speed
of the cargo’s movement leads the companies to choose
this modality; they make themselves more agile in the
business and increase their profit.
According to the World Air Cargo Forecast (2007 to
2008), a study that was made by the Boeing aircraft
manufacture (2008), the sector should be worried with

7166 Afr. J. Bus. Manage.
the high prices of fuel that in average, represents 30% of
the aviation’s costs, with an agio of 42% in 2008 for the
world’s market. Even with this problem, the report shows
that cargo air companies registered a growth of 3.1%
during this period and a growth forecast of today’s 1,780
cargo aircrafts to 3,500 in 2025.
In this scenario, the United States of America represents
the largest market, with 28% of cargo movement
done by air. However, Asia will contribute to the fast
growth of this segment, due to the economic growth of
10% a year in China. The question to ask is: what about
the Brazilian aviation market? What are its operational
characteristics?
THE BRAZILIAN AVIATION MARKET’S PANORAMA
The Brazilian aviation market has its own particularities.
Since 2005, Vasp stopped flying when its license was
cancelled by the Civil Aviation Department (DAC), the
former inspection agency, which was substituted by the
Anac. The motives were related to the lack of payment to
the suppliers, their operational high cost and the low
occupation level in the planes of their flying routes.
Varig, the most traditional company in this segment in
Brazil, was subdivided into several business groups, as
result of their high level of debts. The maintenance division
was sold to the Portuguese TAP, while the Variglog,
their cargo subsidiary, was sold to a North-American
investment fund for US $ 100 million. The Varig brand
that flew passengers, was bought by the Áurea Group
(owner of Gol Intelligent Airway). The size of the old Varig
can be summarized in a debt of R $ 7.7 billion to
suppliers, debts with the Central Bank, Infraero, DAC and
tax debits. The other US $ 70 million were with reference
to aircraft leasing (Anac, 2009).
For sometime, it was cogitated the union between Varig
and TAM, with the help of the Brazilian govern-ment and
the contribution of US $ 1.8 million so that the company,
then with its headquarters in the State of Rio Grande do
Sul, could pay its debts and avoid bankruptcy.
When Gol Intelligent Airways entered the sector, the
attention of the aviation specialists were directed to the
low cost, low fares model that were implemented be the
company in Brazil. With a modern fleet consisting of
Boeing 737 family aircrafts, the company used a logistic
model of high permanency of its airplanes in the air, with
less time on the ground and with simpler board services
than the competitors, which enabled them to reduce their
fare prices. The result is that today, their domestic market
share is 40%.
Historically, the aviation market has had strong negative
impacts due to heterodox economic plans, such as
fare price freezing during the “Cruzado” Plan and the high
cost of aviation kerosene, supplied exclusively by
Petrobras. These factors caused Transbrasil’s bankruptcy
that, since 2001, opted to withdraw from the market. The
company left a debt of R $ 1 billion, mainly with its fuel
suppliers.
Not so long ago, Ocean Air, now called Avianca, tried to
bring Transbrasil back to life, with the idea of transforming
it into a cargo company, but this idea was not
approved by the federal government. Ocean Air, itself,
carried out a dismissal program of 600 employees, which
was motivated by the increase of the fuel’s prices, resulting
in the interruption of its expansion plan in 2008.
The government’s actions in the aviation market are
linked to the approval of the bankruptcy law, allowing the
companies of this segment to discount their losses, as the
result of economical plans in the past, until the bankruptcy
is declared.
Since January of 2009, the newly named, Azul, en-tered
the national market. It is an enterprise that belongs to the
businessman David Neelman (one of the ex-controllers of
the north-American Jetblue, the creator of low costs, low
fare in the world), with the support of national and
international banks that are interested in the growth of the
Brazilian airfreight sector.
In spite of all the data that was mentioned before, the
perspectives for the aviation sector are positive. Most of
the aircraft manufacturing companies, among them
Boeing, Airbus and Embraer, have been producing new
models as an answer to the airline companies’ demand.
Data from Iata (2008) shows that, in this year’s first
semester, there was a growth of 9.4% in the occupancy
rate, with an average of 74% and a possible growth of
14.9% in the numbers of flights in Latin America. This fact
can be proved by the operation of new international
flights, for example, that are flying out of the city of Belo
Horizonte, in the State of Minas Gerais, to the following
destinations: Portugal, with connections to other localities
in the European Union (Lisbon – TAP); United States of
America (Miami – American Airlines); Panama, with
connections to North America, Central America and other
destinations (Panama – Copa Airlines).
Air cargo transport
When evaluating the cargo transport sector, it is possible
to understand that Brazil has a network of services and
companies that are focused on this segment, with the
participation of national and international companies.
According to data from Boeing (2008), the Brazilian
market will follow the tendency of the world’s market, with
expected growth.
In spite of the expectations, there is a necessity to solve
the existing problems. Data from the Ipea (2010) shows
that, the Brazilian economy grew with 0.4% in 2009, which
represents a higher value of the Real and the devaluation
of the dollar’s quotation. Data from the Banco Central
Bank (2010) indicates the existence a check account
deficit, due to the facilities in the quotation of the national
currency, in the import of capital assets, In
detriment to exporting. The ideal would be to have a
balance between the Real and the dollar, in order to

stimulate the international commerce. The impact is
found in the small exporter, which has difficulty in
accessing international markets and the air freight modal.
Another negative aspect is the interruption of the
Federal Fiscal Revenue services that in the last years,
has stopped its activities, in average, one hundred days a
year, causing delays and incalculable losses to the
companies in the international commerce segment.
According to Infraero’s data (2009), the total of cargo
transported during 2008 was of 185 thousand tons, being
that before the end of 2009, the volume that was registered
reached the total amount of 210 thousand tons.
This increase should be credited to the importation of
machinery and products with aggregated value, besides
the diversification of destines and products, such as the
milk by-products (powder milk), hay, electric-electronic
products, machines and other kinds of equipment,
automobile products, medicines, among others.
International companies
The international companies that operate in the national
territory carry out their operations mixing passenger
transport with the idleness of their cargo holds, in the
flights between countries and by companies that are only
dedicated to cargo movement, according to the Anac
(2009).
As a company that does not have aircraft specifically
used for cargo transport, American Airlines transported to
Brazil in 2008, 42 thousand tons, offering a volume of 2.6
million cubic meters in the whole world. Only the
company’s cargo division has three thousand employees
in the world, having received the title of year’s best airline
company in the world, according to the Logistic and Rapid
Delivery Association, during the annual Con-ference of Air
Freight of 2008, in Orlando, Florida, in the United States
of America. The company uses the Boeing models 777
and 767-300, with daily flights flying out of Guarulhos and
with road connections to cities, such as, Belo Horizonte,
Campinas, Curitiba, Florianópolis and Porto Alegre, flying
to New York (John Kennedy Airport), Dallas and Miami.
Among the companies that are dedicated to
transporting cargo, FedEx has been in Brazil since 1990,
concentrating its operations in the Viracopos Airport, in
Campinas. It has about 600 employees and five weekly
flights to Memphis and Tennessee, both in the United
States of America.
Another company that works in Brazil is UPS. They
started their operation in 1989, through third parties, only
having its own address in São Paulo in 1995. Flying out of
Viracopos Airport, the company flies to 500 destines
around the world, with a gross billing of US $ 47 billion
worldwide.
An important player of this segment is the German
Lufthansa, which has been present in Brazil since 1956.
One of the programs with the best results in this segment
Braga and Moreira 7167
is the Business Partnership Program, created by the
company by dividing the cargos, with the intention of
achieving partnerships and as a consequence, strengthening
its distribution network. Its routes respect the
Frankfurt Airport as the main cargo storage and distribution
center. In Brazil, the company’s operations are
concentrated in Viracopos and Guarulhos Airports, with
daily flights to every part of the world, with a total of more
than 500 destinations. Only in 2007, Lufthansa
transported 21 thousand tons in the Brazilian market, with
a hundred percent of efficiency in the delivery.
National companies
The national aviation market is not only exploited by big
foreign companies. In Brazil, there are companies that
operated with profit, respecting the signed contracts, the
movement period of time, the services implicit quality and
maintaining reasonable operational cost.
Among these companies, the Total Linhas Aéreas is an
important agent in the Brazilian aviation market. With its
headquarters in Belo Horizonte, the company transports,
in average, 5 thousand tons of cargo per month, with
flights to the south, southeast and north of Brazil. Currently,
the company has three aircrafts model 727-200,
with the capacity of 20 tons of cargo, through its Total
Cargo Division.
Another important company is the ABSA that has
gained relevance due to the economic problems
registered in Venezuela. All the supply of cargos leaving
Brazil, was of this company’s responsibility, which operates
with DC-10 and 767-300 aircraft models, and that
operates in other countries other that Venezuela, such as
Chile, Mexico, Peru, Argentina and the United States, by
means of partnerships with other embarking companies.
In 2006, the ABSA registered an average of 20 thousand
tons of transported cargo.
TAM announced in 2009, an investment of more than
R$ 30 million, adopting a new name. The company will
stop operating as TAM Express, being renamed TAM
Cargo, with a new infrastructure in the domestic cargo
terminals and the implementation of a new information
technology in the whole country. In 2007, the company’s
total revenue was R $ 776 million, with the expectation of
growing in 2008, as a result of the purchase of new
equipment, totalizing 123 aircrafts.
However, the biggest national aviation cargo agent is
still Variglog. Even with all its financial and judicial problems,
the company detains about 47% of the national
market and 20% of the Brazilian international cargo
destinations. Nowadays, Variglog’s operations involve
aircrafts such as the 757-200, with expansion plans for its
route and aircrafts. All of the company’s operations are
centralized in the Galeão Airport.
Companies such as MTA and TAF operate with
expressive results in Brazil and could not be left out of
this research.

7168 Afr. J. Bus. Manage.
Cargo movement in Brazil
The data about the cargo transportation in Brazil are
interesting. According to Anac (2009), in its statistic
annual report, the main source of transport revenue is the
domestic market, with a value equivalent to R $ 940
million, compared with the international traffic, that
registered R $ 645 million, according to the 2008’s data.
The composition to the segment’s revenue comes from
the cargo movement, representing 84% of the total, being
completed by 13% of the mail company and 3% of charter
services.
The analysis of Anac’s data (2009) indicates that the
operational costs of the companies in the national cargo
segment have its largest concentration on the payment of
fuel, around 34%, followed by personnel salaries with
19% and others. Now, in the international market, the
biggest costs are with the fuel at 26%, followed by
personnel with 13% and others. It is possible to observe
that in the international freight the presence of exchange
rates is a factor to be considered.
The concentration of the distribution of materials is in
the southeast and north regions of the country, observing
the cargo movement and air-mail. One of the interesting
points of the cargo movement in Brazil is related to the
main origins and destinations of the international traffic.
Brazil sends most of its cargos to the United States,
Germany, Chile, Portugal and Argentina. In counterpart, it
receives most of its cargos from Germany, Argentina,
United States, Chile and France, respectively.
In the domestic traffic, the main origins are the states of
São Paulo, Federal District, Rio de Janeiro, Amazonas,
Bahia and Paraná. The main destinies are the states of
São Paulo, Federal District, Rio de Janeiro, Bahia and the
Amazonas.
It is possible to identify the strong presence of the state
of São Paulo and its economical participation in the air
cargo segment, especially due to its production in the
industrial sector of the region. Then, what is the
importance of the concept of industrial airport for the
national economy?
INDUSTRIAL AIRPORT VS. AIRPORT- CITIES
This item has as its objective to investigate the concepts
about industrial airports and, a posteriori, the model of the
airport-cities as a possible solution for the functionality of
today’s airports.
Industrial airport
The concept about industrial airport is associated with the
development model that brings economical gains with
stock of goods, transporting for the companies, and for
the regions that adopt the airport structure as a logistics
center and in the promotion of industrial areas with a
strong technological appeal. Its origins are associated
with the “Exporting Processing Zones (EPZ)”, which were
abandoned in the 90s by the Fernando Henrique
Cardoso’s government, according to Tadeu (2008).
The beginning of the industrial airport concept is correlated
with the appliance of a service network around the
airports’ terminals.
The first industrial airport authorized by the Federal
Fiscal Revenue in Brazil, was the TNIA, in the metropolitan
region of Belo Horizonte, with the signature of the
authorizing declaration act in 2005. The airport was
authorized to develop activities of stocking, exposition,
demonstration, functioning tests, industrialization, maintenance
and repair. The credentials given by the Federal
Fiscal Revenue was the first step for the installation of
companies in and around the airport, in specific areas for
each company, where they can operate with a special
regime of a custom’s entrepôt for importing and
exporting.
This procedure permits stock materials with the
suspension of tax payments and the right to use the fiscal
benefits relative to exporting. The Confins Airport has
today around its area, companies such as: Jabil,
Clamper, Maxtrack VMI, Mecan and Gol Linhas Aéreas
Inteligentes’ Maintenance Center. The second industrial
airport in Brazil was Viracopos, in Campinas, which has
its authorization declared in 2006.
Only the Gol’s installations resulted in an investment of
R$ 15 million to give the adequate conditions to its
terminal.
The economy resulting by the initiative of the company
in operating in the Confins Airport, was 5% in the maintenance
costs of its fleet, that is about R $ 250 millions a
year, besides the revenue received from the maintenance
services given to other aviation companies.
Gol’s performance in Minas Gerais has produced 250
direct jobs and 750 indirect ones. By the agreement
signed with the State Government, the company will have
to maintain itself in the airport for at least ten years and
do all custom work at the Confins Airport.
After Gol, several other aviation companies have
started their operations in Minas Gerais and there are yet
several studies and consults by other companies, which
are interested in operating at the TNIA, due to the good
practices and experiences that have been shown by the
industrial airport concept that was implanted. However,
what is the difference between the industrial airport
concept and the airport-city concept?
Airport-cities
The idea of airport-cities is related to the formation of
urban centers around the industrial airports, offering
multivariable services and increasing the creation of jobs
in the airport’s region, according to Kasarda (2008).
Having clusters with complementary activities, which are
attracted to the region, these centers can be expanded in
a ratio of up to 20 km around the airport, forming more

ample metropolitan areas, according to the modern
concept of “Airtropolis”, that are to airport-cities as
metropolitan centers are to urban centers.
It is, therefore, possible to identify two evolution levels
of embryonic industrial airports: the airport-city, equivalent
to a center of services that offer all the functions of a
modern urban center around the airport terminal; and the
Airtropolis, arterial network related to the whole metropolitan
region, more complex and more ample, that
develops itself because of the industrial airport
economical potential.
The new services that will be offered at the airports
include: restaurants, commercial centers, research
centers, gyms, hospitals and even golf courses. Around it,
it is still possible to install transport routes and
communication fluxes, business offices, technological
compounds, hotel networks and entertainment parks,
industrial centers, free commerce zones and storage and
supply logistic centers.
A classical example of an airport-city is Las Colinas, an
urban center close to Dallas airport, Forth Worth (DFW),
that has 12, 000 ac of extension, with an ample network
of business offices, industrial spaces and service centers
that included 13,300 homes, 3,700 hotel beds and more
than 75 restaurants.
The changes in the organizing form of the airports,
expresses an evolution in the functions that they carry out
and in the ways of financing the airport’s basic infrastructure,
other than the traditional functionality of the
airports. However, there are barriers that have to be
overcome in the process of implementing this development
model. The question is: which are the barriers?
The barriers to the airport-city model
The tributary question represents a considerable problem
in implementing the airport-city model. After all, to attract
companies, it will not only be necessary to offer logistic
advantages, but also tax incentives, Kasarda (2008). The
airport-city model guarantees that the companies will
have tax free incentive when importing the components
used in producing export products, according to the
entrepôt’s custom regime of the Normative Instruction
number 241 of the Federal Revenue’s Secretariat.
One of the advantages for the companies to come and
install themselves in an industrial airport is that the
exporting platforms will be created, in which the components
will be free from importing taxes. The mechanism is
something like of a free-trade zone, in which the manufacturers
can produce without paying the components
importing taxes. However, the difference is that, in the
free-trade zone, the manufacturer can aggregate input
resources from the national industries, in other words,
include in the composition of their products, components
supplied by Brazilian companies. In Brazil, the products
manufactured in the free-trade zone end up also
supplying the internal market, which would not be legally
Braga and Moreira 7169
allowed in an industrial airport, for there is the
requirement that, products that are made with imported
components inside the airport zone have to be exclusively
exported.
The TNIA was the first airport to be approved by the
Federal Revenue to operate as an industrial airport, and
is operating since August of 2006, with the promulgation
of the edit number 44,301/06. Thus, companies that are
installed in the international airport’s area will have suspended
the federal taxes for importing and exporting, but
there still is not a clear definition about the suspension of
the tax over Merchandise’s Circulation and Services
(ICMS) when purchasing raw material from the internal
market. Even with these problems and in a joint effort of
the federal, state and municipal governments together
with the private initiative, before the end of 2009, we will
know the norms that will discipline this special regime,
suspension and/or economic custom entrepôt, more
specifically the industrial airport.
Further, a case study about the Tancredo Neves
International Airport (TNIA) in Belo Horizonte will be
presented.
CASE STUDY - TANCREDO NEVES INTERNATIONAL
AIRPORT (TNIA)
The TNIA is localized in the municipality of Confins, in the
metropolitan area of Belo Horizonte (RMBH), which
started to be built in the decade of 1970. This enterprise
happened due to the diagnostic about the Carlos
Drummond de Andrade Airport (Pampulha) that was
saturated and could not support any longer, the intense
growth of cargo and passengers’ movement at the time.
At the beginning, the idea was that Pampulha Airport was
to be used for regional traffic, with smaller aircraft for
shorter distances. However, this did not occur. Because
of the precariousness of the access to the Tancredo
Neves International Airport (TNIA), passengers preferred
do fly using the flights based at the Pampulha Airport,
economizing time and money, due the fact that the airport
was qualified to operate national lines and not only the
regional ones. Based on this scenario, the weak
performance of the TNIA is justified.
According to Infraero (2009), the TNIA dealt with just
over 4.7 million passengers and 26.7 thousand tons of
cargo, being that its operational capacity is of 5 million
passengers and 40 thousand tons of cargo. These
numbers puts the airport as the eighth busiest one of the
country, when considering the volume of passengers and
the tenth busiest one considering the volume of cargo. It
is known, however, that the demand for the metropolitan
area of Belo Horizonte, computing the movement of the
International Airport and the Pampulha Airport, is placed
in the fifth place among the metropolitan areas with the
largest air traffic.
The main effects of the TNIA’s idleness on the state of
Minas Gerais’ economy, lies on the fact that the airport

7170 Afr. J. Bus. Manage.
has produced a very small number of direct and indirect
jobs, besides the lack of international connections, The
air cargo of Minas Gerais is loaded in the airports of Rio
de Janeiro and São Paulo. Due to this fact, the companies
from Minas Gerais have lost their competitiveness,
agility in their production and in the delivery of their
products, while the state government has lost in tax
collection.
Based on these data, the Tancredo Neves International
Airport (TNIA) has, since 1998, presented proposed
actions to transform it in a center for international commerce
activities. These actions are directed to transform
TNIA in an industrial airport, where investments will be
made in infrastructure with the objective of making the
airport’s site adequate for industries to be installed. A
second action is to make it more feasible for more
international flights leaving from TNIA; a fact has been
proven with the operations of TAP (Lisbon), Copa Airlines
(Panama), American Airlines (Miami) and other advanced
negotiations to other destinations.
The development of an industrial airport will generate a
gradual growth of the cargo’s volume, which will bring a
bigger interest of the aviation companies. This will bring
quality jobs and as consequence, the growth of the
region’s income. The next step would be the
implementation of the city-airport model, being the first
national model to stimulate the national economy, with the
TNIA being an important hub of cargo and passengers
transport.
It is necessary to considerer that there are no legal
restrictions, since the TNIA is the first Brazilian airport to
have a homologated environment license and which is
recognized by national, state and municipal authorities. It
is possible to visualize the Airforce base of Lagoa Santa,
the municipalities of Vespasiano and Lagoa Santa, the
Microelectronic Center and the MG-10 Highway.
The future projects for the TNIA involve the
improvement of the accesses, the amplification of Gol
Linhas Aéreas’ aircraft maintenance center, amplification
of the runways, cargo terminal and an ample
development of a chain of public and private services.
Therefore, the TNIA is a pioneer project in Brazil,
visualizing the future of a national transport matrix, in
comparison only with countries like the United States,
Holland, Singapore, among others.
CONCLUSIONS
In this article, it was possible to understand that the
Brazilian airports are in favorable operational conditions,
when analyzed by the conditions of the past. The specific
contributions of this study are associated with the observation
of the concepts about the industrial airport model
and its evolution to airport-cities. At the end, long term
proposals were made, tied to the opportunities of this
segment’s activities, which will generate suggestions for
future studies.
REFERENCES
Boeing (2008). http://www.boeing.com.
Bowersox DJ (2001) Logística Empresarial: The process of integrating
the supply chain. São Paulo: Atlas.
Infraero (2009). http://www.infraero.gov.br.
Institute of Applied Economic Research (2010). http://www.ipea.gov.br.
International Air Transport Association (2008). http://www.iata.org.
Kasarda JD (2008). Kenan Institute of Private Enterprise .The
University of North Carolina at Chapel Hill.
National Agencies (2010). http://www.bc.gov.br.
National Agency of Civil Aviation (2009). http://www.anac.gov.br.
Tadeu HFB (2008) Logística Empresarial Prospects and Opportunities.
Belo Horizonte: Fundac.

African Journal of Business Management Vol. 5(17), pp. 7171-7178, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM10.1338
ISSN 1993-8233 ©2011 Academic Journals
Review
Understanding and approaching the cultural gap
between First World leaders and their Third World
workforce: An African focus
E. S. van Zyl 1 *, R. Kleynhans 1 and M. du Plessis 2
1 Department of Industrial Psychology, Faculty of Economic and Management Sciences, P .O. Box 33 (23), University of
the Free State, Bloemfontein 9300. South Africa.
2 PE Corporate Services, P. O. Box 77, Totiusdal, Pretoria 2000. South Africa.
Accepted 30 March, 2011
The world is characterised by political, social and economic environmental changes.
Internationalisation and globalisation for instance, have brought about world competition and require
managers to interact with and manage people who are culturally diverse. The aim of this qualitative
research article therefore, is to discuss an appropriate and relevant way in which First World leaders
can understand and approach their Third World workforce in Africa. Important concepts are defined,
with the focus on cultural intelligence and the significance thereof to the First World leaders’
understanding and approach towards Third World subordinates. Cultural intelligence can be improved
by inter alia, obtaining knowledge of current leadership and management practices in Africa. Therefore,
leadership and management in Africa are discussed, followed by a description of a cultural intelligence
implementation model of leadership. Lastly, the focus is on servant leadership as a tool to implement
cultural intelligence in the organisational context.
Key words: First world leader, third world workforce, culture, cultural intelligence, leadership, management.
INTRODUCTION
The world is characterised by political, social and
economic environmental changes (Van Zyl, 2009).
Internationalisation and globalisation for instance, have
brought about world competition and require managers to
interact with and manage people who are culturally
diverse (Alam 2009; Alam et al., 2010; Penceliah, 2008).
Africa is no exception to the global revolution that is
sweeping across managerial and organisational thinking.
Thus, Africa has seen a dramatic change in the way in
which organisations and individuals within the business
environment view culture, ethnicity, socioeconomics,
gender and race (Penceliah, 2008; Sales, 2006). With an
increasing number of culturally diverse African and
foreign national employees entering the labour market,
there has been a greater focus on culture than ever before
*Corresponding author. E-mail: vanzyles@ufs.ac.za. Fax:
0514019397.
(Sales, 2006).
Although Africans have been exposed to diverse
cultures within a business organisational and occupational
context, however, in today’s complex and fastchanging
world of multinational business where the workforce
has become increasingly diverse in national and
cultural origins and work assignments are more commonly
performed by team members of varying nationalities,
managing multinational teams is increasingly becoming a
critical function (Van der Wal and Ramotsehoa, 2001).
The power of Africa and its long-term impact on global
markets and economies are only beginning to surface
and to be understood by the world, which will increase
the pressure on leaders, as well as the complexity of
leading businesses in the years to come. Africa has, for
example, 60% of the world’s uncultivated arable land.
Furthermore, Africa’s infrastructure projects represent
13% of the emerging market total and the need for
development remains huge (Mckinsey’s Global Institute,
2010). The increased global demand for Africa’s

7172 Afr. J. Bus. Manage.
resources, oil, gas and minerals will continue to grow,
with increased returns for the continent. By 2040, Africa
will be home to 25% of the planet’s youth and will have
the world’s largest working age population. Lastly, the
rate of return on foreign investment in Africa is higher
than in any developing region (McKinsey’s Global
Institute, 2010).
Mkhize (2009) as well as Van der Wal and Ramotsehoa
(2001) indicated that changing external realities could
result in cultures, which were once effective, becoming
ineffective. The external realities that face African organisations
currently reinforce the necessity to identify the
cultural gap, that is, the gap between actual and desired
cultural norms, and addressing this to make
organisations more effective. Unfortunately, modern and
Westernised African organisations are conceptualised
and structured in a Western mould (Van der Wal and
Ramotsehoa, 2001). The cultures of organisations are
dominated by the values of predominantly male top
management structures, which ignore the fact that the
largest proportion of the population is neither European
nor American, but African (Van der Wal and
Ramotsehoa, 2001). Many employees are unable to
identify with these cultures and little congruence exists
between organisational goals and those of the general
workforce. Therefore, cross-cultural people skills are
important because, managing people effectively is critical
to organisational efficacy. According to House and
Javidan (2001), the management of people is a result of
the cultural forces in the countries and regions in which
the leader functions. Leadership across cultural differences,
whether international or organisational, requires
specific interpersonal attitudes and skills, as well as
technical and organisational knowledge (Manning, 2003).
Zaidi et al. (2010) indicated the need for more effective
leadership and decision making skills due to diversity in
the working environment.
The aim of this qualitative research article therefore, is
to discuss an appropriate and relevant way in which First
World leaders can understand and approach their Third
World workforce in Africa.
DEFINING CONCEPTS
Different concepts related to this research need to be
understood and will be briefly discussed.
Culture refers to a group or community whose members
share common experiences that shape the way in
which they understand the world. It includes groups that a
person is born into, such as, gender, race or origin, as
well as groups that the individual joined or became part of
(Penceliah, 2008). Cultural knowledge, on the other
hand, refers to shared knowledge that accompanies the
behaviour and practices of a particular group. In effect,
cultural knowledge would be a deep understanding of the
beliefs, customs and traditions of a particular group
(Penceliah, 2008). According to Sackman (1992), cultural
knowledge is necessary in organisational life and serves
a crucial coordinating function as it is ‘the body of knowledge
that is drawn upon as a resource for explaining and
making sense of new experiences’. Cultural knowledge is
a fundamental building block in an organisation and,
consequently, managing in a multicultural context would
translate into building culturally appropriate relationships
across various differences (Sackman, 1992). Cultural
knowledge can give rise to cultural intelligence.
Cultural intelligence (CQ) provides managers with practical
techniques for functioning effectively in any culture,
as CQ is ‘a person’s capability for successful adaptation
to new cultural settings, that is, for unfamiliar settings
attributable to cultural context’ (Earley and Ang, 2003).
According to Earley and Ang (2003), cultural intelligence
comprises a cognitive, emotional and behavioural component.
The cognitive component refers to one’s specific
knowledge to perceive and understand a new culture
based on various types of cultural cues. The motivational
component refers to one’s self-motivation and
commitment to adapt and adjust to a new culture, and the
behavioural component refers to acting according to
one’s commitment and new culture (Deng and Gibson,
2008).
In order to achieve cultural intelligence (CQ) in an organisational
context, it is important to understand leadership
and management issues and circumstances which are
unique to the African context.
LEADERSHIP AND MANAGEMENT IN AFRICA
To improve cultural intelligence (CQ) in the organisational
context, leaders should try to achieve a better understanding
of the changing African context, important crosscultural
challenges and the African cultural value system.
The changing African context
Managers place a distinct focus on taking on the
challenges prevalent in Africa’s present-day business
environment. As a consequence of the changes that
accompany these challenges, a shift is taking place from
cultural ethnocentrism based on self-praise, towards
mutual respect between the races (Shonhiwa, 2006).
This enables African countries to weave an entirely new
economic tapestry, in which business is undertaken,
creating an environment that differs markedly from that of
the old Africa (Shonhiwa, 2006; Van Rensburg, 2007).
According to Van Rensburg (2007), the new environment
has particular characteristics. Firstly, there is an

emerging new class of management with an adaptable
style of leadership that enables leaders to integrate the
various cultures of those who answer to them. The changing
economic landscape demands greater sensitivity
and understanding of subtle cultural nuances in each
particular country. Homebred management styles are
developed that differ from those of multinational corporations
and tend to be parochial, mostly owing to people’s
lack of exposure to different environments and
challenges, while international players have the benefit of
tapping into a wider source of knowledge (Van Rensburg,
2007).
The impact of culture and value systems, shape managerial
response to similar business stimuli, for example, a
bright, young person who questions the manager’s
instructions in order to understand them better might be
seen as rude within an African context, but a European
manager would welcome or even expect such input
(Shonhiwa, 2006). Prevailing political and economic
imperatives dictate the respective management competencies
required in a particular situation. This means that
a manager would be faced with the difficult task of trying
to understand many new aspects of an unknown
situation. Companies today, apply new critical success
factors, which affect leadership and managerial
effectiveness. The major key performance indicators in
this regard, express a dire need for cross-cultural
management and leadership skills which will enable
managers to cope with the various demands in different
countries (Van Rensburg, 2007; Mkhize, 2009).
Significant mega-trends ushered in a new value
system, that influenced leadership style, can also be
identified, that is, the arrival of the cash economy, which
emerged through foreign traders (Van Zyl, 2009). The
advent of the cash economy also created an entrepreneurial
drive in those who are motivated to create wealth.
Core African life emphasises humanity and relationships
over material wealth and, thus, the focus on material
values may clash with Africanism. Managers who pursue
success too strongly may find themselves isolated from
their staff or support group (Shonhiwa, 2006). Another
change determinant is the evolution of the political system
from traditional dynasties towards a more Western,
democratic system, creating the problem of ‘Senior
Young People’, who now preside over their elders by
virtue of their political power. This situation currently
pervades the entire business environment where
‘Youngsters’ have advanced up the corporate ladder and
who are, in fact, the preferred high-flying managers (Van
Rensburg, 2007).
Cross-cultural challenges
Mkhize (2009), Nussbaum et al. (2010), Shonhiwa (2006)
and Van Rensburg (2007) indicated some cross-cultural
challenges confronting African managers:
Poor-rich individual
Zyl et al . 7173
The manager in the Afro-centric cross-cultural context is
perceived by the rank and file to be materially and
intellectually rich. This perception develops because poverty
is rife on the African continent. Employees usually
seem materially worse off than their managers, but very
often, managers in the African context are not as well off
as their employees may think. The erroneous perception
that managers are rich can lead to complex personal
problems for managers in the African context.
Shifting ethical platforms
The Cultural Revolution taking place in Africa leads to
ethical boundaries being in a continual state of flux. What
used to be taboo is now commonplace, as cultural goalposts
are being shifted to suit new preferences. The
conflict between old- and new-school managers further
complicates the situation.
Overriding political environments
As political change occurs at a much slower pace than
social and economic changes, managers continue to feel
the weight of political restrictions. They are torn between
patriotism and the demands of the new international
business scenario.
Cultural confines and conflicts
In some scenarios, managers are unable to support a
specific change or product because it will clash with
tradition, and they feel they cannot risk being the first to
step out of line.
Skills and productivity gaps
Although advances in technology surge onwards, the
process of upgrading skills is lagging behind, creating a
widening productivity gap. Most African governments
prevent the inflow of foreigners in order to retain
employment for locals. However, managers fail to meet
targets due to a lack of skills in the available workforce.
Society’s crisis of expectations
In an African context, one is not sure whether to openly

7174 Afr. J. Bus. Manage.
celebrate one’s success or if this behaviour will be
construed as arrogant and boastful. The majority of
African society is still operating in a communalism mode,
expecting all citizens to be either equally poor or equally
wealthy. Those who are first to achieve higher status,
such as a management position, are targets of the
African PHD (‘pull-him-or-her-down’) syndrome. This
places the cross-cultural manager in a frustrating pushpull
position.
From the aforementioned, it is evident that the African
value system must be well understood before any effective
leadership system can be implemented. Therefore,
the focus of further discussion will be on the African
cultural value system.
The African cultural value system
It is clear that the effective cross-cultural manager should
have an in-depth understanding of the African cultural
value system which determines the behaviour of subordinates.
This value system can be summarised as (Khoza,
2005; Mbigi, 2005; Shonhiwa, 2006; Van Rensburg,
2007):
i) The African prefers spiritual collectivism to
individualism. Spiritual guidance is expected and
respected;
ii) There is an inclination towards consensus in problemsolving,
rather than dissension;
iii) Humility and helpfulness are expected, instead of
wanton criticism. The spirit of ubuntu (the concept of
fellowship, loosely translated as ‘you are who you are
through other people’) is greatly valued and each person
is very much conscious of this philosophy;
iv) There is an inherent trust and belief in the fairness of
those in leadership, hence a lack of criticism;
v) African moral standards are based on ancestral
precedents and, thus, history plays a prominent role in
guiding future conduct;
vi) Society is a structure in which an inclusive system of
hierarchy plays a role. This inspires orderliness and
acceptance of authority;
vii) Perpetual optimism and a belief in superior forces
underlie the African sense of being and attitude towards
life. This explains the ease with which fanatic allegiance
is instilled into the minds of young people who become
guerrilla fighters; and
viii) There is a tacit expectation that those who are in a
supervisory position will display sound leadership and not
let their subordinates down. Subordinates expect their
leaders to display a heightened sense of ethics, fairness,
transparency and accountability. Unfortunately, many
leaders today fail to uphold these values.
A CULTURAL INTELLIGENCE IMPLEMENTATION
MODEL BY WHICH FIRST WORLD LEADERS CAN
ATTEMPT TO UNDERSTAND AND APPROACH THIRD
WORLD SUBORDINATES
In order to improve the cultural intelligence (CQ) amongst
leaders (by means of understanding and managing people
from diverse cultural groups), the following adapted
model of Van de Wal and Ramotsehoa (2001) can be
considered (Figure 1).
From Figure 1, it is evident that there are four cornerstones
which contribute to organisational success and
effectiveness. Each of these cornerstones will now be
discussed.
Cornerstone 1: Commitment from top management
Arsenijevic et al. (2009) as well as Wang and Abdul-
Rahman (2010) are of the opinion that culture of every
organisation is to a great extent, defined by leadership.
Lundin and Nelson (2010) are of the opinion that top
management should come to the conclusion or
understanding that the business and social culture is
business; this must be a believe set, not only words or lip
service.
In order to focus on the business and social culture as
well as to improve cultural intelligence amongst leaders
and employees, top management should be committed to
improving their own cultural intelligence, as well as that of
subordinates.
Dalglish and Therin (2003) are of the opinion that, it is
the primary responsibility of top management to instruct,
motivate and inspire their employees with regard to
openness towards other cultural groups. Lundin and
Nelson (2010) indicated that top management should live
the new values and purposely influence the leaders
below the executive team. Furthermore, top management
should set a company policy with regard to cultural
openness and the improvement of cultural intelligence
which should be communicated clearly to all employees.
Employees should be told and retold in unmistakable
terms that the company is firmly committed to cultural
openness and improvement of cultural intelligence in all
its activities (Dalglish and Therin, 2003; Nussbaum et
al., 2010).
Cornerstone 2: Create a shared value organisational
culture
Arsenijevic et al. (2009) and Dorasamy (2010)
acknowledged the importance and crucial role of the
culture of an organisation in the productivity and learning
at all levels. Zaidi et al. (2010) explained that good
performance and effective decision making are achieved

Cornerstone 3
Training and development
Cornerstone 4
Implementation, mentoring, team
building and strategic theory
Contribute to individual and
organisational success /
effectiveness
Cornerstone 2
Create a shared value /
organisational culture
Cornerstone 1
Commitment from top management
Figure 1. A cultural intelligence implementation model (adapted model from Van de Wal and Ramotsehoa, 2001).
through teamwork and a shared value system within the
organisation.
According to Penceliah (2008), the focus on improving
the cultural quotient (CQ) of employees can aid in the
understanding and management within a diverse cultural
environment. By being culturally intelligent, one can
develop skills and an understanding regarding culture,
learning more about it from one’s own interactions with
adherents of the specific culture, and gradually reshaping
one’s thinking to be more sympathetic towards that
culture. Sales (2006) argues that having the necessary
knowledge and understanding of cultures will no doubt
empower managers to instil trust and confidence in their
employees and to appreciate the values and norms of
their staff.
Van der Wal and Ramotsehoa (2001) indicate that the
cultural quotient of employees can be developed by
means of implementing ubuntu within the organisational
culture. Ubuntu, embraces a set of social behaviours,
such as sharing, seeking consensus and interdependent
helpfulness which, if recognised, valued and incorporated
into the culture of organisations, could yield considerable
positive outcomes on business results. Karsten and Illa
(2005) as well as Lundin and Nelson (2010) define
Zyl et al . 7175
ubuntu as a pervasive spirit of caring and community,
harmony and hospitality, respect and responsiveness that
groups and individuals display towards one another. They
are also of the opinion that ubuntu represents a specific
African worldview, which can further be translated into
the ‘African dream in management’. It is the label that
covers the way in which members interact and share
experiences. Ubuntu, therefore, strives to reach beyond a
purely managerial approach and strengthens an attitude
of listening to one another and to open conversations.
Karsten and Illa (2005) indicate that storytelling, inclusive
decision-making and participatory team meetings are key
features of ubuntu. The setting of an organisational
culture is the function of the top management of that
specific organisation, and top management should
therefore, be responsible for implementing ubuntu into
the organisation’s culture.
Cornerstone 3: Training and development
Zaidi et al. (2010) explained that differences in the organisation
could lead to conflicts. Conflicts however can be
resolved through improved human resource policies,

7176 Afr. J. Bus. Manage.
effective communication, participative decision making
and a constant training schedule within the organisation
(Zaidi et al., 2010).
According to Van der Wal and Ramotsehoa (2001),
training that provides an understanding of the values,
beliefs, customs and preferences of the other group will
enhance cultural diversity. Developmental sessions by
means of practical workshops can be held where people
of different cultural groups discuss areas of similarities
and differences with regard to cultural values and
behaviour. Communication sessions, focusing on ‘where
are we now and where do we want to go’ should be
implemented in the organisation (Nussbaum et al., 2010).
Every employee should be given the opportunity and
responsibility to improve their cultural intelligence. To
achieve this, the following steps can be taken (Karsten
and Illa, 2005; Lundin and Nelson, 2010; Nussbaum et
al., 2010):
i) Obtain knowledge about the cultures of different
employees. Language courses, programmes focusing on
breaking cultural barriers or stereotypes, and the valuing
of cultural differences, should be focused on;
ii) Develop special events or schemes to expose
employees (and managers) to people from different
cultural groups; and
iii) Provide effective training in order to improve skills in
listening, interpersonal communication, conflict resolution
and negotiations, and explore ways to alter current
assumptions and paradigms. Workplace teams should
utilise these skills, as well as reinforce diversity efforts.
Cornerstone 4: Implementation: Mentoring,
teambuilding and strategic thinking
Van der Wal and Ramotsehoa (2001) assert that
employees should be empowered by means of relevant
mentoring in the organisation. A mentoring system in the
organisation can develop a sense of competence and
professional identity which, in turn, will help employees to
mature personally. Agumba and Fester (2010) explained
that mentoring refers to an interactive and dyadic
relationship with a senior and experienced employee. By
having an interactive relationship with an experienced
person, complex issues with regard to new culture/values
can be sorted out (Agumba and Fester, 2010). Agumba
and Fester (2010) highlighted the following characteristics
mentors should have; be approachable, have selfconfidence,
show desire to be a mentor, provide honest
feedback, be self knowledgeable and be dedicated to
mentoring.
Teambuilding can be used to build a culture of
intercultural understanding. In this way, enhanced communication
channels between supervisor and subordinates
can be established. This can lead to an improvement in
work co-operation and can provide a useful basis for the
introduction of permanent problem solving groups at work
(Nussbaum et al., 2010; Van der Wal and Ramotsehoa,
2001).
Visions, missions and objectives should be modified
according to the new culture in the organisation. The
involvement and participation of all employees in the
planning, wording and setting of the new vision, mission
and objectives will help to commit everyone to implementing
the new value system (Nussbaum et al., 2010).
Alam et al. (2010) are of the opinion that if employees are
well informed with strategic objectives and values, trained
and involved with the implementation of that, work quality
and accountability will be the result.
Weibo et al. (2010) indicated that new values will only
become shared values in organisational context if it is
being lived by all employees in the organisation. Living it
means the constant evaluation of how successful aligning
between business and social culture are taking place.
This may imply that subtle changes may be required on a
constant basis that will have to be filtered through to the
organisation (Weibo, et al., 2010).
Van der Wal and Ramotsehoa (2001) indicate that the
afore-mentioned cornerstones can contribute to
individual/organisational effectiveness which, in turn, can
have a positive influence towards improving the four
cornerstones.
SERVANT LEADERSHIP AS A TOOL TO IMPLEMENT
THE CULTURAL INTELLIGENCE IMPLEMENTATION
MODEL
According to West et al. (2008), a leadership style that
has emerged with great intensity over the past few years
is that of servant leadership. Greenleaf introduced servant
leadership by stating that leaders are to be servants
first, for it is the proven record of service that provides the
basis on which the led, choose those whom they will
follow (Irving, 2008; Joseph and Winston, 2005).
West et al. (2008) claim that servant leadership, in
many ways, provides answers to some of the cultural and
ethical dilemmas faced by people in businesses and
other organisations. Larry Spears, president and CEO of
the Greenleaf Center for Servant Leadership, identifies
two primary reasons for the rise in importance of servant
leadership, that is, people in today’s workplaces are
generally dissatisfied with the level of caring and
encouraging behaviours they experience at work and that
servant leadership provides a different approach which
answers contemporary expectations better than do
traditional leadership models. He also suggests that
businesses and other organisations which practice
servant leadership increasingly find themselves at the top

of their industries, primarily due to their having the ability
to better meet customer, client and community
expectations (Joseph and Winston, 2005).
Mumley (2007) discusses the fact that servant
leadership factors, such as love, humility, altruism, incurporation
of the followers’ vision, trust, empowerment and
service, correspond well with the ubuntu ideal in African
companies.
He further indicates that the connection of servant
leadership with the indigenous values of ubuntu
represents a significant breakthrough in the potential of
implementing servant leadership theory throughout
African companies. Creff (2004) is of the opinion that
servant leadership provides a bridge by which ubuntu can
be applied within African companies. He also states that
a concerted, wise application of servant leadership
should be practiced through training and development
actions within organisational context.
West et al. (2008) explored cultural constructs of transformational
and servant leadership theories and describe
differences that include; (a) transformational leadership
that accounts for intellectual stimulation where servant
leadership does not; and (b) servant leadership that
stresses employee’s well-being where transformational
leadership does not.
Although some researchers (Smith et al., 2004) postulate
that it will be difficult to implement servant leadership
in a very dynamic, high-demanding work environment,
the following research indicates the successful implementation
of servant leaderships in public and private
companies:
i) Servant leadership with organisational outcomes (West
et al., 2008).
ii) Servant leadership with organisational culture (Smith et
al., 2004).
iii) Servant leadership with team effectiveness (Irving,
2008).
Finally, West et al. (2008) indicate that characteristics of
the servant leader, such as building trust, caring,
developing others, sharing leadership, listening before
speaking, building community and providing leadership,
are probably the best way to undertake cultural changes
within the modern company today.
CONCLUSIONS
According to Karsten and Illa (2005), ‘It is not our
differences that divide us, it’s our judgments about each
other that do’. Cultural differences are rarely the source
of interpersonal or inter-group conflict. The most common
source is what can be called ‘mindsets’, such as filters,
through which people view the world, the self and others
Zyl et al . 7177
(Karsten and Illa, 2005). Influenced by their mindsets,
some people appreciate and work effectively with
individual and cultural differences, while others are
awkward, threatened or uncomfortable (Mumley, 2007).
To meet the challenge of a diverse workforce,
managers in the African context need to develop a
greater appreciation of understanding and managing
Third World subordinates with different value systems. In
the African context, the need exist to emphasise the
affirming of different values which will create a corporate
environment where individuals will reach their potential to
the benefit of their organisation. By improving cultural
knowledge (and implementing the cultural intelligence
implementation model), the ability to better meet
employees, customers, clients and communities’
expectations, improve (Mumley, 2007). This could lead to
a more effective and sufficient work environment and to
improved individual/organisational performance. Servant
leadership can be a critical tool to implement cultural
knowledge and the cultural intelligence implementation
model within the organisational context.
Leaders/managers in the African context have the
responsibility to not only focus on improved productivity
amongst employees, but also to set an example of
commitment to the cultural values of others and how
these can be implemented in the organisational context
(Van der Wal and Ramotsehoa, 2001). Perhaps, this
spirit was best captured by Lao-Tzu, the 6 th -century
Chinese philosopher (Van Zyl, 2009), who wrote: ‘A
leader is best when living to potential and understands
others fully in order to help them to reach their potential
to the benefit of everyone involved.’
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African Journal of Business Management Vol. 5(17), pp. 7179-7187, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM10.1512
ISSN 1993-8233 ©2011 Academic Journals
Review
TQM, role stressors and counterproductive behaviour:
A proposed framework on strain reduction
Julian Hong-Leong Teh* and Shwu-Shing Ng
Faculty of Business and Finance, Universiti Tunku Abdul Rahman (UTAR), Malaysia.
Accepted 27 May, 2011
Previous studies reveal that Total Quality Management (TQM) practices reduce the perception of role
stressors among employees. Some questions nevertheless remain to be answered. This paper attempts
to fill these gaps by developing a conceptual model that extends previous work done on the ‘TQM - role
stressor’ relationship. The conceptual model in this paper therefore incorporates two additional, yet
important stress-related variables, namely ‘strain’ which are the actual manifestations of stress, and
‘withdrawal behaviors’ which are the coping strategies employees engage in when exposed to role
stressors. This paper contributes to TQM literature by highlighting the following important areas:
Firstly, although past literature indicates that TQM practices reduce role stressors, this paper proposes
that TQM practices do not completely eliminate the existence of role stressors and individuals may still
need to engage in coping strategies to further safeguard their wellbeing. Secondly, this paper
challenges the traditional notion that all components of counterproductive behaviors (CWB) are harmful
for the organization. In a stressful environment, withdrawal behaviours, a type of CWB, is proposed to
be a coping strategy done out of necessity to reduce strain, rather than to solely harm the organization.
The proposed model serves important managerial implications because withdrawal behaviors,
traditionally perceived to warrant disciplinary action, should be viewed in a different light.
Key words: Total quality management, role stressors, strain, counterproductive behaviour, coping.
INTRODUCTION
Total quality management (TQM) is a management
philosophy that spans the entire organization with the aim
of providing products and services with a level of quality
that satisfies customers (Talha, 2004; The W. Edward
Deming Institute, 2010). TQM is a stellar management
philosophy that has been proven time and again to
improve organizational performance, competitiveness
and efficiency (Escrig-Tena, 2004; Kuruppuarachchi and
Perera, 2010; Wruck and Jensen, 1994; Zhang, 2000).
Besides organizational level performance TQM has also
been accredited at the individual level, whereby TQM was
found to reduce the perception of role stressors among
individual employees (Teh et al., 2009a, b). It is important
*Corresponding author. E-mail: julianteh8@gmail.com
to note that role stressors are merely the stimuli that
trigger stress, and not the actual outcome of stress
(Beehr and Newman, 1978; Onyemah, 2008). Strain on
the other hand, is the outcome of stress. Strain is
commonplace in the working environment, and occurs
when individuals are exposed to role stressors over a
long period of time (Maslach and Leiter, 2008). Strain is
identified in individuals via the manifestation of the
following symptoms: physical symptoms (such as tension
headaches), psychological symptoms (such as anxiety,
depression, frustration) and behavioural symptoms (such
as absenteeism, turnover) (Jex and Beehr, 1991; Kahill,
1988). Nevertheless, according to Skinner et al. (2003),
not all employees experience strain, as some may
engage in defensive coping mechanisms to reduce the
effects of strain.
Within TQM literature, the following gaps are observed:

7180 Afr. J. Bus. Manage.
firstly, no studies have attempted to investigate beyond
the ‘TQM - role stressor’ relationship by incorporating the
‘strain’ component (Hartline and Ferrell, 1996; Teh et al.,
2009a, b; Victor et al., 2000). Previous studies have only
examined the direct relationship between TQM practices
and the stimuli of stress (such as role stressors), but not
the impact of these stimuli (for example, role stressors)
on actual stress outcomes (for example, strain). With
reference to the study by Teh et al. (2009a, b), although
we know that TQM practices reduce role stressors, it is
not specified whether the reduction of role stressors also
cause a significant reduction in strain.
There also appears to be a lack of TQM literature on
the type of coping mechanisms that employees rely on to
reduce role stressors. When exposed to stressors, not all
employees break under pressure as some may engage in
coping strategies to reduce the effect of these stressors
(Skinner et al., 2003). It is a b to assume that coping
mechanisms are not necessary just because TQM
practices reduce role stressors. With reference to the
study by Teh et al. (2009a, b), TQM practices only
account for between 19 to 25% of the variation in role
stressors, with the remaining variation being unaccounted
for. This means that although TQM practices reduce role
stressors, TQM does not completely eliminate the
existence of role stressors. This argument is supported
within TQM literature itself, as studies have revealed that
role stressors remain to be part-and-parcel of TQM firms,
and are continually present even within the best TQM
firms (Hartline and Ferrell, 1996; Victor et al., 2000).
Therefore, because TQM practices do not completely
eliminate the existence of role stressors, some employees
may be forced to rely on coping strategies to further
reduce the ‘residual’ amount of these role stressors.
Within literature, these behaviors (for example, behaviors
that reduce the residual amount of role stressors) may be
instinctual, as individuals automatically protect themselves
from threats if the environment (such as the TQM
firm) fails to completely eliminate it (Gross, 1998; Scapini,
2001; Skinner et al., 2003). Furthermore, within neuroscience
literature, these behaviors may even occur at the
subconscious level, as part of an individual’s subconscious
drive to defend against threats (Lawrence and
Nohria, 2002; LeDoux, 2000; Winkielman and Berridge,
2004). To recapitulate, there is a lack of literature on the
type of coping strategies used to reduce role stressors
within a TQM environment.
Pertaining to the third gap and stemming from the
second, within TQM literature and management literature
in general, counterproductive behaviours (CWB) are
behaviours traditionally perceived to be harmful to the
organization (Robinson and Bennett, 1995). Thus employees
caught engaging in CWB are normally handed
disciplinary action. However, in a recent study by Krischer
et al. (2010), ‘withdrawal’ behaviours, a type of CWB,
were revealed to be an important ‘coping mechanism’
that employees relied on to significantly reduce strain.
Interestingly, the study revealed that employees who
engaged in ‘withdrawal’ behaviours (for example, taking
longer breaks than allowed, arriving late and leaving
early) do it out of necessity to reduce strain, rather than
to deliberately harm the organization. Thus the third
research gap emerges because the majority of TQM
literature only paints CWB in a negative light, but does
not consider the possible advantages and necessity of
CWB in a TQM environment. To recapitulate, no prior
studies within TQM literature have attempted to examine
the moderating effects of CWB on the ‘role stressor -
strain’ framework.
To fill these gaps, this paper will attempt to design a
conceptual model that extends prior work done on the
‘TQM - role stressor’ relationship by Teh et al. (2009a, b)
by proposing a ‘TQM - role stressor - strain’ framework. In
addition to that, withdrawal behaviours (the coping
mechanism) will be incorporated as a moderating
variable in our model. As a summary, our final model will
propose that both TQM practices and CWB co-exist
together in a single framework to explain how strain
levels are reduced.
This paper contributes to TQM literature in three ways.
Firstly, our model extends previous work done on the
‘TQM - role stressor’ framework by adding in a ‘strain’
component (thus focusing on the actual outcome of
stress, and not just the stimuli of stress). Secondly, this
paper suggests that TQM practices do not completely
eliminate the existence of role stressors, and therefore
some employees may need to rely on coping
mechanisms to reduce the residual amount of these role
stressors. Thirdly, our model challenges the traditional
notion that all components of CWB are detrimental for
TQM firms. Our model proposes that employees engage
in withdrawal out of necessity to reduce strain, rather
than to harm the organization.
LITERATURE REVIEW
TQM practices
TQM encompasses the wide range of management
activities that span the entire organization to provide
products and services with a level of quality that satisfies
customers (Talha, 2004; The W. Edward Deming Institute,
2010). Generally, firms that embrace the TQM philosophy
have been found to improve overall organizational
performance, competitiveness and efficiency (Escrig-
Tena, 2004; Kuruppuarachchi and Perera, 2010; Williams
et al., 2004; Wruck and Jensen, 1994; Zhang, 2000).

According to Jha and Kumar (2010), three prestigious
quality awards namely the Malcolm Baldrige National
Quality Award (MBNQA), the European Quality Award
(EFQM) and the Deming prize serve as common
frameworks for TQM implementation within organizations.
Benchmarking against these awards have proven time
and again to be effective, as well as practical in achieving
quality excellence (Calvo-Mora, Leal and Rolda´n, 2005;
Saizarbitoria, 2006; Wong et al., 2010). Organizations
conferred these awards are usually role models in their
industries, and personify the TQM quintessence of
quality. Pertaining to the MBNQA, across literature many
authors have advocated conceptualizing the TQM
component using the six dimensions in the MBNQA
framework (for example, leadership, strategic planning,
customer focus, human resource focus, process
management, and information analysis) (Ooi, 2009; Teh
et al., 2009a, b; Dean and Bowen, 1994; Samson and
Terziovski, 1999; Wong et al., 2010). Conceptualizing the
TQM construct using the MBNQA is commendable,
because the MBNQA is very versatile as it has been
applied across a wide variety of sectors including manufacturing,
service industries, non-profit organizations,
education, healthcare, and small-medium businesses
(American Society for Quality, 2010). Furthermore,
according to Ooi (2009), these six dimensions have been
widely acknowledged as part-and-parcel of TQM practice
by both academicians and practitioners alike. Additionally,
the MBNQA framework has also received international
recognition, with its six dimensions widely adopted across
different countries (Jha and Kumar, 2010). As a result,
our model will conceptualize the TQM construct using the
six dimensions outlined in the MBNQA framework, namely
leadership, strategic planning, customer focus, human
resource focus, process management, and information
analysis.
Role stressors
First and foremost, it is important to highlight the distinction
between the term stressor and stress. Stressors (for
example, role stressors) are the stimuli that trigger stress,
and are not the actual outcome of stress (strain) (Beehr
and Newman, 1978; Onyemah, 2008). Generally, the
long-term exposure to role stressors causes strain.
Stressors are commonplace in the working environment,
and role stressors are no exception (Beehr and Newman,
1973; Krischer et al., 2010). Derived from role theory,
‘role stressors’ are the stimuli that cause stress, due to
the roles an individual holds within the organization.
According to Rizzo et al. (1970), role stressors encapsulate
two smaller dimensions, namely role conflict and
role ambiguity. The first dimension, role conflict, occurs
Teh and Ng 7181
when employees face contradictory role expectations
when on the job. Role conflict is defined as “the simultaneous
occurrence of two or more sets of pressures, such
that compliance with one would make more difficult
compliance with the other" (Kahn et al., 1964). Role conflict
is commonplace in the working environment because
employees are required to constantly juggle conflicting
demands across the different roles they hold. Pertaining
to the second dimension of role stressors, role ambiguity
occurs when an individual lacks clarity as to what
behaviours are expected at work (Rizzo et al., 1970).
Role ambiguity causes a lot of psychological discomfort
and stress because individuals who are unduly troubled
about how to proceed with a critical task experience
frustration.
Conceptualizing role stressors using these two dimensions
has been a common practice within literature (Mulki
et al., 2008; Onyemah, 2008; Rangarajan et al., 2005;
Rizzo et al., 1970; Weeks and Fournier, 2010). Although
factorially independent, in certain studies, these two
dimensions were sometimes combined into a single
unidimensional measure for simplicity purposes (Bowling
and Eschleman, 2010). As a result, and for the purpose
of model simplicity, role conflict and role ambiguity will
also be combined into a single unidimensional measure
to represent our role stressor construct.
Strain
Strain is usually detected in individuals via the manifesttation
of the following symptoms: ‘physical symptoms’
(such as tension headaches), ‘psychological symptoms’
(such as frustration, depression, anxiety) and ‘behavioural
symptoms’ (such as absenteeism, turnover) (Jex
and Beehr, 1991). Strain is the first indicator of burnout,
and if not properly monitored, leads to full burnout
(Hunsaker, 1986). If strain continues over the long-term,
the following worst case scenarios will occur: Physical
worse case scenarios (such as chronic insomnia,
gastrointestinal problems, poor appetite and chest pains)
interpersonal worse case scenarios (such as antisocial
behaviour and poor working relations) and behavioural
worse case scenarios (such as turnover, absenteeism,
decreased performance, excessive smoking, binge
drinking and even drug abuse) (Halbesleben and Bowler,
2007; Kahill, 1988; LePine, 2005; O'Driscoll and Beehr,
1994; Schaubroeck et al., 1989; Wallace et al., 2009;
Wright and Cropanzano, 1998).
From a practical perspective, strain also takes a heavy
toll on a firm’s financial resources, as the annual costs
associated with long-term strain has doubled in merely a
decade from $ 150 to 300 billion in 2007 (Cynkar, 2007;
Wright and Smye, 1996). Due to the various detrimental

7182 Afr. J. Bus. Manage.
TQM
practice
Figure 1. Proposed conceptual framework.
Role
Stressor
outcomes commonly associated with strain, it is therefore
important to identify the processes and mechanisms
whereby strain operates, which will thus be the focus of
this paper.
Counterproductive behaviours
Traditionally, CWB has been perceived to be behaviours
that harm the organization or its members (Robinson and
Bennett, 1995). Spector et al. (2006) outlines a typology
of five of these behaviours namely: abusing others,
sabotage, theft, production deviance and withdrawal. In
the past, CWB has been viewed as detrimental as it is
claimed to cost organizations billions (Bennett and
Robinson, 2000). Because CWB has been perceived to
be detrimental, employees caught engaging in CWB are
normally dispensed strict disciplinary action. Furthermore,
throughout the ages, researchers and practitioners alike
have either attempted to control or reduce the occurrence
of CWB within the organization (Spector et al., 2006).
THE CONCEPTUAL MODEL AND PROPOSITIONS
DEVELOPMENT
With literature laying the foundation for our framework,
Figure 1 illustrates the relationships between our constructs.
Firstly, TQM practices are proposed to reduce
role stressors. This reduction in role stressors are subsequently
proposed to reduce strain. However, because
TQM practices do not completely eliminate the existence
Coping mechanism
CWB:
withdrawal
Strain
of stressors, a residual amount of role stressors still exist
within the organization. As a means to cope, some employees
may instinctively engage in coping strategies (for
example, withdrawal behaviors) to further weaken the
stressor-strain relationship. As a result, employees that
cope, for example, in withdrawal experience, lower levels
of strain, compared to their counterparts who do not
engage in withdrawal at all.
Propositions between TQM practices and role
stressors
In a pioneer study by Teh et al. (2009a, b), an interesting
relationship was established between TQM practices and
role conflict. The authors found that in general, TQM
when conceptualized using the MBNQA, was revealed to
significantly reduce employees’ perception of role conflict.
In these two studies, TQM practices accounted for
between 19 to 25% of the variation in role conflict.
Previous authors’ findings are widely supported across
management literature. Within literature, each of the six
TQM dimensions was closely associated with the reduction
of role stressors. Leaders providing proper guidance
and direction were found to be an important factor in
reducing role conflict among employees (House and
Rizzo, 1972; Lee, 2000; Conger and Kanungo, 1988).
Subsequently, leaders that displayed supportive leadership
styles also reduced the level of role stressors among
employees (Babin and Boles, 1996; Michaels et al., 1987;
Teas, 1983). Pertaining to the TQM dimension of ‘process
management’ (for example, formalization, rules and
procedures), process management was found to reduce

ole stressors because formalization helps clarify role
perceptions (Morris et al., 1979; Rizzo, 1970). Formalization
involves the proper documentation of rules and
procedures and this is helpful in guiding action and
clearing uncertainties (Zhang et al., 2000). Additionally,
organizations that coordinate activities through rules and
procedures reduce role conflict and role ambiguity
because required behaviours are specifically outlined
(House and Rizzo, 1972; Rizzo et al., 1970). ‘Information
analysis’ refers to the quality and timeliness of information
within the organization. Quality and timely information
facilitates better decision making (Lin and Brian,
1996; Loke et al., 2010) and this subsequently reduces
role ambiguity at work. According to Gunasekaran et al.
(1994), the presence of reliable and timely information is
important because it reduces the probability of role
conflict between two or more departments. In a recent
study by Tan et al. (2010), a higher emphasis on quality
was also found to increase knowledge sharing behaviours
among individuals, and in certain cases among the
members of the supply chain itself (Loke et al., 2010).
This increase in knowledge sharing behaviours is
postulated to reduce role ambiguity because information
flows smoothly within the organization and its supply
chain. Furthermore, Chong et al. (2010) sheds light on
the possibility that TQM firms are also more likely to
adopt new technologies to ensure the smooth flow of
information within the supply chain. Next, ‘strategic
planning’ refers to the process of translating goals into
action plans that permeate every layer of the organization
(such as strategic, tactical and functional layers). TQM
firms that implement strategic planning thus improve goal
convergence between these three layers (Ketokivi and
Castaner, 2004) and this reduces role conflict and role
ambiguity. ‘Customer-oriented’ firms are generally more
in-tuned to their customer’s needs (Gatewood and
Riordan, 1997) and therefore groom employees to reflect
more customer-oriented behaviours. Because customeroriented
firms train employees to be better equipped to
serve customers, this reduces the level of role ambiguity
faced by employees when serving these customers
(Singh, 1993). According to Parkington and Schneider
(1979), customer-oriented firms are also more closely
associated with lower levels of role stressors among its
employees. Pertaining to the ‘human resource focus’
dimension of TQM, although found in certain studies to
have a positive relationship with role conflict, nevertheless,
it is still a valid predictor of role stressors when
incorporated into the TQM model as a whole (Teh et al.,
2009a, b). As literature generally advocates that TQM
practices reduce role stressors, we therefore propose
that:
P1: TQM practices have a negative relationship with role
stressors.
Teh and Ng 7183
Propositions between role stressors and strain
In general, role stressors increase strain, as role stresssors
are categorized as a type of hindrance-based
stressor (Gilboa et al., 2008). Pertaining to our first
dimension, ‘role conflict’ increases ‘strain’ and the positive
relationship between these two constructs have been
widely supported across literature. It is important to note
that within stress literature, another synonym for strain is
also ‘emotional exhaustion’ (Lee and Ashforth, 1996).
Across literature, higher levels of role conflict have been
found to be associated with higher levels of strain
(Brewer and Clippard, 2002; Cordes and Dougherty,
1993; Singh et al., 1994; Ngo et al., 2005; O'Driscoll and
Beehr, 1994; Lee and Ashforth, 1996), anxiety and
tension (Jackson and Schuler, 1985: Schaubroeck, et al.,
1989), distress (Floyd and Lane, 2000) and frustration
(Keenan and Newton, 1984). In certain cases, role conflict
was also found to be the strongest predictor of strain
compared to the other stressors (Maslach and Leiter,
2008). The rationale for the positive relationship between
role conflict and strain is explained by the fact that when
conflicting role demands arise (such as when employees
faces conflicting pressures from each role), the continuous
exposure to this form of stressor takes a heavy toll
on the employees’ psychological wellbeing (such as
higher strain levels).
The positive relationship between ‘role ambiguity’ and
strain has also been widely supported across literature.
Higher levels of role ambiguity have been associated with
higher levels of strain (Lee and Ashforth, 1996; Maslach
and Leiter, 2008; Ngo et al., 2005; O'Driscoll and Beehr,
1994), anxiety and tension (Jackson and Schuler, 1985;
Keenan and Newton, 1984; Schaubroeck et al., 1989),
higher stress levels (Wallace et al., 2009) and even
burnout (Cordes and Dougherty, 1993). Schaubroeck et
al. (1989) explains the rationale for this phenomenon by
stating that the long-term exposure to role ambiguity
increases strain because individuals who are unduly troubled
about how to proceed with a critical task experience
frustration. This frustration eventually builds up and
results in tension, and if left unchecked would eventually
lead to strain.
As findings across literature strongly support the
positive relationship between role stressors and strain,
the converse would also be true, whereby lower levels of
role stressors would also be associated with lower levels
of strain. Thus we posit that:
P2: Role stressors have a positive relationship with strain.
Therefore, lower levels of role stressors are associated

7184 Afr. J. Bus. Manage.
with lower levels of strain.
Propositions on the moderating effect of
counterproductive behaviour
It is a fallacy to assume that coping mechanisms are not
necessary just because TQM practices reduce role stressors.
With reference to the study by Teh et al. (2009a, b),
TQM practices only account for between 19 to 25% of the
variation in role stressors, with the remaining variation
being unaccounted for. This means that although TQM
practices reduce role stressors, TQM does not completely
eliminate the existence of role stressors. This argument is
supported within TQM literature itself, as studies have
revealed that role stressors remain to be part-and-parcel
of TQM firms, and are continually present even within the
best TQM firms (Hartline and Ferrell, 1996; Victor et al.,
2000). Therefore, because TQM practices do not completely
eliminate the existence of role stressors, some
employees may instinctively engage in coping strategies
to further reduce the ‘residual’ amount of these role
stressors. Within stress literature, these behaviors (e.g.
behaviors that reduce the residual amount of role
stressors) may be instinctual, as individuals automatically
protect themselves from threats if the environment (e.g.
the TQM firm) fails to completely eliminate it (Gross,
1998; Scapini, 2001; Skinner et al., 2003). Furthermore,
within neuroscience literature, these behaviors may even
occur at the subconscious level, as part of an individual’s
subconscious drive to defend against threats (Lawrence
and Nohria, 2002; LeDoux, 2000; Winkielman and
Berridge, 2004).
Coping behaviours are described by Folkman et al.
(1986) as behaviours that aim to conserve emotional,
cognitive and physical resources by either eliminating the
stressor (that is, the stimuli) or reducing the negative
emotional outcome (for example, the strain). Two types of
coping behaviours are highlighted within stress literature,
namely problem-focused coping and emotion-focused
coping (Skinner et al., 2003). ‘Problem-focused coping’
occurs when employees directly target the source of the
problem (that is, tries to eliminate the stressor).
Employees select this type of coping strategy when the
‘stressor’ is perceived to be within their control. ‘Emotionfocused
coping’ on the other hand occurs when
employees try to reduce the negative emotions (that is,
reduce the strain) that arises during the stressful event.
Employees select this type of coping strategy when the
‘stressor’ is perceived to be beyond their control
(uncontrollable). With reference to our study, Wallace et
al. (2009) classifies role stressors as an ‘uncontrollable’
type of stressor. As a result, because employees in TQM
firms perceive role stressors to be uncontrollable they will
therefore engage in ‘emotion-focused coping’ rather than
problem-focused coping. Hypothetically, if ‘emotionfocused
coping’ really does occur, then a significant
reduction in ‘strain’ levels would be an indication of
successful versus unsuccessful coping among TQM
employees.
This brings us to the next important section of our
paper, counterproductive work behaviours. CWB has
been traditionally perceived to be behaviours that are
harmful to the organization, and therefore perceived to
warrant strict disciplinary action (Robinson and Bennett,
1995). Spector et al. (2006) outlines a typology of five of
these behaviours namely: abusing others, sabotage,
theft, production deviance and withdrawal. However, a
recent and groundbreaking study conducted by Krischer
et al. (2010) revealed that there is more to CWB than
meets the eye. With relevance to our study, the authors
discovered that ‘withdrawal’ (for example, taking longer
breaks than allowed, arriving late, leaving early) actually
improved productivity because these behaviours significantly
reduced the amount of strain felt by employees
when exposed to stressors. ‘Withdrawal’ was discovered
to be a type of ‘emotion-focused coping’ strategy used
during stressful situations. Employees that engaged in
withdrawal behaviours were found to do it out of necessity
to reduce strain, rather than to harm the organization.
Technically speaking, withdrawal was found to moderate
the stressors-strain relationship, whereby engaging in
withdrawal behaviours reduced the long-term strain felt
by these employees.
The rationale for this phenomenon is strongly supported
within stress literature. Within stress literature,
withdrawal allows employees to temporarily replenish
emotional resources by taking time out from the stressful
environment. For example, leaving work early or taking
longer breaks enables employees to temporarily escape
a situation that induces negative emotions. These findings
reflect similarities with a study by Westman and
Etzion (2001) whereby blue-collar employees that spend
time away from the workplace had significantly lower levels
of strain. Furthermore, while spending time away,
negative feelings induced by the stressors dissipate, and
“emotional homeostasis is restored” (Krischer et al.,
2010). This defensive coping mechanism is described as
the process of ‘emotional regulation’ by Gross (1998),
whereby the author states that individuals may deliberately
avoid situations to safeguard themselves from unwanted
emotions. In a meta-analysis conducted by Darr
and Johns (2008), deliberate absence from stressors was
found to reduce strain, and the various psychological and
physical illnesses along with it. Being temporarily away
from work gives employees the opportunity to temporarily
escape stressors, and this protects them from long-term
strain (Etzion et al., 1998). Additionally, Fritz and Sonnen

tag (2005) highlight the benefits of temporary withdrawal
during the weekends, as it allows employees to go
through an important rejuvenation process that replenish
emotional resources that were previously depleted.
To recapitulate, because TQM practices do not completely
eliminate the existence of role stressors, some
employees may instinctively engage in coping strategies
(such as withdrawal) to further reduce the residual
amount of these role stressors. This is done so as to
weaken the stressor-strain relationship within the model.
Thus, building our model on previous empirical findings,
we propose that:
P3: CWB (for example, withdrawal) moderates the
relationship between role stressors and strain.
This is such that the positive relationship between role
stressors and strain becomes weaker when withdrawal
behaviours increase.
THEORETICAL IMPLICATION
Our conceptual model contributes to TQM literature in
three ways. Firstly, our model extends previous work
done on the ‘TQM-role stressor’ relationship by adding in
a ‘strain’ component (thus focusing on the actual outcome
of stress, and not just the stimuli of stress as done in
previous studies). Secondly, our model suggests that
TQM practices do not completely eliminate the existence
of role stressors (Hartline and Ferrell, 1996; Victor et al.,
2000) and therefore, some employees may instinctively
rely on coping strategies to further reduce the ‘residual’
amount of these role stressors. Such behaviors are
instinctual in nature, because individuals automatically
protect themselves from threats that the environment (the
TQM firm) fails to completely eliminate (Gross, 1998;
Scapini, 2001; Skinner et al., 2003). Thirdly, our model
challenges the traditional notion that all components of
CWB are detrimental for TQM firms. Although withdrawal
has been traditionally perceived to be harmful for
organizations, our model proposes that employees
engage in withdrawal out of necessity to reduce strain,
rather than to solely harm the organization (Krischer et
al., 2010).
MANAGERIAL IMPLICATION
The proposed model serves important managerial
implications because withdrawal behaviors, traditionally
perceived to warrant disciplinary action, should instead
be viewed in a different light. Withdrawal may be done
out of necessity rather than to deliberately harm the
Teh and Ng 7185
organization. This is especially true for jobs highly
susceptible to stressors. Two important managerial
implications stem from the model. Firstly, it is important to
create awareness among managers and supervisors
when dispensing disciplinary action on subordinates
found to have engaged in withdrawal (for example, taking
longer breaks, leaving early and coming late).
Disciplinary action should be exercised with discernment,
by taking into consideration the previous track record of
these subordinate and to gauge the intensity of role
stressors the employee is exposed to on a daily basis.
The next managerial implication pertains more to
employees that resist the urge to withdraw due to various
commendable reasons (such as high level of personal
accountability, highly responsible individuals). It is
recommended that these employees be given adequate
opportunities to withdraw, albeit different ways. Although
annual leave may be viewed as a good means for these
employees to recover and rejuvenate, in reality, despite
the accumulation of annual leaves, certain category of
employees (especially those that hold relatively important
positions in the hierarchy or hold critical roles that no one
else can substitute) may find it hard to exercise their
liberty to withdraw. Therefore, it is recommended that
organizations provide sufficient opportunities for these
employees to do so. This can be done via pre-allocated
vacation slots for these employees, or via training their
second-in-command to competently handle their post
while the former is away rejuvenating.
CONCLUSION
As a conclusion, our model proposes that TQM practices
and CWB co-exist together in a single framework to
explain how strain levels are reduced. Our conceptual
model contributes to TQM literature in three ways: Firstly,
our model extends previous work done on the ‘TQM-role
stressor’ relationship by adding in a ‘strain’ component
(thus focusing on the actual outcome of stress, and not
just the stimuli of stress). Secondly, our model suggests
that TQM practices do not completely eliminate the
existence of role stressors, and therefore some
employees may instinctively rely on coping mechanisms
to reduce the residual amount of these role stressors.
Thirdly, our model challenges the traditional notion that all
components of CWB are detrimental for TQM firms.
Although withdrawal has been traditionally perceived to
be harmful for organizations, our model proposes that
employees engage in withdrawal out of necessity to
reduce strain, rather than to deliberately harm the
organization (Hartline and Ferrell, 1996; Victor et al.,
2000). The proposed model serves important managerial
implications because withdrawal behaviors, traditionally
perceived to warrant disciplinary action, should be viewed

7186 Afr. J. Bus. Manage.
in a different light.
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African Journal of Business Management Vol. 5(17), pp. 7188-7197, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.144
ISSN 1993-8233 ©2011 Academic Journals
Review
A survey of empirical studies on management
ownership
Mahdi Salehi 1 * and Bahram Baezegar 2
1 Islamic Aazad University, Takestan Branch, Iran.
2 Islamic Aazad University, Bousheher Branch, Iran.
Accepted 16 May, 2011
The current study reviews relationship between management ownership and firm performance with
regard to empirical evidences. Although in the financial literature, management ownership is suggested
for reduction of agency problem, there are contradictory view points on this suggestion. Some
empirical studies show that increasing equities of managements can be responsible for better
alignment of the monetary incentives between the managers and other equity owners. In contrast, other
studies support the entrenchment argument hypothesis. The hypothesis stats that increasing of
management’s equity can contribute to reduce financial performance and may it creates control
problem, when level of management ownership is high. In disputation between the incentive alignment
and entrenchment argument, combined argument and Stultz's integrated theory arise. These arguments
which are integrated by other arguments show that corporate performance is a non-monotonous
function of management ownership. In spite of these arguments, some scholars believe that
management ownership has a passive role in corporate governance, because of being a function of
financial performance. However, others state that there is absolutely no relationship between
management ownership and financial performance. In circumstances, perhaps a new combination of
ownership alternative mechanisms can do work competently.
Key words: Management ownership, agency problem, financial performance.
INTRODUCTION
The relationship between ownership structure and firm
performance has been an important subject and an
ongoing debate in corporate finance literature since the
work of Berle and Means (1932). They debated about
conflict interests between controllers and managers.
They assert, that in view of growing diffusion of ownership,
ability of shareholders to control managements will
be less. Therefore, they suggest that correlation between
ownership concentration and firm performance should be
a negative one.
Corporate governance studies have addressed that
problems are generated by the separation of ownership
and control. Scholars have tried to find a device to solve
agency problem. They prescribe a variety of possible
solutions to align managerial interests with shareholders’
*Corresponding author. E-mail: mahdi_salehi54@yahoo.com.
interests, including such devices as high corporate
leverage, more effective monitoring by the board of directors,
which is of special interest in this paper- managerial
ownership. Agency theory suggests that the structure of
corporate ownership can affect firm performance by
alleviating agency conflicts between management and
shareholders (Putterman, 1993). By the same token,
Jensen and Meckling (1976) argue that increased levels
of managerial share ownership in a firm helps align the
interests of owners and managers and therefore, mitigating
agency problems. However, Demsetz (1983) and Fama
and Jensen (1983a) amongst others, argue that managers
get entrenched when there is high managerial share
ownership, thereby exacerbating the agency problem.
Although studies to reduce conflict between incentives
of shareholders and managers have presented a number
of possible solutions, it is worth noting that there are open
questions concerning the relationship between managers
and corporate performance. It is not clear whether firm

performance depends on fraction of shares owned by
managers and denominated shares of company to
managers can create a motivation for better performance.
This paper reviews a considerable number of hypotheses
and prominent researches about relationship between
managerial ownership and financial performance for
finding near accurate answer to the above questions.
AGENCY PROBLEM
The agency theory was formularized in the 1970s; it
originated from economics and developed in to the
domain of finance as a means to examine the relationship
between owners and managers. The problems created
by the separation of ownership and control are not
new issues. Smith (1776) first raised questions about the
separation of equity from control and whether corporations
could be managed optimally for shareholders. Smith
(669 to 700) writes about the case when control is
separated from ownership in joint stock companies: “The
directors of such companies, however, being the managers
rather of people’s money than of their own, it cannot
be well expected, that they should watch over it with the
same anxious vigilance with which the partners in private
copartnery frequently watch over their own. Like the
stewards of a rich man, they are apt to consider attention
to small matters as not for their master’s honour, and
very easily give themselves a dispensation from having”
Exactly two hundred years after Adam Smith, a theoretical
foundation for the agency problem was provided
by Jensen and Meckling (1976).They defined the agency
relation as a contract between one or more persons as
principal that engages another person as agent to
perform some services. Under this agreement, some decisions
making authority are delegated to the agent. They
state that the firm is a legal body that serves merely as a
nexus of contracts for agreements between managers,
shareholders, suppliers, costumers and other parties.
Each number of the contract acts out of self-interest. In
fact, shareholders, debt holders and managers parties
have different interests and perspectives regarding
values of the firm. Shareholders will tend to maximize
their shares, forcing managers to act their interest despite
of the debt holders’ interests. Debt holders on the other
side will protect their fund already placed in firm with
covenant and strict monitoring policy. Indeed, they
suggest that because of the fact that shareholders are
not involved in the daily company activities, corporate
governance mechanisms are important in monitoring
managers, thereby aligning their interests with those of
shareholders. The reverse of the afore viewpoint, Shleifer
and Vishny (1997) state that professional managers are
hired by shareholders to run the firm’s business with the
aim of maximizing corporate profit and shareholder’s
wealth, but in the act, the managers do not follow the
shareholder’s interests and pay less attention to promote
Salehi and Barzegar 7189
efficient allocation of resources. In other words, the
separation between ownership and control in the modern
corporate organization give rise to agency problems. The
first problem arises when there is conflict between goals
of the principal and agent. In this condition, it is difficult
for owners to confirm what goals managers pursue. The
second problem is risk sharing that arises when the
principal and agent have different attitudes toward risk
(Fama, 1980b; Eisenhardt, 1989). Agency theory is
concerned with resolving these problems.
However, when a firm is not completely owned by management,
agency cost is raised between management
and other parties. To align the interests of managers and
shareholders, principals incur incentive costs related to
the design of monitoring systems that control self-serving
activities of managers. Agents incur bonding costs to
ensure that their actions will be compatible with the best
interests of the principals. Finally, there is the residual
loss, which is the reduction in wealth that occurs when
the agent does not act in the best interests of the principals.
However, the principal or the agent is not able to
ensure that the agent will make optimum decisions from
the principal’s viewpoint at zero cost (Jensen and
Meckling, 1976).
As Figure 1 shows, there are some incentive
mechanisms that may affect financial performance and
reduction of agency problem. Since the major emphasis
on this paper is especially on managerial ownership,
different mechanisms which can have influence upon
financial performance are described briefly, then the
study reviews some hypotheses and empirical studies
over relationship between ownership managerial and firm
performance.
Decision systems
One of the most important factors directly related to financial
performance is decision system. According to Fama
and Jensen (1983a, b), decision systems are defined as
the system by which corporate decisions are distributed
between the general assemble, the board of directors
and the management. In addition, it can prevent the raise
of issues in the corporate charter of relevance, for the
distribution of control.
Performance monitoring systems
Performance monitoring systems are able to provide
possibility of the firm's constituencies to gather and analyze
information about the firm. Cash flow approach that
fundamental value analysts use to estimate corporate value
and corporate disclosure rules, are good illustrations
of this system. Jensen and Meckling (1976), and
Copeland et al. (1996) are classic references on the
system.

7190 Afr. J. Bus. Manage.
Decision systems
Bankruptcy
system
Remuneration
systems
Product market
competition
Figure 1. Effective incentive mechanisms on financial performance.
Remuneration systems
Hart and Holmstrom (1987) suggest remuneration
systems as incentive based compensation systems. They
believe that the mechanism of remuneration can regulate
the pecuniary compensation of managers for their ‘sale’
of management services.
Bankruptcy systems
According to Smith and Warner (1979), bankruptcy
systems are defined by the bankruptcy procedures. To
transfer control of a company from stockholders to
creditors when a firm goes bankrupt, can be illustrated by
bankruptcy system.
Creditor structures
The creditor structure describes how distribution of debt
firm takes the identity of the creditors into consideration.
In financial literature, Berle (1926), and Stiglitz (1985) are
known as two references on creditor structures.
Capital structures
The capital structure refers to the combination of funds, in
Performance
monitoring
systems
Financial
performance
Ownership
structures
Creditor structures
Capital structures
The market for
corporate control
The market for
management
services
the form of debt and equity. In other words, it is the firm’s
policy with regard to leverage and dividend payments.
The market for corporate control
The market for corporate control, defined as shares of
firms, are traded, and in large enough blocks, this means
control over corporations is traded. That puts some
pressure on managers to perform; otherwise, their corporation
can be taken over. Two classic references on the
market for corporate control are Manne (1965) and Marris
(1964).
The market for management services
The market for management services refers to the market
for managerial labor. A classic reference on the market
for management services is Fama (1980b).
Product market competition
There are two product market competitions that are
relevant in corporate governance; first is competition in
the firm's product markets and second is competition in
the product markets of the firm’s owners. A classic

eference on product market competition is Hart (1983).
MANAGERIAL OWNERSHIP
Managerial ownership became important in the 1980s,
although the debate on relationship between managerial
ownership and firm performance dates back to Berle and
Means’ thesis (1932). Managerial ownership is defined by
Zhou (2001) as “the aggregate number of shares held by
the CEO, including restricted shares but excluding stock
options, expressed as the percentage of the firm’s total
shares outstanding”. Similarly, this definition to explain
managerial ownership has been suggested by Agrawal
and Knoeber (1996); Chung and Pruitt (1996). Moreover,
Barnhart and Rosenstein (1998) define managerial
ownership with a slightly wider scope. They defined managerial
ownership as “the percentage of shares owned
by officers and directors as a group, including shares for
which officers have shared voting power, plus shares
available for purchase and options or warrants
exercisable within sixty days of the proxy date”.
With respect to the conflict interests between managers
and shareholders, the agency theory (Jensen and
Meckling, 1976; Fama, 1980b; Leftwich et al., 1981)
suggests that share ownership by managers helps to
alleviate the conflicts of interest that exist between managers
and shareholders. Jensen and Meckling (1976)
contend that as managerial share ownership increases, a
firm’s performance increases because managers are less
inclined to expropriate wealth. Thus, this notion suggests
that the greater the ownership stake by managers, greater
the costs for not pursuing the wealth maximization
goal (Weir et al., 2002). However, Morck et al. (1988)
argue that high share ownership by managers could
result in entrenchment because they become difficult to
control. This suggests that at certain levels of ownership,
managers may have incentives to act for their own
interests at the expense of wealth maximization (Short
and Keasey, 1999). These views suggest that the
relationship between management ownership and firm
performance is non-linear.
Managerial ownership is an endogenous variable which
is influenced by differences in industry and business
environment as much as by characteristics of a firm and
its managers (Himmelberg et al., 1999); therefore, some
studies consider importance of board of directors’ characteristics,
such as board size and board composition. For
instance, Fama and Jensen (1983a) suggest that the
board has an important function of alleviating agency
costs that arise from the separation of ownership and
decision control in corporations. Short et al. (1999)
believe that the board of directors is the central corporate
governance control mechanism responsible for
monitoring the activities of managers. In the same way,
several researchers have suggested that the board size
is an important aspect of effective corporate governance
Salehi and Barzegar 7191
(Pearce and Zahra, 1992; Jensen, 1993; Yermack,
1996).
According to studies, a larger board is more likely to
have a greater range of expertise to monitor the actions
of management effectively (Beasley, 1996; Forbes and
Milliken, 1999; Karamanou and Vafeas, 2005) which is
required, not only for enhancing the monitoring activities
of managers (Monks and Minow, 2001), but also in
securing critical resources (Pearce and Zahra, 1992;
Goodstein et al., 1994; Haniffa and Hudaib, 2006). However,
others argue that a small board is more effective
(Lipton and Lorsch, 1992; Jensen, 1993; Yermack, 1996).
According to them, large boards may be less cohesive
and slow in making decisions (Lipton and Lorsch, 1992),
less-candid in discussions of managerial performance
(Lipton and Lorsch, 1992; Vafeas, 1999) and more
difficult to coordinate (Forbes and Milliken, 1999). Jensen
(1993) argues that large boards are less likely to function
effectively and are easier for the CEO to control.
Yermack (1986), by means of Tobin’s Q as a measure
of firm performance, finds an inverse relationship. He
suggests that small boards of directors are more effective.
This is consistent with Yermack (1996) and Haniffa
and Hudaib (2006) who also used the Tobin’s Q and
reported similar results. However, when they employ
return on assets, an accounting measure of performance,
they find a positive association. They argue that while the
market may perceive large boards as ineffective, they are
beneficial to the company as they provide the diversity of
knowledge that is necessary for directing the operations
of the company.
Regarding the relationship between board size and firm
performance, Holthausen and Larcker (1993) consider
board size among other variables which are more likely to
influence firm performance, but they fail to detect consistent
evidence of a relationship between board size and
firm performance. Empirically, the evidence on the
importance of board size on firm performance is mixed.
The next character that can be considerable is board
composition. Fama (1980b) and Jensen (1983)
emphasize on the degree of board independence. They
debate that non-executive directors (NEDs) can have a
viable role as an internal control mechanism. Also, they
believe that collusion between NEDs and executive
directors is implausible to expropriate shareholder wealth.
Due to labour market who indicate price of NEDs
according their performance, they try to maintain and
develop their reputations as experts.
Although financial literature argues over advantages of
NEDs, there are conflict viewpoints with proportion on
non-executive directors on the board. According to
Rosenstein and Wyatt (1990), the addition of NEDs to the
board leads to improved shareholder’s wealth. Weisbach
(1998) show that boards with higher proportion of NEDs
is more likely to remove poor performing CEOs. Moreover,
there is an expected that, the companies with a
higher proportion of NEDs are able to participate in major

7192 Afr. J. Bus. Manage.
restructuring events such as mergers, takeovers and
tender offers.
In contrast, the higher proportion of NEDs on the board
has been criticized by some researchers (Baysinger and
Butler, 1985; Patton and Baker, 1987; Demb and
Neubauer, 1992; Goodstein et al., 1994; Agrawal and
Knoeber, 1996). They argue that a higher proportion of
NEDs may have detrimental effect on firm performance.
For instance, Agrawal and Knoeber (1996) document a
negative association between proportion of NEDs and
firm performance. Moreover, results of other studies
reveal that it is hard to find a relationship between the
proportion of NEDs and performance (Hermalin and
Weisbach, 1991; Bhagat and Black, 2000; Weir et al.,
2002; Haniffa and Hudaib, 2006).
Some hypotheses and evidences
Economic questions relate to well-functioning enterprises
dating back to centuries ago. From Smith (1776) to
Marshall (1890), Marx (1894) and Schumpeter (1926),
the relationship between firm performance and ownership
structure has been discussed extensively with a lot of
attentions. In the last century, the study titled "the modem
corporation and private property" by Berle and Means
(1932) served as a reference for discussions on the vast
subject of "corporate governance" which forms the framework
of this paper: the relationship between performance
and ownership structure; especially management ownership.
However, because of different results regarding
management ownership, the authors classified previous
researches into four categories as presented thus.
Financial performance is a function of management
ownership
This category covers two sub-categories; each of them
supports different hypotheses:
1) Incentive alignment argument: This hypothesis asserts
that corporate performance is an increasing func-tion of
managerial ownership. According to Jensen and
Meckling (1976), increasing equity of management can
be responsible for better alignment of the monetary
incentives between the manager and other equity
owners.
Regarding to relation between ownership control (OC),
management control (MC) and firm performance, the
findings of the study by Leach and Leahy (1991) show
that the OC firms are significantly more profitable than
MC firms by using return on equity, return on sales,
growth of sales and growth of net assets as measures of
performance. At the level of ownership control, less than
5, 10 and 20% are never significant. More ownership
concentration causes significantly less performance in
terms of historic market value to ordinary share capital
and return on sales. Also, McConnell and Servaes (1990)
indicate that there is significant relationship between
profitability and ownership by managers and directors.
This idea that OC firms are significantly more profitable
than MC firms is supported by Larner (1970) and Steer
and Cable (1978). In this area, Monsen et al. (1968)
believe that not only OC firms are more profitable than
MC firms but they also claim that there is significant and
strong positive relationship. The result of the study
carried out by Stano (1976) showed that the strong owner
control (SOC) firms are significantly more profitable than
MC firms. McEachern (1975) stated that the OM and
external control (EC) firms are significantly more
profitable than MC firms.
In contrast, according to a survey by Thonet and
Poensgen (1979), it has been shown that OC firms are
significantly less profitable than MC firms in terms of
return on equity and market value to book value. Also
difference between MC and OC with regard to return on
stocks, growth, and variance on equity and beta risk is
not significant. Similarly, Ware (1975) show that OC firms
are significantly less profitable than MC firms with regard
to return on equity. OC firms have significantly higher net
sales to number of employees and retained earnings to
net income. With respect to subject of abnormal returns
and managerial ownership, a survey conducted by Gupta
and Rosenthal (1991) show that the abnormal returns of
a leveraged recapitalization increases marginally (10%
level) with changes in managerial ownership and
increases significantly with the level of distributable cash
flow. Han and Suk (1998) show that between abnormal
returns at the announcement of stock splits and the level
of insider ownership, there is a positive relationship. Also,
Cotter and Zenner (1994) find that successful tender offer
can have a connection with managerial ownership and it
is associated with significant abnormal returns.
On the other hand, results of research by Song and
Walkling (1993) reveal that the cumulative abnormal
return (CAR) has positive significant relationship with
managerial ownership. Other results show that probability
of acquisition attempts is significantly decreasing with
managerial ownership at the target firm. Finally, managerial
ownership is significantly lower in contested acquisitions,
compared to uncontested acquisitions. According to Stulz
et al. (1990), target CAR increases significantly with
target managerial ownership in success-ful, multiple bids.
Furthermore, bidder CAR increases significantly with
bidder management's ownership of the bidder company
(Lewellen et al., 1985).
Finally, Mehran (1995) show that firm performance
increases significantly with CEO Ownership. Moreover,
the findings reveal that there is no significant effect of
ownership by all officers and directors or ownership by
outside directors.
2) Entrenchment argument: According to this hypothesis,
corporate performance is a decreasing function of
managerial ownership. Morck et al. (1988) believe that
increasing management’s equity can contribute to reduce
financial performance. Under the circumstances,

managers may become too powerful; hence, they do not
have to consider other stockholder’s interests. Moreover,
they argue that at high levels of ownership, managements
could cause control problems. As a result, when
managers perform poorly, shareholders are not able to
dispense them.
Denis and Denis (1994) examine 72 US firms with over
50% insider ownership by managers and directors. The
findings reveal there is no difference in performance
between majority controlled firms and other firms.
Agrawal and Mandelker (1990) studied 356 US listed
firms which announced adoption of anti-takeover charter
amendments between 1979 and 1985. They employed
insider ownership by managers and directors as one of
the ownership variables to test the hypothesis. Results
reveal that CAR decreases significantly with the adoption
of anti-takeover amendments. However, there is no evidence
of a difference in CAR in different levels of insider
ownership. Moreover, this finding is confirmed by using
OLS regression. It also shows the higher decrease in
CAR, the more entrenching the amendments. Likewise,
Jarrell and Poulsen (1987) support the above findings
that CAR decreases significantly with the adoption of
anti-takeover amendments. Indeed, both the above
studies assert that managers are able to entrench themselves
using anti-takeover provisions instead of stock
ownership. In addition, the study by Jarrell and Poulsen
(1988) show that CAR decreases significantly with insider
ownership.
Malatesta and Walkling (1988) examine the effect of
the “poison pill securities” on shareholder’s wealth. Findings
show that the adoption of the “poison pill securities”
has a negatively significant effect on the shareholder’s
wealth and “poison pills” are more subject to takeover
attempts than firms in the same industries without this
right. In short, they believe that managers are able to
entrench themselves using “poison pill securities” instead
of stock ownership. Johnson et al. (1985) conducted a
study to find the effects resulting in the death of an
executive of publicity listed US firms. They tested a
sample including 53 non-anticipated deaths of senior
executives between 1971 and 1982. The findings
revealed that there was no general effect resulted from
executive death. However, there was a significant
positive return if the executive was the founder.
Boyle et al. (1998) find that insider ownership at 10%
level is negatively related to the number of anti-takeover
provisions. The finding confirms entrenchment
arguments. Finally, DeAngelo and Rise (1983) and Dann
and DeAngelo (1983) find evidences in support of
entrenchment arguments.
Relationship between management ownership and
financial performance is non- monotonous
With reference to the hypothesis which covers two
Salehi and Barzegar 7193
arguments; Stultz's integrated theory (1988) and Morck et
al. combined argument (1988), corporate performance is
a non-monotonous function of management ownership.
In fact, these models are not independent patterns to
predicate relationship between firm performance and
management ownership. Due to this, they are integrated
by other arguments, such as takeover premium,
entrenchment and incentive alignment.
Stultz's integrated theory: Stultz (1988) present a
model for predicting relationship between managerial
ownership and financial performance which is integrated
by the takeover premium argument and entrenchment
argument. According to this model, the relation is roofshaped.
Stultz believes that more equity ownership can
have positive effect on firm performance, because
managers are more competent of opposing a takeover
threat from the market for corporate control.
Morck et al. combined argument: Morck et al. (1988)
present a hypothesis based on the dominant effect of
entrenchment arguments on the incentive alignment
arguments. They argue that the performance effect of the
incentive alignment argument dominates the performance
effect of the entrenchment argument at low levels of
managerial ownership and for higher levels, around 5%
managerial ownership, the picture is reversed and for still
higher 30% ownership, the picture is reversed back once
again. In other words, the dominant effect is only for
medium concentrated levels of management ownership.
As shown in Figure 2, the empirical findings can not provide
a clean “bell-shaped relation” between performance
and ownership. For this reason, entrenchment effect will
dominate the incentive effect only for medium concentrated
levels of management ownership.In the same way,
Short and Keasey (1999) conducted a research that
covers 225 UK firms at the London Stock Exchange
between 1988 and 1992. They employ Tobin’s Q and
return on equity as performance variables. The findings
show that although squared director ownership is significantly
negative, director ownership and its cubic are significantly
positive. The comparison between the findings
of the above two studies reveal that entrenchment level in
UK companies is higher than that of US.
Keasey et al. (1994) show that relation between firm
performance and management ownership is significantly
positive and roof-shaped. Their findings support non-
monotonous relationship between performance and
ownership with emphasis on entrenchment and incentive
alignment arguments. Moreover, Hubbard and Palia
(1995) found the evidence to confirm this assertion. In a
study conducted by MaConnell and Servaes (1990), the
results showed that relation between management
ownership and profitability is significantly positive and
roof-shaped with performance.
In addition, linear regression showed that profitability
increased significantly for insider ownership between 0

7194 Afr. J. Bus. Manage.
Performance
Ownership
Incentive theory
Morck et al. argument
Entrenchment argument
Figure 2. Relationship between firm performance and management ownership regarding some
arguments.
and 5% range. In 1995, they conducted another study
based on pervious study. The only difference between
the two studies is that Tobin’s Q now is significantly
increasing with block holder ownership. According to
Hermalin and Weisback (1991), Tobin’s Q and return on
assets as Performance measure increased significantly
with CEO ownership in the 0 to 1% range and depressed
significantly in the 1 to 5% range. The findings rejected
the hypothesis that there was no simultaneity at the 5%
level. Chen et al. (1993) take three samples to examine
relation between firm performance and management
ownership. The findings show that firm performance
increases for management ownership in the range of 0 to
7% and decreases in the range 7 to 12%. In spite of
decreasing the 1976 sample in the 12 to 100% range,
performance increased for the 1980 and 1984 samples.
Also, Curcio (1994) shows that firm performance has a
negative relationship with board ownership in the 25 to
100% range.
Holderness et al. (1999) by means of two selected
sample assert that relation between profitability and
management ownership is significant in the 0 to 5%
range and this relation is significantly negative in the 5 to
25% range in the 1935 sample. But for the 1995 sample,
performance is significantly increasing for management
ownership only in the 0 to 5% range.
Management ownership is a function of financial
performance
The following arguments support this concept that
management ownership levels are related to financial
performance and root of well financial performance
depends on the ability of managers and their insights.
When value of firm increases; managers are willing to
obtain equity compensation as reward. Therefore, it is
safe to say that management ownership is a function of
financial performance. The main related hypotheses to
this concept are as follows:
i. Reward argument: As per this concept, because of
good prior financial performance, firms reward their managers
by giving them equity ownership; consequently,
better financial performance lead to more management
ownership (Kole, 1996).
ii. Insider-reward argument: According to Cho (1998),
“other things being equal, managers may prefer equity
compensation when they expect their firm to perform well
and, consequently, the value of the firm to increase. As a
result, higher levels of insider ownership are expected at
firms with high corporate values.”
iii. Insider-investment argument: Insider-investment argument
states that owner-managers may increase their
equity when they expect firm value to increase. On the
other hand, they decline their ownership when financial
performance begins to deteriorate (Loderer and Martin,
1997).
With respect to the insider-investment argument, results
of a survey conducted by Rozeff and Zaman (1998) show
that the proportion of officers and directors buying shares
significantly decreases with prior stock returns. Indeed,

the proportion has significant positive relation with the
ratio of cash flow to stock price as well as book value to
stock price. Yermack (1997) studies effect of stock option
award in 500 of the largest US firms between 1992 and
1994. Yermack claims that CAR increases significantly
after the award of CEO stock options and it is lower for
grants at predictable times. Moreover, CAR is four times
higher than average if the CEO is represented in the
remuneration committee and often after good news
announcements, there are more awards. Rozeff and
Zaman (1988) studied 698 trading events by insider and
622 trading events by outsiders. The findings show that
for both kinds of ownership, the standard CAR, with or
without transaction costs, is significant and positive. Also,
insiders have significant and positive relation with size
and e/p adjusted CAR with or without transaction costs.
Seyhun (1986) tested 59148 trading events by 769
public firms between 1975 and 1981. They consider
insider sales and purchases by officers, directors and
holder above 10% shares. They found that after insider
purchases, CAR increases significantly and decrease
after insiders sales. Indeed, CAR decreases significantly
before insider purchases and it increases significantly
before insider sales. Moreover, employing of GLS regressions
reveals that CAR increases significantly for insiders
who are both officers and directors and insider. The
findings of Loire and Niederhoffer (1968), Pratt and De
Vera (1970), Jaffe (1974) and Givoly and Palmon (1985),
showed that insiders make abnormal returns when
trading in their firm's stock.
With reference to the incentive argument versus the
insider-investment argument, the findings of Loderer and
Martin (1997) show that insider ownership decreases
significantly with performance and Tobin’s Q as
performance measure declines insignificantly with the
insider.Based on reproducing the model of Morck et al.
(1988), Kole (1996) finds that profitability is only
significantly increasing for board ownership in the 0 to 5%
range. Also, regarding running a series of lagged OLS
regressions, the result reveals that ownership is
endogenous.
No relationship between management ownership and
financial performance; Natural selection argument
With regard to Darwin's theory (1958), natural selection is
a process that occurs over successive generations. Two
requirements are essential for the occurrence of this
theory: first, having a heritable variation for some trait,
then existence of differential survival and reproduction
associated with the possession of that trait. Some researchers
believe that the theory may help to determine
ownership structure (Demsetz, 1983; Demsetz and Lehn,
1985; Kole and Lehn, 1997). Hence, financial performance
can be a basic player to determine ownership
structure. In that sense, corporations with inefficient
ownership structures will fail to survive in the long run.
Salehi and Barzegar 7195
Himmelberg et al. (1999) found endogenous evidence
of managerial ownership caused by unobserved heterogeneity
as opposed to reverse causality. In spite of their
findings of evidence of a roof-shaped, after con-trolling
for firm characteristics and firm fixed effects, they found
that there was no relationship between managerial ownership
and performance. Thomsen and Pedersen (1999)
selected a sample including non-financial firms in 12 EU
countries between 1990 and 1993. They used return on
equity to measure performance. Results revealed that
performance has negative relation with ownership
concentration but was not significant. Also, ownership
concentration is not regressed against performance.
Denis and Denis (1994) studied 72 US firms with the
above 50% insider ownership by managers and directors.
The findings reveal that there is no difference between
majorities controlled firms and other firms in performance.
The likelihood of majority control increases significantly
with family or founder involvement. Indeed, 80% of majority
controlled firms have substantial family or founder
involvement. Majority controlled firms have significantly
less outside directors and block holders. Finally, Demsetz
and Lehn (1985) show that performance by accounting
return is insignificantly decreasing with ownership by 5 or
20 largest shareholders or the Herfindal index. Ownership
by 5 or 20 largest shareholders increase significantly
by standard error of market return.
CONCLUSION
Managerial ownership has been a controversial argument
since the 1980s. Basically, debate on this subject has its
roots in agency problem. Although conflicting interests
between managers and ownership have been a motivation
for scholars that try to device a mechanism to reduce
agency problem, empirical results are so different and
contradictory. Regarding incentive alignment hypothesis,
some empirical studies try to document that giving equity
ownership to managers is a suitable remuneration to
align interest between shareholders and managers.
Therefore, in such conditions, firm performance will
improve. On the reverse side, the number of empirical research
confirms entrenchment arguments that increasing
of management’s equity leads to less consideration to
shareholders interest and finally it can create management
control problems. In the circumstances, Morck et al.
(1988) provide a moderate way between these mechanisms.
They suggest that firm performance can improve
at low management ownership level as well as at the high
level. But at medium concentrated levels, entrenchment
mechanism becomes active. In spite of these findings,
there is an argument that state levels of management
ownership are determined by financial performance.
Managers prefer equity compensations while firm value is
increasing and they decline their equity when financial
performance begins to deteriorate. Despite arguments for
and against positive and negative relationships between

7196 Afr. J. Bus. Manage.
firm performance and ownership management, some
empirical findings, such as Himmelberg et al. (1999)
show that there is no relationship between managerial
ownership and performance.The aforementioned arguments
on managerial ownership reveal that researchers
still have not been able to show clear and constant
evidences for the effect of managerial ownership on
corporate performance and retain the same view point on
this matter. Undoubtedly, only managerial ownership
cannot lead to harder work by managers and boost
performance because it may not give adequate inducement
to managers. In fact, there can be other causes for
managers’ effort to maximize shareholder’s value such as
the competition in the labor markets. Also, ownership
management is just a part of different mechanisms to
reduce agency cost. To solve this problem, perhaps a
new combination of alternative mechanisms can do work
competently. In conclusion, there is still a deep gap
between theories and fact on relationship between
ownership management and performance. Regarding
new global market’s situation, aspects of the problem
may change; therefore, future studies should focus on
this matter before it becomes too serious a global
problem. Since the conflict of interests between agents
and principals result from complex human behaviors,
maybe, further advances in physiology science to understand
better human behaviors mechanism can help us to
detect practical approaches for reduction of the agency
problem.
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African Journal Of Business Management Vol. 5(17), pp. 7198-7208, 4 September, 2011
Available Online At Http://Www.Academicjournals.Org/Ajbm
DOI: 10.5897/AJBM09.255
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
The commercialisation process of patents by
universities
Kamariah Ismail 1 *, Wan Zaidi Wan Omar 2 and Izaidin Abdul Majid 3
1 Innovation and Commercialisation Centre, Universiti Teknologi Malaysia, 81310 JOHOR BAHRU, Malaysia.
2 Dept. of Aeronautical Engineering, Faculty of Mechanical Engineering, Universiti Teknologi Malaysia, 81310 JOHOR
BAHRU, Malaysia.
3 Centre for Continuous Learning, Universiti Teknikal Malaysia Melaka, Jalan Hang Tuah, 75300 MELAKA, Malaysia.
Accepted 8 July, 2011
The commercialisation process of university patents and how the decisions were made to patent new
scientific discoveries and to commercialise them have not been studied extensively. This paper
attempts to understand in detail, the process of commercialisation of university patents from the initial
scientific disclosures through patent filings to the choice of commercialisation routes. A series of
interviews were conducted with seven directors of technology transfer offices (TTO) of UK universities.
The interviews were structured in a way so as to discover how new disclosures in their universities
were chosen to be patented and how the patents were commercialised. The interviews were recorded,
transcribed and analysed with the help of Nvivo software. Then, case and cross case analysis were
done. The result of the study showed that there are variations in practices between universities in how
they decide to patent and in the routes of exploitation. Universities do differ on which inventions need
to be patented and which route to go for their commercialisation. Universities that practice very highly
selective procedures would only patent an invention after a very thorough market analysis. But there
are universities that practiced low selective procedures; as such, they file for patent as long as the
invention fulfils an expectation of potential value. Decisions on which route to commercialise are
sought after the patent filings. Overall, only one university practice a very systematic selection
procedure, from which, inventions were patented and specific route of commercialisation was chosen.
Most of the universities based their selection criteria on motivations of the inventors, either to patent
and which commercialisation route to utilise for their inventions.
Key words: University commercialization process, invention disclosure, patent filing, commercialisation route.
INTRODUCTION
The commercialisation of technologies within universities
is increasingly important to generate university income
and in the creation of new businesses and jobs (Shane,
2003, 2004, 2005; O’Shea, 2005). Despite the importance
of commercialisation to universities as well as to
local economic development, there is little systematic
understanding of institutional practices in the commerciallisation
process of university technologies (Harmon et al.,
1997; Ndonzuau and Surlemont, 2002; Shane, 2004).
*Corresponding author. E-mail: m-maria@utm.my. Tel:
+6075591503. Fax: +6075591500.
This paper answered the research question ‘how do universities
get involved in the decision making and what are
the decision criteria in the commercialisation processes’?
In order to increase the effectiveness of the commercialisation
processes, it is important to understand who are
involved in the decision making and the criteria used, to
transform the ideas from the laboratory into commercially
viable products. This paper examined those who are
involved in the decision making processes from the
disclosure of the scientific discovery, the decision criteria
used and the route of exploitation.
This paper presents a literature review to understand
the general commercialisation process followed by the
commercialisation process as practised by universities in

the United Kingdom. The similarities and differences of
the practices between the UK universities are highlighted
as the finding of the study.
To understand the processes in depth, interviews have
been conducted with seven directors of technology
transfer offices (TTO) of United Kingdom Universities. In
addition, annual reports and universities’ web sites were
used to gather rich information on the process.
The discussion on the processes focused on institutional
factors such as sources of funding for research and
availability of the capital for spin-offs, how the decisions
to seek patent protections was arrived at, how the
decisions as to which route to exploit the patents were
reached, networking and the search for licensees, universities’
policies, ownership and overall management of the
IPRs.
It was found that only one university practice a very
systematic selection procedure, from which, inventions
were patented and from which specific route of comercialisation
was chosen immediately after the technology
disclosure. Most other universities based their selection
criteria on motivations of the inventors, either to patent
and which commercialisation route to utilise for their
inventions. Some others do practice the ‘last resort’
commercialisation route when no licensees were found
after a time.
The finding of the study would enhance the understanding
and the effectiveness of the commercialisation
process and would benefit university policy makers and
TTO managers.
LITERATURE REVIEW
General model of university commercialisation
process
The general process of commercialisation of university
technologies starts from the scientific discoveries in the
university laboratories. Generally, inventors disclose their
inventions to the TTO, although, universities do not give
any incentive for them to disclose their inventions to the
TTO. Thursby et al. (2001) found that only half of the
inventions that have economic potentials were ever
disclosed to the TTOs. In some cases, a faculty may not
realise the commercial potential of his ideas. However,
very often, they are unwilling to disclose it to the TTO
because they are afraid the application for a patent will
delay their journal publications.
The TTO then evaluates the disclosures to determine if
the inventions need patent protections. The TTO, based
on the information from the inventors, will evaluate the
market potential for the inventions and how to exploit
them. If there are potential licensees for the inventions,
global protection will be discussed depending on the
market for the inventions. If there are still no takers after
the filing date, the TTOs and the inventors will continue to
Kamariah et al. 7199
try to commercialise the invention for a period of up to
one year. After that period, attempts to commercialise the
inventions would normally be abandoned.
Normally, the decision to commercialise is either
through a license to established companies or as a
license to spin-off companies. These would normally be
the result of joint decisions between TTOs and the inventtors.
Basically, for all the universities, the decision as to
whether to file a patent application are generally based
on at least three main questions, which are similar to
those practiced by US universities (CORG, 2000;
Rootner, 2004). They are:
i. Do the inventions have no prior art?
ii. Do the inventions have commercial value to attract
commercial investments?
iii. Are there funds available within the institution or prospective
licensees to pay for the patenting cost?
If the answers are yes to all three questions, then,
universities will normally take positive steps to patent the
inventions, even though at that time, they have to make
difficult decisions due to the uncertainty of the potential
products that will utilise the technology, and their associated
markets. Delaying the decision to patent will affect
publications, and competitors might be the first to file for
patent for the same or similar inventions. If the inventors
published a paper on the invention, the patent application
can no longer be filed, as it is considered that the
invention now has prior art. Some of the universities file
for patents as quickly as they can, after the disclosure, or
immediately after a board meeting. Prospective licensees
are sought immediately after patent applications are filed.
Networking and license to established companies or
to spin-off companies
Networking is a crucial aspect in the choice of comercialisation
route. According to Colyvas et al. (2002), and
Hsu and Bersntien (1997), early network with industry
give greater chance the invention will be exploited.
Industry could advise and monitor the project according
to the market needs. These personal contacts are an
effective way to attract companies to university technologies
(Kneller, 2000; Thursby et al., 2001; Colyvas et al.,
2002; Thursby and Thursby, 2004). Universities’
technologies are unproven and normally need further
investment before any product utilising them can really
sell into the market. In addition, due to the technology
being in its early stage, it is very high risk. Moreover,
some of the technologies have a market that is so broad,
that it is difficult to identify which market to target. Thus,
network and collaboration with industry is important.
Inventions that receives early funding from established
companies and where the inventors work together with
industry teams, have greater chance of being licensed

7200 Afr. J. Bus. Manage.
to established companies.
Pressman (1999) explains why marketing university
inventions are so difficult:
“... University inventions are ‘embryonic’. At the time
a university is ready to hand over its inventions to
industry, most have not even reached the prototype
stage, much less demonstrated manufacturing and
practicality in the market. These inventions will
require substantial investments in product market
development, and many will never succeed. Thus,
the task of the university is to find industrial
licensees willing to make the high risk investment …”
Informal and formal networks with individuals and
organisations are important for spin-off formations (Birley,
1985). These networks link new firms to resources
providers such as venture capitalists, business angels,
banks and advisers as well as to potential customers.
Shane and Cable (2002) pointed out that informal networks
are important means of accessing finance, thereby
giving more chance to spin-off formations. Shane (2003,
2004) further suggests that the link to financiers give a
better chance of founders’ access to a broader network
such as suppliers, customers and other resources that a
new firm requires.
The decision to form a spin-off company depends on
various other factors. According to a survey of TTO directors,
the decision to form a spin-off company depends on
the following factors (Minshall and Wickteed, 2005):
i. technologies are considered as platform technologies,
ii. the inventors are very keen to commercialise the
technology themselves,
iii. when the idea needs to attract substantial investment
to develop more IPs relating to the initial technology for
subsequent licensing,
iv. when the technology is not readily licensable, and
v. the technology is a generic technology with many
different applications.
Spin-off formation needs technologies that have made
significant advances in a scientific field and will have
significant economic value (Shane, 2004) although they
are at the very early stage of development. The technology
needs to be cutting edge and do not duplicate
existing technologies (Shane, 2004). Furthermore, the
technology must be in demand and it is expected to bring
in substantially more profits than alternative technologies
(Amit et al., 1995). Small and newest spin-offs always
invest in uncertain technologies (Shane, 2002, 2004).
Lowe (1996) also found that most of the spin-off
companies at the University of California were founded
because established firms were unwilling to license these
technologies. Thursby et al. (2001) surveyed 62 TTOs in
US and they found that established firms tend to license
university inventions at the later stages.
Most universities also have links and investments in
their incubators. The role of the incubators is to nurture
spin-off companies until they are mature and ready to
compete in the open market. The incubators provide
common facilities for new firms with a lower market price
than other places and management support services.
Various studies have reported on the direct and indirect
roles of incubators in spin-off formations (Rogers et al.,
2001; Phillips, 2002; Grimaldi and Grandi, 2003;
Georghiou, 2001; Markman et al., 2005b; Siegal, 2006).
Some universities are now creating holding companies
for their spin-offs such as Qubis Ltd in Queen’s University
in Ireland (Blair and Hitchen, 1998; Leitch, 2004; Leitch
and Harrison, 2005). This specific company is a wholly
owned subsidiary that invests in first order and second
order spin-offs from the university. It is not only a support
mechanism but is "doing business" by establishing
businesses (Leitch, 2004) and taking equity in them. In
addition, the company provides incubation facilities,
management support and help with running the company.
A university spin-off also enhances economic growth by
transforming university technologies into business opportunities.
Forming spin-off companies will have multiplier
effects, provide jobs to the local people and stimulate the
local economy (Tornatzky, 2000; Pressman, 2002;
Shane, 2004; Smailes and Cooper, 2004), as they
usually locate their operation around the university.
METHODOLOGY
This research adapted case study approach to understand the
process of commercialisation, as suggested by Yin (1984, 1994,
2003). The main argument for choosing case study as the research
strategy is the descriptive nature of the research, which does not
require control of behavioural events but rather documents them.
The dominance of ‘how’ and the exploratory ‘what’ requires an
insight to answer the research question of ‘how has the commercialisation
process of university patents taken place?” Particularly, the
question of what explains why some university patents are exploited,
and why some are not exploited. How universities decided
to patent and commercialise their patents were asked during the
interviews. In qualitative studies, the nature of research question
often starts with a “how” or a “what”, so that it will give an initial
general description on what is going on (Yin, 1994; Miles and
Huberman, 1994; Creswell, 1998; Patton, 2002).
To understand the process in practice, interviews with seven
directors of technology transfer offices (TTO) in UK universities
were conducted. The ‘how’ and ‘why’ questions on the commercialisation
process were asked during the interview as suggested by
Yin (1994). Four are from Scotland and three from England.
Scottish and English universities were chosen to get a holistic view
of the process in the UK, and to see if there is any difference in the
Scottish and English practices. The interviews were recorded,
transcribed and analysed using Nvivo software.
Within case analysis, it typically involves a detailed case study
write-up for every case (seven universities). Eisenhardt (1989)
contended that there is no standard format for this analysis, and it
often involves pure descriptions to help researchers to get insight of
the early analysis process. Miles and Huberman (1994) suggested
that case analysis involves going back and forth through the
interview transcripts to compare the data from different transcripts
and to repeat examples of the themes and sub themes (Miles and
Huberman, 1994). Cross case analysis were then conducted to

understand the process and identify salient points in the practices
of each TTO.
FINDINGS
The invention disclosures
Disclosure to the TTO would normally briefly describe the
idea of the new discovery, technology or invention, on
what platform it has been developed and so on. Other
types of information included in a disclosure form typically
are:
i) Name of the inventors.
ii) Who funded the research that led to the inventions?
iii) Has there any publication on the inventions?
iv) Potential commercial market.
v) Companies that may be interested in licensing the
discovery.
The University of Southampton is proactive and is quite
different from the other universities studied. The Centre
for Enterprise and Innovation (CEI) at the university has a
group of managers recruited from industry. These
business managers will seek out a business partner,
identify opportunities, and then draw up business plans
for technologies they selected for commercialisation. The
CEI will then bring the resources required from within the
CEI to implement the plan (Minshall and Wicksteed,
2005). In addition, it has an academic representative
within every department and these representatives give
specific briefings to the academics on patenting activities
and the role and importance of patents to encourage
academics to disclose their inventions. Courses are also
given to the academics to familiarise them with the
patenting activities and procedures.
How the decision to patent arises
The decision to patent and how they were arrived at are
different among universities. The differences are due to
the supportiveness and selectivity of the TTOs, depending
on who is involved in the patenting process, the
resources available to them, and the skills and
experience of the TTO staff. Most of the universities,
especially Warwick University, University College
London, Glasgow University and Southampton
University, are very selective on what types of inventions
they patented. Some of the TTO directors have full
control over which invention is going to be filed for patent
and which exploitation route to take, even though the
views of the academic inventors are always sought.
The inventions will be evaluated for potential applications
and patent protection potential. At this level, the
personnel who are involved in the decision to proceed, or
otherwise, to patent application, and how to conduct
Kamariah et al. 7201
market research differ between universities. Initially and
generally, inventors and the TTO directors or the TTO
Director himself will decide whether or not to patent the
inventions.
In some cases such as the University of Edinburgh, the
discussion initially is between the inventors and the
business development managers of the TTO. These
people would decide whether the inventions should be
patented. They would also discuss the initial possible
applications and markets for the inventions. Their
decisions are then reported to the Director of the TTO
and the Director will decide whether to patent the inventtions
and whichever route to exploit it. On the other hand,
at Herriot Watt University, inventors and board members
will have a meeting together to decide, the board consists
of six internal members and a few experts external to the
university. At the University of Glasgow the Business
Management team is involved at this stage. The team is
made up of nine members and one secretary. Some
universities like the University of Strathclyde have a
second meeting with committee members. The university
has a small committee comprised of the TTO Director,
IPR officer or the TTO representative and a patent agent.
In the selection process, the University of Warwick has
the most systematic method and is very selective with
regard to the characteristics of the inventions that would
influence the decision to file for patent or otherwise. The
University of Warwick also has a special and comprehensive
evaluation form compared to other universities. It
uses a scoring system to identify the market potential of
the inventions with 10 dimensional rating scales.
Each project should be scored from 5 (excellence) to 0
(very poor) on each dimension. Scores on each of the ten
scales can be totalled and doubled, to give a score out of
100. If the marks scored were more than 56%, the inventtion
will be filed for patent. University of Southampton and
Warwick University would normally have identified the
market size and the potential value of the inventions, and
also identified who are the players in the field and their
potential customers before filing for patents. Other
universities totally rely on their inventors for market
information on the inventions. Only inventions that have
commercial value and that need protection are patented.
Finding licensees and networking
Most of the universities only start to find licensees
immediately after the patent is filed, for the obvious
reason of prior art. Several strategies are implemented.
The strategies are similar to those in US universities. The
strategies implemented and how licensees are chosen is
explained further.
Licensing strategies
Most of the universities applied similar methods in their

7202 Afr. J. Bus. Manage.
marketing strategies to find licensees. Involvement of the
inventors from the beginning is important until the
identification of the specific market for the inventions.
Usually, the universities together with the inventors will
identify the prospective licensees immediately after they
file for patents. Universities use their web sites, flyers,
conferences and seminars to advertise technologies that
are patented and available for licensing. On the web
sites, the general background and the potential applications
of the technologies are explained. However, the
web sites do not work very well. The most effective strategy
was to find all the active companies involved with
particular technologies and approach them either by mail
or direct personal contacts. A face-to-face meeting will
then follow if the company is interested in the technologies.
One of the TTO directors commented:
“… all universities use the initial contact of
academics to market their technologies. The TTO
will assist them in negotiating contracts and contract
agreements. The TTO will study what are the
commercial values of the technologies and how
much time they [need to] spend to bring the
inventions to the market. The value of technology
becomes higher when the period to produce is
shortened. The product [could] become a market
leader before other companies could introduce their
products [using the same technologies] …”
“… The difficult stage is to find the companies that
could be the potential licensees and who are willing
to give support to the technology. Most of the
licensees are from US companies. Companies in the
United Kingdom are poor in R and D and are much
less likely to support technologies from universities
[this is supported by Steil et al. (2002) and Bower
(2003)]. In addition universities target few potential
licensees and tend to build long-term personal
contacts in the industry. At this stage, universities
always have a problem convincing the prospective
licensees of their technologies.”
Universities usually target worldwide markets for
licensing, especially when licensing to established companies.
The University of Southampton has an invention
involving infrared (IRed), which attracted interests from
major companies around the world, especially Korean
and Japanese. The same thing happened to the
University of Strathclyde with its anti obesity drug, which
was granted a patent in 1995/1996. This patent attracted
one Korean company to collaborate and to conduct
further research into the drug and invest to the tune of £ 1
million.
Exclusive or non-exclusive license within a field (or
in all fields) and the distribution of royalty
A licence granted by a university may be non-exclusive
(licences may be granted to a number of companies) or
exclusive (granted to one company only). Universities
grant exclusive licences when the investment to develop
the technology is high-risk. Exclusive licences are granted
to permit licensees the right to develop the technology
without fear of competitors. The patent can also be
licensed exclusively, but limited to certain applications or
methods of use of the technology, or limited to a certain
geographical area or nations. Universities sometimes
grant exclusive licences where the industry funded the
research. The University of Southampton for example,
gives exclusive licenses to Glaxo who funded research
on pharmaceutical products.
If an exclusive licence is granted to a company, the
university must monitor and ensure that the company
works hard to develop the invention and not just shelve it.
Some companies may want to license the invention in
order to prevent the invention from threatening their
existing products.
Diligence provisions are an important part of any negotiation
with licensees. In these provisions, the company is
required to specify the number of people in the company
assigned to develop the invention and the amount of
funding it will commit. It must also specify the date when
the prototype of the product will be completed, the date
when the first product must be sold, and dates by when
sales levels must be achieved. Diligence provisions are a
mandatory contractual commitment. If these terms of the
provision are not met, the university may cancel the
licence or the university may make it non-exclusive,
thereby regaining the option to grant licences to others
(CORG, 2000).
The distribution of royalty incomes varies across universities.
Revenues are generally distributed according to
a formula that has been adopted by the university. Most
of the universities implement sliding scales, with a higher
share for the inventors in the early years of a licence
when the royalty returns tend to be lower. The royalties
will be distributed between inventors, inventors’ faculty
and to the university general funds.
Decision to commercialise through spin-off or
licensing
Academic staff aspirations and interests are considered
when deciding the route for the exploitation of intellectual
properties. There is a similar process in the US
universities.
Most of the universities have discussions with the
invent-tor as to which route they want for the exploitation
of their inventions. However, in certain cases, the TTO
Directors have the final say as to which route is to be
utilised, such as Edinburgh, Southampton, Strathclyde
and Warwick Universities.
Some universities preferred to license their intellectual
properties to established companies rather than to form
spin-off companies, for example, the University of

Figure 1. Stages of funding in spin-off development.
Glasgow and Heriot-Watt University. Similarly, the University
of Glasgow prefers to exploit their technologies by
licensing to established companies because it is less
risky. However, based on the interviews with the TTO directors
for this study, generally, it is apparent that several
other factors influence the universities’ decision to form
companies. Many universities consider that if the
technology is of advanced type, at a very early stage, has
potential value, together with the availability of resources
and when there were no licensing takers, then,
universities have to take the risk of forming a company.
The details factors are discussed further.
Academics commitment
Academics’ aspirations and commitments are very
important and are the main factors considered in forming
a company. At the first stage, universities consult with
academic inventors as to which route to the market they
prefer to exploit. Then, market analysis would be
conducted: who the competitors are, market accessibility,
and the market size. Inventors are not necessarily equity
members of the company but their minimum involvement
is required to ensure the development of the technology,
such as being a consultant to the spin-off company. The
academics’ commitment is crucial if the licensing route is
chosen when the technology is at an early stage. Without
the academic’s contribution and involvement, the
chances of success are limited. As one of the TTO
directors reported:
“… The report comes to the Director of ERI and that
report makes recommendations as to whether we
should protect, how we should protect and how to
exploit the inventions. The technology exploitation
route can be to set up a company, to license the
technology through existing firms, or may be to take
some contract research and to continue research
with support from the existing companies. The
start up
Kamariah et al. 7203
decision as to which route to go forward, is basically
decided by the Director. The decision always takes
academics’ wishes into account because they have
to work with us to exploit the technology …”
Another TTO director said:
“… The decision to form a spin-off company is made
based upon discussions with academics and one of
the university signatories. This is due to the cost
involved in the formation of spin out company. We
then quickly look for outside funding and investors.
Sometimes academic staff can bring in investors and
put their own money into the company …”
Spin-offs funding
Universities need external funding to form spin-off companies.
These funding come from either government or
industry. However, since the patents licensed to spin-off
companies are usually early stage technologies, most of
the funding for seed monies comes from the government.
The UK Government has set-up the University
Challenge Funds (UFC) to encourage universities to
exploit research output and fund the early stage of
commercialisation projects. Scottish enterprise has set up
proof of concept fund to support spin-off companies.
Business angels and venture capitalists are also
important for start-ups. For post start-up, the companies
would seek capitals for further growth from venture capital
companies or go to initial public offering (IPO). Figure
1 shows the stage of technology development and the
amount investment required for each stage in a spin-off
company. It also matches the potential source of fund for
the development of the technology.
The SMART scheme and UFC provides inventors with
seed money to develop their inventions to prototype
stage and to cover patent costs, business assessment,
market research, and business plan development. The

7204 Afr. J. Bus. Manage.
initial amount given is less than £ 50, 000 for each new
company. Universities normally provide £ 5, 000 to 10,
000 to the inventors for these activities like the University
College London, University of Warwick and University of
Strathclyde. University of Strathclyde has the commercial
development fund, which is controlled by the BVG
(business ventures group). Any returns from spin-offs are
invested straight to the fund.
University challenge funds (UFC) basically funds
university spin-off companies, with amounts between £
10, 000 to 250, 000. For example, the University of
Edinburgh has its own internally managed fund called the
Integrated Company Development Scheme. The grant is
given during the pre-incubation stage. The total fund is £
4 million and each company receives a maximum of £ 75,
000. The funding is given for the first-year and includes
the cost of market survey, prototyping and additional lab
works. The university takes 10% of equity per £ 50, 000
investments. Other universities take 10 to 20% equity in
the companies.
Further development of the product or additional investment
is likely to require funding from venture capitalists
and business angels. Business angels and their network
also provide the money as investments, typically in the
range £ 50, 000 to 250, 000. Venture capital firms fund
university spin-offs at early stage of formation with
amounts up to £ 1 million, which is called venture capital
Series A. For further growth, venture capital Series B and
C could come in with amounts of up to £ 5 million and up
to £ 10 million subsequently.
Networking
Universities that have built formal networks with venture
capitalists and business angels have an advantage in
helping to narrow the market of the university inventions.
As one of the TTO assistants said:
“… We seldom go out to market the technology. We
have marketed the technologies based on having
good relationship with financiers, which includes
business angels and venture capitalists. VCs and
BAs help in narrowing the market. They will identify
the potential market before they invest in the
company. … The London Technology Network is a
good channel to link the potential industry and the
technology. It is very rare that the TTO goes to the
general market …”
In order to access more sources of capital and future
investors, universities have built external linkages. For
example, the University of Strathclyde has strong links
with Scottish Enterprise Glasgow. The University of
Southampton has a different strategy. CEI has built
strong links with a number of early stage investment
funds, including SULIS (£ 9 million), WessexBio (£ 400,
000) and IP2IPO (£ 5 million) and runs its own
presentation day annually in London. Universities have
also developed specific mechanisms to build strong
networks with industries.
Other universities have links through particular
mechanisms. The University of Warwick and Midland
universities have access to Connect Midlands and universities
in Scotland have access to Connect Scotland.
These are designed to connect technology-based companies
or inventors to potential financiers and investors.
These organisations were established with the main
objectives of generating a network for entrepreneurs,
drawing together people such as investors, business
service providers and regional key players. Events,
seminars and conferences aimed at investors are held to
present the new ideas and the latest technologies from
the spin-off companies and the universities and to build
networks. Connect events are designed to add value to
technology companies at different stages in the business
and investment life cycle. The exchange of ideas,
networking with peers, facilitating technology transfer
opportunities, meeting potential non-execs and/or
potential investors are some of the opportunities created
by such events.
Beside external links or formal networks, most
universities have internal links in order to support spin-off
companies or to give access to sources of investment
and other resources. Most of the universities have strong
internal links with their own business schools or their
Centre or Institute for Entrepreneurship, their Alumni and
incubators as suggested by Minshall and Wicksteed
(2005).
The entrepreneurship centres focus on entrepreneurship
education that provides entrepreneurial awareness
to students and faculty. Universities alumni also give
access to a broader network for new firm resources such
as the Strathclyde 100 event in the University of
Strathclyde.
When technology is radical, unique and has market
potential
Consistent with the literature reviews, most of the TTO
directors agreed that a spin-off formation is imperative
when the technology is the core resource and is of major
innovation. One TTO Director said:
“… if there is a core technology, and it represents a
big jump in technology or is a revolutionary
technology or will create major turbulence rather
than an enhancement of an existing technology,
then we look to form a spin-off company …”
Universities also consider setting-up a company, when
the technology is at a very early stage of its development
cycle, and is unique with high potential value that can be
utilised in many products. Shane (2004) also found that
university spin-offs are effective vehicles for

commercialising uncertain and early stage technologies.
Where the technology is too advanced and the potential
value is uncertain, some universities will form a spinoff
company as a last resort action, especially when there
are no licensees came forward for the inventions. For
example, where the technology really has potential value,
the University of Glasgow, will spin-off a company,
although no licensees are interested in the technology, or
licensees are difficult to find.
High expected level of return
Another consideration is the expected annual income
from a spin-off company. One of the TTO directors reported
that the university would form a spin-off company
when the expected income is more than USD 100 million
per annum. If the company is projected to bring less than
that, they would find trouble finding investors, as venture
capitalists would usually refuse to make any investment:
“… we do the technology review; for example the
modification of a microprocessor. It is not sensible to
set up a company to compete with Intel. We rather
license to Intel. We carry out the technology review;
we look at the industry; who are the competitors,
market accessibility, and the size of the market. We
are looking to build a company that at least gives
turnover of USD100m per year. That is the target. If
[it is projected to bring in] less than that, we will not
form a company. We have to look for a unique
market. … If the company is not worth more than
USD100m dollars, you cannot get investors …”
External factors
Economic factors are another consideration in forming a
spin-off company. TTO directors of the University of
Strathclyde and the University of Edinburgh both
mentioned this objective. Government or local authorities
require the development of their local economy.
However, if the universities license their technologies to
international licensees, it will reduce the chances and
opportunities to develop the local economy as mentioned
before. Another factor is the geographical position of the
market, which can lead to another reason for the creation
of a spin-off. This depends on whether the technology
has a local or international market. A local spin-off company
will directly and indirectly stimulate local economic
development, as was concluded in other studies
(Tornatzky, 2000; Pressman, 2002; Shane, 2004;Smailes
and Cooper, 2004).
If the market is outside the United Kingdom, licensing is
preferred. However, the local population does not benefit
from the development of the technology through job
creation. Moreover, the type of technology and the cost
incurred if the technology is further developed also has to
be taken into account. After consultation has been carried
Kamariah et al. 7205
out with the inventor, the university will study the amount
of finance required to create the company. What is the
cost to transform the product into the next stage; the time
line involved to take the product to market; and whether
or not the technology could be incorporated into a single
or multi products. Licensing to an established company is
safer than taking the risk of forming a spin-off company
where the costs to take the product to market are huge or
it takes a long time to harvest. A good example is the
development of new drugs or compounds.
Ownership of IPR
Universities differ in terms of their practice of the ownership
of IPR. The University of Strathclyde, the University
of Glasgow and University College London retain their
ownership of the intellectual property (IPR) even though
industry funds the research. At the University of Warwick,
Heriot-Watt University and the University of
Southampton, the IPR is retained by industry if the
industry funds the research. However, universities still
earn the royalties subsequently paid by licensees (which
may include the companies that funded the research).
Whether the IPR is owned by industry or the universities,
there are advantages and disadvantages. One of
the advantages of industry retaining the ownership is that
they own the technologies, such that they would be more
willing to invest more for further development. In addition
they can sell the patent if the venture fails (Levie et al.,
2003). The disadvantage is that the university does not
have a final say in the development of the technology that
was initially invented by them.
The University of Edinburgh, the University of
Strathclyde and Glasgow University have different
systems to other universities on students’ IPR. Undergraduate
or postgraduate students can retain ownership of
the IPR if the student does the research in the university.
Most of the universities interviewed retain the ownership
if a member of staff does the research, even though
industry funded the research, but the industry that funded
the research has the first option to license the
technology. Joint IPR between students and academics
are allowed if the project is sponsored by industry.
Strathclyde University so far, does not have any
established system for students who are doing research
in the university. According to the TTO Director, it is good
practice to oblige students to sign IP agreement if the
university funds the research.
DISCUSSION
The universities’ approach to commercialisation and their
decision making process has not been intensively
scrutinised in academic literatures. This study attempts to
understand in detail the process of commercialisation

7206 Afr. J. Bus. Manage.
from the initial scientific discovery and who made the
decisions as to the choice of commercialisation route.
The findings of this study enhance the understanding of
the process as preliminary steps to understanding the
specific processes of commercialisation of university
technologies.
The findings revealed that there are differences
between universities in how they decide to patent and in
the route to exploitation.
It is a normal practice among all the universities for the
inventors to bring their inventions to the TTOs. None of
the universities scout for invention disclosures although
inventors are encouraged to disclose inventions to their
respective TTO offices. This is because most of the TTOs
do not have enough staff to scout for the inventions.
Universities or TTOs also believed that the inventors
should be highly enthusiastic if they want to see their
inventions implemented. So, it is normal for them to
expect the academic inventors to bring their inventions to
the TTO, not the other way round.
Universities differ on the need to patent an invention.
Even though the inventors are involved, the final decision
is up to specific committee(s) or the TTO. Some universities
practise low selectivity and patent as long as the
invention fulfils the patenting criteria and is expected to
have a potential value (‘patent first and find licensees
later’). The licensee is immediately sought after the
patent filings as there is a need to patent before general
disclosure of the inventions, and to avoid competitors
from copying the inventions. Other universities license
the invention to established companies, if the technology
requires further development, needs intensive investments
and the market is world wide like a drug discovery.
Drugs need intensive investment and testing which
involves a huge amount of money. With these types of
inventions, the university usually licenses them to
established companies.
Some universities practice a highly selective procedure
and only patent the inventions that they believe have big
market potential. This means market research is
undertaken prior to filing for patent protections, as is the
practice at Southampton University. This University also
shares the cost of patenting with the inventor’s department
to ensure the involvement of inventors or faculty in
the marketing and development of the invention.
The decision to choose which route to commerciallisation
also varies between universities. Some universities
are very selective. The selection or due diligence
process starts as early as from invention disclosure.
However, the capability of the TTO to evaluate the
inventions for a spin-off company also varies depending
on the business and technical experience of the TTO.
Some universities have experienced TTOs who are proficient
in the spin-off process. University College of London
has a strong network including investors, which helps the
University evaluate the University’s inventions. University
of Warwick and Southampton University conduct
thorough market research before they decide to form
spin-off companies. Only Warwick University is very
systematic in the patenting and commercialisation procedure.
The University has a scoring system to evaluate
disclosed inventions and which mechanism to exploit. In
the case of Heriot-Watt University, they prefer licensing to
established companies. The reason is that, many of their
technologies have global applications and are very
technical. Licensing the technology to an existing
company that is already active in that field is considered
the best mechanism. However, other factors such as
resources and inventors’ commitments are also taken
into account. If the technology is at the late stage of
development, the inventors will be encouraged to take
the licensing route.
Other universities practise the ‘last resort’ decision
when a licensee is not available. However, this practice is
for the technologies that have an outstanding market
value and the inventors have high motivations. Other
factors such as characteristics of technologies, resource
availability, expected return at specific time affect the
decision making process.
The decision to award an exclusive or non-exclusive
licence depends on the strength of the patents and the
competence of the licensing companies. All the
universities practice the same procedures. Granting nonexclusive
licences mean universities can license to as
many companies as they can. This could lead to new
inventions or technologies, which could be patented and
then further exploited, as broadly as they can and using
multiple applications. However, royalty rates for nonexclusive
licences are normally a lot lower than the
exclusive licence rates. The royalty rates for exclusive
licences in the University of Edinburgh for instance, are
normally between fifteen and twenty percent of the
turnover of the products compared to between five to
seven percent for non-exclusive licences.
The ownership of the IPR varies between universities.
Some universities retain their ownership such as the
University of Strathclyde, the University of Glasgow and
University College of London even though industry funds
the research. On the other hand, for the University of
Warwick, Herriot-Watt University and the University of
Southampton, the IPR is retained by the industry if they
fund the research.
Universities in England have easier access to venture
capitalist companies compared to Scottish universities.
To attract venture capital companies they have various
links and events to exhibit their technologies. Certain
characteristics of the technologies such as a clear route
to market, size of potential market, strong management
team, viable technology and level of patent protection are
required by venture capitalists as reported by UNEI
(2004) and Shane (2004). The TTO directors who have
experience and come from entrepreneurial background
influence how they network, and they employ different
strategies in getting funding and building internal and

external networking. Finally, all the universities confirmed
that commercialisation activities are not included in the
academics’ promotional exercise. If promotion incentives
are given to the TTO or inventors who could commercialise
their inventions, this might increase the number of
invention disclosures to the TTO as argued by Thursby
and Thursby (2001).
Conclusion
This paper revealed that universities are different in how
they decide to patent and in their decisions of which route
to exploit their technologies. Universities that practice
very intense selection in their patenting and firm formation
may discourage commercialisation activities. On the
other hand, being less stringent, the universities may
encourage the inventors towards more disclosures and
patents, but they might not be successful in commercialising
the patents. This wastes university resources
such as time, manpower and money.
But overall, universities need to encourage disclosures
and from them try to pick out the very high quality
inventions to be patented and further on commercialised.
Commercialisation success of their technologies would
not only bring in monetary returns, but also prestige to
the university and to its research efforts.
Implications of the study
Understanding the process of commercialisation will
enhance the effectiveness of university TTOs in their
decision making process to patent and commercialise
university technologies. The findings of this research
points towards specific god practices that could be
adopted by university TTOs to increase effectiveness in
technology commercialisation, and pitfalls to avoid.
Limitation
The study was conducted in seven universities in the UK.
The UK patenting system and the general process might
influence the result of the study. The study did not include
the views from the inventors or the TTO staffs other than
the directors. As such, the result might be biased.
Future research
Future research should include TTO offices from other
countries, and the views of other TTO staff members
should also be sought. This will give a broader view in
understanding commercialisation process of university
inventions. Inventors’ views from the respective
universities should also be considered, as this would give
the view from the other side of the coin.
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African Journal of Business Management Vol. 5(17), pp. 7209-7215, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM10.254
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
A note on “A mixed integer programming formulation
for multi floor layout” [African Journal of Business
Management 3 (2009) 616-620]
Krishna k. Krishnan 1 and Amir Ardestani Jaafari 2 *
1 Industrial and Manufacturing Engineering, Wichita State University, Wichita, Kansas, USA.
2 Department of Industrial Engineering, Amirkabir University of Technology, Tehran, Iran.
Accepted 15 July, 2010
In the aforesaid paper, some pages are omitted reluctantly and are corrected thus. In this paper, the
two-floor facility layout problem with unequal departmental areas in multi-bay environments is
addressed. A mixed integer programming formulation is developed to find the optimal solution to the
problem. This model determines position and number of elevators with consideration of conflicting
objectives simultaneously. Objectives include to minimize material handling cost and to maximize
closeness rating. A memetic algorithm (MA) is designed to solve the problem and it is compared with
the corresponding genetic algorithm for large-sized test instances and with a commercial linear
programming solver solution to small-sized test instances. Computational results proved the efficiency
of solution procedure to the problem.
Key words: Mixed integer programming, multi floor layout, multi objective, memetic algorithm.
INTRODUCTION
One of the oldest activities done by industrial engineers is
facilities planning. The term facilities planning can be
divided into two parts: facility location and facility layout.
The latter is one of the foremost problems of modern
manufacturing systems and has three sections: layout
design, material handling system design and facility
system design (Tompkins et al., 2003).
Determining the most efficient arrangement of physical
departments within a facility is defined as a facility layout
problem (FLP). Layout problems are known to be
complex and are generally NP-Hard (Enea et al., 2005).
Classical approaches to layout designing problems tend
to maximize the efficiency of layouts measured by the
handling cost related to the interdepartmental flow and
the distance among the departments. However, the
actual problem involves several conflicting objectives
hence requires a multi-objective formulation (Aiello et al.,
2006). The common objectives to layout designing are
*Corresponding author. E-mail:
ardestanijaafari.amir@yahoo.com, ardestani.amir@aut.ac.ir.
minimizing the total cost of material transportation and
maximizing the total closeness rating between the two
departments. In some cases, they are combined as
(Meller and Gau, 1996):
∑∑
i j
( f ij cij
) d ij − ( −α
)∑∑
min α 1
i j
which is the weighted coefficient of objective functions,
that is, it shows the material flow between the departments,
it shows the cost of moving in unit distance of
material flow between the two departments, it shows the
closeness ratio between the two departments and is an
indicator which shows that when the departments have
common boundary, it is otherwise zero. Setting the parameter
α has been studied by Meller and Gau (1997).
Aiello et al. (2006) represented a two-stage multiobjective
flexible-bay layout. Genetic Algorithm (GA) was
used to find Pareto-optimal in the first stage and the
selection of an optimal solution was carried out by Electre
method in the second stage. These objectives considered
minimization of the material handling cost, maximization
r
ij
x
ij
(1)

7210 Afr. J. Bus. Manage.
of the satisfaction of weighted adjacency, maximization of
the satisfaction of distance requests and maximization of
the satisfaction of aspect ratio requests. Pierreval et al.
(2003) described evolutionary approaches to the design
of manufacturing systems. Chen and Sha (2005) presented
a multi-objective heuristic which contained workflow,
closeness rating, material-handling time and hazardous
movement. Şahin and Türkbey (2008) proposed
simulated annealing algorithm to find Pareto solutions for
multi-objective facility layout problems including total
material handling cost and closeness rating. A qualitative
and quantitative multi-objective approach to facility layout
was developed by Peters and Yang (1997). Peer and
Sharma (2008) considered material handling and
closeness relationships in multi-goal facilities layout.
Konak et al. (2006) conducted a survey on multi-objective
optimization using genetic algorithms and Loiola et al.
(2007) provided a review paper for the quadratic assignment
problem (QAP) which concerned multi-objective
QAP.
In this paper, we consider both issue of multi objective
and multi floor. Nowadays, when it comes to the
construction of a factory in an urban area, land providing
is generally insufficient and expensive. The limitation of
available horizontal space creates a need to use a vertical
dimension of the workshop. Then, it can be relevant
to locate the facilities on several floors Drira et al. (2007).
Meller and Bozer (1997) compared approaches of
multi-floor facility layout. Lee et al. (2005) used GA multifloor
layout which minimized the total cost of material
transportation and adjacency requirement between departments
while satisfied constraints of area and aspect
ratios of departments. A five-segmented chromosome
represented multi-floor facility layout. Many firms are
likely to consider renovating or constructing multi-floor
buildings, particularly in those cases where land is limited
(Bozer and Meller, 1994). Matsuzaki et al. (1999) developed
a heuristic for multi-floor facility layout considering
capacity of elevator. Patsiatzis et al. (2002) presented a
mixed integer linear formulation for the multi-floor facility
layout problem. This work was extended model of the
single-floor work of Papageorgiou and Rotstein (1998).
We focus on flexible bay-structured layout. In the baystructured
facility layout problems, a pre-specified
rectangular floor space is first partitioned horizontally or
vertically into bays and then each bay is divided into
blocks with equal width but different lengths. Some
typical works in bay layout are Aiello et al. (2006),
Arapoglu et al. (2001), Castillo and Peters (2004), Chae
and Peters (2006), Chen et al. (2002), Eklund et al.
(2006), Enea et al. (2005), Garey and Johnson (1979),
Konak et al. (2006), Kulturel-Konak et al. (2004), Meller
(1997), Peters and Yang (1997) and Tate and Smith
(1995).
In this paper, we formulate a multi floor layout
considering conflicting objectives. Objectives are commonused
in previous works and include to minimize material
handling cost and to maximize closeness rating. Then, a
memetic algorithm is developed to solve the problem.
MATHEMATICAL MODEL
Sets and indices
Set of cells in block layout graph.
A. Variables
z ik
′
z ik
r ij
δ k
δ '
G i
y ij
⎧1,
⎪
= ⎨
⎪
⎩0,
⎧1,
⎪
= ⎨
⎪
⎩0,
⎧1
⎪
= ⎨
⎪
⎩0
k
If
department
bay k in the first floor
otherwise
If
department
bay k in the second
otherwise
If department
department
otherwise
i is assigned
i is assigned
floor
i is located
to
above
j in the same bay
⎧1,
If bay k is occupied in the first floor
= ⎨
⎩0,
otherwise
⎧1,
= ⎨
⎩0,
If bay k is occupied in the second floor
otherwise
⎧1
If departmenti
is located in the first floor
= ⎨
⎩0
Otherwise
⎧1,
If department s i and j have
⎪
= ⎨ common boundary
⎪
⎩0,
Otherwise
wk Width (the length in the x-axis direction) of bay i in
first floor; w′ k Width (the length in the x-axis direction) of
1
bay i in second floor; w ik Width (the length in the x-axis
2
direction) of bay i in bay k in first floor; w ik Width (the
length in the x-axis direction) of bay i in bay k in second
floor;
l
y
i
Height (the length in the y-axis direction) of de-
partment i in first floor;
l′
y
i
to
Height (the length in the y- axis

x y
direction) of department i in second floor; ( o , )
i i o
Coordinates of the centroid of department i in first floor;
x y
o o ′ , ′ Coordinates of the centroid of department i in
( )
i
i
x
second floor; dij Distance between the centroid of
departments i and j in the x-axis direction in first floor;
d′ Distance between the centroid of departments i and j
x
ij
y
in the x-axis direction in second floor; dij Distance
between the centroid of departments i and j in the y-axis
direction in first floor;
d′ Distance between the centroid
y
ij
of departments i and j in the y-axis direction in second
floor; hik Height (the length in the y-axis direction) of
department i in first floor; h′ ik Height (the length in the y-
x y
axis direction) of department i in second floor; ( Up , )
i i Up
Coordinates of the northeastern corner of department i;
x y ( i i ) Lo Lo , Coordinates of the southwestern corner of
department i.
s 1
s2
s3
⎧1,
= ⎨
⎩0,
⎧1,
⎪
= ⎨
⎪0,
⎪
⎩
⎧1,
⎪
= ⎨
⎪0,
⎪
⎩
B. Parameters
if thefirst
elevatoris
used
otherwise
if the first elevator is located in
the southwest corner of
if the first elevator is located in
the northwest corner of
the southeast corner of
the northeast corner of
facility
facility
if the second elevator is located in
facility
if the second elevator is located in
facility
n: Number of departments; W: Width of the facility along
the x-axis; H: Width of the facility along the y-axis; ai
:
Area requirement of department i; α i : Aspect ratio of
max
department i; l : Maximum permissible side length of
min
department i; l :
i
i
Maximum permissible side length of
department i: fij
Amount of material flow between
departments i and j; cij
: Amount of material cost
between departments i and j if they would be in different
floors in y-axis; adjij
: Adjacency ratio between departments
i and j; He : Distance between two department
Krishnan and Jaafari 7211
in z-axis; p 1, p2
: Weights of objective functions.
C. Assumptions
i. The coordinates of the southwestern corner of the
facility are (0, 0).
ii. In the model description, the long side of the facility is
along the x-axis direction, and bays are assumed to be
vertically arranged within the facility.
iii. If a department is assigned to a bay, then the bay
must be completely filled.
iv. If the aspect ratio is specified to control departmental
min
max
shapes, then l = a α , li = aiαi
D. Problem formulation
i
i
i
In our paper, we extend their model with following
constraints:
x x x
( 2 G − G ) + d ≥ ( o o )
W − − ∀i
< j,
i
j
x x x
( 2 G − G ) + d ≥ ( o o )
i
j
ij
W − − ∀i
< j,
x x x
( 2 G − G ) + d ≥ ( o o )
i
j
ij
ij
L − − ∀i
< j,
x x x
( 2 G − G ) + d ≥ ( o o )
i
j
ij
i
j
i
j
i
j
j
i
(1)
(2)
(3)
L − − ∀ i < j,
(4)
x x x
( 2 ( 1−
G ) − ( 1−
G ) ) + d′
≥ ( o′
− o )
W − ′ ∀ i < j,
(5)
i
j
x x x
( 2 ( 1−G
) −(
1−G
) + d′
≥ ( o′
−o
)
i
j
ij
ij
W − ′ ∀ i < j,
(6)
y y y
( 2 ( 1−
G ) − ( 1−
G ) + d′
≥ ( o′
− o )
L − ′ ∀ i < j,
(7)
i
j
y y y
( 2 ( 1−
G ) − ( 1−
G ) + d′
≥ ( o′
− o )
i
j
ij
L − ′ ∀ i < j,
(8)
ij
Constraints (1) to (8) linearize the absolute value term in
the rectilinear distance function in the first and second
floor.
∑ z ik = G ∀ i,
(9)
i
k
∑ z ′ ik
k
= 1 − G i
i,
j
i
i
j
∀ (10)
Constraints (9) and (10) states that each department is
located in a bay.
w
k
=
1
∑ z ik a ∀ k,
(11)
i
L
i
i
i
j
j

7212 Afr. J. Bus. Manage.
′ w
k
min
i
=
ik
∑ ′
1
z ik a i
L
i
k
max
i
∀ k,
(12)
( z )
l z ≤ w ≤ l + W 1−
min
i
ik
k
max
i
ik
( − z )
l z′
≤ w′
≤ l + W 1 ′
x
i ≤ ∑
j≤k
j
k
ik
∀i,
k,
∀ i,
k,
min ( W − l )( 1 z )
o w − 0.
5w
+ −
x
i ≥ ∑
j≤k
j
k
i
ik
(14)
min ( W −l
)( 1 z )
o w − 0.
5w
− −
x ′ i ≤ ∑
j≤k
j
k
i
ik
min ( W −l
)( 1−
z )
o w′
− 0.
5w′
+
′
x ′ i ≥ ∑
j≤k
j
k
i
ik
min ( W −l
)( 1−
z )
o w′
− 0.
5w′
−
′
h
a
i
h
a
max max
h ⎪⎧
⎪⎫
jk l l i j
− − max⎨
, ⎬ ik jk
a j ⎪⎩ ai
a j ⎪⎭
i
ik
( 2 − z − ) ≤ 0
ik z
i
max max
h ⎪⎧
⎪⎫
jk l l i j
− + max⎨
, ⎬ ik jk
a j ⎪⎩ ai
a j ⎪⎭
( 2 − z − ) ≥ 0
ik z
h′
⎪⎧
li
− max⎨
⎪⎩ ai
l j
,
a
( 2 − z′
− ′ ) ≤ 0
max max
′ ik jk
⎪
−
⎬ ik z jk
i a j
j
h
a
h′
⎪⎧
li
+ max⎨
⎪⎩ ai
l j
,
a
⎫
⎪⎭
( 2 − z′
− ′ ) ≥ 0
max max
′ ik jk
⎪
−
⎬ ik z jk
i a j
j
h
a
∑
i
∑
l
i
min
i
min
i
h = Hδ
ik
ik
k
h′ = Hδ
′
z
ik
ik
≤ h
ik
k
≤ l
ik
max
i
l z′
≤ h′
≤ l z′
∑
k
∑
k
h = l
ik
ik
y
i
h ′ = l′
y
i
⎫
⎪⎭
∀i
, j,
k
∀i
, j,
k
∀i
, j,
k
∀i
, j,
k
(13)
(15)
(16)
(17)
(18)
∀i
, j,
k (19)
∀i
, j,
k
(20)
∀ i , j,
k (21)
∀i
, j,
k
(22)
∀ i, k
(23)
∀ i, k
(24)
z
ik
max
i
∀ i, k
(25)
ik
∀ i, k
(26)
∀ i, k
(27)
∀ i, k
(28)
y
i
y
i
y
j
y
j
( r )
o − 0.
5l
≥ o + 0.
5l
− H 1−
y
i
y
i
y
j
y
j
ij
( r )
o′ − 0.
5l′
≥ o′
+ 0.
5l′
− H 1−
r
ij
+ r ≥ ′ + ′
ji zik
z jk
y
i
y
i
−1
0. 5l
≤ o ≤ H − 0.
5l
y
i
y
i
y
i
0.
5l
′ ≤ o′
≤ H − 0.
5l′
∀i
< j ,k,
y
i
∀i
≠ j,
ij
∀i
≠ j,
(29)
(30)
(31)
∀ i,
(32)
∀ i,
(33)
Constraints (11) to (33) state restrictions of length and
width of each department and determine coordination of
each department.
w 1
i
w 2
i
x
i
= ∑ zik
wk
k
∑ ′ ′ = zik
wk
k
x
o ≤ 0.
5 w
j
∀ i, k
(34)
∀ i, k
(35)
1 1 ( + w ) + W ( y )
o − 1−
x
j
x
i
i
j
1 1 ( w + w ) + W ( y )
o − o ≤ 0.
5
1−
x
i
x
j
i
j
2 2 ( w + w ) + W ( y )
o′ − o′
≤ 0.
5
1−
x
j
x
i
i
i
2 2 ( w + w ) + W ( y )
o′ − o′
≤ 0.
5
1−
y
i
y
j
i
i
y y ( l + l ) + W ( y )
o − o ≤ 0.
5
1−
y
j
y
i
i
j
y y ( l + l ) + W ( y )
o − o ≤ 0.
5
1−
y
i
y
j
i
j
y y ( l′
+ l′
) + W ( y )
o′ − o′
≤ 0.
5
1−
y
j
y
i
i
j
y y ( l′
+ l′
) + W ( y )
o′ − o′
≤ 0.
5
1−
y
ij
≤ Gi
− G j
+ 1
i
j
∀i
< j,
ij
ij
ij
ij
ij
ij
ij
∀i
< j,
ij
∀i
< j,
∀i
< j,
∀i
< j,
∀i
< j,
∀i
< j,
∀i
< j,
∀i
< j,
(36)
(37)
(38)
(39)
(40)
(41)
(42)
(43)
(44)
Constraints (34) and (44) determine which two
departments can have common boundary.
x y ( d ) ⎞
ij + dij
⎟(
GiG
j + ( 1−
Gi)(
1−
G j )
x y ( d′
+ d′
) ⎟
⎛
F ⎜
1 = ∑∑ cij
fij
)
⎜
j> i i ⎝+
ij ij ⎠
(45)
Statement (45) calculates material handling cost if two

departments are in the same floor.
x y x
I = 1−
s ) s (( o + o ) + ( o'
+ o'
( 1 3
i
y x
y
II = 1−
s )( 1−
s )((( L −o
) + o ) + (( L −o'
) + o'
( 1 2
i
i
i
i
y
i
))
i
x
i
)))
(46)
(47))
x y
x y
III = s s (( W −o
) + o ) + (( W −o'
) + o'
)) (48)
1 2
i
i
x
y
x
y
( − s ) ( ( W − o ) + ( L − o ) + ( ( W − o'
) + ( L − o ) ) )
IV = s
'
1 1 2
i
⎛ cij
He + ⎞
F ∑∑ ⎜
⎟
2 = fij
⎜
⎟ i j j 1
j> i i ⎝(
I + II + III + IV ) ⎠
i
i
i
i
( G ( 1−
G ) + G ( − G ) )
i
i
(49)
(50)
(46) to (50) determine material handling cost between
two departments if they are in different floors.
x
i
x x
1 2
( o + o′
) + . 5(
w w )
Up =
+
x
i
i
i
0 i i
x x
1 2
( o + o′
) − . 5(
w w )
Lo =
+
y
i
i
i
0 i i
y y
y y
( o + o′
) + 0.
( l + l )
Up = 5 ′
y
i
i
i
y y
y y
( o + o′
) − 0.
( l + l )
Lo = 5 ′
F
4
=∑∑
j> i i
i
⎛
adj ⎜
ij⎜
⎝
i
i
i
i
i
∀ i,
(51)
∀ i,
(52)
∀ i,
(53)
∀ i,
(54)
x x
x x
( min{
Upi
, Upj
} −max{
Loi
, Loj
} )
y y
y y
+ ( min{
Upi
, Upj
} −max{
Loi
, Loj
} )
( GG
+ ( 1−G
)( 1−G
)
i
j
i
j
⎞
⎟
⎟
⎠
(55)
(51) to (55) calculate summation of closeness rating
between departments.
1
( F1
+ F2
+ F3
) p2
4
Min Z = p
− F
p1
+ p2
= 1, p1,
p2
≥ 0
(56)
(57)
Objectives were formulated in a weighted form using (56)
and (57)
A = x.
y;
x ≥ 0,
y ∈
A ≤ My;
M is big
( y)
A ≤ x + M 1−
( y)
A ≥ x − M 1−
{ 0,
1}
number
(58)
(59)
(60)
(61)
Krishnan and Jaafari 7213
Constraints (58) to (61) can afford to linearize product of
variable by integer variable.
GA and MA IMPLEMENTATION
Evolutionary algorithms have been applied to many fields
of optimization, and it has been observed that combination
of evolutionary algorithms with problem-specific
heuristics can lead to highly effective procedures. A
memetic algorithm (MA) is a hybrid algorithm that augments
a population-based search approach with a local
search heuristic. MA is similar to genetic algorithm (GA).
However, GA is based on biological evolution while MA
imitates cultural evolution- in the sense that memes can
be modified during an individual's lifetime whereas genes
cannot. Thus, MAs are more likely to improve the quality
of an individual. This approach proved to be highly
efficient for this problem when large-sized test instances
were used.
Chromosome definition
A flexible bay structure is used to place departments. The
bay width is flexibly adjusted for departments assigned to
the bay. However, the emphasis is on the location of the
bay rather than on the arrangement of the departments.
A chromosome is divided into three sections (Figure 1),
two of which are composed of numbers that represent the
departments for first floor and second one, and there is
no explicit indication of the breakpoints between bays.
However, the sequentially arranged departments can be
grouped if they meet the conditions for forming a bay
when the areas of the departments are added
sequentially from left to right. If the summed area is in the
range of the designated bay size and the length and
width of the departments are within permissible intervals,
then this set of departments can be grouped into a bay.
Thus, a set of candidate breakpoints between each pair
of bays can be determined. The third section of the
chromosome represents binary variables S1, S2 and S3 to
determine the number and location of elevators. There
can be one or two elevators. The mathematical model
and the solution procedure are to determine the number
of elevators after doing a trade-off between vertical
material handling cost and elevator setup cost.
Parent selection
The same first individuals are uniformly randomly generated,
and the selection of the parents for the next
generation is done through tournament 3; consequently,
the best individuals in the generation are more likely to
move to the next generation.

7214 Afr. J. Bus. Manage.
procedure are to determine the number of elevators after doing a trade-off between vertical material handling cost a
Bay 1 Bay 2 Bay 1'… S1 S2 S3
Figure 1. The designed chromosome.
Crossover
Figure 2. An example to illustrate crossover method.
A modified partially matched crossover is used to prevent
generation of infeasible solutions; since the partially
matched crossover method exchanges genes within a
parent, feasible offspring are obtained. The integer number
in a chromosome, which displays the department,
should not be duplicated after the process of crossover is
finished since each number is unique within the chromosome.
After exchange between the chromosomes, each
chromosome is checked to see whether there are two of
the same numbers in the new chromosomes. If there is a
repeated number, then the repeated gene outside the
crossed-over segment is selected and replaced with the
first number from 1 to n, which is absent within the
mentioned chromosome. This method is iterated until
there is no repeated number. This method was easier to
be coded and proved to perform crossover operation with
less number of computations rather than partially
matched crossover. Figure 2 shows an example of the
crossover method. After exchanging genes between the
two chromosomes in child 1, the first and third genes
(number 5) are the same. So, the first gene which is
outside the crossed-over segment must be replaced with
4 1 3 5 9 6 … 8 7 2 …
The First floor The Second floor Elevators
4, as the first number from 1 to n which does not already
exist within child 1. The same method is applied to child
2.
Mutation
A swap mutation operator is used for the mutation. Two
uniformly randomly selected genes are swapped to
generate a new chromosome. As mentioned with the
crossover operator, the gene that represents each
department is unique in the chromosome and should not
be duplicated. The standard mutation operator chooses
one of the genes in the chromosome and changes its
value, but in this problem, the chromosome becomes an
infeasible representation because the new gene would be
either one of the integer numbers already in the
chromosome or a number that does not stand for one of
the departments.
Local search
A simple 2-opt algorithm, also known as a pairwise-
interchange heuristic, was used to enhance the GA to

MA. The 2-opt algorithm considers only two departments
at a time for exchange, and the algorithm discards the
previous best solution whenever a better solution is
found.
Computational results
The revolutionary algorithm was tested for different sizes.
For small-sized test instances departments, the mathematical
model yielded the optimal solution in reasonable
time using Lingo 8:00. The algorithm obtained the optimal
solution to some small-sized test instances. For largesized
test instances, the combined SA and MA was
compared with the combination of SA and corresponding
GA and proved to yield better solutions but in more CPU
runtime. The results proved that the designed algorithm is
quite efficient in terms of runtime and quality of solutions.
CONCLUSION
In this paper, a multi-objective mixed integer linear programming
model was developed to find the optimal solution
to the multi-floor facility layout problem with unequal
departmental areas in multi-bay environments where the
bays are connected at one or two ends by an inter-bay
material handling system. Also, a memetic algorithm was
designed to solve large-sized test problems, and
obtained optimal solution to some small-sized test
instances. It proved to be highly efficient after a comparison
with corresponding genetic algorithm for large-sized
test instances and with the mixed integer formulation for
small-sized test instances.
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African Journal of Business Management Vol. 5(17), pp. 7216-7223, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM10.436
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
A phenomenographic study investigating consumers’
conceptions of marketing in Taiwan
Hung-Ming Lin
Department of Business Administration, Minghsin University of Science and Technology, No.1 Hsin Hsing Rd., Hsinchu,
30401,Taiwan. E-mail: hmlin@must.edu.tw. Tel: 886-3-5593142/3512. Fax: 886-3-5593142/3573.
Accepted 7 April, 2011
Consumers’ understandings of marketing are related to their product attitudes or brand image
formation. However, little empirical evidence exists of what marketing means to consumers. This study
documents a new term called conceptions of marketing, which refers to the beliefs and understandings
held by consumers about marketing. The purpose of this research is to investigate the variation in how
marketing is conceptualized by consumers. The interview data were gathered from thirty participants
with various characteristics in Taiwan and were analyzed using a qualitative research method, the
phenomenographic approach. The study identified four qualitatively different categories by which
marketing is understood by these participants, including marketing as ‘delivery’, ‘creating attraction’,
‘guidance’ and ‘agency’. Within each concept, a functional and a philosophical view of marketing are
discerned, and some general characteristics of the conceptions of marketing are also described.
Key words: Conceptions of marketing, phenomenographic approach, Taiwan.
INTRODUCTION
According to the American Marketing Association,
"marketing is an organizational function and a set of processes
for creating, communicating and delivering value
to customers and for managing customer relationships in
ways that benefit the organization and its stakeholders".
This official definition of marketing is widely used in
textbooks and taught in university lecture halls around the
world, but not all individuals fully understand it (Alam and
Khalifa, 2009). They cannot accurately memorize or
comprehend it in a certain way, although they may be
exposed to the definition. In fact, though ordinary
consumers are immersed in marketing activities (for
example, advertisements, sales promotions) in their daily
life (Alam, 2009), their views about marketing may be
formed as a result of experiencing marketing activities,
and thus they may have their own views about marketing.
Consumers’ understanding of marketing is thus probably
distinct from the academic marketing definition. Therefore,
the study is interested in knowing what marketing
means to consumers.
This research documents a new term the study calls
conceptions of marketing, which refers to the beliefs and
understandings held by consumers about marketing. A
“conception” can be further defined as the fundamental
way a person understands a phenomenon or an object in
the surrounding world (Eklund-Myrskog, 1998). Conceptions
of marketing emphasize how consumers interpret,
perceive, understand, and conceptualize marketing.
In the marketing literature, the term marketing concept
is often advocated as a fundamental idea of marketing by
which organizations survive and prosper through
satisfying the needs and wants of customers (Evans and
Berman, 1997; Pride and Ferrell, 2000). It is regarded as
a philosophy of doing business. Marketing concept differs
from the term conceptions of marketing mentioned in this
study. As illustrated in Figure 1, marketing concept leads
organizations to plan and perform marketing activities in
order to communicate with a target, for example, using
the 4Ps’ strategy. In a marketing environment, consumers’
conceptions of learning would be formed when
experiencing these activities delivered by the organization.
Marketing concept focuses on how an organization
integrates marketing into its business process, while
conceptions concentrate on how consumers interpret
marketing based on their experience (Alam et al., 2010).
Why are consumers’ conceptions of marketing important?
Previous research has shown that the adoption of
the marketing concept influences marketing activities,

Figure 1. Marketing concept versus conceptions of marketing.
such as new product planning (Lawton and
Parasuraman, 1980). Marketing practitioners are marketing
originators and planners. Their understanding of
the marketing concept and extent of putting the concept
into practice might impact their firm’s marketing performance.
In the same way, consumers’ conceptions and
understandings of marketing might affect their reaction to
the organization marketing activity and then influence
product attitudes or brand image formation. Organizations
can further utilize consumers’ reactions to modify
their marketing plans (Figure 1). What marketing means
to consumers and the role of conceptions of marketing in
consumer behavior might be an important issue in
marketing research.
How can the study capture consumers’ conceptions of
marketing? Phenomenography, a qualitative research
approach, is a type of interview which probes deeply into
how each subject perceives the phenomenon of interest.
It aims to reveal the qualitatively different ways in which
people experience or conceptualize various phenomena
in the world around them (Marton and Booth, 1997).
General practice deals with people with a diversity of
experiences, and it is important to be able to recognize
them all. Consumers experience marketing activity
diversely in their daily life, and this study is concerned
with what kind of conceptions of marketing exist. The
phenomenographic approach is adapted in the present
investigation to illustrate consumers’ conceptions of
marketing.
This paper will introduce phenomenography, followed by
an explanation of the methodological approach taken to
collect data before presenting the findings of that data
collection. The study considers some of the academic
and practical implications of the data before drawing
conclusions and making some suggestions for future
research in this area.
LITERATURE REVIEW OF PHENOMENOGRAPHY
Phenomenography is designed to answer particular
questions about people’s thinking and learning (Marton,
1981). It aims at identifying and mapping the qualitative
different ways that people experience, conceptualize,
perceive, and understand various aspects of the world
around them. Such ways of differentiating should prove
useful in understanding other people’s understandings
Lin 7217
(Marton, 1986). The major characteristics of phenomenography
are concerned with its attempt to capture
conceptualizations that are profound to the experience of
a selected phenomenon, and categorizations of different
ways of understanding.
Phenomenography developed in education research. It
originated with Frence Marton and his colleagues at the
University of Goteborg in Sweden. Their phenomenographic
research revealed that when a group of students
read the same excerpt from a passage of text, they
understood it in a finite number of qualitatively different
ways. The students described different understandings of
the same material, and this variation in understanding
could be clearly allocated by researchers into distinct
categories (Marton, 1995; Marton and Svensson, 1979).
As a consequence of their initial research, it was
proposed that if students had a limited number of
qualitatively different understandings of learning, then it
was reasonable to expect that people hold limited
numbers of different understandings of all kinds of phenomena
(Marton, 1986). Subsequent studies have shown
that their hypothesis was correct (Gerber et al., 1995;
Renstrom et al., 1990; Svensson, 1989). Phenomenography,
on the one hand, has continued to emerge in
educational research (Eklund-Myrskog, 1998; Hella,
2008; Marshall et al., 1999; Ingerman et al., 2009; Lin
and Tsai, 2008); on the other hand, it has gradually
begun to be utilized in various other academic disciplines,
such as leisure (Watkins and Bond, 2007), health care
(Björk and Ahlström, 2008; Jensen and Lidell, 2009), and
life science (Yang and Chen, 2002). Although there is
almost no phenomenographic research published in the
area of marketing research, the potential of this research
approach indicates the need to become aware of its
development. The objective of the study in phenomenographic
research is not the phenomenon being discussed
per se (first-order perspective), but rather the relation
between the subjects and that phenomenon (secondorder
perspective) (Uljens, 1991) (Figure 2). Phenomenography
is a second-order perspective that describes the
various ways in which a phenomenon is experienced by
subjects, but not a first-order perspective that is a statement
about the phenomenon (Marton and Booth, 1997).
The ways of understanding experiences are the principle
theme of interest. Phenomenographers are interested in
describing alternative views of phenomena as people of
certain groups perceive them. To acquire the subjects’

7218 Afr. J. Bus. Manage.
Figure 2. First- and second-order perspectives (Uljens, 1991).
qualitatively different understanding or conceptualization
of the phenomenon is the main concern of phenomenographic
research.
The purpose of this qualitative research is to investigate
variations in consumers’ conceptions of marketing
through the phenomenographic approach. The study
focuses on the second-order perspective, as it concerns
the relationship between consumers and marketing phenomena
(Alam et al., 2010). It should be noted that the
current study is not to controvert or debate the essence
of the marketing, but to provide a different view of
marketing from the consumers’ perspective.
METHODS
Participants
As Bowden and Green (2005) suggested, in a phenomenographic
study, the number of interview participants should ensure sufficient
variation in ways of seeing, but not be so many that it makes it
difficult to manage the data. In practice, most phenomenographers
find that between 20 and 30 participants meet the two criteria.
The participants in this study were selected based on their age,
family status, education, occupation and geographic area within
Taiwan. Since individuals’ conceptions of marketing may be related
to their life experience, participants with different characteristics,
such as age and occupation, would reflect different life environments
and experiences. The purpose of considering geographic
variations is thus for exploring possible existing views about
marketing. Thirty participants were enrolled in the sample from
northern, middle, and southern Taiwan, and there were an almost
equal number of both genders. For each area, approximately ten
participants were selected for the interviews about their marketing
meanings. The mean age of the participants was 38.3 years.
Details of the demographic profile of the participants are shown in
Table 1.
Data collection
The interviews were undertaken in a semi-structured way. The aim
was to bring forth the interviewee’s awareness of his or her own
insights into life experience concerning marketing. The guiding
interview questions were oriented towards the experience under
investigation. The discourse directed each participant to describe
their conceptions of marketing and consider their experience based
on questions such as “in your life experience, what is marketing?”
“What do you mean by marketing?”, and “In your view, what is the
role of marketing in your life?” During the interview, additional
questions such as: “Could you tell me more about that?”, “Could
you explain that further?” “What do you mean by that?”, and “Why
did you say that?” were posed in order to clarify the meaning,
deepen the understanding of the answer, and ensure that the interviewer
had understood the informant correctly (Bowden and Green,
2005). Each interview, which lasted 25 to 40 min, was taperecorded
and transcribed verbatim. The interviews were conducted
in Chinese and then fully transcribed for further analysis. The
transcripts of these interviews were the main data source for
analyzing participants’ conceptions of marketing.
Data analysis
The transcribed material was analyzed according to the
phenomenographic procedure as elaborated by Marton and Booth
(1997). It is described step by step by Dahlgren and Fallsberg
(1991). The data analysis started with repeated readings of all the
interview transcripts to become acquainted with the content (familiarization).
The second step involved compilation, as the researchers
considered the selected parts of the transcribed material, and
picked out the significant statements that characterized the
interviewees’ views of marketing (condensation). A total of 342
statements were identified and compared. The third step involved
sorting; similar statements were placed together into groups as
preliminary categories (grouping). The fourth step involved comparison;
the content of the categories was compared with regard to
similarities and differences both within and between the groups
(comparison). The categories were labeled in order to illustrate their
essence (naming). Finally, contrasts within each category were
made clear by means of quotations that illuminated the variation in
statements (contrasting). Two researchers, the author and an
experienced phenomenographer, performed each step of the
analysis separately. Säljö (1988) believed that interjudge correlation
coefficients exceeding .80 may be considered adequate. In this
study, the two researchers classified the interviewees’ conceptions
of marketing, reaching 88% agreement. For the interview data
which they did not agree upon, they reviewed the interview
transcripts again and discussed them case by case until consensus
was reached, and then determined a final categorization together.
FINDINGS
Through a phenomenographic analysis of the participants’
interview results, four qualitatively different

Table 1. Profile of participants.
ID No. Age Gender Occupation Education Family status
#1 19 Female Student BS (in progress) Single
#2 24 Male Graduate student MS (in progress) Single
#3 37 Female Teacher PhD (in progress) Married
#4 42 Male Engineer Master Married
#5 30 Female Hair stylist High school Divorced
#6 55 Male Factory director BS Married
#7 56 Female Nurse BS Divorced with kids
#8 25 Female Technician BS Married
#9 68 Male Retired police officer BS Married, empty nester
#10 29 Female Technician BS (in progress) Single
#11 63 Male Post office worker High school Married
#12 39 Male Small buiness owner High school Married
#13 32 Male Life insurance salesman BS Married
#14 33 Female Teacher MS Married
#15 31 Female Civil servant MS Married
#16 40 Female Marketing manager MBA Married
#17 44 Female Housewife Married
#18 27 Male Graduate student PhD (in progress) Single
#19 47 Male Production manager BS Divorced with kids
#20 54 Female Small buiness owner BS Married
#21 37 Male Taxi driver BS Married
#22 43 Male Sales manager MS Married
#23 26 Female Research assistant MS Single
#24 52 Male College professor PhD Married
#25 32 Female Dietician MS Married
#26 20 Male Student BS (in progress) Single
#27 35 Male Consultant MBA Married
#28 24 Female Graduate student MBA (in progress) Single
#29 33 Female Engineer BS Married
#30 51 Female Small business owner High school Married
conceptions of marketing, including ‘delivery’, ‘creating
attraction’, ‘guidance’ and ‘agency’, were identified in this
study. The four categories about conceptions of
marketing are described as follows, with some interview
quotations provided as illustration.
Marketing as ‘delivery’
In the first category, the participants conceptualize marketing
as the delivery of information. These participants
tend to regard marketing as an activity related to informing,
broadcasting, providing, announcing, or introducing
some product information (for example brand, function,
price) to the people. Marketing activity lets them know
and acquire the product information. For example, they
responded that:
i) Marketing is to deliver products or services to
customers, and make them aware of the merchandise or
Lin 7219
service. (#5)
ii) Marketing is a way of introducing merchandise to
people who need it. (#11)
iii) Marketing is to introduce products, brands and
functions for customers. (#13)
iv) Marketing is to provide information, including products
offered, specific functions and new product launches.
(#15)
Marketing as ‘creating attraction’
In the second category, the participants regard marketing
as creating attraction. The purpose of marketing is to
make the product more interesting, and then to catch the
consumers’ attention and elicit consumers’ desire. This
will help make them buy the product. For example, they
stated that:
i) Marketing is to make things interesting, so as to

7220 Afr. J. Bus. Manage.
stimulate one’s interest. (#9)
ii) Through marketing, it will draw one’s attention to the
product and tempt someone to buy the goods. (#10)
iii) Marketing is doing something to draw your attention,
and making things valuable for you to purchase or
consume. (#21)
Marketing as ‘guidance’
In the third category, marketing is viewed as guidance.
The participants characterized in this category, highlightted
that marketing can lead a company’s selling activity
through planning, and give direction for marketers’
decision making. For instance, they stated that:
i) Marketing is like a pilot or compass that guides you in
the right direction and helps you to make adjustments
accordingly. (#6)
ii) Marketing is a helper to market intelligence gathering,
product selling and production management. (#16)
Marketing as ‘agency’
In the final category, marketing is conceptualized as
agency. For these participants, marketing plays a mediator
role between sellers and buyers. Moreover, they
emphasize that the sellers and buyers should be considered
simultaneously when doing marketing planning.
For them, marketing is like an interface between sellers
and buyers, supply and demand; it is also a two-way
process of thinking, not a one-way process. For instance,
these participants replied that:
i) Marketing plays the role of incorporating customer
needs and enterprise profits. (#1)
ii) Marketing plays the role of an agent and a mediator.
(#20)
iii) Marketing is to forecast customers’ demands and
satisfy customers’ needs in order to gain the most
benefits for both sides. (#22)
iv) Marketing is to build up the bridge between customers
and industries. (#22)
Distribution of interviewees’ conceptions of
marketing
The main purpose of this study is to characterize the
variations in conceptions of marketing among the interviewees,
rather than to focus on classifying or labeling
individual interviewees. Therefore, for a fuller representation
of the interviewed participants’ conceptions of
marketing, each was allowed to be included in one or
more categories according to his/her conceptions of marketing.
The distribution of each participant’s conceptions
of marketing among the four categories is presented in
Table 2.
As presented in Table 2, ‘delivery’ was conceptualized
as the major feature of marketing for all interviewed
participants. In addition, the ‘creating attraction’ category
was expressed by fourteen participants. However, the
‘guidance’ category was found to be mentioned by merely
five participants, whereas the ‘agency’ category was
mentioned by only four. Moreover, the fact that most
participants have multiple conceptions of marketing is
clearly verified in this study.
Relationships among the four conceptions of
marketing
Four categories of the conceptions of marketing,
‘delivery’, ‘creating attraction’, ‘guidance’ and ‘agency’,
are revealed in this study. The study consider that the first
two conceptions are related to a functional view of
marketing, as these two place more emphasis on what
marketing does. The functional view implies that
marketing is confined to helping to promote products and
services through the provision of product information, and
hence stimulates demand. The last two conceptions are
related to a philosophical view of marketing, as these two
put more weight on how marketing does what it does.
The philosophical view implies that marketing can be
seen as a guiding philosophy which considers customers’
wants and needs while meeting the organization’s goals
for the organization. Based on the marketing definition,
marketing emphasizes that doing marketing should coordinate
consumers’ needs and the organization’s goals
simultaneously. From this perspective, the philosophical
view is closer to the marketing definition than the functional
view. The level of the philosophical view is higher
than that of the functional view. Moreover, consumers
who hold ‘delivery’or ‘creating attraction’ conceptions
focus on marketing activities they can perceive, such as
advertisements, sales promotions, and product packaging.
On the other hand, consumers who hold ‘guidance’
or ‘agency’ conceptions, concentrate on the efforts
behind the marketing activities such as planning and
strategy. Therefore, the functional view is oriented to a
focus on the ‘outer’ aspects of marketing (communication
between consumers and organization), while the philosophical
view is oriented to a focus on ‘inner’ aspects
(communication within the organization). The relationships
among the four conceptions of marketing are
summarized in Table 3.
DISCUSSION
The aim of this study was to employ the phenomenographic
approach and analysis method to investigate
consumers’ conceptions of marketing, and attempt to

Table 2. Participants’ conceptions of marketing.
ID No. Delivery Creating attraction Guidance Agency
#1 � �
#2 �
#3 �
#4 �
#5 �
#6 � �
#7 � �
#8 � �
#9 � �
#10 � �
#11 � �
#12 � �
#13 �
#14 �
#15 � �
#16 ) ) ) )
#17 )
#18 )
#19 ) )
#20 ) ) )
#21 ) ) )
#22 ) )
#23 )
#24 ) )
#25 ) )
#26 ) )
#27 � �
#28 � � �
#29 � �
#30 � �
Total 27 19 6 4
Table 3. Relationships among the four conceptions of marketing.
Conceptions of marketing View of marketing Level Focus
Delivery
Functional view Lower level Outer focus
Creating attraction
Guidance
Agency
to provide a different aspect of marketing from the
consumers’ perspective. This study is the first to propose
the idea of conceptions of marketing, then identifie four
qualitatively different categories of conceptions of
marketing, including marketing as ‘delivery’, ‘creating
attraction’, ‘guidance’ and ‘agency’. The functional-philosophical
view, higher-lower level, and outer-inner focus
are proposed to describe the structural relationships
Philosophical view Higher level Inner focus
Lin 7221
among these four conceptions. Obviously, consumers
have their own understandings of marketing which are
quite different from the marketing definition.
According to the distribution of the interviewed participants’
conceptions, most of them expressed the ‘delivery’
conception of marketing. In general, the sellers often
utilize mass media to communicate with consumers when
promoting their products. Consumers directly experience

7222 Afr. J. Bus. Manage.
these communication activities, such as advertisements,
sales campaigns, road shows, etc., and acquire product
information through these activities in their daily life.
As consumers are exposed to the environment over
a long period of time, their conceptions of marketing are
gradually formed. Thus, the ‘delivery’ conception of
marketing was highly emphasized by the interviewed
participants.
The ‘agency’ conception, which considers both sellers
and buyers simultaneously when doing marketing, is
closer to the accepted marketing definition than the other
three. However, the least number of interviewees indicated
the ‘agency’ conception in this study. It seems that
most of the interviewees do not fully comprehend this
marketing definition. This might be related to work
experience. Table 2 shows that there were four interviewees
who hold the ‘agency’ conception (#1, #16, # 20
and #22); most of them have work experience related to
marketing, such as marketing manager (#16), small
business owner (#20), and sales manager (#22). For
them, authentic marketing work experience might be
helpful in forming a higher level marketing conception.
Market segmentation centers on the belief that everyone
wants the same thing. It comprises dividing a market
into identifiable groups of similar consumers (Nath,
2009). The classification of conceptions of marketing in
this study, for marketing managers, can be implemented
in market segmentation. For example, for consumers who
view marketing as ‘delivery’, a good marketing practice
may mean a well-implemented communication activity.
When they are aware of a good product communication
activity, they may have a positive attitude toward the
product. This shows that sellers should pay more
attention to their communication activity plan if they target
these consumers. When consumers hold the ‘agency’
conception, they can understand that sellers aim all their
efforts at satisfying their consumers - at a profit. They
would be likely to sacrifice appropriately, such as making
a monetary sacrifice. Honesty would be the best policy
for sellers when communicating with these consumers.
Also, this simple classification of conceptions of
marketing would be helpful in recruiting new marketing
employees. Marketing managers can promptly realize
interviewees’ understanding of marketing through interviews,
and recruit appropriate employees according to
the needs of the position.
While acknowledging that the study results are afore
described, two limitations are noted. The first limitation
concerns the interpretation of complexity. A less or more
complex understanding of marketing may have been a
product of individuals’ varying linguistic abilities to
articulate their experiences or of their varying interest in
studying marketing as much as it was of their capabilities
of relating to marketing. However, this limitation is
tempered by the phenomenographic proposition that
capabilities reflect how individuals relate to situations in
which they are discussing their experiences. The second,
the data collection was from Taiwanese consumers with
different characteristics. Phenomenography does not
attempt to assert that participants hold specific conceptions,
but instead, gathers evidence to illustrate the
range of conceptions present within the population under
study (Marton and Pong, 2005). This study does not aim
to make the findings to arrive at a generalized conclusion,
but focuses on the aggregate understandings of these
participants. As this study argues, consumers’ conceptions
of marketing are related to their experience of
marketing activities. Marketing environments vary across
countries. Exploring different groups’ (for example
Americans’, Europeans’, teenagers’, women’s) conceptions
of marketing should be pursued in future research.
This would be helpful for understanding consumers’
conceptions of marketing more broadly and deeply.
Cohen (1999) proposed a comprehensive and systematic
model, dimensional qualitative research (DQR), for
approaching and realizing the objectives typically set in a
qualitative research study. DQR comprises eight
dimensions which are referred to as BASIC IDS,
including behavior, affect, sensation, imagery, cognition,
interpersonal relations, drugs, and socio-cultural aspects.
The dimensions of BASIC IDS can be employed to
systematically explore market-related contexts. Phenomenography
aims to reveal the different ways in which
people experience or conceptualize various phenomena
in the world around them (Marton and Booth, 1997). As
phenomenography uses different people’s experience or
thoughts as a resource, it is expected to contribute to
exploring aspects of the behavioral and cognitive
dimensions, where a diversity of experience or thought
can provide a more thorough understanding of a phenolmenon.
For example, interviewers can ask respondents
to share their experience of service or their thoughts
about what service means to them. Ways of experiencing
service or conceptions of service would be identified, and
then such findings might provide useful information for
service design. The phenomenographical approach can
be effectively employed in market research applications
to explore behavioral and cognitive dimensions.
ACKNOWLEDGEMENT
Funding of this research was provided by the National
Science Council, Taiwan, under grant NSC 98-2511-
S159-001-MY2
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African Journal of Business Management Vol. 5(17), pp. 7224-7231, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM10.605
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Diffusion of Internet Protocol Television (IPTV) service
demands: An empirical study in the Serbian market
Valentina Radojicic*, Bojan Bakmaz and Goran Markovic
Faculty of Transport and Traffic Engineering, University of Belgrade, Vojvode Stepe 305, 11000 Belgrade, Serbia.
Accepted 7 April, 2011
In this paper, we consider diffusion process of new services in the residential market. We described the
main influences and decision factors of new telecommunication services adoption. In order to forecast
the adoption of new service, diffusion theory is applied. Building upon the Bass diffusion model, we
proposed an innovative approach, which encompasses a new model for residential market potential
estimation. Based on such analyses, we performed the forecast of Internet Protocol Television (IPTV)
demand in the Serbian market until the end of the year 2012. Such forecast are not only important for
the providers introducing the innovation service, but also for all others that provide related services
that complement or substitute for the innovation.
Key words: Diffusion theory, forecasting, Internet Protocol Television (IPTV), market potential, operator.
INTRODUCTION
Television distribution is one of the largest technology
systems deployed after electric power and telephone
networks. Digital technologies have completely transformed
the telephone and data networks creating much
more versatile and dynamic telecommunication infrastructure
and services. The television distribution is now
undergoing a similar digital evolution. Internet Protocol
Television (IPTV) is one of the promising services/
technologies, which takes a step further in distribution of
video streams over communications networks.
It is obvious that IPTV will be the killer application for
the next-generation Internet and will provide exciting new
revenue opportunities for service providers (Xiao et al.,
2007). Asia-Pacific region has been at the forefront of
IPTV, lunching IPTV service tests in 2002. The worldwide
growth of IPTV subscribers during the last years was very
dynamic. The new forecast from Multimedia Research
Group (MRG) indicates that the number of global IPTV
subscribers will grow from 28 million in 2009 to 83 million
in 2013, a compound annual growth rate of 31%
(Maisonnueve et al., 2009).
The success of the IPTV services is determined by the
*Corresponding author. E-mail: valentin@sf.bg.ac.rs. Tel: +381
11 3091 275.
time and volume of profitable operations. Getting the
maximum number of subscribers as soon as possible for
IPTV services is clear goal for any service provider. IPTV
adoption in Western Europe will continue to enjoy dynamic
growth up to the 2014 (19% per year) resulting in
20.3 million IPTV users (IPTV Global Forecast, 2009).
However, during that period, the dynamics of the IPTV
market will change: The main growth factors that drove
the IPTV market during its launch phase (home broadband
adoption and the analog TV switch-off process) will
gradually fade out, and short-term growth will mainly
come from the conversion of secondary TVs to digital TV.
The IPTV forecast for the next five years is both conservative
and optimistic, based on very detailed semi-annual
analysis of individual service providers and on a countryby-country
basis. Such a projected growth will have a
number of implications for the evolution of IPTV related
technologies (Ahmad and Begen, 2009).
The diffusion of IPTV service follows the S-shape
curve, similar to the diffusion of technological innovations.
The curve rises gradually at first; accelerates after taking
off (if the service is successfully adopted); begins to level
off following the inflection point, and finally increases
slowly to approach saturation.
In this paper, we focused on forecasting the number of
IPTV subscribers in Serbian telecommunication market in
a case of the main national telecom operator. For this

Table 1. Comparison between traditional TV systems and IPTV.
Terrestrial TV Cable TV Satellite TV IPTV
No interactivity Limited interactivity No or very limited
interactivity
Full interactivity
Service not guaranteed Service not guaranteed Service not guaranteed Guaranteed QoS/QoE
Not user centric Limited user centric (video
on demand)
Broadcast all channels
all the time
Broadcast all channels all
the time
Radojicic et al. 7225
Not user centric User centric (personal video
recorder, video on demand)
Broadcast all channels all
the time
Broadcast only those channels
being watched at given time
Limited content Limited content Limited content Unlimited content
purpose, we used the basic Bass diffusion model, which
is a very useful tool for forecasting the adoption of a new
service (Bass, 1969). A key area of uncertainty in forecasting
of a new telecommunication service is the estimation
of the overall market potential. A new model for
estimating the total market potential which encompasses
several parameters of interest for considered marketplace
is proposed here. Such forecast are not only
important for the company introducing the innovation
service, but also for other companies that make related
services that complement or substitute for the innovation
(Lavrence, 2008; Radojicic, 2003; Vanston and Hodges,
2004).
Further, we give a background and main challenges for
IPTV service. Then, we describe the basic analytical
expression of the Bass diffusion model and a new model
for estimation the total market potential. Determining the
main Bass parameters is possible by using analogies
with other services or analytically. Forecasted results
obtained in this paper are based on the collected data of
IPTV service sales during the year 2009. A new model for
residential market potential is used. In the final section
the concluding remarks are given.
BACKGROUND FOR IPTV SERVICE DEPLOYMENT
IPTV is actually a complex interplay of a number of technology
areas, drawing from TV broadcast technologies,
video coding (for example, MPEG-2 and H.264) and
encryption (for example, digital rights management), IP
transport networks, heterogeneous access networks
(WiFi, WiMAX, LTE), quality of service (QoS), quality of
experience (QoE), and so on. Advances in IPTV technology
will be based on progress in any one or more of
these fields and its relationship with the other
components of the overall IPTV system.
Comparing with traditional cable, terrestrial and satellite
TV, IPTV distinguishes itself with full interactivity, high
personalization and flexibility as shown in Table 1. IPTV
has been an initial driver for telecom investments for the
last few years. The bandwidth requirements of video
transmission make it one of, if not the most, demanding
mass-market telecommunication applications to date
(Maisonneuve et al., 2009). Transmission of a standard
definition (SD) video stream takes several Mbit/s, while
high definition (HD) reaches into the tens Mbit/s. This is
far more than what is required for voice transmission
(typically 32 to 64 kbit/s), or even web browsing. As a
result, IPTV has been the best motivation for operators to
deploy higher-speed DSL, and to consider deploying fiber
technologies (FTTx) and wireless broadband networks
(for example, WiMAX). These capacity upgrades also
bring much higher communication speed and enable new
services such as video telephony or file sharing, but it is
not certain that in isolation they would have been a
sufficient motivation for operators to invest in massive
new infrastructures, or indeed for customers to pay
premium subscriptions. IPTV has been the catalyst for a
technology leap.
BASS DIFFUSION MODEL PERFORMANCES
The Bass diffusion model has been widely used as forecasting
procedure of new services and it was proposed to
deal with the problem of initial adopters. This modeling
approach assumes that potential adopters become aware
of an innovation by means of external events, for
instance, marketing efforts. Bass introduced the idea of
dividing the innovation adoption rate into two factors, one
endogenous, usually called "imitation factor", and the
other exogenous, and commonly referred to as the
"innovation factor". Figure 1 represents the Bass diffusion
adoption process (Radojicic and Markovic, 2009). Figure
2 represents a basic customer choice model, which is
used to examine competition between visual services
such as cable, terrestrial TV, video-on-demand, video
shop rental, satellite or IPTV.
Three service characteristics (marketing, quality, and

7226 Afr. J. Bus. Manage.
Figure 1. The Bass diffusion adoption process.
Figure 2. A system dynamics representation of the adoption of new telecoms services.
price) influence the consumer’s valuation of the service
and these in turn lead to adoption (Fildes, 2002). Despite
the focus of these models on policy, they may also be
used in forecasting, in part because of the transparent
inadequacies of statistical methods. Thus, to model and
forecast the demand for new service, awareness is seen
as a pre-cursor to possible adoption, but no measurements
were available on this variable and its growth was
seen as affected by both marketing plans and culture
specific preferences. The compound diffusion path

esulting from a developing awareness and subsequent
adoption is then simulated based on estimated parameters.
A key output of this model was a set of forecasts.
Understanding of new service may be affected by
changing the actions of marketing. On the other hand, the
understanding of the service greatly affect users who
have already accepted a new service. Service utilization
is a factor that should include the actual need of users for
the service, the importance of their work or daily life, the
benefits that can be achieved by new service etc. On the
utility can be affected by changing the quality and
marketing functions controlled by the service provider,
and depending on the factors of the final acceptance of
services (Lu et al., 2009). The acceptability of the service
affects the price and quality, which also controls the
service provider. In addition to these, there are a number
of external influences such as culture, changes in price
and quality equipment, competitive on the market, and so
on.
The Bass model is a very useful tool for forecasting the
adoption of an innovation. A key feature of the model is
that it embeds a contagion process to characterize the
spread of word-of-mouth between those who have
adopted the innovation and those who have not yet
adopted innovation.
The mathematical interpretation of the Bass model is
derived from a hazard function corresponding to the
conditional probability that an adoption will occur at time t
given that it has not yet occurred (Bass, 1969; Bass et
al., 1994; Meade and Islam, 2006). If f(t) is the density
function of time to adoption and F(t) is the cumulative
fraction of adopters at time t, the basic hazard function
underlying the Bass model is given by following equation
(Bass, 1969):
f ( t)
= p + q ⋅ F(
t)
. (1)
1−
F ( t)
Parameter q reflects the influence of those consumers
who have already adopted the product/service (that is,
word-of-mouth communication from previous adopters),
while p captures the influence that is independent from
the number of adopters (that is, external communication).
The solution of equation (1) is given by following
equation:
F(
t)
=
1−
e
q
1+
e
p
−(
p+
q)
t
−(
p+
q)
t
. (2)
If m denotes the market potential for the new
product/service, then the cumulative number of
adoptions, Y(t), at time t is given by:
Y ( t)
= mF(
t)
. (3)
The current (non-cumulative) service sale at time t, S(t),
is given by:
Radojicic et al. 7227
2
q 2
s( t)
= mf ( t)
= pm + ( q − p)
mF(
t)
− qmF ( t)
= pm + ( q − p)
Y ( t)
− Y ( t)
m
(4)
For estimation the parameters p, q and m from discrete
time series data the following analogue can be used:
2
( )
−1 −1
− + = s t a bYt
cYt
(5)
where a, b and c are the coefficients that have to be calculated
based on the regression analysis. For estimated
the value of market potential, m:
− b −
m =
b
2c
2 −
4ac
, (6)
the Bass model parameters of innovation p and imitation
q, could be obtained by following equations:
a
p = (7)
m
and
q = −mc
. (8)
Based on these parameters, the new service adoption
could be calculated. The model can forecast the longterm
sales pattern of new services and technologies
under two types of conditions (Bass et al., 1994):
i. The company has recently introduced the service or
technology and has observed its sales for a few time
periods;
ii. The company has not yet introduced the service or
technology, but its market behavior is likely to be similar
to some existing services or technologies whose adoption
pattern is known.
One of the most uncertain issues concerned with
application of the Bass diffusion model is correct
estimation of the market potential. This value has direct
impact on diffusion process profile of new service, in
other words on parameters p and q. In order to estimate
the market potential for IPTV, we have to forecast the
total number of residential customers (households) in the
area of interest. We could increase the accuracy of the
forecast by sub-dividing the total number of households
into different economic levels. If we distinguish between
four classes of household economic levels HE = (1, 2, 3,
4), we proposed the new model for residential market
potential estimation, m:
= ⋅ ⋅ s k m
4
∑
HE=
1
HE ⋅ HP HH
HE
. (9)

7228 Afr. J. Bus. Manage.
Table 2. Number of IPTV subscribers (in thousands).
Month Monthly # of IPTV subscribers s(t) Cumulative # of IPTV subscribers Y(t)
September, 2008. 146 146
October 331 477
November 836 1,313
December 1,793 3,106
January, 2009. 1,849 4,955
February 1,594 6,549
March 1,427 7,976
April 1,154 913
May 1,932 11,062
June 3,412 14,474
July 3,419 17,893
August 264 20,533
September 1,679 22,212
October 1,509 23,721
November 1,509 2,523
December 1,704 26,934
January, 2010. 1,579 28,513
February 1,053 29,566
Table 3. Parameters obtained by regression analysis.
a b c p q m
0.621 0.257 - 0.0087 0.0195 0.277 31.84
Where: HH is the number of households; it could be
estimated as the ratio of the total population and mean
number of households’ members; HP is household
penetration of the considered area (numerical value from
0 to 1 or even above 1); HE could be high income
families (HE = 1), middle income families (HE = 2), lower
income families (HE = 3) and poor families (HE = 4); k is
a parameter of technological availability of network
infrastructure; s is a service substitution parameter.
Before a decision is made about the implementation of
IPTV as a new service, it is necessary to test the entire
network infrastructure in order to qualify the copper pairs,
ready to support this service. The parameter of
technological availability, k, has to be calculated based
on the results of such testing in the Telecom Serbia
network. Substitution parameter, (s) is estimated based
on forecasted share of competing services (terrestrial TV,
cable TV, satellite TV and IPTV) in the Serbian market.
IPTV SUBSCRIBERS FORECASTING MODEL
EVALUATION
Bass parameters, p and q, can usually be evaluated in
two manners. One way is to use analogies with other
similar services or diffusion process. As we have shown,
the second is analytical, using equations (5) to (8).
Based on the data of actual and forecasted total IPTV
subscribers in the world, it was shown that the estimated
Bass parameters p and q are not directly applicable to
the Serbian telecommunication market. Namely, if we use
the same values for p and q (calculated based on the
relevant historical data), we obtained the great disproportion
between the actual and forecasted results for the
IPTV users in Serbia. Therefore, we try to estimate the
valid values of parameters p, q and m based on the
Equations (6) to (8) and the actual statistics from the
Serbian IPTV market during the previous year. Table 2
gives the actual statistics of IPTV service from service
introduction in the Serbian market.
We performed the linear regression analysis using
equation (5) to calculate the unknown parameters a, b, c
and corresponding parameters m, p, q by equations (6) to
(8), respectively. Table 3 gives the results of the
regression analysis. Thus, the forecasted values of noncumulative
sales at time t, obtained by the Bass diffusion
model could be calculated using the expression (4).
Calculated number of IPTV users obtained by the Bass
model is given in Table 4. Figure 3 illustrates the comparative
results for actual and calculated cumulative number
of IPTV subscribers in a case of regression parameters
values p = 0.0195, q = 0.277 and m = 31.84. Authors
believe that the obtained estimated value for market

Table 4. Calculated number of IPTV subscribers (p = 0.0195, q = 0.277, m = 31.84).
Radojicic et al. 7229
Month Monthly # of IPTV subscribers s(t) Cumulative # of IPTV subscribers Y(t)
September, 2008. 707 707
October 0.902 1.609
November 1.135 2.744
December 1.398 4.142
January, 2009. 1.682 5.824
February 1.965 7.789
March 2.217 10.006
April 2.41 12.416
May 2.51 14.926
June 2.505 17.431
July 2.394 19.825
August 2.195 22.020
September 1.936 23.956
October 1.653 25.609
November 1.371 26.980
December 1.11 28.090
January, 2010. 0.881 28.971
February 0.689 29.660
Figure 3. Cumulative number of IPTV subscribers
potential, m, is considerably less than it is expected to be.
Therefore, the total market potential for IPTV service in
Serbia market has to be estimated based on new model
as proposed by equation (9). The major advantage of this
model is that it takes into account the main relevant
influence parameters of market potential. The corresponding
parameters values are: the total population of
Serbia is 7.5 millions; the mean number of household
members is 3.1; parameter of technological availability of
network infrastructure is 0.8. The number of households

7230 Afr. J. Bus. Manage.
Figure 4. Graphs for household penetration determination
that could potentially become IPTV service users entering
households with high-income households (HE = 1) and
middle-income households (HE = 2). Household penetration
of the Serbia is determined according to the
available statistical data and graphs depicted in Figure 4
(Leiijon, 1996) and service substitution parameter is
estimated to be 0.6. We performed the necessary calculations
based on the statistical data from National
Telecommunication Agency (RATEL, 2009).
We assumed that 10% of total Serbian population is
classified as high-income households and 35% as
middle-income households. Depending on household
m = k ⋅ s ⋅
2
∑ HH ⋅ HP
HE=
1
= 0.
8⋅
0.
6⋅
penetration, global trend and local economy relative to
global economy, low household penetration curve type
seams to be appropriate for Serbian market.
Assuming that HE1=1 (household economy for high
income families), we estimated that the HP1 = 0.9
(household penetration for high income families),
assuming that HE2 =2 (household economy for middle
income families) we estimated that the HP2 = 0.35
(household penetration for middle income families),
based on Figure 4. Based on such given parameters, we
estimated the total residential market potential as the
results of the expression (10):
( 0.
1⋅
7500 / 3.
1⋅
0.
9 + 0.
35⋅
7500 / 3.
1⋅0.
35)
= 247
HE HE
(10)
For modified value of the residential market potential (m),
it is necessary to adjust the Bass diffusion parameters p
and q. By using the data curve fit creator, we obtained
the following modified values for p = 0.002, q = 0.14. For
these values, the best matching between actual and
forecasted data are obtained, as shown in Figure 5. In
addition, Figure 5 illustrates the cumulative forecasted
number of IPTV user for Serbian residential market up to
the end of 2012.
The preliminary Serbian Telecom expectations about
the adoption rate of the IPTV service were not achieved
at the present time. It was about 50% less than previously
planed. The main reasons could be found in facts
that the time of the service launched was delayed, also
due to relatively high service implementation costs for
residential subscribers. Such situation indicates that the
potential market was not considered adequately. We took
into account that circumstances in our forecasting procedure
and tried to determine the future IPTV service
demands more precisely.
CONCLUSION
The IPTV might become the leading broadband application
in the near future. Both, telecom as well as cable
operators are highly interested in offering the IPTV service
to their customers, mainly due to increase their
profits and also to achieve the greater satisfaction of the
end users. There were many research studies concerned

Figure 5: Forecasted and actual cumulative number of IPTV subscribers (p = 0.002, q = 0.14, m = 247)
with forecasting the number of IPTV subscribers in
different part of the world. However, a particular and
precise forecast has to be done for each country as well
as for each operator in the considered country.
In this paper, we presented the results of the forecasted
number of IPTV subscribers in Serbia until the
end of 2012. The forecasting procedure was performed
based on the diffusion theory. We made a modification of
the main Bass diffusion model in order to estimate the
residential potential market. The new model takes into
account the availability of network technology capable to
support a new service. The authors believe that the
infrastructure network in the case of broadband
applications may be a limiting factor in the provision of
new services. This factor could be decisive in comparison
with some other factors such as marketing, quality and
price that may contribute to the adoption of services. In
addition, the presence of substitution services has to be
taken into account.
It is obvious that the future IPTV demands will significantly
depend on various influence factors, primary
economic, technological, marketing, etc. Additionally, the
IPTV operators have to be ready to take part in highly
competitive market circumstances. The actual IPTV
demands will depend largely on operator’s ability to
promptly and effectively respond to user requests.
Consequently, our further research could encompass the
concurrent perspective of the future IPTV market in
Serbia.
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African Journal of Business Management Vol. 5(17), pp. 7232-7239, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM10.617
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Cause-related marketing and consumer behaviour in
the greater eThekweni area
Karen M. Corbishley* and Roger B. Mason
Department of Marketing, Retail and Public Relations, Durban University of Technology, South Africa.
Accepted 31 March, 2011
Cause-related marketing (CRM) is a marketing strategy in which a company’s name, brand or service is
partnered with a cause or a charity. This type of link has become increasingly popular throughout the
world, presenting economic and social opportunities for businesses. Various research studies in such
first world countries as the United States and the United Kingdom reveal that a large proportion of
consumers are responsive to CRM. One of the objectives of this study was to establish whether
selected socio-demographic factors affect the evaluation of a CRM offer in the eThekweni region of
South Africa. It is anticipated that, its findings will be of assistance to marketers enabling them to make
a more accurate identification as to the responsiveness of various groups to a CRM strategy. A
quantitative study was conducted in shopping malls, using a structured questionnaire administered via
interviews. Results established that there is a relationship between socio-demographic characteristics
and the evaluation of a CRM offer.
Key words: Consumer behaviour, cause-related marketing, socio-demographic variables.
INTRODUCTION
Helping others is an impulse, recognised worldwide
(Benapudi et al., 1996). Over time, the pressure on
business to contribute towards non-profit causes has
increased (Cui et al., 2003). Cause-related marketing
(CRM) has become a popular marketing strategy used by
brand managers, retailers and service companies. Shabir
et al. (2009) define CRM as a “process of formulating and
implementing marketing activities that are characterized
by a promise of the firm to donate company resources to
a worthy cause for each sold product or service, satisfying
organizational and individual objectives”. Charities
are faced with an increasing struggle as demand for their
service escalates, and government support diminishes
(Alam, 2009). For these reasons, charities have had to
look beyond traditional methods for support (Benapudi et
al., 1996).
Various research studies conducted in such first world
countries as the USA and the UK, show that many
consumers would be prepared to change to brands that
*Corresponding author. E-mail: karenc@dut.ac.za. Tel:
+27(0)31 373 5393. Fax: +27(0)86 674 0607.
were supportive of a cause, especially if all other factors
such as price and quality were seen as equal
(Subrahmanyan, 2004; Till and Nowak, 2000). It has also
been suggested that, consumers that differ according to
socio-demographic variables such as age, gender and
income, would also have varying opinions towards CRM.
Meaningful research such as this has only been conducted
in a few countries. Such data is not yet available for
South Africa or more specifically, the eThekweni market.
Marketers often make use of demographics when
segmenting markets. Demography is useful to marketers
as it is easily obtainable and can usually be connected to
consumer buying behaviour (Lamb et al., 2008). This
article concentrates on cause-related marketing in South
Africa, specifically the eThekweni (Durban) region. It
focuses on the socio-demographic characteristics of participants
and any possible links to their attitudes towards
CRM. Cui et al. (2003) state that, marketers might find
socio-demographic variables useful in identifying whether
various groups would be responsive towards CRM.
Furthermore, the same characteristics could be studied to
establish which causes, each group would be more likely
to respond to as well as whether that profile fits a particular
brand. As the South African and the eThekweni

consumer profile are very different to those of other
countries that have already conducted some research in
this field, it is believed that more localised information on
this topic would be most useful for both academic and
business purposes.
Background to the eThekweni region
The eThekweni municipal area is located in the province
of KwaZulu-Natal, on the east coast of South Africa. This
area covers 1.4% of the province’s total land area, but
has over a third of its population and 60% of its economic
activity (eThekweni Municipality, 2004). The city has a
population of more than 3 million of which, 68% are of an
economically active age and 38% are under the age of 19
(South African Yearbook, 2005). The population is made
up of approximately 3 million inhabitants with 60% being
black, 21% Indian, 11% white and 3% coloured (Moodley,
2004).
THEORETICAL FRAMEWORK
Corporate social responsibility
Corporate social responsibility (CSR) refers to companies,
recognising that they have an obligation towards
a broad range of entities, such as customers, employees,
suppliers, shareholders and the broader community.
Kotler and Lee (2005) define CSR as the contribution of
both business resources and practices towards the
betterment of the general community. Many causes
throughout the world look to the corporate sector for
assistance because of the financial power they are
believed to wield (Adkins, 2000).
Possible benefits to businesses that engage in CSR
include a better reputation and greater retention and
loyalty of employees (Moir, 2001). Business people recognise
that their success is often linked to the well being
of the community in which they operate. Corporations
that have CSR as a core value often make more than
purely profit driven companies in the same sector (Ali et
al.,2010). Businesses that support social causes receive
good publicity, as well as favourable responses from
consumers. Furthermore, as time passes, consumers
develop the expectation that this behaviour is normal for
the business involved (Alam et al., 2010). CSR is thus
becoming an important differentiator in competitive
environments. As price and quality barely vary between
offerings, consumers become increasingly demanding
and expectant (Ali et al., 2010).
Cause related marketing
There are a number of ways in which CSR could be initiated.
Kotler and Lee (2005) identified six major initiatives.
Corbishley and Mason 7233
First, cause promotions is used to describe a method in
which business would provide funding, contributions and
concern towards a cause. Second, corporate social
marketing describes behaviour focused on behaviour
change, where a campaign designed to improve a
situation is implemented. A direct contribution towards a
charity or cause is termed corporate philanthropy, while
the involvement in adopting practices and investments
that support social causes is called socially responsible
business practice. Staff can be encouraged to give their
time to support causes. This is described as community
volunteering. Lastly, cause related marketing (CRM) is a
marketing practice where a contribution is made towards
a cause based on the number of sales that are generated.
As a type of CSR, CRM has received particular
corporate interest as it has been established that it can
have a positive impact on consumer behaviour (van den
Brink et al., 2006).
In a seminal study, Varadarajan and Menon (1988)
identify two main objectives of CRM. One is to be of
assistance towards a social cause and the other is for the
benefit of the business. Berglind and Nakata (2005)
described CRM as a mutually beneficial relationship. A
CRM campaign is specific as it has a prescribed end date
and it is for an indefinable product and charity (Kotler and
Lee, 2005) and the transaction is emphasised. As a result
of the consumer’s behaviour, a donation is made to the
cause that the company has identified (Cornwell and
Coote, 2005).
To sum up, there is a connection between product
sales, the raising of funds for a charity, and potential
increased sales for the business with all parties benefiting
(Kotler and Lee, 2005).
Benefits of CRM
Nelson et al. (2007) describe CRM as a ‘win-win’ situation
as both the business and the cause benefits.
Carringer (1994) believes that CRM has become a good
choice for corporations as it provides a message that is
unique, well targeted and effective. It is a most efficient
way for companies to differentiate themselves in a highly
competitive environment.
Successful CRM initiatives can assist in attracting new
customers, reach unique market segments, build sales,
and build equity. Furthermore, CRM is a highly effective
strategy for raising funds for worthwhile causes (Kotler
and Lee, 2005).
Central to a successful CRM campaign is the consumer
who is demanding social responsibility from business.
Consumers benefit as well from the intangible feelings
associated with giving as well, the tangibles received
from the product itself (Tustin and Pienaar, 2005). Finally,
leaders of not-for-profit organizations are most appreciative
of the flow of funds and publicity coming their way
through these initiatives (Berglind and Nakata, 2005).

7234 Afr. J. Bus. Manage.
CRM research
Although CRM has expanded throughout the world, only
a few countries have conducted meaningful research in
areas involved with this topic. Some of the countries
where research has been identified include, Europe, the
USA, Australia, New Zealand, Mexico and the UK
(Endacott, 2004). Results have established that there is a
more favourable attitude towards businesses that have
strategies that involve a relationship with a cause. In turn,
consumer decision-making is affected by these attitudes
through a more positive evaluation of the business and
product (Szykman et al., 2004).
Although international research is evident on attitudes
and opinions towards CRM, it was more difficult to find
information on behaviour according to detailed socio-demographic
standing. For example, Cui et al. (2003) stated
that consumer research on CRM seldom focused on age.
Their study found that Generation Y respondents were
generally positive towards CRM. This view was supported
by Tustin and Pienaar (2005), who stated that, those
born between 1977 and 1994 are a particularly philanthropic
generation. Cui et al. (2003) went on to establish
that female students had a more positive outlook on CRM
than male students did. Cone Roper (1994) also found
that education could be a defining factor, as those with a
higher education were more likely to be positive towards
CRM. Previous studies conducted by Cui et al. (2003)
and Kotler and Lee (2005) suggested that, those in middle
to higher income categories were more open towards
CRM. Research carried out in 2001 by Cone Roper (cited
in Kotler and Lee, 2005) concurred with this view stating
that those in higher income categories were more receptive
towards CRM. Furthermore, those who had families
also seemed to make more purchases associated with
CRM. A reason for this was that many in this group
wished to support causes, but did not have sufficient free
time to do it in any other way (Business in the
Community, 2003).
Business in the Community is an organization in the UK
that specializes in CSR and represents many companies.
A number of research studies have been commissioned
by Business in the Community in the field of CRM. Statistics
revealed that, 98% of respondents in the UK and
USA are aware of a CRM program, 83% of respondents
had been involved in a CRM program and 48% of consumers
had responded to a CRM programme by adjusting
their purchasing behaviour (Catalyst, 2006). Catalyst
(2006) established that, 82% of the population in general
had been involved in CRM during the previous year.
The amount was even more for the 35 to 44 year old
age group (89%) and 94% for those who were members
of a household with children.
CRM in South Africa
There is not a lot of information on consumer opinions
and attitudes toward CRM in South Africa. A study was
commissioned by Nedbank (one of the major banking
groups) in 2002, that established five top causes that
South African consumers prefer business to support.
These were (in descending order); crime/personal safety,
poverty, HIV/Aids, unemployment and the economy.
However, it provided no data on attitudes and opinions
towards brands that were involved with CRM (Endacott,
2004).
Most major fast-moving consumer goods companies in
South Africa are aware of CRM, but many of them still
have their doubts about how to action CRM, in order for it
to be beneficial to all. There is a perception by a number
of businesses in South Africa that charities are not
always accountable for the funds that they receive (Tustin
and Pienaar, 2005). Nevertheless, investors (both locally
and abroad) are placing increasing pressure on businesses
to be involved in good causes. Therefore, CRM is
one of the ways in which South African businesses and
stakeholders can demonstrate their commitment towards
social responsibility (Tustin and Pienaar, 2005).
It has been established that knowledge of CRM in
South Africa is limited. Therefore, this paper attempts to
provide marketers with additional information on the relationship
between causes and socio-demographic factors.
In order to meet this objective, a relationship between
socio-demographic characteristics and the evaluation of a
CRM offer, has been hypothesised. It has also been
hypothesised that, eThekweni consumers would be more
likely to switch brands to one that is involved with CRM,
given equal price and quality.
METHODS
The study was cross-sectional and made use of a quantitative methodology.
The setting was non-contrived and minimal interference
was made in the participant’s normal pattern of life. Non-probability
sampling; quota sampling was used to select respondents (Cooper
and Schindler, 2001). The relevant control dimensions are given in
Table 1. The age divisions were based on generations that are
recognised as potential market segments. Generation Y (or Generation
next) – born between 1977 and 1994, Generation X – born
between 1965 and 1976, Baby Boomers – born between 1946 and
1964, and the elderly or ‘grey’ market – elderly baby boomers and
those born before 1946 (Lamb et al., 2008). Controls to guide final
selection were 200 per category for gender and 50 per category for
other variables.
Specific respondents were chosen via systematic sampling,
which involved the selection of individuals as they entered the
shopping centre, according to a predetermined number sequence.
The number sequence was chosen according to a random element
between 1 and 10 (Leedy, 1993).
For populations from 75 000 to one million, a sample of between
382 and 384 should be used (Cavana et al., 2001). Therefore, a
sample of 400 was selected, but because of spoiled questionnaires,
the final number used in the analysis was 391. To collect the empirical
data, a survey was conducted. The data was gathered through
the use of questionnaires administered during mall intercepts at,
The Pavilion (a large regional mall that draws clientele from
throughout the region) and The Workshop (a smaller mall in the city
centre). A number of students were trained to conduct the

Table 1. Socio-demographic dimensions.
Gender Age Household income per month (South Africa Rands) Education
Male 12-29 R30000 Post-graduate
interviews.
The questionnaire was derived from literature, highlighting research
conducted elsewhere in the world, predominantly Business
in the Community studies (2002 and 2003) and the article written by
Cui et al. (2003). The data was analysed and shown in the form of
frequency tabulations and cross tabulations and the appropriate
significance tests were applied. The Statistical Package for the
Social Sciences (SPSS) Version 13.0 was used to analyse the
data.
RESULTS
The demographics of the sample are shown in Table
2.This study concentrated on seven socio-demographic
variables: Age, gender, income and education as in Table
2, plus marital status, and children (stage of the family life
cycle). It was difficult to obtain sufficient respondents in
some sub-sections of education, so, these results were
interpreted with care.
Univariate analysis
A number of opinions and attitudes were identified in this
section. These did not pertain to socio-demographics, but
were nevertheless useful to know. Chi square goodnessof-fit
testing was carried out on all questions. The 0.05
level of significance was used. Significant findings were
that, 94% of respondents believed that it was important
for businesses to spend money on charities, and 88%
agreed that a business that practiced CRM had a better
image. Sixty-nine percent of respondents stated that they
had purchased a CRM product, but 25% could not recall
whether they had purchased a CRM product. Twenty-four
percent of respondents felt that CRM would not influence
their purchase decision, whereas, 76% of respondents
stated that they would choose to buy from a retailer that
practiced CRM. A high percentage (87%) of respondents
agreed that they were happy to support CRM initiatives
as such initiatives provided them with an opportunity to
support deserving causes, with 65% of respondents
preferring CRM to putting money in a collection box.
Many of the respondents (64%) said that they were short
of time and so a CRM project enabled them to contribute
towards a cause without using too much time. However,
76% of the respondents indicated that they had already
participated in some activity to raise funds for charity.
Bivariate analysis
Corbishley and Mason 7235
The main objective of this research was to establish
whether socio-demographic variables have an affect on
various opinions and attitudes towards CRM. To assess
this, cross tabulations of two variables was conducted.
The chi-square test of dependence was applied to most
questions. When conditions were not met, a Fisher’s
exact test was carried out. Exact tests provide a way of
obtaining accurate results when the data fails to meet the
underlying assumptions necessary for reliable results
using the standard asymptotic method.
Opinions and attitudes towards CRM were crosstabulated
against the socio-demographic variables identified
in the study. It was found that more females than
males agreed that it was important for businesses to
spend money on charities. When it came to the purchase
of a CRM product, significant links were found between
education, gender, marital status, children and income.
Those who recalled purchasing a CRM product were
more likely to be highly educated, female, married, had
older children and earned a higher income than average.
Results are illustrated in Table 3.
Analysis shows that respondents who have very little
education and earn a lower income were more likely not
to be aware of whether they have purchased a CRM product.
A higher proportion of males also indicated that they
“did not know”. These results could be useful in that, they
show that there are groups that would be less responsive
to a CRM offer. However, they might be more likely to
respond if they are better educated as to the nature of
CRM. This has implications for marketing communications
by businesses practicing CRM. These results are
shown in Table 4.
Respondents were requested to select between a
retailer that supported CRM and any other retailer, given
that the product was equal in quality and price and the
retailer was accessible. Only one socio-demographic
variable showed significance (p = 0.18 60
age group), were found to respond positively to retailers
who support causes. One might question whether the
elderly have more time to be more selective in their
choice of retailer.
This study established that there is a relationship between
socio-demographic characteristics, such as, age,
income, gender, education, marital status and age of

7236 Afr. J. Bus. Manage.
Table 2. Socio-demographics of the sample.
Demographic variable Characteristics Frequency Percentage (%)
12-29 179 45.8
Age (years)
30-41
42-60
101
77
25.8
19.7
Over 60 34 8.7
Gender
Household income (in Rands per annum)
Male 173 44.2
Female 218 55.8
Less than R5 000 134 34.3
R5 001 to R10 000 97 24.8
R10 001 to R20 000 71 18.2
R20 001 to R30 000 37 9.5
More than R30 000 47 12.0
Primary school 12 3.1
High school 218 56.8
Education
Diploma 85 22.1
Degree 44 11.5
Post graduate 25 6.5
Total sample 391 100.0
Table 3. Demographics and purchase of a CRM product.
Variable Proportion who have bought a CRM product Χ 2 df P value
Education
Primary
33.33%
High
67.89%
Diploma
76.05%
Degree
88.64%
Post-graduate
76%
16.041 5 0.007*
Income
Marital
Status
Children
Gender
*Significant at p < 0.05.
R30000
52.99% 74.23% 77.46% 78.38% 89.36%
Single Married Widowed Div/Sep
62.33% 80.47% 65.22% 80%
No Children Children under 12 Children 12-18 Children over 18
73.26% 57.14% 75% 72.73%
Male Female
63.15% 74.55%
children and the evaluation of the CRM offer.
DISCUSSION
The overall objective of this study was to gain an understanding
of consumer behaviour towards companies
using CRM in the greater eThekweni region. Results
31.769 8 0.0005*
17.704
6 0.007*
12.999 6 0.043*
6.042 2 0.049*
gathered in the eThekweni area were similar to those
from elsewhere in the world, despite different lifestyles
and socio-demographics.
Of the respondents that were interviewed, 94% agreed
that it was important for businesses to spend money on
charities. The number of respondents that had recalled
purchasing a CRM product amounted to 69%, which was
a little lower than previous international results. This
could be attributed to the fact that CRM is not yet common

Table 4. Demographics and lack of knowledge of a CRM purchase.
Corbishley and Mason 7237
Variable Proportion who did not know if they had purchased a CRM product Χ 2 df P value
Education
Primary
66.67%
High
32.11%
Diploma
32.94%
Degree
11.36%
Post-graduate
28.57%
16.041 5 .007*
Income
Marital status
Children
Gender
*Significant at p < 0.05.
R30000
37.31% 20.62% 21.13% 16.22% 8.51%
Single Married Widowed Div/Sep
28.84% 18.75% 26.09% 16%
None < 12 12-18 >18
19.19% 36.26% 20% 25%
Male Female
29.24% 20.91%
in South Africa and a number of respondents had to have
the concept explained to them. They also could be a link
with perceptions that charities in South Africa are not all
professionally managed (Tustin and Pienaar, 2005). In a
similar result to those gained else-where in the world,
88% of respondents agreed that a business would have a
better image if they were seen to be supporting a cause
in some way.
It was interesting to observe that 76% of respondents
indicated that they had participated in some activity to
raise funds for charity. This figure is substantially higher
than the figures of 21 and 35% obtained by Business in
the Community (2003). A possible explanation for this
could be the highly visible needs in the eThekweni region
and the rest of South Africa.
Where these results did correspond to some extent
with the international results was that, 58% of the respondents
claimed that they did not get involved with charity
because of time pressure problems. Despite the
similarity, the international figures were higher. A possible
explanation for this is that those residing in first-world
countries such as the UK or USA might be more aware of
time-pressure than those in an emerging economy such
as South Africa. Less than the international figures, but
still quite high, 64% of respondents agreed that getting
involved with a CRM purchase was a time-saving
exercise, in that they could support a charity by
purchasing a product, rather than having to go out and
make an active contribution.
Cross-tabulations were carried out in order to establish
whether any socio-demographic variables were related to
opinions and attitudes towards CRM. It was found to be
significant that females were more positive about the
importance of business, spending money on charities.
Regarding level of education, there was a more positive
31.769 8 .0005*
17.704 6 .007*
12.999 6 .043*
6.042 2 .049*
relationship between respondents with degrees and the
purchase of a product linked with CRM than those who
had less education. It was also established that married
people were more likely to have purchased a CRM
product. Fewer single people had purchased a CRM
product.
However, parents of smaller children (under 12) are not
as aware whether they have purchased a CRM product
or not. Fewer parents of young children recalled
purchasing a CRM product. When it came to age, the
younger age group (12 to 29) disagreed with the
suggestion that a business would have a better image if it
supported a CRM product. In contrast, older people (> 60
age group) were more positive towards supporting a
retailer who supported a cause. Regarding income, fewer
people in the lowest income group recalled purchasing a
product linked with CRM, compared to those in the higher
income groups.
It was interesting to observe that many of the results
above were similar to those from studies conducted
elsewhere in the world. Areas in agreement with previous
findings include the finding that females are more responsive
towards CRM than males. Furthermore, there is
agreement that those that are better educated (university
level qualifications) and are in a higher income group are
also more positive towards CRM.
Married people seem to be more positive towards
CRM, although, those with small children do not seem to
recall purchasing a CRM product as much as would be
expected. A possible reason could be that a mother of
small children might be more preoccupied with other
things when shopping than those with older children. The
lack of time that parents of small children seem to
experience could be a possible explanation for this
situation.

7238 Afr. J. Bus. Manage.
The one area that did not appear to give similar results
to previous research was that of age. Younger respondents
did not appear to be impressed by a business that
was practicing CRM, whereas among those over the age
of 60, a more than expected number would support a
retailer that practised CRM. This could possibly be
explained by the fact that this generation has grown up in
a media-saturated environment and is very aware of
marketing hype (Schiffman and Kanuk, 2004). They are
generally seen as sceptical of the media. A suggestion
would be that, if businesses selected a cause to support
that this generation identified with, the response might be
different.
IMPLICATIONS FOR MARKETERS
Marketers should find this research useful for a number
of reasons. Firstly, it would of interest to the local
marketer to have confirmation that the consumers in the
eThekweni area are supportive of CRM. It means that,
this is a valid form of marketing that is not only acceptable
to the consumer, but actually improves the image of
the business in the eyes of most consumers. Consumers
also indicated that they would actually be prepared to
change brands to one that is supporting a cause that they
cared about. There is still a small proportion of
consumers that views this form of marketing with some
scepticism as to the motives of the business, but they are
in the minority. For the academic, this research has
contributed to the body of knowledge on CRM.
Information on attitudes and opinions towards CRM has
added to that of previous studies.
LIMITATIONS
When bi-variate analysis is conducted, the cross tabulation,
results in a table of many more cells than that with
uni-variate analysis. Because of this, some cell
frequencies could be quite small, and therefore, the precision
of estimates within cells could be less than those
obtained in a uni-variate analysis. For this reason,
analysis was conducted with care and significance tests
including a Fisher’s exact test that was carried out when
cell numbers did not meet the required conditions.
Furthermore, questions that have an element of
prestige or adherence to social norms can typically result
in an upward response bias (Kinnear and Taylor, 1991). It
could be said that questions related to charitable support
and giving, could be seen in this light. This is unavoidable
and it is impossible to know if, and when it occurs, and
therefore, it should be borne in mind when interpreting
results.
Findings are limited to eThekweni and should therefore
be generalised to the rest of South Africa with care.
RECOMMENDATIONS
This study could be expanded by gathering information
on a wider scale. For economical reasons, only the
eThekweni region was used. Research could therefore
be expanded to encompass the whole of South Africa,
which would provide marketers with information to guide
national, rather than just regional, marketing.
Further studies could also incorporate a number of
additional socio-demographic variables, and even
psychographics. It has also been observed that not much
research has been carried out to examine CRM from the
cause’s point of view. This could be an important angle to
provide charity marketers with helpful information on
which to base their marketing strategies when seeking to
form alliances with the corporate sector.
ACKNOWLEDGEMENTS
The authors would like to thank the anonymous reviewers
whose comments contributed to improving this paper.
They would also like to thank Women in research of the
National Research Foundation, South Africa for the
financial support that made this research possible.
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African Journal of Business Management Vol. 5(17), pp. 7240-7247, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM10.746
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Supply chain management: success factors from the
Malaysian manufacturer’s perspective
Ai Chin Thoo* Hon Tat Huam, Rosman Md Yusoff, Amran Md Rasli, Abu Bakar Abd Hamid
Department of Management, Universiti Teknologi Malaysia, Johor, Malaysia.
Accepted 15 December, 2010
The purpose of this paper is to shed the light on the critical success factors that lead to high supply
chain performance outcomes in a Malaysian manufacturing company. The critical success factors
consist of relationship with customer and supplier, information communication and technology (ICT),
material flow management, corporate culture and performance measurement. Questionnaire was the
main instrument for the study and it was distributed to 84 staff from departments of purchasing,
planning, logistics and operation. Data analysis was conducted by employing descriptive analysis
(mean and standard deviation), reliability analysis, Pearson correlation analysis and multiple
regression. The findings show that there are relationships exist between relationship with customer and
supplier, ICT, material flow management, performance measurement and supply chain management
(SCM) performance, but not for corporate culture. Forming a good customer and supplier relationship is
the main predictor of SCM performance, followed by performance measurement, material flow
management and ICT. It is recommended that future study to determine additional success factors that
are pertinent to firms’ current SCM strategies and directions, competitive advantages and missions.
Logic suggests that further study to include more geographical data coverage, other nature of
businesses and research instruments.
Key words: Supply chain management, critical success factor.
INTRODUCTION
Back in the 1960s, the cornerstone to every successful
company is to make customers, keep customers, and
maximise customer profitability. Later, the focus moved
away from low costs and low quality product markets to
high quality products markets at lower costs with greater
responsiveness (Chin et al., 2004). Numerous quality initiatives
were initiated by many companies, including total
quality management (TQM), international organisation for
standardisation (ISO) and just-in-time (JIT) for quality
assurance and measurement (Chandra and Kumar,
2000). By the early 1990s, intense competition and global
markets forced organisations to get a product and service
to the right customer, at the most opportune time and at
the lowest cost (Altekar, 2005; Li et al., 2003). More and
*Corresponding author. E-mail: acthoo@utm.my. Tel: 6012
2581 935. Fax: 607 556 6911.
more organisations are promoting supply chain competitiveness
to attain organisational efficiency, as present
competition is between effective supply networks rather
than individual organisations.
In the 21st century, supply chain management (SCM)
shapes a new manufacturing paradigm of organisational
sustainability and competitiveness (Gunasekaran, 2004).
SCM is progressively recognised as a key and vital corporate
strategy, which links both suppliers and customers
in order to enhance overall manufacturing flexibility.
Besides, successful SCM is a prominent tool to reduce
cost of operation by eliminating all non value added
activities in the flow of various kinds of materials from
supplier to end customer (Chan and Lee, 2005).
Statement of the problem
Enhancing superior supply chain performance has

ecome one of the critical approaches for sustaining
competitive advantages for companies (Cai et al., 2009).
This manufacturing company is truly striving hard to
achieve superior supply chain performance in order to
outperform its competitors. However, the problem the
company is faced with is what to do with supply chain
inefficiency under its organisational control.
A key problem for this manufacturing company is the
management of customer relationship. Customers demand
faster and timelier delivery of orders. The company
is in the high levels of demand variation that causes the
demand changes are always hard to anticipate (Lummus
and Vokurka, 1999). Failure to meet customers demand
could result in lost revenues, lower customer satisfaction
and potential claims for late delivery. In addition, the
company finds itself locked-in to its supplier. This lock-in
is dominated by the suppliers by imposing restricted
terms and conditions to the company order. The order is
non-cancellable, non-returnable and cannot be rescheduled
to a later date. For an example, if customer cancels
demand not fulfilled on time, it may lead to high inventory
carrying costs and high material exposure. Another
problem is the relative lack of information communication
and technology (ICT), both inside and outside the
company (Ayers, 2001). Substantial ICT differences
between the company and its suppliers can hinder the
coordination activities for transactions, the quality of
information sharing and information visibility. As a result,
supplier response time for a purchase order is increased.
Besides, there is a problem on the raw material flow or
raw material availability, the delivery reliability of the
supplier (Van Weele, 2005). Supplier fails to deliver raw
materials at the required time to meet production schedule.
Because the company relies on its supplier for on
time shipments, the late deliveries can result in shipment
delay to its customers. As a consequence, customers can
decrease or cancel orders. Each functional department is
well aware of the requirements of customers and makes
cooperative contributions to achieve higher profitability.
But there is a lack of commitment and cooperative efforts
between departments. Issues of materials default location,
identification, traceability and the inaccurate records
on the actual amount and value of inventories (Altekar,
2005) have direct impact on the timely production and
performance of others in the organisation.
The company seldom undertakes ways to improve its
supply chain performance and measures whether or not
they have been successful. Basically, supply chain measurements
consist of four main activities namely plan,
source, make and delivery (Gunasekaran et al., 2001).
Supply chain metrics such as capacity utilisation, human
resource productivity, percentage of defects, supplier
delivery performance and delivery reliability performance
are not being deployed to track supply chain performance
(Gunasekaran et al., 2004) in the company.
Measurement is helpful and is the only way to understand
whether process performance is improving or
Thoo et al. 7241
worsening and whether or not correction action is
required urgently (Roussel and Cohen, 2005).
Background of the study
Electronic manufacturing services (EMS) industry is one
of the industries that require SCM to optimise both operations
and profits. EMS provides electronics manufacturing
services to other electronic companies. EMS focuses on
printed circuit board fabrication, electronic design,
assembly and testing. EMS industry aims to achieve a
large economy of scale, make the fullest use of capitalintensive
manufacturing equipment, source raw materials
and pool together resources, and provide postmanufacturing
services including warranty and repairs.
The objective of SCM in the manufacturing company is
to deliver high customer service at minimal inventory and
low unit cost by synchronising the customers need with a
smooth flow of material from suppliers. The structure of
supply chain in this manufacturing company is driven by
the design, planning and operation of four key drivers: the
physical network, inventory management, transportation
management and information systems. These four major
drivers manage the flows of material and enhance cost
efficiency of the entire supply chain.
Objective of the study
This paper seeks to explore the relationship between
relationship with customer and supplier, information and
communication technology (ICT), material flow management,
corporate culture, performance measurement and
its SCM performance of an established manufacturing
company.
LITERATURE REVIEW
Supply chain performance measurement approach
Performance measurement is described as “a parameter
used to quantify the effectiveness and efficiency of
action” (Neely et al., 1995). Effectiveness is to measure
how a customer's need is fulfilled and efficiency is to
measure how an organisation's resources are exploited in
order to increase customer value. Performance measurement
systems are defined as a complete set of
approaches applied to measure the “efficiency and
effectiveness of action” (Neely et al., 1995; Shepherd and
Gunter, 2006).
Balanced scorecard
The balanced scorecard is a company performance
measurement tool and this framework was introduced by
Robert S. Kaplan and David P. Norton in 1992 (Kaplan

7242 Afr. J. Bus. Manage.
and Norton, 1996). Four major categories are identified
including financial measurement, customer services measurement,
internal company performance measurement
and learning.
Supply-chain operations reference (SCOR) model
The supply-chain operations reference (SCOR) model
was developed by the supply-chain council (SCC) to help
organisations to improve the efficiencies and competitiveness
of their supply chains (Stewart, 1997). According
to Christopher (1998), the objectives of SCOR include a
standardised approach to measure supply chain performance
and apply a set of metrics to benchmark against
other organisations. The SCOR model is categorised by
four management processes:
(1) Plan: match supply and demand
(2) Source: procurement of raw materials
(3) Make: transformation of the raw materials into finished
goods
(4) Deliver: delivery of products or services
Benchmarking
Benchmarking is a systematic process of determining
and implementing best practices in strategic planning and
operational improvement. Benchmarking is a technique
for comparing a firm’s business processes against the
best practices of other firms (Camp, 1989). Benchmarking
is important for the firms to compare similar performance
metrics. As suggested by Splendolini (1992),
benchmarking process consists of five fundamental
purposes:
(1) Strategy: short and long term planning execution
(2) Forecasting: predict trends
(3) New ideas: suggest new insight
(4) Compare processes
(5) Objectives and goal-setting against best practices
Previous studies on relationship between SCM
success factors and SCM performance
Relationship with customer and supplier
The foundation of a business alliance is the relationships
between supply chain partners, that is, customer and
supplier. Effective partnership is dependent upon an
environment grounded in mutual trust, loyalty, positive
sum game, fairness in negotiations, goal and intent revelation,
and commitment among partners (Chandra and
Kumar, 2000). Spekman et al. (1998) claimed that sustainable
business success relates to the strength of the
relationship between firm and its supply chain partners.
Good partnerships have regarded as strategic decisions
in expanding revenue and reducing cost. Therefore, a
company’s long-term success is primarily dependent on
customer satisfaction and the supplier reliability (Chandra
and Kumar, 2000; Choy et al., 2003). Various studies
(Fearne and Hughes, 1999; Humphreys et al., 2001;
Valsamakis and Sprague, 2001; Vereecke and Muylle,
2006; Bartlett et al., 2007; Ounna et al., 2007) have
addressed the needs of close collaborative linkages
through the entire supply chain. According to Alfred
Wong (2002), firms with a high supplier satisfaction and
contribution achieve a higher level of customer satisfaction
and SCM performance outcomes than those that
show weaker supplier value focus.
Information and communication technology (ICT)
ICT is an enabling strategic vehicle for supply chain performance
that facilitates inter- and intra organisational
communications (Boubekri, 2001; Yu et al., 2001;
Jonsson and Gunnarsson, 2005). Information technology
(IT) is seen as the key ingredient to business survival and
information quality (Gunasekaran and Ngai, 2004;
Auramo et al., 2005). Dawson (2002) found that a seamless
supply chain network demonstrates high productivity
and high customer satisfaction, also allow firms to
communicate with other partners, with online and timing
information to improve visibility to orders. Being able to
adopt new IT in SCM is a strategic imperative for all
successful businesses (McLaughlin et al., 2003). The
right SCM information system can enhance firms’
operational efficiency and operational flexibility (McLaren
et al., 2004).
Material flow management
Effective logistics network is the crucial link between
market and production. The implementation of material
flow management aims at reducing costs of non-valueadding
efforts and the stocks while simultaneously
achieving long-term sustainability (Spath and Baumeister,
2001). Childerhouse et al. (2003) studied the best
practices on how to re-engineering a construction supply
chain by using material flow control system, providing
examples of nine different companies. Therefore, the
development of creative solutions to material flow offers
firms a high potential for realising new economic
competitive advantages. In this context, logistic capability
is expected to result in improved supply chain efficiency.
The capabilities include timely materials delivery, global
delivery capabilities, shipments accuracy and good
knowledge of logistics (Meier et al., 2004).
Corporate culture
Corporate culture is defined as common expectations,

practices and goals that are shared by the majority of the
organisation (Deresky, 2008). Management support has
become a critical factor for successful supply chain
performance (Van Hoek et al., 2002). Meier et al. (2004)
supported the importance of management support and
pointed out that leadership management is an important
element in the SCM. Leadership management requires
shared culture, privacy protection, accountability, high
management expertise, good mindset and professional,
decisive in decision making, ethical and continuous
performance measurement. Mello and Stank (2005)
found that firms have inappropriate or inadequate cultural
elements (for example, shared assumptions, values and
artifacts) are inclined to fail when adopting SCM practices.
According to Fawcett et al. (2006), a successful
supply chain is driven by organisational commitment and
governance. There are four types of managerial support
required to achieve high supply chain performance: from
upper management support to departmental support,
channel support and infrastructural support.
Performance measurement
Gunasekaran et al. (2001) stressed the importance of
supply chain performance measurement for a successful
SCM. Using customer satisfaction measurement has
enabled a business to compete more effectively in its
targeted mission. Customer feedback provides a platform
for the strategic alignment of organisational resources to
meet customer expectations (Swinehart and Smith,
2005). In addition, as suggested by Liang et al. (2006),
suitable supply chain performance metrics are important
for a successful company. Shepherd and Gunter (2006)
reviewed numerous literatures of supply chain performance
measurement techniques and suggested several
issues that further studies should address. The issues
include success factors that influence the actual implementation
of supply chain performance measurement
metrics, the forces shaping their evolution over time and
problems related to their continuous improvement.
RESEARCH METHODOLOGY
Sample
The study included four manufacturing departments: purchasing,
planning, logistics and operation. The total population comprised 84
persons in the company. According to Issac and Michael (1995),
with a confidence level of 95%, the sample size would be 80 respondents.
Evidently, the sample size was too small, so researcher
included the entire population in the study. Out of 84 questionnaires
distributed to the respondents, 100% completed questionnaires
were collected successfully via e-mail. Profile of respondents is
shown in Table 1. The majority of respondents were in the 21 to 30
age band (58.3%), female (60.7%) and Chinese (46.4%). They had
a degree qualification (46.4%), worked in this company for less than
5 years, but more than a year (46.4%). Most of them were officer or
Thoo et al. 7243
executive position (81.0%) and from purchasing department
(45.2%).
Measurement
The instrument used in this study was adapted from the studies of
Chin et al. (2004), Tumala et al. (2006), Davis et al. (1989) and
Huan et al. (2004). Respondents were asked to rate their agreement
to statements regarding critical success factors - SCM
performance relationships on a 5-point Likert scale (1 = “Strongly
Disagree” to 5 = “Strongly Agree”) and (1 = “Decrease” to 5 =
“Increase”). The reliability test was assessed in the study, and the
alpha scores were more than 0.65 as shown in Table 2. In this
sense, the scales used were reliable and consistent.
RESULTS
A descriptive analysis (means) of relations between
critical success factors and supply chain performance
was carried out in the manufacturing company. The
average distribution of scores was slanted toward agreement.
Participants in the survey rated that the factor of
performance measurement had the most influence on
supply chain performance.
The Pearson’s correlation was used to explore a correlation
between SCM performance and critical success
factors. As shown in Table 3, the results indicated a
significant positive correlation between SCM performance
and critical success factors. The value ranges from +0.4
to +0.7.
The multiple regression analysis was employed to test
hypotheses and to examine the strength of relationships
between SCM performance and critical success factors.
The result is summarised in Table 4, the final model
accounted for 70.1 % of the variance (Adjusted R 2 =
0.701). The factor of relationship with customer and
supplier demonstrated the greatest impact on SCM
performance, followed by performance measurement,
material flow management and ICT.
Table 5 presented the results of hypotheses testing.
The results indicate that relationship with customer and
supplier, information communication technology, material
flow management and performance measurement are
imperative for overall SCM performance in the company.
In this study, four hypotheses are accepted and only one
hypothesis is rejected.
DISSCUSSION AND IMPLICATIONS
The findings of this study validate the research of Tumala
et al. (2006) and Chin et al. (2004), it is noted that SCM
critical success factors help manufacturing companies to
maximise efficiency, reduce operational cost, build
stronger supplier and customer relationships, improve
profitability and lead times, increase system flexibility and
firm competitiveness. The study results are consistent
with the findings of previous similar research. Because

7244 Afr. J. Bus. Manage.
Table 1. Profile of respondents.
Demographic variable Frequency Percentage
Age
2 1to 30 49 58.3
31 to 40 28 33.3
41 to 50 5 6.0
51 and above 2 2.4
Gender
Female 51 60.7
Male 33 39.3
Race
Malay 31 36.9
Chinese 39 46.4
Indian 12 14.3
Others 2 2.4
Highest academic qualification
SPM/STPM 10 11.9
Diploma 31 36.9
Degree 39 46.4
Master 2 2.4
PhD/DBA 1 1.2
Others 1 1.2
Years of working experience
Less than 1 year 2 2.4
1 to 5 years 39 46.4
6 to10 years 28 33.3
11 to15 years 11 13.1
16 years and above 4 4.8
Position
Officer/executive 68 81.0
Manager/supervisor 16 19.0
Department
Purchasing 38 45.2
Planning 10 11.9
Logistics 21 25.0
Operation 15 17.9
Source: Field survey, (2009).
the study shows that the studied companies have
operational focus in the manufacturing.
The results from multiple regression analysis demonstrate
that four predictors influence the SCM performance,
except for the corporate culture. It found that
relationship with customer and supplier had the highest
beta value (0.455) that would impact the criterion variable
the most. It is notable that strong corporate culture can
improve firm performance, but not for weak corporate
culture (Gordon and DiTomaso, 1992; Kotter and
Heskett, 1992). A later study by Siew and Kelvin (2004)
advanced the view that strong culture can affect the
success of the business in some cases. In contrast, weak
culture can lead to employee feelings of separateness

Table 2. Cronbach’s alpha scores for variables.
No. Variable No. of Item Cronbach’s alpha
1 Relationship with customer and supplier 13 0.698
2 Information and communication technology (ICT) 9 0.712
3 Material flow management 9 0.673
4 Corporate culture 16 0.732
5 Performance measurement 11 0.712
6 Supply chain management performance 9 0.773
Source: Field survey, (2009).
Table 3. Correlation coefficient for critical success factors-SCM performance.
SCM
performance
Pearson
correlation
SCM
performance
Relationship
with customer
and supplier
ICT
Material flow
management
Corporate
culture
Thoo et al. 7245
Performance
measurement
1 0.735** 0.428** 0.527** 0.369** 0.569**
Sig. (2 tailed) 0.000 0.000 0.001 0.000
N 84 84 84 84 84 84
** Correlation is significant at the 0.05 level (2-tailed). Source: Field survey, (2009).
Table 4. Regression result for critical success factors – SCM performance.
Critical success factors SCM performance
Beta (β) +
Relationship with customer and supplier 0.455**
Information and communication technology (ICT) 0.184**
Material flow management 0.234**
Corporate culture 0.070
Performance measurement 0.276**
Adjusted R 2 0.701
F Statistic 40.01
Sig. F 0.000
** p-value < 0.05
** Correlation is significant at the 0.05 level (2-tailed).
Source: Field survey, (2009).
from the organisation; hence it can impair organisational
performance (Smircich, 1983).
The result shows that corporate culture is not significantly
related with SCM performance in the manufacturing
company. Cultural traits such as empowerment,
constantly changing environment, management style and
work flexibility are not correlated with SCM performance
indicators. A potential reason for this may be due to the
manufacturing company has many subcultures and they
vary by divisions or by departments. Each department
has a unique set of culture and its own personality.
Therefore, respective department has its own folklore to
run its operation, solve problems, make decisions and
communicate with each others (Ross, 2000). As a result,
the company with numerous subcultures which lack of
cooperative efforts is difficult to pursue the success of the
overall SCM implementation process.
The finding of the study has been proven that building a
good relationship with customer and supplier is very
important to a successful SCM implementation. The

7246 Afr. J. Bus. Manage.
Table 5. Summary of research hypotheses result.
Research hypotheses Results
H1: There is a significant positive relationship between relationship with customer and supplier and
SCM performance.
Accepted
H2: There is a significant positive relationship between information and communication technology and
SCM performance.
H3: There is a significant positive relationship between material flow management and SCM
performance.
Accepted
Accepted
H4: There is a significant positive relationship between corporate culture and SCM performance. Rejected
H5: There is a significant positive relationship between performance measurement and SCM
performance.
Source: Field survey, (2009).
success or failure of SCM hinges on a company’s ability
to integrate its key supply chain partners. The company
should develop a trust-based relationship with customer
and supplier, in order to improve visibility to orders which
generated by time-phased demand and supply planning.
Besides this, supply chain performance measurement
plays an important role in increasing supply chain
efficiency. Therefore, the company should develop supply
chain performance measures on a timely basis. Of
course, it requires commitment and cooperative efforts
from managers of different functional areas such as
planning, purchasing, operation and logistics. An effective
supply chain network is also characterised by a good flow
of materials and products. Applying good inventory
management can yield significant improvements in both
inventory cost and customer satisfaction level. Finally,
scalable technology is a key component in propelling
company into new directions in the demand and supply
process linkages. In fact, a good quality of information
sharing with suppliers helps to create the best material
and products flows (Lambert and Cooper, 2000). Thus, it
can be said that an efficient synchronisation of information
and material flows directly affect the performance of
the company and its supply chain.
Limitations and suggestions for future research
This study implies some limitations and scarcity, logic
suggests that future researchers include more geographical
data coverage, because small sample size makes
it very difficult to generalise the result to manufacturing
sector. Therefore, it is of great importance to include
more manufacturing companies in future research. The
result would be much better if it can represent the full
picture of Malaysia manufacturing industry. In addition,
the other nature of businesses including food industry
Accepted
and cosmetic industry should be examined in determining
the success factors of supply chain performance. Apart
from the five critical success factors in this study, it is
recommended that future study to determine additional
success factors that are pertinent to firms’ current SCM
strategies and directions, competitive advantages and
missions. Future researchers should also extend their
research by investigating actual SCM strategies implementation.
The strategies include leagile supply chains,
web-based supply and demand integration, supplier
partnership and logistic strategy. Further study could be
conducted to identify the measurement of supply chain
effectiveness before and after the SCM strategies
implementation.
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African Journal of Business Management Vol.5 (17), pp. 7248-7257, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM10.867
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Dimensions of information technology infrastructure
flexibility in improving management efficacy of
construction industry perspective: A conceptual study
Nurshuhada Zainon 1 * and Hafez Salleh 2
1 Department of Quantity Surveying, Faculty of Built Environment, University Malaya 50603, Kuala Lumpur, Malaysia.
2 University Malaya, Kuala Lumpur, Malaysia.
Accepted 10 February, 2011
As technologies change rapidly, improved information technology (IT) products and services are
released daily throughout the world. This phenomenon gives tremendous pressure on organization
managers to plan, implement and adopt new technology solution in accommodating such changes.
Thus, one of the most significant current discussions is IT infrastructure flexibility. Most of the studies
in IT infrastructure flexibility have been carried out across industries; however less attention has been
paid to measure flexibility of IT infrastructure in construction industry. The purpose of this paper is to
provide a conceptual understanding on how IT infrastructure flexibility responds in changing the
business demand by exploring the dimensions that could be used to measure IT within construction
industry. The study is based on textual reading in a range of recently published works, of which
majority of them are from 2000 to 2010. The findings will provide potential variables about each
dimension in measuring IT infrastructure flexibility, indicating factors that can be used for future
development of an IT infrastructure flexibility maturity model. In this context, the maturity model will be
useful for construction organisations to determine where they are. It also offers a benchmark for
assessing different organisations for equivalent comparison.
Key words: IT infrastructure flexibility, technical infrastructure flexibility, human infrastructure flexibility, IS
flexibility.
INTRODUCTION
In the current economic climate, people has realised the
importance of IT in altering and improving the way
businesses operate. In construction industry, IT is
perceived as a driver for many of the construction
business and operational processes (Aouad et al., 1999;
Eadie et al., 2010). The establishment of e-business in
the industry such as e-tendering, e-procurement, e-portal,
and other electronic transaction process is a proof that
there has been a technological shift in construction sector
*Corresponding author. E-mail: zshuhada@perdana.um.edu.my.
Tel: +603-7967 7603. Fax: +0603-7967 5713.
Abbreviations: ITIF, IT infrastructure flexibility; IT, information
technology; IS, information system.
from IT driven solutions to IT enabling ones.
Nevertheless, IT environments today are dramatically
different from the host-centric systems of 20 years ago.
Today, IT systems span complex networks with multiple
access points and servers, hundreds of software
components and thousands of computing devices (Raad
et al., 2010). IT changes rapidly and due to the ecommerce
revolution, it may be changing faster than
ever. The industry has started to realise how IT
infrastructure can be managed to best achieve today’s
business goals under ever-changing business
environments, in the midst of rapid changes of
technology (Abukhder et al., 2004; Ahmad et al., 2002;
Alam, 2009; Aouad, et al., 1999).
Few researchers agree that the development of a
flexible IT infrastructure is important (Boar, 1997;
Brancheau et al., 1996; Niederman et al., 1991). Despite

the global financial crisis in early September 2009, the
recent report by the Forrester Research (2009) indicated
that the IT investment increases in late 2009 and 2010.
The Gartner Group (2010b) confirms this with a
prediction that worldwide enterprise IT spending across
all industry markets will rise 4.1% in 2010, surpassing
USD2.4 trillion. Construction industry, however, has
always become one of the lowest investor in IT (Kennet,
2010). For instance, Construct IT recently reported that
the UK construction industry’s spending on IT stands at
£2,556 (USD3,870) per head and this make up a total
annual spending on IT in the industry in 2009 to be £1.2
billion (USD1.82 billion) only (Kennet, 2010). This finding
is consistent with data found by Gartner Group (2010a)
where the industry spent the lowest amount in IT. This
figure, nevertheless, is much improved if compared to 20
years ago (Kennet, 2010). A group of researchers from
Canada found out that construction organisations were
spending a relatively very small proportion of their total
budget on IT, which about up to 1% of total revenue
(Hewage et al., 2008).
Out of this small investment of construction
organisations on IT, its adoptions are still facing failure
even after years of IT introduction in the industry (KPMG
IT Advisory, 2008; Standish Group, 2009). The
fragmented nature of construction industry is the core
explanation of why IT meets challenges in its adoption.
Construction involves various parties in one project, and
the team changes for every project. Furthermore, every
party has its different needs and different functions in
using IT. That is why, the technology providers face
difficulties in understanding the needs of the construction
firms and how to address the overall IT integration to
successfully increase the level of communication
(Hewage et al., 2008). The industry also has
discontinuous nature of the building design and
construction supply chain, for instant, design and
construction teams form for a single project and then,
dissolve. Hence, there is no way to use the same type of
technology for all types of construction projects, as every
construction project is unique and complex. Moreover, it
is impossible to select tailor-made IT for each and every
construction project because it would be very extremely
costly. These reasons answer a question of why is IT
investment is much less intensive in construction than the
other sectors even though many evidence have been
found that IT highly impact on construction organisation’s
performance (Gaith et al., 2009). With these characterristics,
how is construction industry coping with the
changes in IT?
Unlike other engineering projects, once an IT
application has been developed or packaged for
commercialization, it will not only have to be further
maintained but it will also have to be enhanced,
extended, and adapted to new or changing platforms (Al-
Ahmad, et al., 2009). Besides the fragmented nature of
construction industry, Hewage et al. (2008) found that
Zainon and Salleh 7249
35% of respondents who were construction managers did
not believe the construction industry is ready for rapid
changes in IT. This is because, upgrading or adopting
new technology consumes large investment, and if they
do so, they have to bear a risk towards the failure of
upgraded or new adopted IT. Additionally, the findings
also reported that construction managers are concerned
about how the workers will respond to the addition of IT
because they are not willing to invest in adding a
technology assistance department at present (Hewage et
al., 2008). This issue does not only bother construction
industry; it worries other industries as well. Acccording to
the latest KPMG Survey (2010), it shows that 450 Chief
Information Officers worldwide who had responded have
agreed that IT needs to have an ability to react to
changes. Not just that, many gigantic companies have
embarked in research concerning this issue such as IBM,
Butlergroup, Oracle and Forrester Research. In
academic journals as well, there has been an increasing
interest in measuring the ability of IT to handle changes
as it is the particular characteristic in IT infrastructure
which has a critical impact on the enterprise’s ability to
use IT competitively (Allen and Boynton, 1991; Byrd and
Turner, 2000; Chung et al., 2005; Chung, et al., 2003;
Davenport and Linder, 1994; Duncan, 1995; Gibson,
1993; Masrek and Jusoff, 2009; Rockart et al., 1996;
Weill, 1993).
Researchers have been investigating the strategic
value of IT infrastructure flexibility (ITIF) since the mid
1990s (Paschke et al., 2008). The concept of ITIF is
based on Duncan’s (1995) works that measured ITIF
through shareable and reusable IT resources. Previous
researchers investigated ITIF by assessing it across
industries and none has ever attempted to examine the
ITIF focusing at construction industry level, therefore, the
understanding of ITIF in construction industry remain
poorly understood. This represents the first theoretical
gap in the extant literature. This paper would further
deepen our understanding on factors that contribute
towards the success of the IT implementation in
construction industry considering that it has several
unique features which distinguishes it from other
industries; namely the fragmental nature, one-off
projects, and multi-participants, as discussed before.
Thus this paper will not contradict, but it will complement
existing research. On top of that, as many researchers
have discussed dimensions to measure ITIF, yet there is
no study known to the authors that investigated the
dimensions of ITIF particularly for construction industry.
Understanding this issue is important for both practice
and research because of its potential to provide
information about each dimension in ITIF for the future
development of an ITIF maturity model. This paper is
addressing these research gaps; guided by the following
research question; with the unique features of
construction industry, what are the suitable dimensions to
be used to measure ITIF?

7250 Afr. J. Bus. Manage.
DEFINING IT INFRASTRUCTURE FLEXIBILITY (ITIF)
There are many other terms that have similar meaning to
ITIF. Ness (2005) has compiled many terms used within
the industry and research which are “IT elasticity, ondemand,
utility-based computing, virtual IT, agile IT, IT
transformation, real-time enterprise and organic IT, and
grid computing (Hietter, 2008)”. These terms vary based
on their focus regarding the scope of IT processes,
strategies, methods, and/or tools to achieve true ITIF
(Ness, 2005). In literature, however, a term commonly
used is ‘IT infrastructure flexibility’. Although not all
researchers have referred directly to the term ITIF, their
concepts and items are relevant to the flexibility of IT
infrastructures.
The term “infrastructure” is referred to the networking
and platform components of the technical architecture
(Ness, 2005). Its meaning has been broadly applied
within research to indicate the rapid deployment of
technology through an organization’s existing technology
and personnel-based resources (Byrd and Turner, 2000;
Tallon and Kraemer, 2003). Further, “IT infrastructure”
has been defined from two perspectives:
(1) An aggregation of technology components (Duncan,
1995).
(2) A combination of technology components and human
factors, including resource planning and management
factors that affect the capabilities of IT (Byrd and Turner,
2000).
In applying the term “flexibility”, there is no single
definition that can be appropriately apply to all resources,
but in general, the term is used to reflect such
characteristics as the ability to control outside
environment effectively (De Leeuw and Volberda, 1996)
which it able to be used for a variety of tasks,
responsiveness to change, or able to be easily
transformed (Gross and Raymond, 1993). Gross and
Raymond (1993) stated that flexibility is emerging as a
key characteristic of all types of resources that involve
hard and soft matters. These include people and tools,
and processes. Furthermore, few researchers added that
flexibility is also the ability to predict and sense
environmental change (Whitworth and Zaic, 2003). With
flexibility, businesses are able to effectively use IT in
dynamic environments. From these explanations, Byrd
and Turner (2000) have come out with ITIF definition:
“ITIF is the ability to easily and readily diffuse or support
a wide variety of hardware, software, communication
technologies, data, core applications, skills and
competencies, commitments, and values within the
technical physical base and the human component of the
existing IT infrastructure”.
Later, (Byrd and Turner, 2000) have comprehended the
ITIF definition.
“ITIF is the ability of the infrastructure to support a wide
variety of hardware, software and other technologies that
can be easily diffused into the overall technological
platform, to distribute any type of information (data, text,
voice, image, video) to anywhere inside of an
organisation and beyond, and to support the design,
development and implementation of a heterogeneity of
business applications”.
As many researchers in their literature used these
definitions, this paper therefore is based on Byrd and
Turner’s as well.
RESEARCH METHODOLOGY
The data and findings presented in this paper are mostly taken from
secondary sources. The information was gathered from journals
and literature books with a focus on the IT infrastructure flexibility
research from when it was introduced until the current research
approach. It apparently does not cover all areas comprehensively,
this paper focuses mainly on IT infrastructure issues of IS projects
embedded within construction industries. Majority of them are from
2000 to 2010. The source materials of the data were obtained
from libraries’ databases of Malaysian universities. In order to
update the information for the findings, the Internet was used as an
important source.
You have explained more with an outline of limitations. This work
has a number of limitations that you must need to acknowledge
BENEFITS OF IT INFRASTRUCTURE FLEXIBILITY
The concept of ITIF comes from a need to have IT that is
able to face the rapid technology changes. To some
point, previous studies agreed that ITIF is a key to
success of IT during periods of intense change,
particularly where flexibility in IT infrastructure acts as a
foundation for overall IT flexibility (Davenport and Linder,
1994; Tallon and Kraemer, 2003). In this situation, ITIF is
believed to benefit from construction organisations in four
aspects as thus explained.
Cost saving
Generally, many researchers believe that a flexible IT
infrastructure helps the organization in handling
increased customer and market demands without
increasing costs (Davenport and Linder, 1994; Weill,
1993). As improved IT products and services are
released every day, it is difficult for construction
organisations to implement new IT without a large reinvestment.
Hence, by having flexible IT infrastructure,
construction organisations are able to support changes
by reusing the existing component of IT infrastructure
every time new technology is introduced as it is designed
to handle changes. Besides, ITIF provides capability of
adjusting to wide variety of environments, and it has
depth and scalability to apply to most construction
organisational needs. On top of that, construction
organisations save the cost from providing training to

their own staffs or clients because with ITIF, it allows the
construction organisations to exert greater control over
IT/IS operations within and beyond the organisation to
ever-changing technologies, legislation, policies,
regulations and constituent expectations (SAP, 2009;
Sweeny, 1995).
Time saving
ITIF allows managers in construction organisations to
make decision towards business-IT infrastructure
alignment so that they can quickly adapt to environmental
changes and explore new ideas of processes (Leana and
Barry, 2000). As re-development of new IT infrastructure
takes too long to implement, ITIF enables IT systems to
support changes and it can be improved without having
to start all over again (Butler Group, 2006a). As a result,
ITIF can shorten product time cycle, increase design
alternatives and produce higher quality products (Omar et
al., 2010). In addition, ITIF implies building a system with
capabilities to anticipate distinct requirements such as a
broad range of products that offer suitability for each
party involved as clients, contractors, and designer team.
They will be communicating using IT systems and this
saves time in term of communication (Hashim et al.,
2010).
Improve communication
ITIF offers expansion plans to other geographical
locations. Thus, ITIF improves connection between
parties involved and the construction organisations will
become more globalised. They can get real time data,
and communicate with other parties at anytime from
anywhere. Therefore ITIF promotes better integration
and better business process.
Increase effectiveness and enhance competitive
advantage
As many researchers have addressed the impact of ITIF
towards IT effectiveness, they agree that ITIF is a
significant factor towards the effective delivery of IT
services and solutions and it provides a powerful and
viable approach to delivering efficacious IT solutions and
services to the business (Butler Group, 2006b; Chung et
al., 2005; Chung, et al., 2003; Masrek and Jusoff, 2009;
Ness, 2005; Sääksjärvi, 2000; Sriprasert and Dawood,
2002). Additionally, the combination of having both
technical infrastructure and human infrastructure in IT is
proven by few studies that it enhances competitive
advantage with their importance is found to be positive to
the organisations’ flexibility (Byrd and Turner, 2001;
Chung et al., 2005; Fink and Neumann, 2007). Hence,
Zainon and Salleh 7251
this paper can safely state that ITIF will improve
effectiveness in construction organisations, as well as
enhancing competitive advantage.
DIMENSIONS OF IT INFRASTRUCTURE FLEXIBILITY
The result of Duncan’s study was a framework for IT
infrastructure, and since then, other authors have
investigated further on ITIF (Table 2). The definition of
flexible IT infrastructure qualities through the dimensions
of connectivity, compatibility, modularity and skilled IT
personnel, and these dimensions appear to be consistent
among the literature reviewed (Table 1). Even though
many researchers included an extra variable for data
transparency/integration/management, this is, however,
is part of Duncan’s original classification and falls into the
categories of compatibility and modularity. In construction
industry context, there are three dimensions suggested
as very important measures to be used; namely technical
infrastructure, human infrastructure and flexible information
system (IS).
Technical infrastructure flexibility deals with hard issue.
It consists of connectivity, modularity, and compatibility.
Connectivity is the ability of any technology component to
communicate with any of the other components intra or
inter organizational environment (Duncan, 1995; Masrek
and Jusoff, 2009) which helps to facilitate the ability to
share of IT resources at the platform level (Tapscott and
Caston, 1993). This means that, with ITIF the system is
readily connected anytime and anywhere it is needed,
with high speed and good telecommunication lines
provided. As for one simple example, text messages can
be shared, or at the other extreme, any document,
process, service, video, image, text, audio, or a
combination of these can be used, regardless of the
manufacturer, make, or type. Compatibility is the ability
to share any type of information across any technology
component throughout the organization (Duncan, 1995)
and across organizations (Masrek and Jusoff, 2009). It
enables an organization to capture data, information and
knowledge, as well as span organizational boundaries
and empower employees at anytime (Tapscott and
Caston, 1993). The ability to easily reconfigure any
technology component with no major overall effect is
known as modularity (Byrd and Turner, 2000; Duncan,
1995; Masrek and Jusoff, 2009; Schilling, 2000). It
relates to the degree to which IT software, hardware, and
data can be either effortlessly diffused into the
infrastructure or easily supported by the infrastructure
(Chung et al., 2005). Consequently, software application
can be more manageable when routines are processed in
separate modules.
Human IT infrastructure puts skilled IT personnel in this
category. It refers to a person, or a professional team
who has knowledge, skills and experiences required to
manage IT resources within organisations and master in

7252 Afr. J. Bus. Manage.
Table 1. ITIF dimensions from research literature.
Authors (by years) ITIF dimensions
Technical infrastructure
Keen (1991) Reach Range
Gibson (1993)
Duncan (1995)
Broadbent, et al. (1996)
Communication
connectivity
Network
connectivity
Communication
management
Computer
compatibility
Application
functionality
Platform
compatibility Modularity
Standards
management
Application
management
Data
transparency
Data
management
Human
infrastructure
Human
infrastructure
Byrd and (2000)
Byrd et al.(2004)
Tallon and Kraemer (2003)
Human IT
infrastructure
Chung et al. (2003) Skilled IT
Chung et al. (2005)
Ness(2005)
personnel
Chanopas et al.(2006)
Connectivity Compatibility Modularity Scalability,
rapidity,
facility,
modernity
Human IT
infrastructure
Paschke et al., (2008)
Masrek and Jusoff (2009)
Skilled IT
personnel
business knowledge as well (Byrd and Turner, 2000;
Chanapos et al., 2006; Chung et al., 2003; Paschke et
al., 2008; Tallon and Kraemer, 2003). The third dimension
is flexibility of IS (Paschke, et al., 2008). The IS
flexibility is the ability of IS to adapt to organization’s
environment changes. Parchke et al. (2008) suggest
three elements fall under this dimension, which are as
market flexibility, integrity flexibility, and network
flexibility.
IMPLICATION TO MANAGEMENT OF
CONSTRUCTION INDUSTRY
Few researchers have examined the importance of IT
infrastructure being flexible, and they have agreed that
ITIF brings positive implications to management
(Chanapos et al., 2006; Chung et al., 2003; Davenport
and Linder, 1994; Duncan, 1995; Ness, 2005; Tallon and
Kraemer, 2003). In construction industry, IT systems
have typically been architected either in a project-centric
way, addressing a business issue at a point in time, or in
Information
system
Market,
integrity and
network
the case of primary transactional systems; resulting
inflexibility in design of individual applications or the
supporting infrastructure. Whilst each system may be fit
for purpose, it is difficult to modify that purpose as
business needs change. To overcome this issue, construction
organisations need to develop an approach to
ITIF for the reason that ITIF enables organizations to
build applications that more closely satisfy business
objectives as proven by Chung et al. (2003).
In practice, there is a gap between business and IT,
and both of the environments are rapidly changing
conditions (Butler Group, 2006a; Robertson and Sribar,
2002). The dimensions of ITIF have positive impacts on
strategic IT-business alignment (Chung et al., 2003;
Tallon and Kraemer, 2003); therefore ITIF seems to
benefit the construction managers in aligning the
relationship between the business and IT infrastructure.
For IT infrastructures to be able to facilitate organisational
responses to dynamic environments, the IT strategy
(technical and human infrastructure and information
system) must be tightly aligned with the organisational
strategy. Thus, ITIF increases levels of an organisation’s

Table 2. Current ITIF research approach.
Study / Research Approach Focus Developers Comment
ITIF dimensions of
evaluation.
ITIF model.
Holistic view of
flexibility on online
business.
The impact of ITIF
on organizations.
Model on how ITIF
and strategic
flexibility interact
with, and shape,
strategic alignment.
The impact of ITIF
on business
performance.
The impact of ITIF
on strategic
alignment and IT
effectiveness.
The role of IT
Technical
infrastructure.
Technical
infrastructure
and human
infrastructure.
Managerial.
Technical
infrastructure
and human
infrastructure.
Technical
infrastructure,
human
infrastructure,
and managerial.
Technical
infrastructure
and human
infrastructure.
Technical
infrastructure.
Managerial,
leadership.
Study of resource
characteristics and their
measure.
Exploratory analysis of
a construct.
Role of flexibility in
online business.
Relationships among
ITIF and strategic
alignment and
application
implementation.
Implications for IT
business value.
Relationships among
ITIF, mass
customization, and
business performance.
Exploring relationships
between strategic
alignment and IT
effectiveness.
Focusing at how to
manage flexible IT
strategy.
(Duncan, 1995)
(Byrd and
Turner, 2000)
(Ozer, 2002)
(Chung et al.,
2003)
(Tallon and
Kraemer, 2003)
(Chung et al.,
2005)
(Ness, 2005)
(Patten et al.,
2005)
Zainon and Salleh 7253
Develop 3 dimensions of IT
flexibility, namely; connectivity,
compatibility, and modularity.
Added IT personnel flexibility as
an important dimension of ITIF
while combining connectivity and
compatibility into one dimension
called integration.
Investigating how online business
can achieve flexibility through the
different functional aspects of their
business; technology, human
resources, operations, marketing,
finance, and management.
Connectivity, modularity and IT
personnel competency have
positive impact on strategic
alignment.
Four components of ITIF
(compatibility, connectivity,
modularity, IT personnel
competency) have positive impact
on the extent of applications
implementation.
ITIF and strategic alignment
complement each other.
ITIF can have both direct and
indirect effects on business value.
ITIF is a determinant of strategic
flexibility.
The relationships exist and ITIF
have positive impact on strategic
alignment and IT effectiveness.
Proposes IT Flexible Framework
(IFF) with three critical aspects
that an organisation should
consider in managing flexible
IT/IS.

7254 Afr. J. Bus. Manage.
Table 2. Contd.
The mediating role of
IT infrastructure
capabilities on
flexibility and IT
personnel
capabilities
Dimensions of ITIF
Relationship
between ITIF and IT
responsiveness.
The effect of ITIF on
intranet
effectiveness.
Technical
infrastructure
and human
infrastructure.
Technical
infrastructure,
human
infrastructure,
and flexible IS.
Technical
infrastructure
and human
infrastructure.
Technical
infrastructure
and human
infrastructure.
Exploring IS as one of
the dimensions of ITIF.
Small-mediumenterprises’
ITIF.
Exploring relationships
between ITIF and
intranet effectiveness.
effectiveness and efficiency. This fact has been
examined by few researchers namely Ness (2005),
Masrek and Jusoff (2009), Chung et al. (2003), and
Chung et al. (2005).
The findings contribute to a more thorough
understanding among top management in construction
organisations of IT infrastructure flexibility. By knowing
this, managers in construction organisations have
freedom to take full advantage of an IT system because
ITIF is able to accommodate and respond to new
initiatives. Furthermore, managers can create an
investment plan by looking at their weak points and make
immediate changes to keep up with the competition.
DISCUSSION
Construction industry brings unique features that differ it
from other industries. Hence the central focus of this
paper is to identify the dimensions that can be proposed
to measure ITIF in construction context. IT infrastructure
developments in construction play a role in changing the
service channels and upgrading processes to the faster
and saver ways with significant efficiencies (Musara and
Fatoki, 2010). Therefore, the element of technical
infrastructure is the major factor that needs to be focused
on in the first place. Without a good infrastructure with
capability to adapt with rapid technology changes, IT
(Fink and
Neumann
2007);
(Paschke et al.,
2008)
(Jie et al.,
2009)
(Masrek and
Jusoff, 2009)
The impact of connectivity and
compatibility on IT responsiveness
is fully mediated by modularity and
IT personnel competency, which in
turn affect IT responsiveness
directly.
Compatibility, connectivity and IT
personnel competency are
significantly related to intranet
effectiveness.
development can be very costly and it could be a burden
and a major hindrance to some construction
organisations (Omar et al., 2010). Consequently, this
element is critical thus technical infrastructures, which
encompasses modularity, compatibility and connectivity,
are identified as one of the dimensions to measure ITIF,
and these dimensions have been proven by many
researchers as discussed earlier.
In order to develop a flexible IT infrastructure, a team of
IT experts must be carefully selected. Currently, there is
a gap between business and IT environment among IT
personnel in construction industry (Rettig, 2005). There
is always a case where IT personnel who are in charge of
IT development for construction organisations may be
very knowledgeable in IT but they may not understand
the nature of construction business. Vice versa, if they
have a team of people from the construction background,
these people may not be as knowledgeable in using IT
and probably not catching up well with the IT technology
advancement. In order to align between business and IT
infrastructure, IT personnel who develop the IT systems
must understand the nature of business that they are
working on, and be an expert in using IT. At the same
time, they must be aware of the changes in business
needs, as well as in technology. For this reason, human
infrastructure is the second crucial dimension to be
considered in evaluating flexibility of IT in construction
industry. This dimension can be assessed through IT
knowledge and business knowledge.

• Market
• Integrity
• Network
Figure 1. Proposed IT infrastructure flexibility dimensions for construction industry.
Flexible IS has been proposed as one of the important
dimensions in ITIF from construction industry
perspective. Even though Salleh (2007) pointed out that
the distinction between IT and IS is almost impossible,
this paper however, notes that there is a difference
between IT and IS according to Paschke et al. (2008). IT
processes, transmits and stores information using
technological base which comprises the computers,
communications, software, and networks which are
brought in from the external environment (Cooper and
Zmud, 1990; Weill and Olson, 1989). On the other hand,
IS is a set of integrated software that uses IT that is
embedded within organisations to support individual,
group and business goals (Hsiao and Ormerod, 1998;
Paschke et al., 2008). In a fragmental nature of
construction industry (Figure 1), IS flexibility is measured
in a separate element from technical infrastructure
because in facing rapid changes of IT, IS has to be
flexible enough to evolve with the changing construction
business process.
SIGNIFICANCE OF THE STUDY
As many researchers and gigantic companies are moving
towards having flexible IT infrastructure, there has been a
• Modularity
• Compatibility
• Connectivity
Zainon and Salleh 7255
• IT knowledge
• Business
knowledge
lack of empirical study conducted in context of
construction industry. Hence, the following are the
reasons why this study is significant:
1. To establish the research gap in ITIF concerning IS
projects within construction companies: This study is
certainly important as that would further deepen our
understanding on factors that contribute towards the
success of the IT/IS implementation in construction
industry considering that construction has several unique
features which distinguish it from other industries; namely
the fragmental nature, one-off projects, and multiparticipants.
Furthermore, IT/IS within construction
companies involve end-users from many and different
levels and backgrounds such as contractors, managers,
suppliers, and construction workers as well. For that
reason, to measure ITIF for IT/IS projects within
construction companies is assumed to be different that
measuring ITIF in other industries.
2. To provide potential information about each
dimension in measuring ITIF: This paper gathers
dimensions to measure ITIF that have been introduced
by many researchers (Table 1). However, the shortlisted
dimensions then are proposed based on its suitability to
construction industry. This information could be used as

7256 Afr. J. Bus. Manage.
critical factors in developing ITIF evaluation framework or
ITIF matrix to assess and measure the flexibility of IT
infrastructure.
3. As a checklist for IT managers in construction
companies: This paper could be a guidance for IT
managers to verify whether IT/IS projects in their
construction companies have got the element of flexibility
or not. The dimensions of ITIF proposed in this paper
could help them in decision making of where to improve
their IT infrastructure to become more flexible and at the
same time enhancing competitive advantage (Figure 1).
4. For the abovementioned reasons, this paper therefore,
will not contradict, but it complements others research.
FUTURE RESEARCH
This paper critically discusses about dimensions of ITIF
that can be used to test ITIF from construction industry
point of view. The authors’ goal for future research is to
develop an ITIF maturity model for IS projects dedicated
to construction industry. The model will be a blended
process from an extensive literature reviews and expert
opinion and will further enhance through pilot study, case
studies and large survey. The model will enable
construction practitioners to benchmark the flexibility of
their own IT. It will also be anticipated in evaluating
construction organisation’s strategies and opportunities to
increase ITIF and resulting business value through
increased IT effectiveness. Furthermore, as the business
and IS agree on the need for growing flexibility towards
increased value, then their efforts can certainly be
supplemented and kept on track through strategic
planning.
Conclusion
The world has witnessed the development of many
technological advances in the construction industry.
Despite the huge spending costs for IT/IS investment, the
failure rate is also increasing. The industry has become
bothered with the failing of IT/IS as many organizations
are facing large quantities of unplanned system
requirements due to changing and continual of customer
demand and technology rapid changes. For this reason,
construction industry definitely needs a new alternative
by having a flexible IT infrastructure that will save huge
long-term costs, save time, increase effectiveness and
competitive advantage. However, even with growing
studies upon ITIF, current research approaches are still
facing limitations resulting to a need of proposing a
maturity model.
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African Journal of Business Management Vol. 5(17), pp. 7258-7271, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM10.983
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Locus of control and readiness to conjure and believe
in mystical powers among small business operators in
Entebbe, Uganda: A multilevel rasch rating scale model
analysis
Aloyce R. Kaliba 1 *, Robert Isabalija 1 , Victor W. Mbarika 1 , Mathieu K. Kourouma 1 , Carlos
Thomas 1 , Moya M. Bukoma 2 , Wilson M. Mande 2 , Mohammed Ndifuna 2 and Akodo Robinah 2
1 Southern University, A and M College, Baton Rouge, USA.
2 Makerere University College of Business, Kampala, Uganda.
Accepted 17 May, 2011
High external locus of control and readiness to conjure and believe in mystical powers has a potential
in disrupting the growing small and medium enterprises in Uganda. If small business operators
abdicate their responsibilities to mystical powers, it will worsen the current low survival rate of start-up
businesses. In this study, we use a multilevel Rasch Rating Scale models to estimate a latent scale for
locus of control and a composite scale that combine three domains: altitude towards wealth
acquisition; paranormal beliefs; and readiness to seek wealth from mystical powers. Correlation
analysis was also conducted to determine the association between the two latent scales. The data was
collected from a random sample of 60 business operators in Entebbe, Uganda. Results indicate that low
education and religion affiliations were determining factor for high external locus of control and
readiness to conjure and believe in mystical powers. Public education through religious organization is
therefore important in addressing these negative issues that may affect immerging entrepreneurship in
Uganda.
Key words: Business operators, locus of control, polytomous Rasch models, Uganda.
INTRODUCTION
In Uganda, as in many African countries and some Asian
countries, the practices of conjuring mystical powers is
based on deep rooted beliefs in witchcraft and superstition.
For instance, in their studies in Bangladesh (one
of the underdeveloped countries in Asia), Alam et el.
(2009) and Alam (2009) find some kind of cultural and
economical similarity in witchcraft and superstition
believes with Uganda. Witchcraft and superstition in
various anthropological, religious and mythological
contexts, is the alleged use of supernatural or mystical
powers to harm and protect or acquire and accumulate
wealth (Asante and Mazima, 2009). In Uganda, it is widely
believed that witches can use these powers to inflict
*Corresponding author: E-mail: aloyce_kaliba@subr.edu. Tel:
225 771 5952.
harm upon members of a community or their property.
Also, they can compel the aid of spirits to grow and expand
their client’s businesses or wealth. Most Ugandans
believes that that personal economic windfall is a sign of
assistance from occult sources or supernatural or mystical
powers. Often, relatively rich people are besieged by
suspicions of witchcraft and having connections to
mystical powers. Therefore, wealth becomes a marker of
connection to mystical powers. Moreover, majority of
Ugandan look at witchcraft and superstition as an
extension of their religious beliefs (Geschiere, 1998).
These beliefs are not unique in Uganda. Paris (2000)
studied a group of young entrepreneurs in Ghana who
operated business in large commercial cities, and who
visited shrines in rural areas in order to buy protection
from witchcraft and conjuring the mystical powers for
more wealth. These beliefs and practices are also wide
spread among different tribes in Kenya (Harries, 2010)

and common in Ghana (Akrong, 2007). Geschiere (1998)
shows that the obsession with seeking wealth from
mystical powers should not be viewed as some sort of
traditional residue. On the contrary, modern developments
coincide with a proliferation of the economies of
the occult. Examples include the upsurge of spirit cults in
Taiwan and China, during economic booms (Weller,
1982; Lang and Ragvald, 1998). Paranormal beliefs and
readiness to seek wealth from mystical powers have
implications on how business operates and make
management decisions. They have a direct effect on
growth and performance of the business.
This study is a follow-up on one issue that have
generated immense curiosity and concern in Uganda. For
the better part of 2004, there were allegations that some
small business operators were consulting the mystical
powers in pursuit of wealth acquisition and accumulation.
The matter attracted the spotlight of both the international
and local dailies and a plethora of views from people of
different shades. In particular, the Worldwide Religious
News paper cited the Uganda Muslim leader as having
asked the government to probe the act of people seeking
wealth from mystical powers.
Bukedde newspaper, a local daily, ran a series of
articles in which a number of personalities admitted to
have had consulted witches to conjure mystical powers
on their behalf. In particular, Bazibumbira (2004) quoted
the head of Traditional Healers Association in Uganda as
having admonished people against seeking wealth from
mystical powers because it involves human sacrifices.
Mutebi (2004) interviewed a Seventh Day Adventist
Pastor who had investigated the subject of people seeking
wealth from mystical powers. The pastor confirmed to
know individuals who seek wealth from mystical powers.
Kizito (2004) reported about a Kampala businessman
who had spent 20 years learning to invoke mystical powers
for individual success. The common feature among
individuals who claimed to engage in these activities was
motivated by wealth acquisition. Those who failed
attributed their failures to inability to closely follow the
rules and providing human sacrifices.
We believe that this study is important especially for the
Uganda’s economy on four counts: 1) to seek wealth
from mystical powers has a potential of disrupting the
bludgeoning Small and Medium Enterprises (SMEs)
sector in Uganda. Some Small Business operators would
not apply themselves fully in their businesses trusting in
the providence of the mystical powers; 2) given their
ability to generate employment and contribution towards
poverty reduction, there is great support for Uganda’s
SMEs as a panacea for economic growth and development;
3) the SMEs in Uganda are vulnerable given the
tenuous financial bases on which many of them hinge,
and low levels of education manifested among many
operators; and 4) whilst Uganda has been lauded as
being among the most entrepreneurial country in Africa
(Acs and Szerb, 2010), the survival rate of businesses is
Kaliba et al. 7259
very low. If Uganda’s small business operators abdicate
their responsibility to external forces the situation could
be exacerbated.
To our knowledge no study has hitherto focused on the
nexus of locus of control and readiness to conjure and
believe in mystical powers among small business operators
in Uganda and elsewhere. This is an area that
requires empirical investigations given the past intense
national debate on the potential negative impact of these
phenomena. Results could help in designing effective
intervention programs that are tailored to educate the
public on negative effects of these activities especially on
business survival, performance, and growth in Entebbe
and other regions in Uganda.
We depart from similar studies that focus on association
between locus of control and paranormal beliefs by
using an extended two-level Rasch Rating Scale model
to estimate latent scales for locus of control and readiness
to conjure and believe in mystical power. Definitions
of locus of control and paranormal beliefs are available in
literature. For this study we follow the text book definition
of readiness, which is defined as a disposition to respond
to some phenomenon. To have readiness, therefore,
implies a willingness, eagerness, and preparedness to
something. In a sense it is an orientation toward seeking
mystical powers for protection and wealth accumulation.
LITERATURE REVIEW
Important definitions and past studies
Rotter (1966) defines locus of control as an individual's
perception about the underlying main causes of events in
life. Zimbardo (1985) adds that a locus of control orientation
is a belief about whether the outcomes of our
actions are contingent on what we do (internal control
orientation) or on events outside our personal control
(external control orientation). Under internal locus of control
an individual believes that his/her behavior is guided
by his/her personal decisions and efforts. Internal locus of
control is associated with self-agency, personal control,
and self-determination. External locus of control occurs if
an individual believes that his/her behavior is guided by
fate, luck, or other external circumstances such as mystical
powers. The Rotter’s locus of control scale therefore
measures the extent of a person's internal or external
reinforcement beliefs.
As postulated by Rotter (1966), the locus of control is a
fundamental personality trait referring to individual
differences in a generalized belief in internal versus
external control of reinforcements. A business operator
with high internal locus of control will attribute changes
related to success and failure to personal action and
business environment. Such a person considers oneself
to be an active agent in charge of one’s business
environment and destiny. A business operator with a high

7260 Afr. J. Bus. Manage.
external locus of control sees oneself as a passive agent
and believes that the events in life are caused by
uncontrollable forces outside of oneself; such as fate,
chance, God, spiritual powers etc (Howard, 1996; Wang
et al., 1999; Boone et al., 2000).
Therefore, in business, locus of control refers to the
extent to which business operators believe that they can
control events that affect their business profitability and
growth. Operators with a high internal locus of control
believe that business performance is influenced by their
own business plans and actions (Ray, 1984). Business
operators with high external locus of control believe that
fate, or chance primarily determine business outcome
including performance and growth. Individuals with high
internal locus of control are more active in seeking
information and knowledge concerning their business.
The propensity to engage in activities to influence business
growth is stronger for operators who have a high
internal locus of control than for those who have a high
external locus of control.
The literature supports a casual relationship between
locus of control and readiness to conjure and believe in
mystical powers (Williams and Irwin, 1991; Dag, 1999;
Peltzer, 2003). Beliefs in mystical powers are those
beliefs which, if genuine, would violate basic limiting
principles of science (Tam and Shiah, 2004; Wiseman
and Watt, 2004). In this study, it is assumed that attitude
towards wealth acquisition and paranormal beliefs are
conjugates for seeking wealth from mystical powers. The
three domains reinforce each other to form a continuum
latent trait. Tobacyk (1995) presents 26 items and techniques
that can be used to measure Paranormal Belief
Scale using a seven-point Likert rating scale. The scale is
composed of seven subscales: traditional religious belief,
Psi, witchcraft, superstition, spiritualism, extraordinary life
forms, and precognition. It should be noted that some
items used to construct the subscale may be regional
specific. For example, the existence of abominable
snowman of Tibet and the Loch Ness monster of
Scotland are not familiar in the African continent mythology,
especially in Uganda. These items are not universal
can be modified to reflect beliefs that are common in a
study area.
Considerable research has been carried out on locus of
control (Adams, 2000; Sohn and Leckenby, 2001;
Thielker et al., 2001; Shewchuk et al., 1990). Stanke
(2004) used analysis of variance to identify specific
characteristics that are associated with locus of control.
The conclusion was that levels of religiosity do not have a
significant relationship with levels of superstitious or
paranormal beliefs that influence locus of control. Positive
correlation existed among external locus of control with
superstitious beliefs. In order to understand the relationship
between locus of control and paranormal beliefs,
Groth-Marnat and Pegden (1998) conducted a study that
included 81 undergraduate students. They used a structured
questionnaire and respondent responses were
used to construct the paranornomal belief, Rotter’s locus
of control, and sensation seeking scales. Results indicated
that a greater external locus of control was associated
with greater overall number of paranormal beliefs.
Greater external locus of control was especially associated
with the Paranormal Belief subscales of spirituality
and precognition. Contrary to expectations, belief in
superstition was associated with a greater internal locus
of control. Whereas overall sensation seeking was not
related to overall paranornomal belief, the paranornomal
belief subscales of greater belief in psi phenomena and
superstition were found to be associated with higher
levels of sensation seeking.
In their study, Tobacyk et al. (1987) studied the relationships
between paranormal beliefs and locus of
control. The paranormal beliefs scale and Paulhus's
Spheres of Control Scale were administered to 349
introductory college students. The results indicated a
significant correlation between greater personal efficacy
control and less belief in superstition and witchcraft, and
greater interpersonal control and less belief in
superstition. Burke et al. (2006) used Pearson correlation
analysis to determine the relationship between measures
of belief in personal control and superstitious behavior
among NCAA Division I Intercollegiate Student-Athletes.
They concluded that statistically significant positive
correlation existed between internal locus of control and
optimism. A statistically significant negative correlation
existed between high internal locus of control and lower
pessimism. Dag (1999) used the Turkish version of
Tobacyk’s revised Paranormal Belief Scale and the
Rotter’s Locus of Control Scale to study the relationships
between paranormal beliefs and locus of control and
psychopathology in a sample of Turkish college students.
The conclusion was that the revised paranormal belief
subscales predicted locus of control better and the
psychopathology subscales. While evidence from these
studies indicates that locus of control has an important
influence on individual belief and decisions, few studies
use quantitative techniques to measure the influence of
individual demographic variables on these phenomena.
This is important in designing customer tailored
intervention programs.
Quantitative latent variable measurement
Locus of control, attitude towards wealth acquisition,
paranormal beliefs and readiness to seek wealth from
mystical powers are all latent variables. Latent variables
are characteristics that cannot be directly measured or
directly observable. Latent variables can be measured
indirectly through their effects on observable indicators
using specific questions or statements commonly known
as items (Bradley et al., 2006). Response to each item
may be analyzed separately or all items may be summed
to create a summative score or a summative latent scale.

Generally, it is not advisable to make inferences based
upon the analysis of a single-item response that is used
in measuring a scaled latent variable (Johnson and
Albert, 1999).
In addition, individual items often suffer from random
measurement error especially when several items
measure the same latent trait. It is therefore statistically
appropriate to create a scale out of these items. A scale
will be more parsimonious and reliable than analyzing
each item individually (Bradley et al., 2006). When the
structure of items is based on a Likert scale, responses
are normally treated as ordinal data. This is because one
cannot assume that respondents perceive the difference
between adjacent levels as equidistant (Fox, 2005). That
is, if the data are ordinal, we can say that one score is
higher than another, however, we cannot say how much
higher.
When responses to several items are summed to
measure a latent variable and all statement in a survey
instrument use the same Likert scale, the responses are
treated as interval data. The interval data tells the
distance between two points and the differences between
each response are equal in distance (Zheng and Rabe-
Hesketh, 2009). Interval estimates of a latent continuum
scale that is based on the Likert scale responses can be
obtained by applying the Polytomous Rasch Models. The
polytomous Rasch model is a generalization of the
dichotomous Rasch model (Rasch, 1960).
The model permits testing of the hypothesis that the
statements in the Likert scale reflect increasing levels of
the latent variable as intended (Bryk and Raudenbush,
1992; Tesio, 2003; Rabe-Hesketh and Skrondal, 2008).
For ordered Likert scale responses, the polytomous
Rasch model is also known as a Rating Scale model
(RSM). The model assumes identical threshold distances
across items (Andrich, 1978).
To operationalize the Rating Scale Model, let X be a
data matrix made up by the responses of v=1... N person
who responds to k=1,.., K polytomous items with the
same number h=1,.., M response categories per item
(that is, Likert scale with M response categories). The
subjects are in the low and items (statements) in the
column. The polytomous rating scale model (RSM) as
suggested by Andrich (1978) is:
exp ( h(
θ v + β k ) + γ h
P( X vk = h | θ v ) = M
.
∑ e xp( l(
θ + β ) + γ
l = 1
v k l
(1)
L e v e l 1 ( in d iv id u a l ) :
Kaliba et al. 7261
Equation 1 express the probability of giving any one of
the possible response categories by respondent v on
items i. The coefficient, βk, is the vector of item
parameters, θv is the vector of subject parameters and
γ h is the vector of category parameters (sometimes
known as step parameters), which are the same for all
items. The parameters, θv equal the subject’s interval
value of the latent scale to be measured. For example it
may represent individual level of locus of control or
readiness to conjure and believe in mystical powers for
wealth acquisition and accumulation.
As the values of θv increase, the probability of selecting
response h in a monotonic manner increases. The βk
parameters measure the marginal or location effect for
item k, which depend on both the response option and
the particular item. The sum in the denominator ensures
that for respondent v the sum of probabilities (P(Xvk=h|θv)
over all response options to item k equals one. To
conform to the Rasch Model methodology, the items
effects are constant or fixed across persons. For strictly
ordered and increasing thresholds, the following constraints
are usually imposed as shown in Equation (2):
m
∑ γ = 0 , a n d γ < γ < L < γ
h = 1
h 1 2
h
When constraints in Equation (2) are imposed, all consecutive
differences defining the item category response
functions will be negative and the sum of the item category
response function will add to one. For parameter
identification purposes γh is usually set to zero
(Chajewski and Lewis, 2009). Notice that in Equation 1
the latent variable parameter (θv) varies across respondents.
Therefore, personal level variables can be
introduced to capture the source of variability and nesting
within groups. Multilevel modelling is therefore needed to
capture variability in individual responses and by group.
Following Fox (2005), defines a general multilevel model
with covariates such that respondents (v=1,.., N) are
nested within group (i = 1,..,I). A two level rating scale
model that estimate a latent variable that depends on
individual respondent characteristics and that vary by
groups is:
e x p ( h ( θ v i + β k ) + γ h
P ( X v k = h | θ v i ) = m
,
∑ e x p ( l(
θ + β ) + γ
l = 1
θ = α + ∑ α z + ε
v i 0 i q i q i v i ,
q = 1
L e v e l 2 ( G r o u p ) : α = η + µ .
In Equation 3, z is a matrix of individual level covariates
with a total numbers of Q variables. The intercept (α0i) is
Q
0 i 0 0 i
v i k l
the average value of the latent variable for each group
after controlling for the covariates. The parameters αqi
(2)
(3)

7262 Afr. J. Bus. Manage.
represents the marginal effects of individual level
covariates on the latent variable. The error term (εvi)
which is assumed to be normally distributed with zero
mean and a constant variance (α0i ~N(0, τ10)) represents
individual level random variation of the latent trait after
controlling for demographic characteristics. In level-2
model, the intercept for the level 1 model (α0i ) is
decomposed into fixed effects (η00) and random effect
that vary across groups (µi). It is also assumed that µi
~N(0, τ20). The fixed effect (η00) is the sample mean of the
estimated latent variable. The random effect represents
variations in the estimated latent variable across group. If
a small variance is observed, it would imply that the latent
variable is similar across groups. If a large variance is
observed, it means that the latent trait differs by groups
(Zheng and Rabe-Hesketh, 2009).
Validity and reliability test of the survey instrument
As mentioned before, latent traits are indirectly measured
using several responses on items that are collected using
a survey instrument. When constructing scales, naturally
we want to know how good the scale is. How reliable is
the scale? What items belong in the scale? Therefore,
before estimating the latent trait, responses have to be
tested for validity and reliability. Validity refers to the
extent to which a survey instrument measures what it
intended to measure. There are a variety of ways to evaluate
validity. However, for a single survey the focus is on
construct validity. Construct validity refers to whether a
survey instrument measures or correlates with the theorized
construct that it purports to measure (Golafshani,
2003). Construct validity defines how well an experiment
measures up to its claims and determine to whether the
operational definition of items actually reflects the true
theoretical meaning of a concept. Highly correlated items
that fit the expected pattern contribute evidence of
construct validity.
Usually, construct validity is a judgment based on the
accumulation of correlations from numerous studies
using the instrument being evaluated (Healy and Perry,
2000; Campbell, 1959). For a single survey that use an
equidistant Likert scale, construct validation it is therefore
equivalent to empirically testing the second expression in
Equation (2). Does moving from a lower to an upper
response category increases the magnitude of the latent
trait variable? Instead of imposing the second expression
in Equation (2), it can be tested empirically.
By definition, reliability refers to the accuracy and precision
or consistency of a survey instrument (Thorndike et
al., 1991). All survey instruments that use different items
to construct a scale constitute some degree of inconsistency.
The inconsistency in a set of items arises from
variation across individuals plus all other sources of
variability within and across the items. Variability is also
made up of true values of the items and error or noise.
For a survey instrument, reliability measures the ratio of
the variability of the true values of the items to the sum of
variability of the true values of the items and associated
errors. Reliability of a survey instrument is increased by
reducing error variance and by increasing the variance of
the true value (Brennan, 2001).
Any survey instrument is reliable if there are greater
interindividual variations in the sample or population.
While there are several measures of reliability, for single
survey the focus is on internal consistency reliability.
This measures the extent to which all of the items in the
model measure the same construct. Do all the items tend
to move together (same direction) or do some items
move to different direction. Internal consistency is measured
by Cronbach’s coefficient alpha, which summarizes
the average correlation between all possible pairs of
items (Cronbach, 1971). In other words, Cronbach’s coefficient
alpha (α) measures how well a survey instrument
measures a single and one dimension latent construct. It
quantifies the internal consistency of the instrument or
the average correlation of items within the instrument. It
is a first step towards measuring construct validity and
reliability of the survey instrument (Cronbach, 2004). The
acceptable value of Cronbach’s coefficient alpha (α)
depends on the objective of the study. However, the
value between 0.6 and 0.8 is commonly accepted
(Blalock, 1970; Cortina, 1993; Zinbarg et al., 2006).
In summary, reliability refers to the degree to which a
psychometric instrument is consistent and stable in
measuring what it is intended to measure. The instrument
is reliable if it is consistent within itself and across time.
Validity refers to the degree to which the instrument
actually measures what it claims to measure. Validity
determines the extent to which inferences, conclusions,
and decisions made on the basis of psychometric instrument
are appropriate and meaningful. Therefore, validity
is a prerequisite to testing for reliability. If a test is not
valid, then reliability is also doubtful.
METHODOLOGY
Source of data and data description
A sample of 60 small business operators in the Entebbe Business
District, Uganda was randomly selected to participate in the current
study. The sample included 30 service providers and 30 general
traders. The sample businesses were selected from a list obtained
from the Entebbe Business District business register office. The
business registrar office divides small business into two groups:
service provider and general traders. They are also classified as
small and medium enterprises if they employ less than 20 and 100
people, respectively. This study concentrated on small businesses.
Based on the list, these businesses constituted more than 80% of
all small and medium enterprises in the Entebbe Business District.
Before administering the survey, content validity of the survey
instrument was substantiated by a focus group. The focus group
carefully reviewed the survey instrument and assisted in providing
guidance in constructing the instrument statements. In addition,
they were required to determine whether the instrument statement
looks valid in terms of measuring the intended latent traits (that is,
locus of control and readiness to conjure and believe in mystical
powers). They also rated each statement/item to determine how

essential a particular statement is; in measuring the particular latent
trait. Statements of the survey instrument were added, dropped and
modified based on the focus group suggestions.
The final survey instrument with 24 items was divided into the
following subsections: altitude towards wealth acquisition (4 items),
locus of control (7 items), paranormal beliefs (4 items), and readiness
to seek wealth from under water spirits (8 items), and
demographic section. The items were on a five Likert scales
(1=Strongly Disagree; 2=Disagree; 3=neither agree nor disagree;
4=agree; and 5=strongly agree). The demographic section collected
data on gender, age, education level, religion, and marital status of
the respondent. The survey instrument was administered to
business owner or manager using a face-to-face interview.
Summary statistics of the responses from all 60 respondents are
presented in Table 1. In the sample, majority of respondents were
single and young males (less than 20 year), with secondary level
education or lower. There was a slightly high representation for
individuals from Catholic and Anglican denominations. In Table 1
and for items, percent frequency includes “neither agree nor
disagree”, “agree”, and “strongly agree” categorical responses. For
example, most of the responses in the attitude towards wealth
acquisition were in the neither agree or disagree and agree
category.
Except for one item in the locus of control domain (other people
tends to dominate my decision making process), most of responses
to other items were in the last three response categories. For
paranormal beliefs domain, most responses from one item (spirits
exist but are not all that powerful to grant anything) was in the last
three categorical responses. Responses on other items were in the
strongly disagree and disagree response categories. Similarly, two
items in the readiness to seek wealth from under water spirits
domains (“If the spirits are able to grant wealthy, I will use them”
and “I believe that spirits can make miracles in one's life and
business”) were in the strongly disagree and disagree response
categories. Most of responses on other items were in the upper
response categories. In general, if the percent frequency is less
than 50%, the most of the responses were in the strongly disagree
and disagree response categories and vice versa.
Data analyses
Variable clustering approach was used to test the validity and
reliability of the survey responses using alpha command in the
statistical package Stata. The command computes inter-item
correlations or covariance for all specified items. This is in addition
to computing Cronbach’s coefficient alpha statistic for the scale
formed by the items. This procedure also iteratively divides groups
of items into subscales until a stopping criterion is reached. This a
more direct way of creating a survey instrument that measure same
construct and direction or grouping questions that measure the
same construct. In Stata, the alpha command can be used to
assess how well the items form a single scale that measure the
same construct (Stata, 2009).
Equation (3) was used to estimate the latent trait that measures
locus of control scale and a composite scale constructed from items
representing altitude towards wealth acquisition, paranormal beliefs
and readiness to seek wealth from under water spirits. The three
domains created a latent trait measuring readiness to conjure and
believe in mystical powers. Due to relatively small sample size and
few items that measures some of the latent traits the “Strongly
Disagree” and Disagree” responses were combined to form a
“disagree” response category. Therefore, the Rasch Rating Scale
Model has four response categories: disagree=1; neither agree or
disagree=2; agree=3; and strongly disagree=4).
For demographic variables, due to low frequency of “Widowed”
response, the marital status variable was collapsed to a
dichotomous variable (that is, single or widowed=1; and zero
Kaliba et al. 7263
otherwise). Also, in order to conform to the standard Rasch model,
four dichotomous variables representing education levels (that is,
University, College, Secondary, and Other) and religion affiliation
(Anglican, Catholic, Muslim, and Evangelical) were constructed. For
education variable, individuals with primary education were combined
with those who did not attend school to form a single dummy
variable. Therefore, the level-1 covariates included a dummy
variable for gender (male=1; zero otherwise), an ordered variable
for age, three dummy variables for education level, three dummy
variables for religion affiliation, and a dummy variable for marital
status. The other dummy for education and Evangelical dummy
variable were not include in the model to avoid perfect collinearality.
As specified in Equation (3), two latent traits (locus of control
scale and readiness to conjure and believe in mystical powers)
were estimated using gllamm program also in Stata. The program
gllamm runs in the statistical package Stata and estimates
GLLAMMs (Generalized Linear Latent and Mixed Models) by
maximum likelihood. An advantage of using gllamm directly is that
the latent variables (common factors or random effects) can be
assumed to be discrete or to have a multivariate normal distribution
(Zheng and Rabe-Hesketh, 2009).
In addition, simple linear correlation analyses (Pearson r) were
conducted to determine the relationship between the estimated two
latent traits. Pearson correlation assumes that the variables are
measured on at least interval and it determines the extent to which
values of the two or more variables are proportional to each other.
The advantage is that the value of correlation (that is, correlation
coefficient) does not depend on the specific measurement units
used; which is important for latent traits constructed using different
items (Stata, 2009)
RESULTS AND DISCUSSION
Validity and reliability tests
Results of validity and reliability tests for all items are
presented in Table 2. The estimated Cronbach’s coefficient
indicated that items included to measures altitude
towards wealth acquisitions and readiness to seek wealth
from mystical powers strongly measure these latent
construct (α>0.6). However, the items used to measure
locus of control and paranormal beliefs were weak in
measuring these latent construct (α

7264 Afr. J. Bus. Manage.
Table 1. Summary Statistics for all variables used in the study 1
Subscale Category/Items Frequency (%)
Demographic characteristic
Business types
Gender
Age
Education
Religion
Marital status
Attitude towards Wealth
Acquisition (WEA)
Locus of Control (LOCI)
Service 50.00
General traders 50.00
Male 63.33
Female 36.67
Less than 20 years of age 58.33
Between 20 - 30 years of age 31.67
Above 30 years of age 10.00
University 18.33
Some College 25.00
Secondary 45.00
Primary 10.00
Illiterate 1.67
Anglican 28.33
Catholic 31.67
Moslem 20.00
Evangelicals 20.00
Single 51.67
Married 46.67
Widowed 1.67
Life is meaningless without wealth (LIFE) 73.33
My reason for working is primarily to acquire wealth (WORKING) 73.33
I will do anything to become wealthy (ANYTHING) 91.67
Anything that is likely to bring in wealth is welcome (BRING) 58.33
Whatever happens in my life and business is my own doing (WATEVER) 61.67
I believe that I control my own destiny (CONTROL) 68.33
I always rely on others to make business decisions (RELAY) 41.67
Other people tend to dominate my decision making process (OTHER) 48.33
Factors other than me determine the direction of my business (FACTOR) 53.33
My success in business is achieved through personal effort (SUCCESS) 75.00
Misfortunes I face in business are consequences of my mistakes (MISFORT) 96.67

Table 1. Contd.
Paranormal Beliefs (PB)
Readiness to seek wealth
from under water spirits
(RSWS)
I believe spirits do exist (SPIRITS) 41.67
Spirits are a mere figment of people's imaginations (MERE) 28.33
Spirits exist but are not all that powerful to grant anything (SPIEXIS) 73.33
Spirits have always influenced people's actions (SPI) 41.67
If the spirits are able to grant wealthy, I will use them (GRANTS) 33.33
I believe spirits are able to influence business success (BELSPI) 66.67
Some wealthy business people acquired their success from mystical powers(RICH) 78.33
Mystical powers are more accessible than God (ACCESS) 95.05
I have no moral inhibition to seeking business success from mystical powers(INHIBIT) 56.67
Without the support of the spiritual forces one cannot succeed in business (WITHOUT) 93.33
I believe that spirits can make miracles in one's life and business (SPIMAKE) 48.33
I believe spirits can take care of my enemies including business competitors (SPICAN) 61.67
1 For item parameters the percent frequency is include "Neither Agree or Disagree", "Agree" and “Strongly Agree" responses
Table 2. Test for Items reliability and validity.
Kaliba et al. 7265
Subscale and New Clusters Cronbach’s coefficient alpha (α) Items 1 Second Eigen value
Altitude towards Wealth Acquisition (AWA) 0.66 All items 1.02
AWA Cluster 1 0.69 life, working, anything 0.90
Locus of Control (LOCI) 0.35 All items 1.59
LOCI Cluster 1 0.41 whatever, control, factor, success 0.99
LOCI Cluster 2 0.48 other, relay, misfort 0.80
Paranormal Beliefs (PB) -0.24 All items 0.88
Readiness to Seek Wealth from Under Water Spirit (RSWS) 0.64 All items 1.35
RSWS Cluster 1 0.78 grant, rich, access, without, spmake, spican 0.87
RSWS Cluster 2 -0.69 BELSPI, INHIBIT 0.76
1 See table 1 for definition of variables.
into two clusters. The first cluster contained four
items and the second cluster contained three
items as shown in Table 2. Readiness to seek
wealth from under water spirit was also subdivided
into two clusters containing, respectively,
six and two items. In all cases, variable clustering
improved validity and reliability outcome.
Results in Table 2 also indicate that the two
clusters of the locus of control domain were both
measuring a similar latent construct (α>0).
However, the items in the readiness to see wealth
from under water spirits were measuring same
construct but in different directions. The Cronbach
coefficient alpha for cluster one is in an acceptable
range and positive and Cronbach coefficient

7266 Afr. J. Bus. Manage.
Table 3. Estimated item parameters for the locus of control rating scale model.
Item Coefficient Std. Err. P>|Z|
Variables include in the Level-1 Model: Item Variables
Whatever happens in my life and business is my own doing. 0.112 0.153 0.081
I believe that I control my own destiny 0.029 0.133 0.095
I always rely on others to make business decisions -0.328 0.198 0.098
Other people tend to dominate my decision making process. -0.503 0.252 0.027
Factors other than me determine the direction of my business 0.413 0.145 0.036
My success in business is achieved through personal mistakes 0.137 0.154 0.077
Misfortunes I face in business are consequences of my mistakes -1.074 0.490 0.028
Variables included in Level-2 Model: Influence of demographic characteristics on Locus of control
Gender -0.011 0.239 0.000
Age -0.137 0.104 0.455
Marital Status 0.101 0.315 0.005
University education -0.693 1.942 0.011
College education -0.255 0.209 0.422
Secondary education -0.244 0.212 0.433
Anglican -0.044 0.177 0.001
Catholic -0.108 0.202 0.076
Muslim 0.082 0.204 0.022
Variance: Level-1model 0.191 0.128 0.126
Variance: level-2 model 0.659 0.001 0.000
γ
Step two ( 3 − γ 2 = 0
) 1.545 0.294 0.000
γ Step three ( 4 − γ 3 = 0 ) 2.698 0.241 0.004
γ Chi- square test ( 2 ≥ γ 3 ≥ γ 4 ) 83.060 0.000
alpha for cluster 2 is in an acceptable range and negative.
In particular and by reviewing the questions asked,
items in cluster one measured the general overview of an
individual on locus of control and items in cluster two
were more specific about personal evaluation (evaluation
of personal character) about locus of control. Similarly,
items in cluster one on readiness to seek wealth from
under water spirits asked questions regarding general
beliefs and the two items in cluster two asked individual
to evaluate themselves about these beliefs. Therefore,
while all items in these domains measured the same
construct, the level and direction of measurement were
different. These results give an insight now how the
results of the rating scale model should be interpreted.
Results of the rasch rating scale model
Results of estimated item parameters for the locus of
control model and readiness to conjure and believe in
mystical powers are presented in Tables 3 and 4,
respectively. Also in Tables 3 and 4, the likelihood ratio
tests the hypothesis that variables all included in the
model are not statistically significant. In both models the
hypothesis is rejected at more than 1% level of significance.
This means that at least some of the variables
included in the model explain observed individual
variations in locus of control and readiness to conjure and
believe in mystical powers. The Chi-Square test is a
lower tail test for the second expression in Equation (2).
In the both cases, the null hypothesis is ( γ 2 ≥ γ 3 ≥ γ 4 ),
which is rejected at more than 1% level of significance.
Because we have four categorical responses, there are
three step parameters. Step one is moving from disagree
to neither agree nor disagree responses. Step two is
moving from “neither agree nor disagree” to “agree”
responses and step three is moving from “agree” to
“strongly agree” responses. Step one is a reference step.
In the second and third steps, we use a two tail test t-test
to test the null hypotheses that γ 3 − γ 2 = 0 andγ 4 − γ 3 = 0,
respectively. The alternative hypotheses are γ 3 − γ 2 ≠ 0
and γ 4 − γ 3 ≠ 0 , respectively. Both null hypotheses are
rejected at more 1% level of significance. The combined
results of the Chi-square and t-test suggest that; overall,
the items included in the locus control and readiness to
conjure and believe in mystical powers have strong and
consistent construct validity.
The first part of Table 3 shows the estimated coefficients
or item parameters for all variables included in the
rating scale model. All item variables are statistically

significant at more than 10% level of significance. This is
acceptable for one time cross sectional survey. The
magnitude of the estimated coefficient determines the
position of the item on thelocus of control scale. Low
score means that the item was easy; most respondents
scored the item as agree or strongly agree. High score
means that the item was difficulty; most respondents
scored the item as disagree, which is a low score. The
three statements: misfortunes I face in business are
consequences of my mistakes; other people tend to
dominate my decision making process; and I always rely
on others to make business decisions are on the left side
of the locus of control scale (high internal locus of
control). These results correspond to the results in Tables
1 and 2. In Table 1, majority of respondents (about
100%) agreed with the first statement. Relatively few
respondents (about 42% and 48%) agreed to the second
and third statements, respectively. In Table 2, the three
items/statements are in the same cluster. However, note
that the Cronbach’s coefficient alpha is positive and not
negative. This is because the structure of the questions is
such that locus of control scale is increasing (from
negative infinity to positive infinity) or from internal locus
of control sub-scale to external locus of control sub-scale.
In most cases, disagree responses were associated with
internal locus of control and strongly agree responses
were associated with external locus of control.
The remaining items/statements in the first part of
Table 3 are on the left side of the locus of control scale
(external locus of control). These statements (in order of
importance) include: factors other than me determine the
direction of my business, my success in business is
achieved through personal mistakes, whatever happens
in my life and business is my own doing and I believe that
I control my own destiny. Except for the item/statement
“factors other than me determine the direction of my
business”, though statistically significant, the estimated
coefficients for other remaining items/statements are
close to the middle of the locus of control scale. From
Table 2, about 58% of the responded agreed with the first
statement and between 60 and 75% of the respondents
agreed with the remaining statements.
The second part of Table 3 shows the influence of
individual characteristics on locus of control. The variable
that were statistically significant at more than 10% level
of significance were gender, marital status, university
education, and all dummy variables for religion affiliation.
Male business owners are more likely to have higher
internal locus of control when compared to female, which
is obvious in the male dominated world. Single and the
widowed business owners are likely to have high external
locus of control when compared to married business
owners. In particular, most respondents who agreed with
the statement “I always relay on others to make business
decisions” where single and widowed business owners.
Lack of reliable family and social support tends to create
dependence and therefore vulnerable to external locus of
Kaliba et al. 7267
control.
While increase in age increased internal locus of
control, the age variable was not statistically significant
(Table 3). This can be attributed to the fact that majority
of business owner where in the same age group. One
average, a business operator with a university education
has a higher internal locus of control when compared to a
business owner with primary education or less. College
education and secondary education dummy variables are
not statistically significant but have expected signs,
negative. This means that business operator with college
education or secondary education has a slightly higher
internal locus of control when compared to a business
owner with primary education or less. Also, the estimated
coefficients for the education dummy variables are in a
descending order. From secondary education to university
education; implying that internal locus of control
increases with education level. On average, Catholics
and Anglicans are more likely to have a high internal
locus of control when compared to evangelicals. However,
evangelicals are more likely to have high locus of
control when compared to Muslim. This may be related to
religious teaching and individual spirituality; a topic
beyond this study.
Correspondingly, the first part of Table 4 presents the
results of rating scale model on readiness to conjure and
believe in mystical powers. All items/statements were
statistically significant at more than 10% level of significance.
The sign and the magnitude of the coefficient
determine the location of the item on the readiness to
conjure and believe in mystical power scale. High score
mean the item/statement is difficulty or few respondents
agreed with the statement (low score) and vice versa.
Four items/statements with high value of estimated
coefficients (in a descending order) include: spirits are a
mere figment of people's imaginations; if the spirits are
able to grant wealthy, I will use them; I believe spirits do
exist; and spirits have always influenced people's actions.
Similarly, five items/statements with low values of
estimated coefficients included: without the support of the
spiritual forces one cannot succeed in business; mystical
powers are more accessible than God; I will do anything
to become wealthy; my reason for working is primarily to
acquire wealth; and life is meaningless without wealth.
For the first group and the second group of items the
estimated coefficients (difficult parameters) ranged
between 1.53 and 1.11 and -0.41 and 0.05, respectively.
For the remaining items/statements the estimated
coefficients ranged between 0.24 and 0.90. These results
suggest that majority of respondents disagreed with the
first group of four items/statements (βk>1) and majority of
respondent strongly agreed with the second group of
items/statements (βk

7268 Afr. J. Bus. Manage.
Table 4. Estimated item parameters for the readiness to conjure and believe in mystical powers.
Item Coefficient Std. Error P>|Z|
Variables of Level-1 Model: Item variables
Life is meaningless without wealth 0.045 0.023 0.049
My reason for working is primarily to acquire wealth 0.050 0.026 0.058
I will do anything to become wealthy -0.222 0.103 0.032
Anything that is likely to bring in wealth is welcome 0.521 0.254 0.042
I believe spirits do exist 1.172 0.265 0.000
Spirits are a mere figment of people's imaginations 1.526 0.283 0.000
Spirits exist but are not all that powerful to grant anything 0.579 0.254 0.024
Spirits have always influenced people's actions 1.107 0.263 0.000
If the spirits are able to grant wealthy, I will use them 1.318 0.271 0.000
I believe spirits are able to influence business success 0.238 0.126 0.060
Some wealthy business people acquired their success from mystical powers 0.464 0.254 0.070
Mystical powers are more accessible than God -0.351 0.127 0.007
I have no moral inhibition to seeking business success from mystical powers 0.550 0.254 0.032
Without the support of the spiritual forces one cannot succeed in business -0.410 0.127 0.002
I believe that spirits can make miracles in one's life and business 0.896 0.257 0.001
I believe spirits can take care of my enemies including business competitors 0.594 0.254 0.021
Variable of Level-2 Model: Influence of demographic characteristics on readiness to conjure and believe in
mystical powers
Gender 0.125 0.094 0.186
Age 0.079 0.070 0.260
Marital Status -0.155 0.103 0.136
University education -0.550 0.256 0.032
College education -0.363 0.149 0.016
Secondary education -0.173 0.052 0.001
Anglican -0.014 0.007 0.040
Catholic -0.044 0.012 0.000
Muslims 0.125 0.042 0.006
Variance level-1 model 0.032 0.029 0.270
Variance level-2 model 3.842 1.384 0.006
Step two ( γ − γ = 0 )
0.591 0.4175 0.001
3
Step three ( γ − γ = 0 )
4
Chi- square test ( γ 2 ≥ γ 3 ≥ γ 4 )
2
3
0.904 0.250 0.000
13.400 0.000
Likelihood ratio test -50.279 0.000
anything to acquire wealth including conjuring. Also, the
statement “without the support of the spiritual forces one
cannot succeed in business” may be misreading. Respondents
may have confused spiritual forces with
religious beliefs and superstitions and thus giving
conflicting responses.
The lower part of Table 4 shows the estimated coefficients
on the influence of demographic characteristics of
the respondents on readiness to conjure and believe in
mystical powers. All education and religion dummy
variables were statistically significant at more than 5%
level of significance. Readiness to conjure and believe in
mystical powers decreased with increase in education
level. Anglican and Catholics were less likely to conjure
and believe in mystical powers than evangelicals. However,
Muslims were more likely to conjure and believe in
mystical powers when compared to Evangelicals. Therefore,
education and religion were the most important
variables that influenced the readiness to conjure and
believe in mystical powers.
In addition, both Tables 3 and 4 show results of estimated
level-1 and level-2 variances. In Table 3 the level-
1 variance was 0.19 and was not statistically significant.
After controlling for demographic characteristics there

Table 5. Comparison of estimated latent traits by type of business.
Kaliba et al. 7269
Estimated latent traite Summary statistic
Type of business
Service Trade
Sample
Mean -0.084 -0.078 -0.081
Internal locus of control
Standard deviation 0.112 0.126 0.118
Frequency 21 17 38
External locus of control
Sample
Not likely to conjure and believe in mystical powers
Likely to conjure and believe in mystical powers
Sample
was little variability on locus of control across
respondents. The Level -2 variance was 0.659 and was
statistically significant at more than 1% level of
significance. This means that the estimated locus of
control varied by types of business. In Table 4, the level-1
variance was 0.032 and was also not statistically
significant. Likewise, level-2 variance was statistically
significant at more than 5% level of significance indicating
variation in readiness to conjure and believe in mystical
powers by type of business.
The summary statistics of estimated level of locus of
control and readiness to conjure and believe in mystical
powers are presented in Table 5. These latent traits were
standardized and ranged from -3 to 3 for practical
purposes. As shown in Table 5, majority of business
operators (38 out of 60), have internal locus of control.
The service sector has more business operators with
internal locus of control when compared to the trade
sector. Likewise, external locus of control was more
common in the trade sector. This can be attributed to
type of customers served. The service sector tends to
have a customer base that is stable and predictable. The
customer base in the trading sector tends to be unstable
therefore creating more business competition in the
sector. These results translate into the second part of
Table 5. Majority of business operators in the service
Mean 0.202 0.175 0.189
Standard deviation 0.088 0.061 0.075
Frequency 9 13 22
Mean 0.002 -0.002 -0.001
Standard deviation 0.169 0.161 0.163
Frequency 30 30 60
Mean -0.185 -0.254 -0.217
Standard deviation 0.141 0.303 0.230
Frequency 22 10 32
Mean 0.407 0.309 0.351
Standard deviation 0.182 0.197 0.193
Frequency 8 20 28
Mean 0.012 0.010 0.001
Standard deviation 0.032 0.038 0.035
Frequency 30 30 60
sector are not likely to conjure and believe in mystical
powers (22 out of 30) and majority business operators in
the trading sector (20 out of 30) are likely to conjure and
believe in mystical powers. Trade competition may be
behind these phenomena.
Correlation analysis was also conducted to determine
the association between the estimated locus of control
index and readiness to conjure and believe in mystical
powers scores. The estimated Pearson correlation
coefficient was 0.62 for the entire sample. Test for
independence was rejected at 5% level of significance.
Also, correlation analyses were conducted by business
types. The Pearson correlation coefficient was 0.81 for
the trade sector and 0.56 for the service sector. Again,
tests for independence for both sectors were rejected at
5% level of significance. These results suggest that there
was a strong positive relationship between external locus
of control and readiness to conjure and believe in
mystical powers. Business operators with high external
locus of control were more likely to be ready to conjure
and believe in mystical powers. Due to inherent business
completion, this relationship was strong in the trade
sector than in the service sector. Apart from culture that
shape beliefs, stiff business competition can be associated
with external locus of control and readiness to
conjure and believe in mystical powers among small

7270 Afr. J. Bus. Manage.
business operators in Uganda.
CONCLUSION AND POLICY IMPLICATIONS
In this study, we used a two-level linear Rasch Rating
Scale models to estimate latent traits related to locus of
control and readiness to conjure and believe in mystical
powers. The second level models were used to determine
the influence of demographic characteristics on
locus of control and readiness to conjure and believe in
mystical powers. Readiness to conjure and believe in
mystical powers was constructed from several items that
measured attitude towards wealth acquisitions, paranormal
beliefs, and readiness to seek wealth from mystical
powers. Correlation analysis was also conducted to
determine the relationship between locus of control and
readiness to conjure and believe in mystical powers.
Data was collected from a random sample of business
operators in Entebbe Business District, Uganda. Uganda
is known as an entrepreneurship country. High external
locus of control and readiness to conjure and believe in
mystical powers has potential of upsetting the achievement
made. A business operator with high external locus
of control will attribute failure or success to mystical
powers and a focus will be on conjuring and not business
improvement as the way it was suggested by Alam et al.
(2010). High external locus of control means that
business operators are not realistic about available
opportunities they can use to develop or expand their
businesses. They will depend on chances or certain
things to happen to them through mystical powers.
Results from this study indicate that education and
religion variables have a strong influenced on both locus
of control and readiness to conjure and believe in
mystical powers. Alam et al 2010 and Alam, 2009 also
strongly stressed these variables in the context of
Bangladesh. Majority of respondents have average
scores in terms of locus of control and were lukewarm on
the influence of mystical powers on business outcomes.
This is an indication that there is unrealistic optimism
about business outcomes among business operators in
Uganda. This can be attributed to culture. The way a
person is brought up, the situations they encounter in life,
and the views that they are exposed to are key factors in
the development of such attitudes and beliefs. Another
cultural way that attitudes and beliefs are formed is
through one’s experience with religion. As indicated in
this study and elsewhere there are surmount evidence
indicating that religion, and the beliefs associated with it,
affect one’s decision making process not only in life but in
business operation.
Post-secondary business and entrepreneurship
education and participation by religious institutions are
fundamental in improving locus of control and changing
people’s attitude on mystical powers and wealth accumulation.
Similar explanations in the context of Bangladesh
was made by Alam et al. (2010) and Alam and Khlifah
(2009) The Ugandan government should collaborate with
other non-government organization such as Uganda
Chambers of Commerce to organize seminars and short
term training on business management and entrepreneurship.
Religious institutions need to synergize their
messages on the importance of internal locus of control
on business decision making, focusing on personal
responsibility and accountability as pillars of success in
business. In addition, mass media has a significant
social influence that can shape and legitimize social
behavior and personal beliefs. The mass media is an
important objective means of communication for social
change. Mass media programs aimed at small business
operators in Uganda is highly recommended. The mass
media will provide effective and efficient mechanisms for
imparting positive attitude towards business management
and dispensing the myth of using mystical power to
accumulate wealth. The focus should be on
understanding the essence of business competitions and
associated technical solution through hard work and
accountability of business operators.
ACKNOWLEDGEMENT
This research was based upon work supported by the
National Science Foundation grant # 0644305. We also
thank anonymous reviewers for their valuable comments.
However, any opinions, findings, and conclusions or
recommendations expressed in this paper are those of
the author(s) and do not necessarily reflect the views of
the NSF or AJBM.
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African Journal of Business Management Vol.5 (17), pp. 7272-7283, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM10.995
ISSN 1993-8233©2011 Academic Journals
Full Length Research Paper
Environmental quality as an important dimension of
customer satisfaction in apartment industry
Siamak Zadkarim 1 , Hossien Emari 2 *, Saeed Sanatkar 3 and Hadi Barghlame 4
1 Islamic Azad University, Bonab Branch, East Azarbaijan, Iran.
2 Department of Management, Faculty of Human Science, Islamic Azad University Bonab Branch, Bonab, 55518/134,
Iran.
3 Canco Corporation, 10 Nipigon Ave Northyork, Ontario MZM 2v8, Toronto, Canada.
4 Islamic Azad University, Ilkhchy Branch, East Azarbaijan, Iran.
Accepted 28 February, 2011
This study aims to determine the dimensions of customer satisfaction. For this purpose, researchers
developed a model by taking an experiential view. In this article, a standard questionnaire was used for
collecting the data and, the authors report a comparative study that was conducted on two samples of
real customers at apartment industry (low income and high income) in Iran. The results from a low
income sample revealed that the customer satisfaction is influenced more by customer cost and
product quality than other constructs. Moreover, the role of customer satisfaction as a mediating factor
in the intention of word of mouth is supported. In contrary, in high income sample customer
satisfaction influenced more by product quality and service quality than other constructs. In addition,
the role of customer satisfaction as a mediating factor in the intention of word of mouth is rejected. A
notable advantage of the model developed in this study is that, it covers essentially all the quality
issues an apartment customer may encounter (that is, physical or product, service, and environment).
Key words: Customer satisfaction, word of mouth, service quality, apartment industry, Iran.
INTRODUCTION
Customer satisfaction significantly influences an
organization's current and future performance (Lewin,
2009, 283; Gilbert and Veloutsou, 2006; Hansemark and
Albinsson, 2004); it is a key issue for all those
organizations that wish to create and keep a competitive
advantage in this highly competitive world. Customer
satisfaction is regarded as a primary determining factor of
purchasing behavior (Burns and Neisner, 2006).
Increased customer satisfaction generates positive word
of mouth (WOM) and brings in new customers to the firm
(Chakraborty et al., 2007; Babin et al., 2005; Aydin and
Ozer, 2005). Moreover, improving customer satisfaction,
which results in increased return intention and positive
WOM endorsement, will in turn not only strengthen
customer loyalty, but also generate greater revenue and
*Corresponding author. E-mail: Emari_hossien@yahoo.com.
Tel: +98 4127238893. Fax: +98 4127230393.
improve reputation of company (Kim et al., 2009).
The organization wants to know how satisfied their
customers are in order to be translated into marketing
strategy and organizational development. Because, it
was important to understand the ways that product and
services can influence customer behavior in terms of
satisfaction (Fonseca, 2009).
Customer satisfaction in housing can have societal
implications far beyond those of standard consumer
product experiences. Housing satisfaction is an important
component of overall life satisfaction. Also, housing
satisfaction has long been a major research topic in such
disciplines as sociology, psychology, planning, civil
engineering, marketing and geography (Lu, 1999).
The housing problem in Iran has been intensifying
since the 1980s. This has been brought about by the
intense population growth. The rapid demand for apartment
homes growth has made the need for adequate
housing for the people a very important concern of the
public or private sector of Iran, especially in the big

Customer Cost
Physical Quality
Environmental
Quality
H2
H3
H1
Overall Customer
Satisfaction
H4
Project Facilities
Figure 1. Hypothesized model of customer satisfaction.
cities. It has been a primary objective of the investors to
provide decent housing to the citizen.
The massive growth of investment in apartment homes
is forever altering the landscape of property investment.
Within the Iran apartment industry, the rise of investment
has created massive companies, in some cases building
hundreds of apartment homes. Despite this unprecedented
concentration, little investigation has been made
into the effects of these developments on customer
satisfaction. However, the rush to respond to these needs
seems to result in a low quality housing that does not
adequately match the needs of these people.
It has become increasingly important to evaluate
customer satisfaction in apartment industry for many
reasons. First of all, evaluating customer satisfaction
provides the necessary information required for ‘feedback’
into current housing stock and ‘feed-forward’ into
future projects. It provides the basis for taking decisions
about improvements in current housing stock and about
the design and development of future housing. Second,
the idea that an evaluation of the performance of housing
may be conducted makes housing managers, designers
and policy makers more accountable (Amole,
2008).Third, Adequate housing is so much an integral
part of the needs of every society that its value for
individuals, families, communities, and society at large is
hardly questioned (Opoku and Muhmin, 2009). Forth,
housing dissatisfaction can have direct impacts on
physical and psychological health (James, 2009).
Because of the distinction between housing
preferences of low-income and high-income consumers,
this paper explored the housing preferences of lowincome
and high-income consumers in Iran, with specific
emphasis on the factors influencing their housing
satisfaction.
Previous studies on housing satisfaction has focused
only on physical housing quality but, this research
H5
H6
H7
Zadkarim et al. 7273
Region Facilities
WOM
Service Quality
presenting a model incorporating physical housing
quality, service quality and environmental quality and
relates these to consumer satisfaction and intention to
engage in word of mouth activity. The model is then
tested with two samples of high-income and low-income
Iranian apartment consumers in major public housing
schemes.
Theoretical background and hypotheses
Figure 1 displays the hypothesized model explaining
Iranian apartment customer’s satisfaction and WOM.
Based on a review of the literature, this study develop a
framework linking customer cost, physical quality,
environmental quality, service quality, project facilities,
and region facilities to customer satisfaction.
Satisfaction is an overall customer attitude towards
products, or is an emotional reaction to the difference
between what customers anticipate and what they
receive, regarding the fulfillment of some need, goal or
desire (Hansemark and Albinsson, 2004). Furthermore,
especially in the service field, customer satisfaction is
typically defined as an overall assessment of the
performance of various attributes that constitute a service
(Fonseca, 2009).
Whether the buyer is satisfied after purchase depends
on the offer's performance in relation to the buyer's
expectations. In general, satisfaction is a person's
feelings of pleasure or disappointment resulting from
comparing a product's and service's perceived performance
(or outcome) in relation to his or her expectations. If
the performance falls short of expectations, the customer
is dissatisfied. If the performance matches the expectations,
the customer is satisfied. If the performance
exceeds expectations, the customer is highly satisfied or
delighted (Kotler and Keller, 2006).

7274 Afr. J. Bus. Manage.
Satisfaction also depends on product and service
quality. What exactly is quality? Various experts have
defined it as "fitness for use," "conformance to
requirements," "freedom from variation," and so on. The
study of Kotler and Keller (2006) showed that quality is
the totality of features and characteristics of a product or
service that bear on its ability to satisfy stated or implied
needs.
Improved service quality endows companies with social
and commercial significance, and ensures greater
customer satisfaction (Lu and Shock, 2008; Kotler, 2002).
Moreover, high quality service contributes to a company’s
profits, customers costs, and encourages word-of-mouth
recommendations to potential customers (Herstein and
Gamliel, 2006).
Housing satisfaction refers to the degree of
contentment experienced by an individual or family with
regard to the current housing situation (Djebarni and Al-
Abed, 2000). Determining the dimensions of customer
satisfaction in apartment industry is less well studied.
Djebarni and Al-Abed (1998, 2000) assessed and
compared residents' satisfaction with their housing and
environment in the three housing schemes in Yemen.
The principal variables of the model of Djebarni and Al-
Abed (2000) are housing environment (the dwelling unit,
neighborhood and community services) and housing
quality (dwelling interior schedule, dwelling exterior
schedule, and dwelling environment schedule).
Interviews with occupants in the study of Djebarni and Al-
Abed (2000) revealed that they attach great importance
to the level of satisfaction with their neighborhoods. The
most important factor associated with neighborhood
satisfaction was privacy, a reflection of the cultural
background in Yemeni society.
The study of Tsemberis et al. (2003) show that housing
satisfaction was influenced not only by the quality of the
home itself, but also by the surrounding neighborhood,
patterns of social interaction, satisfaction with the
management practice of repairs, and tenant involvement.
Phillips et al. (2005) examined the role of residential
satisfaction (satisfaction with dwelling unit, estate and
district) in mediating the effects of dwelling conditions
(interior environment and exterior environment) on
psychological well-being. Phillips et al. (2005) suggested
that dwelling conditions can act as stressors and become
contributing factors that impact on older persons’
residential satisfaction and psychological well-being
(subjective well-being).
Tu and Lin (2008) identified the internal evaluative
structure with which Taipei City’s residents assess the
quality of their residential environment. Tu and Lin (2008)
developed a multidimensional evaluative structure of
residential environment quality, which consists of six
evaluation scales (that is, urban planning and design,
security and social relationship, transportation and commercial
services, residential atmosphere, environmental
health, and facility management) with eleven underlying
factors.
Amole (2009) studied the residential satisfaction in
students’ housing in Nigeria, and examined how satisfied
students were and the factors which predicted residential
satisfaction. Specifically, it examined whether the
morphological configurations of the halls of residence
would predict residential satisfaction. The study of Amole
(2009) show that more than half (53%) of the
respondents were dissatisfied with their residences and
the variables which explained satisfaction were the social
qualities of the residences, especially, the social
densities; the kitchenette, bathroom and storage facilities
and some demographic characteristics of the students.
Nahmens and Ikuma (2009) described an exploratory
study that focused on customer satisfaction with service
quality, and assessed the correlations between various
factors on home buyer expectations and their perceptions
of service quality.
Yau et al. (2009) used the Building Quality Index (BQI),
developed by The University of Hong Kong, to assess the
performance of the whole stock of buildings in Hong
Kong. Building Quality Index indicated that architecture,
building services, operations and maintenance, external
environment, and management approaches are
significant determinants of the building performance.
Opoku and Muhmin (2010) examined the housing
preferences of low-income consumers in Saudi Arabia,
with specific emphasis on their preferences for alternative
dwelling types and tenure options, factors influencing
their housing decisions, and how these vary across
socio-demographic sub-segments of this population
segment. Opoku and Muhmin (2010) find that majority of
respondents prefer the small house to duplex or
apartment, and despite their limited incomes the majority
prefer buying over renting. On importance of housing
attributes in Opoku and Muhmins’ research, a factor
analysis of 35 housing attributes included in the study
produced 10 factors, of which financial considerations,
private living space, and aesthetic aspects of the house
rank as the top 3 important factors in the low-income
consumers’ housing decisions.
The results of the preceding studies have
demonstrated, on the whole, effects of product, service,
and environmental quality dimensions on overall
customer satisfaction (Rosen and Suprenant, 1998;
Johnson et al., 2001; Humburg and Giering, 2001; Lin,
2007; Tu and Lin, 2008; Lewin, 2009; Fonseca, 2009;
Denge et al., 2009; Wu and Liang, 2009; Frank and
Enkawa, 2009; Kim and Lee, 2010). Moreover, from the
suggested relationships in the literature (Rosen and
Suprenant, 1998; Johnson et al., 2001; Denge et al.,
2009; Wu and Liang, 2009; Frank and Enkawa, 2009),
customer cost is particularly important in customer
satisfaction formation.
To assess the importance of other dimensions of
customer satisfaction in apartment industry that were not
addressed in the profiles described above, we presented

espondents with a list of housing-related factors and
asked them to indicate how important each would be if
they were making a decision purchase a house. The
factors were obtained through an exploratory study
utilizing a combination of literature review, depth
interviews and focus group discussions. The depth
interviews and focus group discussions were conducted
by civil engineers and undergraduate students of a
marketing research class taught by one of the authors.
Consequently, the following hypotheses are proposed:
H1: Customer cost has a significant positive direct effect
on overall customer satisfaction.
H2: Physical quality has a significant positive direct effect
on overall customer satisfaction.
H3: Environmental quality has a significant positive direct
effect on overall customer satisfaction.
H4: Project facilities have a significant positive direct
effect on overall customer satisfaction.
H5: Region facilities have a significant positive direct
effect on overall customer satisfaction.
H6: Service quality has a significant positive direct effect
on overall customer satisfaction.
One of the aspects of post-purchase behavior is WOM.
WOM communication simply involves people sharing an
assessment of their experiences (Kim et al., 2009). WOM
is defined as the extent to which a customer informs
friends, relatives and colleagues about an event that has
created a certain level of satisfaction (Soderlund, 1998).
According the work of Macintosh (2007), WOM
communication can be defined as “informal communications
directed at other consumers about the ownership,
usage, or characteristics of particular goods and services
and/or their sellers”. WOM is a social behavior involving
person-to-person communication where the receiver
perceives the giver to be non-commercial with regard to a
service, product, or brand (Ferguson et al., 2010). Word
of mouth is much more credible than your most sincere
salesperson. It is able to reach more people and faster
than advertising and direct mail because it can spread
like wildfire (Procter and Richards, 2002). Information
obtained through WOM is generally very credible and is
relied on, particularly in the later stages of product or
service evaluation and purchase (Swanson and Kelley,
2001). Evidence indicates that WOM is often related to
consumers’ satisfaction or dissatisfaction with previous
purchasing experiences (Mangold et al., 1999).
Kim et al. (2009) investigated the relative importance of
institutional DINESERV factors (that is, food quality,
atmosphere, service quality, convenience, and price and
value) that affect customer satisfaction in the university
dining facilities and to examine the influence of customer
satisfaction on return intention and WOM endorsement.
The study of Kim et al. (2009) showed that all Institutional
DINESERV Dimensions had a significant positive effect
on overall customer satisfaction and revisit intention.
Zadkarim et al. 7275
Maxham (2001) examined the effects that different
levels of service recovery have on satisfaction, purchase
intentions, and one’s propensity to spread positive WOM.
The results of Maxham s (2001) study indicated that
moderate to high service recovery efforts significantly
increase post-failure levels of satisfaction, purchase
intent, and positive WOM. Alternatively, poor service
recoveries seemingly exacerbate the discontent
attributed to a service failure.
Macintosh (2007) examined the potential links between
customer orientation, expertise, and relationship quality
at the interpersonal level and the link between
relationship quality and positive service outcomes at the
firm level, such as positive word of mouth. The results of
Macintosh s (2001) research showed significant links
between relationship quality at the interpersonal level and
positive outcomes at the organizational level. In addition,
interpersonal relationship quality enhanced customer
satisfaction with the service firm but was also directly
linked to positive WOM about the firm.
Chaniotakis and Lymperopoulos (2009) studied the
effect of service quality dimensions on satisfaction and
WOM for maternities in Greece. The results of research
of Chaniotakis and Lymperopoulos (2009) suggested
that, in addition to “satisfaction”, the only service quality
dimension that directly affects WOM, is “empathy”. In
addition, “empathy” affects “responsiveness”, “assurance”
and “tangibles” which in turn have only an indirect effect
to WOM through “satisfaction”.
Kim and Lee (2010) examined the relative importance
of perceived service quality and the relationship between
perceived service quality, customer satisfaction and
behavioral intention using multidimensional methods. The
results of the study of Kim and Lee (2010) indicated that
the significant dimensions of customer satisfaction are
tangibles and responsiveness. In addition, the study
confirms the significant consequences of customer
satisfaction including WOM communication, purchase
intentions, and complaining behavior.
Babin et al. (2005) studied the relations between
hedonic value, utilitarian value, and customer satisfaction
with WOM in restaurant industry. The research of Babin
et al. (2005) showed that customer satisfaction has a
significant positive direct effect on WOM.
Finally, the end result is a model offering an
explanation of Iranian customer’s WOM. While WOM is a
critically important factor in any culture, its importance
may be amplified in cultures with relatively high
communal orientations. Since Iran is considered among
the most collectivist societies (Hofstede, 2003), we
believe word-of-mouth communication plays a critical role
in our model.
Iran's lowest Hofstede ranking is Individuality (IDV) at
41(Figure 2), compared to the Muslim countries average
of 38. The low ranking on this Dimension indicates the
society is Collectivist as compared to Individualist. This is
manifest in a close long-term commitment to the member

7276 Afr. J. Bus. Manage.
Score of Iran
Dimensions of Hofstede Framework
Figure 2. Ranking of Iran in Hofstede model.
'group', is that a family, extended family, or extended
relationships. Loyalty in a collectivist culture is
paramount, and over-rides most other societal rules and
regulations. The society fosters strong relationships
where everyone takes responsibility for fellow members
of their group (Hofstede, 2003).
Hence, based on the above definitions and suggested
relationships in the literature, the following hypothesis is
formulated:
H7. Overall customer satisfaction has a significant
positive direct effect on word of mouth.
MATERIALS AND METHODS
The target population of this study was low income (that is, with
monthly incomes less than 500000 Rials (US$500) and high
income (that is, with monthly incomes more than 500000 Rials)
apartment buyers in Iran. This study collected data through a
survey conducted in the major cities of Iran using a structured self
administered questionnaire. The questionnaire addressed several
housing related issues and respondents also provided socio
demographic information.
Eleven male and nine female undergraduate students were
trained for the data collection. 1200 apartment buyers of public
projects in the major cities (project A:400 , project B:200 , project
C:250 and project D:350) were selected through cluster sampling
and were studied. A total of 931 usable questionnaires were
collected. Of these 674 (72.4%) met the low income classification
criterion and 257 (27.6%) met the high income classification.
Measures
Eight constructs, physical quality, customer costs, environmental
security, project situation, project facilities, word of mouth, service
quality, and customer satisfaction, were operational defined in order
to test the research model. Customer satisfaction and WOM items
were modified in English for cell phone and restaurant industries,
and then translated into Persian. These instruments were reviewed
by two Iranian experts to ensure that the Persian wording and
content of items was appropriate. Other items (that is, physical
quality, customer cost and etc) were generated via a series of focus
groups.
Overall customer satisfaction scale
A number of both national and international barometers have been
introduced in the last decade. The development of national
customer satisfaction barometers can be summarized in the
following main efforts (Grigoroudis and Siskos, 2004; Johnson et
al., 2001):
1. The first attempt to develop and install a national measure for
customer satisfaction was reported in Sweden in 1989. Professor
Claes Fornell was the main architect of the Swedish National
Customer Satisfaction Barometer.
2. The national quality and satisfaction barometer of Germany (The
German Customer Barometer––Quality and Satisfaction) focuses
mainly on the micro-economical level of business organisations and
it was established in 1992.
3. Professor Claes Fornell supervised the conduct of the preliminary
analysis of the American Customer Satisfaction Index (ACSI) in
1993. This particular index constitutes an effort to adopt the
Sweden satisfaction barometer in America, with some
improvements, revisions, and reconciliation. The ACSI provides
complete data since 1994.
4. It should be noted that the European Union is interested in the
development and installation of a comparative system of national
satisfaction indices since 1998. The preliminary study in a limited
number of industry sectors was conducted within 1999, while
results for the European Customer Satisfaction Index (ECSI) were
published in 2000.
5. Other individual efforts of establishing national satisfaction
indices in the European area concern Denmark, Austria, France,

Table 1. Service quality dimension definitions (modified from Zeithaml et al., 1990).
Service quality dimension Original definition Tailored definition for home building
Appearance Visual impression of the service
organization: facilities, equipment, and
personnel.
Reliability Consistency of performance and
dependability.
Zadkarim et al. 7277
Visual impression of the home builder: nice brochures,
Well decorated sales office, sales personnel, etc.
Consistency of performance and dependability of the
service before, during and after the home-buying process.
Timeliness Timeliness of service. Timeliness of the service before, during and after the
Home buying process.
Knowledge Possession of the required skills and
knowledge to perform the Service,
Ability to inspire trust and confidence.
Empathy Politeness, respect and friendliness of
contact personnel. Individualized
attention, making the effort to know
customers and their needs.
The Netherlands, Switzerland, and others.
6. Both Taiwan and New Zealand measure and report the customer
satisfaction of a limited number of companies since 1995. Also, the
preliminary survey for the installation of a permanent satisfaction
barometer in South Korea was conducted in 1998, while in
Malaysia, a pilot survey is planned for the next year.
In this study customer satisfaction was measured using a scale
developed by Oliver and Swan (Burns and Neisner, 2006). Since
the original items were developed for the automobile buying
experience, it was necessary to modify the items to relate to
apartment buying experience (Appendix). All eight items were
measured using 5-point scales anchored by “Strongly disagree” (1)
and “Strongly agree” (5).
Service quality scale
Researchers have tried to develop conceptual models to explain
the service quality and to measure consumers’ perceived service
quality in different industries (Seth et al., 2005). In the absence of
objective measures for assessing service quality, Berry, Zeithaml,
and Parasuraman developed a multiple-item scale instrument
(SERVQUAL) for measuring customer perception of service quality.
SERVQUAL is considered robust in different environments (Wong
and Sohal, 2002; Nahmens and Ikuma, 2009; Oneill et al., 1998;
Baumann et al., 2007).
In this research, the five SERVQUAL dimensions were modified
and used to measure service quality (Table 1). The purpose of
SERVQUAL is to measure current service quality with diagnostic
abilities. It is not predictive. This assessment model was used in
this study with some modifications to reflect the housing industry
domain. This model (Table 1) defines service quality as the
discrepancy between apartment buyer’s service expectations and
service experienced. Apartment buyer’s service expectations are
influenced by past experiences, communication (builder’s
advertisement, brochures, etc.) and personal needs. Service
experienced is the actual service apartment buyers received from
their builders during the entire process of sale through the warranty
period.
This model also identifies five dimensions that apartment buyers
use to assess service quality and represent the evaluative criteria of
Appropriate knowledge and skills required to perform the
service before, during and after the home-buying process.
Politeness, respect and friendliness of the sales personnel
or any other builder’s employee that directly interacts with
the home buyers.
the current study. To quantify the five dimensions of service quality
in the home building context, it was necessary to tailor the original
definitions and provide a simple, conceptually sound definition of
each dimension of service quality within the home-building process
(Table 1).
Word of mouth scale
Word of mouth was measured using a scale developed by Babin,
Lee, Kim, and Griffin (Babin et al., 2005). Word of mouth intentions
(WOM) were assessed using three items. The items measured
agreement using a 5-point Likert scale with statements concerning
intentions to say positive things to others, recommend the
apartments of project to another consumer, and encourage friends
and relatives to buy the apartment from this project.
Customer satisfaction dimensions scales
Phillips et al. (2005) suggested that assessment of dwelling
conditions includes at least ten dwelling characteristics (such as
lighting, levels of crowding and temperature) and ten neighborhood
characteristics (such as lighting in corridor, lobby, public space,
stairs, lift, escalator, air and noise pollution).
Residents' satisfaction in the model of Djebarni and Al-Abed
(2000) measured by tow variables (housing environment and
housing quality). Housing environment items are dwelling unit
(number of bedrooms, size, sunshine, and etc), neighborhood
(neighbor, roads, lighting, and etc), and community services
(drainage system, fire protection, and transportation). Housing
quality items are dwelling interior schedule, dwelling exterior
schedule, and dwelling environment schedule.
Based on the research of Tu and Lin (2008), environmental
quality was measured by six variables. These variables are citywide
housing status (dwelling types), residential density in typical
residential zones (dwelling unit density, avenue floor area per
dwelling unit, avenue floor area per person), mixed use intensity,
and spatial features in typical residential zones (typical block size,
building height, side walk, street scope).
The model of Nahmens and Ikuma (2009) identified five
dimensions that homebuyers use to assess service quality. These
dimensions are appearance (visual impression of the service

7278 Afr. J. Bus. Manage.
Table 2. Reliability and validity test.
Scales Alpha χ 2 /df NNFI RMSEA NFI
Customer cost 0.51 3 0.93 0.03 0.93
Product quality 0.83 2 0.90 0.02 0.89
Region facilities 0.62 2 0.91 0.01 0.95
Project facilities 0.67 3 0.89 0.04 0.97
Service quality 0.72 2 0.95 0.08 0.90
Environmental quality 0.86 2 0.92 0.02 0.92
Customer satisfaction 0.77 2 0.88 0.03 0.94
Word of mouth 0.80 3 0.90 0.02 0.89
organization: facilities, equipment and personnel), reliability
(consistency of performance and dependability), timeliness
(timeliness of service), knowledge (possession of the required skills
and knowledge to perform the service, and ability to inspire trust
and confidence), and empathy (politeness, respect and friendliness
of contact personnel, individualized attention, making the effort to
know customers and their needs).
Based on the study of Yau et al. (2009), a list of building factors
that fit the institutional and cultural settings of apartment buildings in
Hong Kong was identified for the development of the Building
Quality Index (BQI). These factors are architecture (size, plan
shape, headroom, windows, noise reduction, and open space),
building services (water supply, drainage, refuse disposal, lift),
external environment (density, adjacent use, air quality, aural
quality, visual obstruction, thermal comfort), operations and
maintenance (cleaning, pest control, refuse handling, drainage
condition, unauthorized alteration, water quality), and management
approaches (owners’ duties, documentation, emergency
preparedness).
Amole (2009) conceptualized residential satisfaction as
influenced by objective and subjective measures of housing
attributes and the demographic characteristics of the students.
Objective physical variables include the morphological configuration
of the hall, number of persons in the bedroom, presence or
absence of reading room, common room, kitchenette and a balcony
(terrace at the back of the bedroom). Subjective variables include
attitudes about comfort, bedroom furnishing, number of persons in
the bedroom, number of persons on the floor, privacy in bedroom,
the sanitary facilities, number of persons using the sanitary
facilities, the kitchenette in general, design of the hall, number of
persons in the hall, location of the hall.
Numerous specific housing attributes and house purchase
factors have been suggested by Opoku and Muhmin (2010) are:
financial/economics, private living space, aesthetics, local
environment, air quality, public living space, building design,
proximity to relatives, outdoor space, and street location.
In this study, the scales of customer satisfaction dimensions were
generated via a series of focus groups. Specifically, the focus group
comprised teams of apartment customers in Iran. Focus group
participants were instructed to formulate questions by using the
dimensions suggested by past research (that is, Amole, 2008;
Djebarni and Al-Abed, 1998; Ilozor, 2009, and etc). These
questions are grouped under different dimensions (Appendix).
These dimensions are: “customer cost” (includes the price and
credit), “physical quality” (includes the cracks, kitchen,
lighting[electronic lighting and window to outside], water[ plumbing
facilities, water quality and water pressure], drainage, commode,
internal architecture), “environmental quality” (includes the traffic,
noise and region security), “project facilities” (includes the parking,
lobby, external staircase, lift, front and warehouse), “region facilities
(includes the existence of park, primary school, at least 5 shops
and public transport within 1 kilometer radius of zone center )” .
Each item was rated on a five-point Likert type scale ranging from
strongly disagree (1) to strongly agree (5).
Preliminary versions of this questionnaire were then reviewed by
project managers in well known building enterprises in Iran and
were subsequently modified. The final revised version was then
presented to apartment customers’ experience with quality in the
apartment industry.
RESULTS
Analysis of scale properties
Before assessing the research model it was necessary to
establish the validity and reliability of the modified items
and the new items developed for this study (Kang and
James, 2004). Confirmatory factor analysis (CFA) was
utilized to verify the construct validity of scales. In order
to have a valid construct, the items comprising a
construct must be one dimensional.
The psychometric properties of each construct were
evaluated in separate confirmatory factor models using
LISREL 8.5. The model fit for each CFA was evaluated
using the Normal Fit Index (NFI), Non Normal Fit Index
(NNFI), the Root Mean Square Error of Approximation
(RMSEA) and χ 2
/df values were also reported as
references for model fit (Table 2).
The coefficient alphas were also reported to evaluate
the reliability of each construct (Table 2). Notably,
Nunnally and Bernstein suggested that 0.7 should be
used as the cut off point for reliability with items that did
not significantly contribute to the reliability (item to total
coefficient alpha 0.5) being deleted for the purpose of
parsimony (chang and chieng, 2006). The reported
values show that, all scales are congener and reliable.
Moreover, the latent constructs are inter-correlated.
Structural model
The 44 measured items were constrained into eight
construct, congeneric measurement model. Co-variances
between these items were computed and used as input
for confirmatory factor analysis (CFA).The results of the

Table 3. The results of structural equation model testing.
Zadkarim et al. 7279
Low income customers
Hypotheses Standardized beta(t) Hypotheses support
H1: customer cost to overall customer satisfaction 0.45(2.21) Yes
H2: physical quality to overall customer satisfaction 0.22(0.86) No
H3: environmental quality to overall customer satisfaction 0.48(2.25) Yes
H4: project facilities to overall customer satisfaction 0.24(1.03) No
H5: region facilities to overall customer satisfaction 0.14(0.67) No
H6: service quality to overall customer satisfaction 0.74(3.05) Yes
H7: overall customer satisfaction to word of mouth 0.91(5.65) Yes
High income customers
Hypotheses Standardized beta(t) Hypotheses support
H1: customer cost to overall customer satisfaction 0.02(0.26) No
H2: physical quality to overall customer satisfaction 0.32(4.11) Yes
H3: environmental quality to overall customer satisfaction 0.13(1.96) Yes
H4: project facilities to overall customer satisfaction 0.21(3.00) Yes
H5: region facilities to overall customer satisfaction - 0.09(- 1.45) No
H6: service quality to overall customer satisfaction 0.47(7.30) Yes
H7: overall customer satisfaction to word of mouth 0.00(0.02) No
Significant p ≤ 0.05.
LISREL estimation of the structural model are
summarized and reported in Tables 3 and 4. The
research model was tested using a structural equation
modeling approach. LISREL 8.52 was used to estimate
the parameters and assess the fit of the model. The
LISREL methodology development started in 1970, when
Karl Joreskog presented a first LISREL model at a
conference. The first generally available LISREL program
was published in 1975. The name LISREL is an acronym
for "Linear Structural Relations". The qualifier "linear" is
restrictive for the current version of the LISREL program,
but the name LISREL has become synonymous with
"structural equation modeling" or SEM (Stephen and
Mathilda, 2008):
Model 1 (Low income customers segment): According
to results, customer cost has a positive effect (H1: γ1 =
0.45 and Tvalue = 2.21) on customer satisfaction (H1 is
confirmed), and physical quality has not a considerable
positive effect (H2: γ2 = 0.22 and Tvalue = 0.86) on
customer satisfaction (H2 is not confirmed).
The path coefficients depicted in Table 3 show that
environmental quality are related positively to customer
satisfaction (H3: γ3 = 0.48 and Tvalue = 2.25), and project
facilities has not a considerable positive effect (H4: γ4 =
0.24 and Tvalue = 1.03) on customer satisfaction, therefore
H3 is confirmed and H4 is rejected. In addition, region
facilities has not a considerable positive effect (H5: γ5 =
0.14 and Tvalue = 0.67) on customer satisfaction, but
service quality has strong positive effect (H6: γ6 = 0.74
and Tvalue = 3.05) on customer satisfaction. Consequently,
H6 is rejected and H5 is supported.
There was also a positive relationship between overall
customer satisfaction and word of mouth (H7: β1=0.91
and Tvalue = 5.65); thus, H7 is supported.
Goodness of fit statistics summarized in Table 4. These
statistics, indicating the overall acceptability of the
structural model analyzed. A large class of omnibus tests
exists for assessing how well the model matches the
observed data. The model fit was evaluated using NFI,
NNFI, RMSEA, χ 2 /df, and the chi-square values (Albright
and Park, 2008).
Model 2 (Low income customers segment): Inspection
of coefficients indicates (Table 3) that, as expected,
customer cost has not a considerable positive effect (H1:
γ1 = 0.02 and Tvalue = 0.26) on customer satisfaction, but
physical quality has strong positive effect (H2: γ2 = 0.32
and Tvalue = 4.11) on customer satisfaction. Consequently,
H1 is rejected and H2 is supported. Moreover, both
environmental quality (H3: γ3 = 0.13 and Tvalue = 1.96) and
project facilities (H4: γ4 = 0.21 and Tvalue = 3.00) have
significant positive impact on overall customer
satisfaction; thus, confirming H3 and H4.
According to results, region facilities has a negative
effect (H5: γ5 = - 0.09 and Tvalue = - 1.45) on customer
satisfaction (H5 is rejected), and service quality has a
considerable positive effect (H6: γ6 = 0.47 and Tvalue =
7.30) on customer satisfaction (H6 is confirmed). Finally,
overall customer satisfaction is not related positively to
WOM (H7: β1 = 0.00 and Tvalue = 0.02). Hence, H7 is
supported.
Goodness-of-fit statistics summarized in Table 4.
These statistics, indicating the overall acceptability of the

7280 Afr. J. Bus. Manage.
Table 4. Goodness of fit statistics.
Low income customers High income customers
NFI 0.92 NFI 0.90
NNFI 0.94 NNFI 0.89
RMSEA 0.03 RMSEA 0.02
χ 2 /df 3 χ 2 /df 3
structural model analyzed.
DISCUSSION
Consumer satisfaction and WOM are important marketing
outcomes affecting the profitability of the enterprise.
Based on the findings from previous empirical studies
(Lu, 1999; Djebarni and Al-Abed, 1998; Tsemberis et al.,
2003; Pillips et al., 2005), a statistical approach to
building housing customer satisfaction assessment is
proposed in this paper. The current study analyzed the
data collected from two different segment of apartment
market in Iran and the following results emerged from the
study:
Low income market segment: in this segment, the main
factors effective on satisfaction of customer include the
environmental quality, services quality and customer
cost. Our results suggest that firms should focus not only
on providing service quality, but they should also make
sure that the environmental quality dimensions (e.g.
traffic, noise and region security) and customer cost
dimensions (e.g. price and credit conditions) provide high
levels of customer satisfaction.
As two factors of service quality and customer cost
simultaneously influence on customer satisfaction, so the
marketers of this field, should have proper market
researches and add those characteristics to their services
(e.g. appearance, reliability, timeliness, knowledge and
empathy) which are acceptable for the customers and in
other words, they are ready to pay the extra expenses of
it.
It should be mentioned that a high percentage of
apartment buyers in Iran belong to this income group and
competition in this section to takeover the market is very
high. So, companies invest on different dimensions of
service quality and customer costs and can satisfy lowincome
customers and obtain a good share in this great
market.
Between low income customers, satisfaction of
customer has a direct and significant effect on word of
mouth and companies can use this method to establish
relations with customers to make their cost effective
instead of investing on other methods of promotion.
High income market segment: in this segment, other
main effective factors on customer satisfaction include
product quality, services quality and project facilities. As
customer cost do not have much effect on customer
satisfaction in the segment, the marketer can add
different characteristics to the product to make it
distinctive.
Thus, it could be recommended that builders apply
particular focus on their efforts to assure high product
quality, service quality, and project facilities on those
product dimensions (that is, cracks, kitchen, lighting,
water, drainage, commode, internal architecture), project
facility dimensions (that is, parking, lobby, external
staircase, lift, front attractiveness and quality,
warehouse), and service quality dimensions that are most
important for each home buyer in order to be more
effective in improving satisfaction. Yet this does not imply
that the other dimensions be neglected as it was shown
that home-buyer overall satisfaction is driven by all
dimensions of product quality, service quality, and project
facilities.
Although a small number of customers in this industry
belong to this income group, a small number of investing
companies can satisfy the satisfaction of customers and
obtain a suitable share in this small but profitable
segment of market through concentrating on different
dimensions of the above-mentioned elements.
Customer satisfaction has not strong effect on word of
mouth in this income group and other promotional
method should be used to establish relations with
customers.
In addition, future research should examine factors
related to the limitations of the current study. First, more
rigorous and detailed testing of measurement scales in
Iran would further our knowledge of cross-cultural
measurement issues. It is possible that some scales
developed in Western culture (e.g. service quality
measure) may not be suitable for the Iran culture.
Second, and related, our results do not directly address
cross-cultural differences between Iranian consumers
and Western consumers. Researchers considering
potential differences in core cultural values in greater
detail may lead to specific hypotheses testing the
moderating effect of culture on the relationships
presented here. This research would require matching
data from multiple cultures.
ACKNOWLEDGMENT
The authors would like to thank the reviewers for the
constructive comments and illustrative suggestions.
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APPENDIX
Overall customer satisfaction
1. The services have not worked out as well as I thought it would.
2. I am satisfied with my decision to use this apartment.
3. Sometimes I have mixed feelings about keeping it.
4. My choice to use this apartment was a wise one.
5. If I could do it over again, I’d choose a different company.
6. I feel bad about my decision to use this apartment.
7. I am not happy that I used this apartment.
8. Using this apartment has been a good experience.
Word of mouth
1. Intentions to say positive things to others
2. Recommend the apartments of project to another consumer
3. Encourage friends and relatives to buy the apartment from this project.
Customer cost
1. Price
2. Credit
Physical quality
1. Cracks
2. Kitchen
3. Lighting [electronic lighting and window to outside]
4. Water [plumbing facilities, water quality and water pressure]
5. Drainage
6. Commode
7. Internal architecture
Environmental quality
1. Traffic
2. Noise
3. Region security
Project facilities
1. Parking
2. Lobby
3. External staircase
4. Lift
5. Front attractiveness and quality
6. Warehouse
Region Facilities
1. Existence of park
2. Primary school
3. At least 5 shops and public transport within 1 kilometer radius of zone center
Zadkarim et al. 7283

African Journal of Business Management Vol. 5(17), pp. 7284-7290, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM10.1004
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
An evaluation of the investors overreaction to the past
financial function criteria: Iranian evidence
Mehdi Moradi 1 , Mahdi Salehi 2 * and Afshin Hasanzadehnamaghi 3
1 Department of Accounting, Ferdowsi University of Mashhad, Iran.
2 Department of Accounting, Islamic Azad University, Takestan Branch, Iran.
3 Department of Accounting, Islamic Azad University, Mashhad Branch, Iran.
Accepted 28 April, 2011
One of the assumptions of the Efficient Market Hypothesis is that logical reaction of investors to known
and available data cause the cost of invested wealth to approach to its main cost. How ever the
experience shows that the behavior of investors in capital market has not always been correct and
market cooperators shows overreaction to new data. The aim of present a study determining whether
the investors have assigned a higher level for the stock of companies that have acquired rather high
criteria in the past from the real values and whether the prices of these stocks will return to original
costs and experience the return of previous returns. Similarly, the companies that have had rather weak
return in the past have been valued in lower price by experts and will acquire more return compared to
their partners in next periods. Among financial functional criteria, Average of Sale Growth Rate,
Average Growth of operational profit, Average Annual Return and Average Cumulative Abnormal
Return (ACAR) have been selected and four hypotheses have been tested in Tehran Stock Exchange
during 2001 to 2009. The evidences of the present research show that the investors in Tehran Stock
Exchange have shown overreaction to financial function criteria.
Key words: Overreaction, output return winner portfolios, and lose portfolio.
INTRODUCTION
According to Efficient Market Hypothesis (EMH) there are
two predictions about market prices behavior and return
first which: the prices observed in tile market are equal to
their innate values and second, the market output cannot
be predicted by public available data. It means that all
stocks are valued correctly and the stock prices are equal
to present values of all future expected based on
available data in evaluation date Experimental evidences
in the last two decades show that the investors
behavioral bias in data processing cause the stock prices
to be diverted from their real values, which will end to
abnormal return based on old data which implicitly refer
to inefficiency even in low level in the market.
LITERATURE REVIEW
Debondt and Thaler (1985) is among pioneer works
*Corresponding author. E-mail: Mahdi_salehi54@yahoo.com.
Tel: +989121425323.
which used psychological evidences for explaining the
investors’ behavior. In their study, the share monthly
abnormal return was calculated for 16 three- year period;
they found that the share purchase with lower return in
the last five years gains the return about 19.6% higher
than the market within next 3-5 years. Whereas the
investor’s strategy in purchase share with higher return
gains return about 5%lower than the market within the
next 3-5 years. Debondt and Thaler (1985) findings can
be explained by factors such as the company’s size,
secondary effects and temporary variations in risk
factors. Debondt and Thaler (1985) showed that their
previous evidences do not attribute to special characteristics
of the company about risk, size and secondary
effects factors. Zarowin (1989) studied overreaction in
similar time return on Debondt and Thaler research in
1985-1987. He studied share return in 17 periods, and
then compared successful and unsuccessful portfolios
return function having controlled the size of the company.
The results showed that the portfolios return difference
has been eliminated for size factor, after size being
controlled and in the companies being equaled no

significant difference was observed in portfolios rerun
(Zarowin, 1989).
Lakonishok and Shleifer (1994) presented evidences
that value strategies make more returns since they use
less optimal behaviors of the investor so these strategies
are not innately risky.
Laporta (1996) studied differential return between
growth share and value share regarding future profit
growth rate predicted by financial analysts from 1982 to
1990. His findings showed that the companies with low
expected profit overcome the companies with high
expected profit about 20% within the first year after the
formation of portfolios. The difference of return between
share growth and share value will continue up to the fifth
years after the formation of portfolios. Performing extra
tests he concluded that his findings are not affected by
factors of size, effects of B/M and other potential risks.
The research results showed strong evidences of
overreaction hypothesis (Alwathainani, 2006).
Gunaratne and Yonesawa (1997) made a research
about the return reverse in Tokyo Stock Market. The
results showed the strong return reverse in Tokyo stock
market. In addition test also the portfolios return were
compared considering risk time difference in ranking and
test period. It showed that the risk difference in the two
periods was very low but the return difference was high.
Barberis (1998) found evidences that markets showed
overreaction to markets as the average share return in
next periods to a series of good data is lower than the
average return after a series of bad news.
Ahmad and Hossain (2001) studied overreaction and
the effect of New Year in stock market of Malaysia. The
results showed that for three periods found some
evidences that showed markets have overacting about
information, as the average return of the shares in its
next periods to a series of good information is lower than
average return to series of bad news.
Chan and Frankel (2004) studied two valuation effects
related to two psychological biases (representative and
conservative biases). This research did not find evidence
of return reverse in companies which have function
during past few years. This research also offered
evidences confirming less reaction derived from
conservative bias.
Alwathainain (2006) tested the hypothesis that
investors show overreaction to growth and evenness of
patterns in the last years financial from a983 to 1999 in
NYSE, NASDAQ and AMEX stock markets.
The results displayed that past growth rates in each of
the research variation led to moving the price to higher
and lower levels. Then in long-term the prices would
return to their innate levels causing higher and lower
returns respectively. Mirada in 2005 overreaction in
Tehran stock market from 1992 to 2003 results showed
significant of ACAR information and testing and testing
periods for winner and loser portfolios, which is the
indicator of overreaction of common shareholders in
Moradi et al. 7285
Tehran stock market.
Bowman et al. (1998) tested the stock price features in
New Zealand after a weekly great change in prices. The
results showed that the existence of short term overreaction
in New Zealand stock market. Issues like time
stability, risk, size and the resulting actions of differences
in prices of sale purchase that can be indicators of
overreaction hypothesis have also been studied in
research. The results of extra teats found any evidence
confirming the above supposition.
Ma et al. (2005) studied the effect of overreaction of
markets on stock which has highest or lowest percentage
of daily change in prices reported in wall street journal
and New York stock in a two year period of 1996-1997.
The results showed strong evidences of overreaction of
stock market on NASDAQ stock.
In the companies’ shares having the most capital Market
value in England show efficient reaction to the market
doubt data. Nonetheless the investors in the companies’
share having average and small capital market value
have shown so different behavior with weak reaction to
the market doubts. More analysis showed that these
group of investors show less reaction to the data including
excessive events. This has mostly been shown in
positive doubts.
Behavioral finance theory
Behavioral economy is one of the most active areas in
economic research in extent and amount. This theory
rejects the behavioral insight of the economic representatives
based on maximization of expected ideal. Concentration
of behavioral finance theory on one approved
definition of human behavior is more under risk and
uncertainty compared to a normal description. One of the
goals of behavioral finance is the comprehension of
psychological traits of economic representatives (Shleifer,
2000). Most financial and economic theories are defined
as the individuals act intellectually and take all available
data into consideration however; researchers have found
great evidences abut this issue (Shelifer, 2000). This
theory says that sometimes it is necessary to accept this
probability that some factors in economy do not act quite
intellectually in order to find an answer for finance experimental
dilemmas (Thaler, 1999). The basic elements of
behavioral finance theory are cognitive psychology (how
individuals think and decide) as well as limitation in
arbitrage that will be described as follows:
Cognitive psychology and decision making
processes
I. Heuristic decision: it refers to roles in which individuals
take complex decisions in uncertain situations. There are
completely justified reasons for using heuristic decisions

7286 Afr. J. Bus. Manage.
Table 1. Needed variables of the study.
Period Formation period Test period
First 2001-2003 2005-2007
Second 2003-2006 2007-2008
Third 2004-2006 2008-2009
especially when the time of decision is limited. Heuristic
processes can lead to non optimal decisions (Tversky
and Kahneman, 1974; Ritter, 2003) same behavioral bias
approved in psychology, related to cognitive psychology
are described in brief.
II. Representativeness Bias: Representativeness bias
guide individuals to overestimate the incidence of one
occurrence based on similarity between the specifications
of that occurrence and the specifications of original community
of that occurrence (Tversky and Kahneman 1974;
Barberis and Thaler, 2001). When evaluating whether
something belongs to a group or not, people overuse that
group representatives and rarely use base rate (like the
similarities of one member of that group). For instance if
somebody looks as a convict, people evaluate the probability
that he is convict more than reality because they
overuse the similarities but they rarely use the fact that
convicts form a very low percent of the society. In behavioral
models representativeness lead to over reaction,
so it predicts return of the next output (over reaction).
III. Overconfidence: Overconfidence between the
partners is a very clear problem. Overconfidence bias in
financial science refers to the fact that investors think of
their ability in valuation of negotiable documents more
than it really is so the variance error of their predictions is
less estimated.
IV. Self-attribution Bias: The investors’ self-confidence
grows when the general information parallels his personal
information. But if they contradict each other this selfconfidence
does not grow equally. Psychological studies
show that, people tend to be proud of their past success
and attribute their failures to external factors and bad luck
(Daniel et al. 1997).
V. Conservatism Bias: Edwards became popular by
discovery of Conservatism Bias in 1968. This bias causes
people to slowly update their opinions about what is used
in Brav’s’ as rationality standard. It means that people
overuse one base scale and rarely use available data.
That is why Brav and Heaton (2002) classified Conservatism
Bias as intuitive, contrary to representative bias in
some concepts.
The implied concept of conservatism valuation in
behavioral finance theory is that this bias leads to lesser
reaction. Therefore conservatism bias predicts speed in
return. Conservatism can be seen as over self-confidence
about individuals’ previous information (Chan et
al., 2004).
It should be number of behavioral finance models in the
companies’ noted that data processing bias is the
infrastructure of a sequential function which foresees systematic
errors in evaluation due to over or lesser reaction.
While each author uses presuppositions and trends with
little difference in developing his model, they all suppose
that investors fail to have a correct interpretation the
companies’ previous function.
Barberis and Shleifer (1998) emphasized both representative
and conservatism bias as stimulators of these
systematic errors.
Limitation in arbitrage
The concept of arbitrage means that wrong valuation of a
property creates profit without risk. According to arbitrage
theory, the investors are in two groups: intelligent traders
who are able to compensate other investor mistakes and
common traders who have bias in decision making most
of the time (Shiller, 2003). One of behavioral finance
findings is limitation in arbitrage. i.e., when common
traders cause deviation of the property price from its
innate value intelligent traders can not do anything to
increase market efficiency and returning the prices to
their original levels due to limitation in arbitrage
opportunities and costs of the trades.
METHODOLOGY
The population of current study is all listed companies in Tehran
Stock Exchange. All companies having the following specification
would elect as a member of statistical community:
1. The company should not be one of investors or financial
intermediate’s companies.
2. All needed data for calculating growth rates in financial function
criteria (sale, profit) and return should be available.
3. The shares of the company should be transacted more than once
during one year.
4. The company financial year should end to March 20th in each
year.
Formation and test period studied companies and operational
definitions of variations
Formation Period and Test Period for each tested functional criteria
and also the number of studied companies is presented in Tables 1
and 2.

Table 2. Period of the study.
Period
Moradi et al. 7287
Studied variations for main hypothesis Added variations in extra tests
Sale Growth Average Operational benefit growth average Annual return average Cumulative abnormal return
Studied
companies
Winner and
looser
companies
Studied
companies
Winner and
looser
companies
Studied
companies
Winner and
looser
companies
Studied
companies
Winner and
looser
companies
First 150 30 140 28 150 30 150 30
Second 150 30 150 30 150 30 150 30
Third 145 29 145 29 150 30 150 30
Varieties calculations and research sample abnormal
return
Meaning of each share abnormal return is the difference
between real and expected return of that share. In this
research it has been supposed that the expected return for
all negotiable instruments is the same and the return of
each negotiable instrument is like market return. The
market return is calculated as follows:
R m
I
=
1
− I
I
0
0
Which I0 is the total price and year index of all normal
share announced by Tehran Stock Exchange in the
beginning of the year, and I1 is the value of this index for
the end of year.
In this research the share real return is calculated as:
Ri, t
P1
=
( 1+
α ) + DPS − [ P + α ( 1000)
]
0
0
P + 1000(
α )
+ SD + SR
Ri,t = real return of i company in t period, P1= share price
in the end of period, P0 = share price in the beginning of
period, DPS= divided profit of each share, a = Capital
growth percentage of place of the earned and claims, SD 1
= Stock Dividends and SR 2 =Stock Right.
Nominal price of each stock companies share is 1000 Rials
(Iranian Currency).
Finally the annual abnormal return is calculated as:
AR − R
it = Ri,
t
Geometric average of sale growth
m
Sale growth shall be calculated by year to year change for
each share. Then the geometric average is calculated for
this variation within three years as:
SG
jt
⎡
= ⎢
⎢
⎢⎣
−1
∏
T = −3
( 1 + ∆SPS)
jT
⎤
⎥
⎥
⎥⎦
1
T
−1
SGj,t stands for Annual geometric average of sale growth
rate of each share of j Company within last three years to
the date of portfolios formation in t time. ∆SPS jT stands for
years to year variations in sale for the share of j Company
in T years.
Geometric average of operational profit growth
Operational profit growth shall be calculated by year to
year variations in operational profit for each share which
has been scaled by the properties in the beginning of the
period.
The geometric average then calculated for this variety
within last three years measurement as:
EG
jt
⎡
=
⎢
⎢
⎢⎣
−1
∏
T = −3
( 1 + ∆EPS)
jT
⎤
⎥
⎥
⎥⎦
1
T
− 1
EG j,t stands for Annual geometric average of operational
profit growth for each share of j Company within last three
years measuring to date of portfolios formation in t time.
∆SPS jT stands for year to year variation in operation profit
for each share of j Company in T year which has been
scaled by the properties in the beginning of the period.
Test methods
Test methods used in present research for confirmation or
rejection of the hypotheses will be done in two parts; Main
portfolios test and extra portfolios test. Companies will be
ranked in five groups for each studied period and studied
criterion.
Then loser and winner portfolios will be formed based on
each financial operation criterion. These portfolios will be
kept for three years since formation, and ranking period
return (formation period) and maintenance period (test
period) are calculated for each year (from one to three
years).
RESULTS
It should be noted that these stages are just for

7288 Afr. J. Bus. Manage.
Table 3. Results for successful Portfolio (ranking based on average sales growth).
period
Average
cumulative
actual return
Formation period Test period
Average of
accumulated
market gain
ACAR
Average
cumulative
actual return
Average of
accumulated
market gain
ACAR p-value
Result
First 264.68 159.10 105.58 111.69 202.12 -90.43 ≤0.01 Rejected H0
second 194.79 154.03 40.75 73.41 138.35 -64.94 ≤0.01 Rejected H0
third 199.70 232.74 -33.04 38.92 14.73 24.19 0.06 H0 confirmed
geometric average growth sale criterion in three years
before formation (for the geometric average growth
criterion of operation profit growth three years before
formation in the same way is repeated):
1. First the data related to sale and return growth
calculation in ranking period are collected for all statistical
society shares.
2. The qualified shares will be ranked in formation period
based on geometric average of annual sale growth rate.
Then 20% of shares with the most geometric average of
annual sale growth rate are determined for each studied
period as winner portfolios and 20% of shares with the
least geometric average of annual sale growth rate is
determined for each studied period as loser portfolios.
3 .In this stage, at first abnormal return for each share is
calculated annually. The Cumulative Abnormal Return
(CAR) for each share within three years period is
calculated as:
CAR = ∑ AR
t
i , t i , t
t = 1
4. Average Cumulative Abnormal Return (ACAR) for
each portfolio for formation and test period is calculated
as:
1
ACAR =
N
t
∑
t=
1
CAR
i,
t
5 .In the final stage ACAR of each portfolios for formation
and test periods are compared and will be decided for
confirmation or rejection of main hypotheses.
Research hypotheses
H1: In the companies of which proportional sale growth is
higher, the ACAR in portfolios formation period is more
than test period. This hypothesis can be expressed in the
form below null hypothesis can be:
H : ACAR ≤
0
fpw
ACAR
tpw
As can be seen in Table 3, in the first period, the ACAR
of winner portfolios in the test period is much less than in
the formation period. This average has reduced from
105.58% in the formation period to -90.43% in the test
period (that is, 196.01% has been reduced).
This reduction has taken place in the second period as
well the other words in the second period ACAR has
reduced from 40.75 to -64.94% (that is, 121.73% has
decreased). Thus in the first period and second period,
the null hypothesis H0 is rejected and the result is that
companies that sell higher relative growth, the average
cumulative abnormal return of these companies formed
during the test period Portfolios more. Study in the third
period, the average non-cumulative output during the test
period has been established that indicate more
hypothesis is confirmed.
H2: In the companies of which proportional operational
profit growth is higher, in portfolios formation period is
more than in the test. This hypothesis can be expressed
in the form below null hypothesis can be:
H : ACAR ≥ ACAR
0
fpL
tpL
The result test shows in Table 4 which in each three
periods of studied confirmed hypothesis H0. In the first
period ACAR in formation period is 42.54% which has
reduced to -79.2% in test period (that is, a reduction of
121.74%). The rate of reduction in the said average in the
second period is -26.52% of the formation period to test
period. In the third period the value of this average has
increase from -23.82% (that is, it had an increase of 1%)
but the increase rate has not been meaning full and the
second hypothesis of the third period is not also
approved.
Therefore, the loser portfolio (having been formed
based on the sale growth average in the last three years)
is resulted to be optimum in formation period than in test
period.
H3: In the companies of which proportional operational
profit growth is higher, ACAR in portfolios formation
period is more than in the test period. This hypothesis
can be expressed in the form below:
H : ACAR ≤ ACAR
0
fpw
tpw

Table 4. Results for unsuccessful Portfolio (ranking based on average sales growth).
Period
Average cumulative
actual return
Formation period Test period
Average of
accumulated market
gain
ACAR
Average
cumulative
actual return
Average of
accumulated
market gain
ACAR p-value
Moradi et al. 7289
First 201.64 159.10 42.54 122.92 202.12 -79.20 ≤0.001 H0 Confirmed
second 101.03 154.03 -53.00 58.83 138.35 -79.52 0.20 H0 Confirmed
third 208.92 232.74 -23.82 15.73 14.73 1.00 0.32 H0 Confirmed
Table 5. Results for successful Portfolio (Ranking based on average operating profit growth).
Period
Average
cumulative actual
return
Formation period Test period
Average of
accumulated market
gain
ACAR
Average
cumulative actual
return
Average of
accumulated market
gain
ACAR p-value
First 325.61 159.10 166.51 148.54 202.12 -53.58 ≤0.001 H0 Rejected
second 284.04 154.03 130.00 87.93 138.35 -50.42 ≤0.001 H0 Rejected
third 277.27 232.74 44.54 41.27 14.73 26.54 0.35 H0 Confirmed
As can be seen in Table 5, ACAR in test period
has reduced to 220.09 compared to the formation
period.
In the second period this average has reduced
from 130% in the formation period to -50.42%.
(that is, equivalent to 180.2% decrease is
observed). But in third period the fall in this
average, from the formation period to test period
is not meaningful statistically.
So the H 0 hypothesis is rejected in the first
and second periods and so it is resulted that in the
companies in which the relative growth of
functional profit is higher, the average of abnormal
accumulated gain of these companies in the
formation period is more than what in the test
period.
H4: In the companies of which proportional
operational profit growth low, ACAR in portfolios
formation period is lower than test period. This
hypothesis can be expressed in the form below
null hypothesis can be:
H : ACAR ≥
0
fpL
ACAR
As can be noted in Table 6, fourth hypothesis
tests results show that ACAR in the first period in
formation period was 42.12% which has reduced
to -103.12%. In the test period, so fourth hypothesis
is rejected in the first period it has a %4
increase to -69.961%. That it is shown by p- value
the increase in not meaningful, therefore H0
hypothesis is approved in this period as well. In
the third period ACAR has increased from -
98.41% to 17.03% in the test period for loser
portfolios (Means that it has increased 115.44).
tpL
Result
Result
So in the third period H0 has been rejected. In the
companies of which the relative functional profit
growth is lower, the average accumulated abnormal
gain in the formation period is higher than in
test period.
Conclusion
This paper presents evidence consistent with the
hypothesis that individual investors overreact to
information in stale public news stories. Newsevent
returns partially reverse only in stocks with
an abundance of old information, based on
several alternative measures. The information
released during these news events is likely to
contain substantial overlap with past information,
and hence likely to be stale. By contrast, news
events likely to convey more new information elicit

7290 Afr. J. Bus. Manage.
Table 6. Results for unsuccessful Portfolio (Ranking based on average operating profit growth).
Period
Average
cumulative actual
return
Formation period Test period
Average of
accumulated market
gain
ACAR
Average
cumulative actual
return
Average of
accumulated
market gain
ACAR p-value
Results
First 116.98 159.10 -42.12 99.00 202.12 -103.12 0.01 H0 Confirmed
second 79.97 154.03 -74.07 68.39 138.35 -69.96 0.45 H0 Confirmed
third 134.33 232.74 -98.41 31.76 14.73 17.03 ≤0.001 H0 Rejected
much smaller return reversals, or even return
continuations In classic economic theories it is
assumed that people are completely rational and
have limited processing capacity. Standards
models of output like the model of pricing the capitalistic
properties, the hypothesis efficient market
and Arbitrage pricing theory are based upon these
two assumptions.
However experimental evidences in decision
making processing and judging shows that divergence
is more prevalent than to be considered as
exception among investors because of limitation
in information processing capacity time and other
source cognitive constrains. The main question of
this paper was does investing over react to
financial function criteria?
These prediction indicates that investors who
had pessimistic for optimistic ideas about past
financial experienced cause the share price to be
higher or lower thus its real value. The evidences
provided in this research showed that the
companies which the period of time had less
average sale growth, annual average outcome,
were more superior to those companies which
were in higher status. In these regards, which
means they are more efficient.
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and the Chinese New Year Effect, J. Bus. Finan.
Account., 28: 63-105.
Alwathainani A (2006). Do Investors Overreact To Patterns
Of Past Financial Performance Measures? PhD
unpublished thesis, Virginia University.
Barberis N, Shleifer D (1998). A model of investor
sentiment. J. Financ. Econ., 49(3): 307-343.
Barberis N, Thaler R (2001). A survey of behavioral finance,
working paper, Geneva University.
Bowman R, Iverson D (1998). Short-run overreaction in the
New Zealand stock market, Pacific-Basin Finan. J., 6:
475-491.
Brav A, Heaton J (2002). Competing Theories of Financial
Anomalies, Rev. Financ. Stud., 15(2): 575-606.
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Theories Using Trends and Consistency in Financial
Performance. J. Account. Econ., 38: 3-50.
Daniel K, Hirshleifer D, Subrahmanyam A (1997). A theory
of overconfidence, self attribution, and market security
under-and overreaction. J. Finan., 53: 1839-1885.
Debondt W, Thaler R (1985). Does the stock market
overreact? J. Finan., 40: 793-805.
La Porta R (1996). Expectations and the cross-section of
stock returns, J. Finan., 51: 1715-1742.
Lakonishok J, Shleifer A (1994). Contrarian investment,
extrapolation, and risk, J. Finan., 49: 1541-1578.
Ma Y, Tang T, Hasan T (2005). The Stock Price
Overreaction Effect: Evidence on Nasdaq Stocks, Q. J.
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11: 429-438.
Shiller D (2003). From efficient markets theory to behavioral
finance, J. Econ. Perspect., 17: 83-104.
Shleifer A (2000). Inefficient market: An Introduction to
Behavioral Finance, oxford University Press.
Thaler R (1999). The End of Behavioral Finance, Financ.
Analysts J., 55: 12-27.
Tversky A, Kahneman D (1974). Judgment under
Uncertainty: Heuristics and Biases. Science, 185: 1124-
1131.
Yonesawa Y, Gunaratne P (1997). Return reversals in the
Tokyo Stock Exchange: A test stock of market
overreaction. Jpn. World Econ., 9: 363-384.
Zarowin P (1989). Dose the stock Market Overreact to
Corporate Earnings Information? J. Financ., 5: 1385-
1389.

African Journal of Business Management Vol. 5(17), pp. 7291-7295, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM10.1122
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Optimal pricing for internet service providers: Fuzzy
geometric programming model
S. J. Sadjadi 1 *, A. Yousefli 1 and R. Ghezelsoflou 2
1 Department of Industrial Engineering, Iran University of Science and Technology, Narmak, Tehran, Iran.
2 Department of Management, Islamic Azad University, South branch, Tehran, Iran.
Accepted 8 February, 2011
An internet service provider (ISPs) normally purchases a bandwidth from a vendor and allocates it to
different services. The primary concern is to maintain a quality service and, at the same time, maximize
the profitability. This paper presents a mathematical model to find the optimal pricing strategy for an
internet service provider when the primary concern on many pricing strategies is the absence of
historical data for services which makes it difficult to provide a good estimate on the necessary pricing
information such as price elasticity and the parameters are taken as a triangular fuzzy numbers. This
paper presents a mathematical model to find the optimal pricing strategy in the fuzzy environment. The
resulted problem is formulated as a general form of possibilistic geometric programming (PGP). The
implementation of the proposed method is demonstrated via a case study on an ISP in Iran.
Key words: Revenue management, pricing, geometric programming, fuzzy programming, internet service
provider.
INTRODUCTION
Revenue Management (RM) has considerable potential
for economical production in order to maximize the total
profit. It can significantly help organizations keep their
advantages in competitive markets. Belobaba, (1987),
McGill and Ryzin (1999) discussed about the origin of the
revenue management. McGill and Ryzin (1999) categorized
revenue management problems into forecasting,
overbooking, pricing and capacity control. Chiang et al.
(2007) extended their model by considering additional
assumptions. As McGill and Ryzin (1999) mentioned,
pricing is one of the most important aspects of RM. The
optimal pricing has been investigated by many researchers
during the past few decades. In the proposed
models, some factors such as selling price, customer
segmentation, marketing expenditure, etc have been
frequently considered as the most effective factors in the
optimal pricing problem. Burger and Fuchs (2005) argued
about the effects of dynamic pricing on RM and showed
*Corresponding author. E-mail: sjsadjadi@iust.ac.ir. Tel:
0982177240129. Fax: 0982177240482.
that it can lead to a decrease in complexity of pricing
process. Frank (2003) discussed about application of sixsigma
at pricing. Lee and Kim (1993) are the first people
who proposed an integrated marketing and production
models. They considered demand as an exponential
function of price and marketing expenditures and, at the
same time, the cost of production was also considered as
a function of demand. Therefore, the resulted problem
was formulated as a geometric programming model. In
another attempt, Kim and Lee (1998) extended their
model when the capacity of a market was also incorporated
either fixed or variable. Sadjadi et al. (2005) developed
Lee΄s model under some additional assumptions.
In other research, Sadjadi et al. (2010) presented a new
marketing and pricing model in the fully uncertain environment
where decision variables were fuzzy numbers.
Also, they developed a decision support system to
inference vector of decision variables without solving
geometric programming problem directly. Tsaia and Hung
(2007) proposed an integrated real options (IRO)
approach for solving competitive/dynamic pricing and RM
problem in internet retailing where environment was
uncertain. They used analytic hierarchy process (AHP) to

7292 Afr. J. Bus. Manage.
determine the weights of the auction commodities. Nair
and Bapna (2001) studied the internet service provider
(ISP) market structure and explained that demand and
supply in this sector is different from other industry
sectors, so that demand and service happened at the
same time. In other words, the clients, at any time of day,
may require the services and therefore, every moment
system must be ready to serve and the possibility of
overbooking does not exist.
Note that we have a high level of competition on ISP
market on one side and technology is under significant
changes on a daily basis and there is a need to develop a
good strategy for assigning the suitable price for ISP
services.
In this paper, a mathematical model is developed for
ADSL service pricing. Since most of the real world
problems occurred in the uncertain environment, to tackle
this uncertainty, the proposed model is formulated in the
fuzzy environment as possibilitic geometric programming
model. To show the performance of the presented model,
details of implementation of proposed method on one of
ISP΄s located in Iran will be explained.
PROBLEM STATEMENT
A fuzzy pricing model for ISP services is developed under
the following assumptions and notations:
Notations
: Selling price elasticity to demand
: Type of service (kb/second)
: Share ratio
: Selling price (decision variable)
: Services demand
B: Total bandwidth that company receives per period
: Predetermined constant
Assumptions
I: Selling price elasticity to demand is uncertain and
depicted in the form of triangular fuzzy number
~ α = ( α , α , α ) .
l
m
r
II: is uncertain and depicted in the form of triangular
~
fuzzy number k = ( kl
, k m,
kr
)
III: Price is a function of demand so that it has inverse
relation with the selling price as follows:
~ ~ α
−
D = kP
.
(1)
Based on the notations and assumptions expressed, the
pricing for ISP services is developed in fuzzy
environment.
Fuzzy pricing model
In this section, the pricing model for ISP services is developed
in the fuzzy environment. As mentioned before,
the objective function is the maximization of revenue and
there is a constraint on bandwidth. If there are in different
services, mathematical pricing model can be formulated
as follow,
n
∑
j=
1
P max (2)
subject to
γ D
n
j j
∑
j = 1 β j
j j D
≤ B
Replacing D in Model (2) by (1) yields:
max
n
∑
j=
1
subject to
~
k P
−
~ α
n
j k jγ
j Pj
∑
j= 1 β j
j
1−
~
α j
j
≤ B
Model (3) is a possibilitic geometric programming that
αˆ and have triangular possibility distribution. In order to
solve Model (3), fuzzy goal programming method is used.
Following goal programming concept, an aspiration level
such as Z = ( Z l , Z m , Z r ) is chosen and the objective
(3)
function is added to constraint via Z ~ as follows:
Z ~
max (4)
subject to
n
∑
j=
1
~ 1−α~
j k P ≥ ( Z , Z , Z )
j
j
~
k γ P
− ~ α
n
j
j j j
∑
j= 1 β j
l
≤ B.
m
r
Model (4) is a possibilitic geometric programming in
which and have triangular possibility distributions.

After defuzzification, Model (4) is reformulated as
Model (5):
max 3
l . Z m.
Z r
subject to
n
∑
j=
1
n
∑
j=
1
n
∑
j=
1
k
k
k
l
j
m
j
r
j
P
Z (5)
r j
( 1−α
)
j
P
P
m j
( 1−α
)
j
r j
( 1−α
)
j
~
n
−α
j
k jγ
j Pj
∑
j= 1 β j
≥ Z ,
l
≥ Z
r
m
≥ Z ,
,
≤ B.
As it is shown in Model (5), geometric mean is used for
objective function defuzzification and the first constraint
of Model (4) is defuzzified using strong comparison rule
(SCR) method. The first, the second and the third constraints
in (5) are not in posynomial form. To solve this
problem we use a simple lemma from Beightler and
Phillips (1976). To this end, consider the first constraint of
the Model (5) that can be rewritten as follows:
Z
r
−1
l ( 1−α
n )
+ L + Z k P 1 (6)
−1
l ( 1−α1
) −1
l ( 1−α
2 )
1 k1
P1
+ Z1
k 2P2
1 n n ≥
Parameter t1 j is defined as follow:
r
l ( 1−α
j )
k jPj
t1 j = n
r
l ( 1−α
j )
∑ k jPj
j = 1
where
n
∑ t 1 j
j = 1
= 1.
,
j = 1,
L,
n
r
r
(7)
So the first constraint in (5) can be rewritten as follow:
n
∏
⎛ l
⎜ k jP
⎜
⎝
( 1−α
)
j
t
j= 1 1 j
r j
Z
−1
l
⎞
⎟
⎟
⎠
−t
1 j
≤ 1
(8)
Sadjadi et al. 7293
Similarly, the define variables and as follow:
m ( 1−α
)
k j Pj
t2 j = n
m
m ( 1−α
j )
∑ k j Pj
j=
1
r
r ( 1−α
j )
k j Pj
t3 j = n
r
r ( 1−α
j )
∑ k j Pj
j = 1
m j
.
,
j = 1,
L,
n
j = 1,
L,
n
(9)
(10)
As well as first constraint, the second and the third
constraints can be reformulated as
follows:
n
∏
⎛
⎜ k
⎜
⎝
m
j
P
m
( 1−α
j )
j
t
j = 1 2 j
n
∏
⎛ r
⎜ k j P
⎜ t
⎝
r
( 1−α
j )
j
j = 1 3 j
Z
Z
−1
m
−1
r
⎞
⎟
⎟
⎠
⎞
⎟
⎟
⎠
−t
2 j
−t
3 j
≤ 1,
≤ 1,
So, Model (5) can be rewritten as follow:
max 3 Z l . Z m.
Z r
subject to
n
∏
⎛ l
⎜ k jP
⎜
⎝
r
( 1−α
j )
j
t
j = 1 1 j
n
∏
⎛
⎜ k
⎜
⎝
m
j
P
j = 1 2 j
n
∏
Z
m
( 1−α
j )
j
t
⎛ r
⎜ k j P
⎜ t
⎝
r
( 1−α
j )
j
j = 1 3 j
n r −α
k jγ
jPj
∑
j = 1 β j
l j
Z
−1
l
Z
⎞
⎟
⎟
⎠
−1
m
−1
r
≤ B.
−t1
j
⎞
⎟
⎟
⎠
⎞
⎟
⎟
⎠
−t
2 j
−t
3 j
≤ 1
≤ 1,
≤ 1,
(11)
(12)
(13)
To defuzzify fourth constraint of Model (5), SCR method
is also used. Since the right hand side of the fourth
constraint of Model (5) is crisp, defuzzification yields one
constraint as fourth restriction of Model (13).

7294 Afr. J. Bus. Manage.
Table 1. The results of the changes on different price elasticity items.
α1 +20% (4.56 ,5.04 ,5.4) 5007 68030 118187 9860280 30225308 105743910 31586763
α1 +20% (3.04,3.36, 3.6) 84652 68030 118187 9860280 30225308 105743910 31586763
α2+20% (3.24,3.36,3.48) 19734 32688 57675 8119298 14976695 46267491.98 17785666
α2-20% (2.16,2.24,2.32) 24898 981295 1893039 123363302 446238559 1570035471 442134273
α3+20% (2.52, 2.64, 2.7) 23885 62173 117153 7818541 28266259 99467126 28012887
α3-20% (1.68,1.76,1.8) 23020 448930 885278 125978910 230436379 708270551 273957183
Note that Problem (8) is a parametric optimization
problem. The regular procedure to solve (13) is to solve it
different times. Each time, we estimate
using (7), (9) and (10) and
the process continues until there are practically no
changes on parameters. The experience shows that we
need only a few iterations to reach the optimal solution.
The study presents the implementation of the developed
model on one of ISPs located in IRAN that
serves ADSL services.
CASE STUDY
The study implemented the proposed model of this paper
for one of the ISPs located in Iran which offers ADSL
services. The company offered three types of desired
services: 128, 256, 512 kb / s.
Based on the experience of experts parameters
and are estimated as follows:
1 . 4
×
,
,
7
7
7
× 10 , 1.
8×
10 , 2.
2 10 ],
7
7
7
[ 1 . 0×
10 , 1.
2 × 10 , 1.
4×
10 ],
12
12
12
[ 7 . 2 × 10 , 7.
6×
10 , 7.
8×
10 ]
Other parameters are:
Problem is solved using CVX software and the optimal
results are obtained as follow:
P
1
= P
4
4
2 . 3864 × 10 , P2
= 6.
8030 × 10 , 3 = 1.
1819 ×
Sensitivity analysis
The changes on price elasticity of three products by
decrease/increase in their values in a range of 20% were
studied. Table 1 summarizes the experimental results.
Also, the effects on changes in price elasticity on prices
were studied. As can be observed from Table 1 the
change on α 1 only changes on the first service and it has
no significant impact on the total revenue. Note that
k1 has relatively lower value compared with other ones
and this is another reason to believe that any change on
α 1 does not change the overall revenue. In this case
study, the change on the price of the first product does
not make a big change on total revenue. On the other
hand, based on the results of table, when the price of the
first product increases the prices of the other two
products remain with no changes. In fact, in some cases
the price of the second service is higher than the first
one. In such a case, customer may prefer to choose the
second service due to higher internet speed and better
availability. The increase on α2 has much more influence
on prices since it has higher value of k2. As can be
observed from the table, a 20% change on the price of
the second service reduces the price of the second and
the third products, significantly. Since the second product
is more popular among people where the case study is
implemented, it can be concluded that this product has a
higher competitive advantage against the other two
products. The changes on the third product are not as
significant as the impacts of price changes of the second
product. In summary, it could be concluded that the
second product plays an important role on the market.
CONCLUSION
In this paper, a mathematical model to formulate and
solve pricing Internet Service Providers (ISP) problems
10
5

was proposed. Developing model in the fuzzy environment
increases model’s stability against different real
world situations. Whereas in the real world problems,
most of effective parameters are estimated by experts as
linguistic variables and on the other hand, linguistic terms
usually quantified using fuzzy numbers, in the proposed
model, uncertain parameters kj;j=1,2,3 and αj; j=1,2,3
are considered as fuzzy numbers with triangular
possibility distribution. Finally, model is formulated as a
possibilitic geometric programming and the effectiveness
of the model has been illustrated via one of the ISP’s
located in Iran.
REFRENCES
Beightler CS, Phillips DT (1976). Applied Geometric Programming.
Wiley, New York.
Belobaba P (1987b). Airline Yield Management: An Overview of Seat
Inventory Control. Transport. Sci., 21(2): 63-73.
Bitran G, Caldentey R (2003). An overview of pricing models for
revenue management. Int. J. Manufact. Serv. Oper. Manage., 5(3):
.203–230
Burger B, Fuchs M (2005). Dynamic pricing – a future airline business
model. Int. J. Revenue Pric. Manage., 4(1): 39-53.
Chiang W, Chen J, Xiaojing X (2007). An overview of research on
revenue management: current issues and future research. Int. J.
Revenue Manage., 1(1): 97-128.
Sadjadi et al. 7295
Frank S (2003). Applying Six Sigma to revenue and pricing
management. Int. J. Revenue Pric. Manage., 2(3): 245–254.
Kim D, Lee WJ (1998). Optimal joint pricing and lot sizing with fixed and
variable capacity. Eur. J. Oper. Res., 109(1): 212-227.
Lee WJ (1993). Determining selling price and order quantity by
geometric programming optimal solution, bounds and sensitivity.
Decis. Sci., 24(1): 76-87.
McGill J, Van Ryzin G (1999). Revenue Management: Research
Overview and prospects. Transport Sci., 33(2): 233-256.
Nair SK, Bapna P (2001) . An application of yield management for
Internet service Providers. Nav Res. Log., 48(5): 348-362
Sadjadi SJ , Oroujee M, Aryanezhad MB (2005). Optimal production
and marketing planning . Comput Optim Appl., 30(2): 195-203.
Sadjadi SJ, Ghazanfari M, Yousefli A (2010). Fuzzy pricing and
marketing planning model:a possibilistic geometric programming
approach. Expert Syst. Appl., 37(4): 3392-3397. Omega Int. J.
Manage., 37(2): 471-481.

African Journal of Business Management Vol. 5(17), pp. 7296-7305, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM10.1212
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Perceptual gap and anatomy of investment risk
decisions
Nidhi Walia 1 * and Ravi Kiran 2
1 Department of Management Studies, Punjabi University Regional centre, Mohali-India.
2 School of management and Social sciences, Thapar University, Patiala-India.
Accepted 21 February, 2011
Mutual funds put forward a way out to investors to approach maximum number of financial securities
and get a well-diversified portfolio. Investors are lured by mutual fund investment because along with
small savings they neither have sufficient expertise nor the means for diversification. The value added
services offered by mutual funds during last decade has definitely lured the untapped investors.
Although, investors have shown their presence in mutual funds market by investing in various
innovative funds than traditional risk-free securities, it still has not become the most preferred choice of
investors. Thus, it becomes imperative here to study the perception gap as well as risk ambiguity which
investors feel with reference to their mutual funds’ investment decisions. Empirical research results
provided that investors experience a significant difference in actual services offered by mutual fund
than they have perceived. Moreover, research results have also revealed that investors perceive mutual
funds as a risky investment but simultaneously the analysis of preferred score provides that they do
not wish to take extreme low or high risk. These findings for investors’ decision to assume risk level
have implications similar to Simonson and Tversky, Benartzi and Thaler.
Key words: Return on investment (RoI), perception, risk, asset management companies (AMCs), volatility.
INTRODUCTION
Investors differ in their choice for various investment
avenues as due to different demographic features they
need to assume varied level of risk. Mutual fund investment
offers promising solutions to investors that suit their
social constraints. Most luring benefits offered by mutual
funds are in term of maintaining a balance between risk
return trade-off as they offer maximum return on investment
(RoI) at calculated risk. The investors’ develop their
preference for investing in mutual funds when their personal
abilities, lack of professional knowledge and limited
resources restrict their actions. An exclusive benefit of
diversification as offered by mutual funds possesses the
ability to reduce unsystematic market risk which may not
be approachable for an individual investor because of his
personal resource constraints. Mutual fund investment is
generally preferred by investors because of its ability to
diversify funds in various sectors and thus reducing the
possibility of unsystematic risk. Based on different
investment objectives fund managers have to use their
*Corresponding author. E-mail: nidhiwalia79@gmail.com
specialized skills and adopt varied investment styles that
give a composition to perfectly diversified portfolio.
Existing literature on benefits of diversification is well
documented in sample of work by Fisher and Lorie
(1970), Elton and Gruber (1977), Statman (1987) and De
Wit (1998) which provided that diversification can reduce
the portfolio risk significantly than holding a single
investment.
Investors may select momentum or contagion trading
depending upon the market trends. Momentum trading
refers to positive feedback trading that believe in purchasing
the stocks that have performed well in the past
and selling the stock that are facing downtrend in the
recent past. In short, momentum trading believes in
buying the winners and selling the loser. Contagion
trading is a cross country phenomenon which follow sale
of securities in one country when asset prices are falling
in another country. Study by Jegadeesh and Titman
(1993), Asness et al. (1997), Grundy and Martin (2001)
and Griffin et al. (2003) found that strategy of buying past
winners and selling losers generate significant positive
return. They concluded that stocks that had performed
well in the immediate past tended to perform well in the

immediate future. Based on these historic trends,
investors just keep on preferring the mutual funds that
may have performed well in the recent past whereas their
actual experience may differ when they find mutual funds
not investing according to their investment style. This
paper has privileged a unique initiative in the direction to
understanding the investors’ perception towards performance
of mutual funds and furthermore, investigate the
actual experiences of investors which they realize after
investing their savings in mutual funds.
Existing Literature: A brief review
Investors are generally more careful while making
investment decision and presence of rationality in every
investor demands higher return at minimum risk but when
markets are efficient it is not possible to gain abnormal
returns. A common parameter used by investors while
deciding to invest in mutual fund is the historic returns of
mutual funds (Elton and Gruber, 1989; Kane et al., 1990;
Patel et al., 1992); however, there is no support for this
belief in the data (Fama and French, 1988). Mutual fund
investment is subject to market risk which provides that
RoI in mutual fund investment is related to stock market
trends. Further, concept of efficient market hypothesis
(EMH) as explained by Fama (1965) denies the scope of
getting abnormal RoI by using some unique information.
Thus, even mutual funds do not have any sophisticated
tools to multiply the investment in short time. However,
few research studies have also contradicted the unpredictable
behavior of stock market (Hakkio and Rush,
1989; Baffes, 1994; Engle, 1996; Fluck et al., 1997). Lo
et al. (2000) also supported this concept by applying
nonparametric statistical techniques that explored and
recognized patterns which can be used to predict market
behavior. Risk is generally, associated with various
applications differently but in common it means negative
connotation such as harm or loss or some undesirable
action. Although different literature available on risk
define it variedly, in common the word risk refers to situations
in which a decision is made whose consequences
depend on the outcomes of future events having known
probabilities. Simonson and Tversky (1992) proposed
that people given choices A, B and C generally find B as
more attractive than A and C whereas those given choice
of B, C and D will prefer cover B and D. Benartzi and
Thaler (2002) supported the earlier views and proposed
that generally investors avoid extreme choices. They
concluded that when people have three choices ranging
from lowest risk to highest risk they generally follow
middle option. Risk averse behavior of investors reflect
the choice of investors to avoid risk or to assume negligible
risk which provides that whenever an individual
investor is given choice among the securities for securities
with guaranteed return and probability of one and
securities with speculative returns and probability less
than one, he will prefer the former one.
Walia and Kiran 7297
Risk attitude of individual investor have got growing
attention from behavioral finance because investors differ
in their investment decision with reference to their social
base and opportunities available in the financial markets.
Risk is a major factor that shapes investors’ investment
decision including financial and investment decisions
(Yang and Qiu, 2005) because it is the risk that
determines the probable return he can get.
A positive relationship between risk and return provide
that investors who will assume high return will be compensated
by the additional returns generated out of it.
Investors generally have a wide range of choice while
making investment decision (Kida et al., 2009) and they
adopt different parameters to finalize their investment
decision that may involve risk.
However, though more options may provide extensive
choice to investors, it simultaneously increases the complexity
of investment decision that may lead to ‘decision
paralysis’ (Iyenger and Lepper, 2000). Moreover, existing
literature provided that final level of risk assumed by any
individual varies significantly with demographic features
like gender (Slovic, 1996; Byrnes et al., 1999), age (Morin
and Suarez, 1983; Bodie et al., 1992; Palsson, 1996;
Heaton and Lucas, 2000), income (Blume, 1978;
Cicchetti and Dubin, 1994; Bernheim et al., 2001) and
marital status (Roszkowski, 1993; Lazzarone, 1996).
Study by Haliassos and Bertaunt (1995) and Schooley
and Worden (1999) on influence of education and
knowledge on risk taking behavior have also explained
that educated investors are less risk averse.
Thus, investment decisions are definitely influenced by
investors’ knowledge which ultimately set a platform for
developing the perception towards a particular decision.
These gave reasoning to assess impact of investors’
knowledge level on their perception towards performance
of mutual funds that ultimately set their risk anatomy.
METHOD
Participants
Empirical research was conducted on total of 400 mutual fund
investors who have experienced the actual working of mutual fund
asset management companies (AMCs).
Total composition of participants included 69.7% married investors
(41% active investor; age ≥ 30 ≤50). With regard to profession
of investors although a mixed stuff was randomly selected but the
major composition of investors included salaried employees
(65.7%).
Design
The study primarily used exploratory research design for obtaining
information on investors’ risk perception and ambiguity regarding
working of mutual fund AMCs.
For the purpose of convenience a 5 point Likert scale has been
used that attempts to understand investors’ psychology with varied
degrees. A 5*5 research factorial has been designed to obtain
investors’ responses on how they perceive risk.

7298 Afr. J. Bus. Manage.
Procedures
A well- structured questionnaire was designed that seek to obtain
information regarding investors’ perception and risk ambiguity.
Designed questionnaire was duly validated and further, its reliability
was also measured for consistency. Reliability of questionnaire was
found to be significant for perception gap (α= 0.834), mutual funds
working (α= 0.8153) and risk ambiguity (α= 0.801). Demographic
information of investors was collected and they were debriefed
about the core objective of the study. Finally collected data was
analyzed through SPSS 17.0 using appropriate statistical
measures.
Hypothesis
As investors knowledge level has a significant effect on their risktaking
decisions, the study was initiated with the following
hypothesis:
Ho: There is no difference in Investors’ perceived services and
actual services offered by mutual funds.
Ha: Difference exists in Investors’ perceived services about and
actual services offered by mutual funds.
Ho: Differences in investors’ knowledge does not influence their
perception towards performance of mutual funds.
Ha: Differences in investors’ knowledge does not influence their
perception towards performance of mutual funds.
Ho: Differences in investors’ knowledge does not influence their risk
perception.
Ha: Differences in investors’ knowledge significantly influence their
risk perception.
RESULTS AND DISCUSSION
The main objective of this research was to find out the
critical perception gaps that mutual fund investors face
when they find that mutual fund AMCs are not responding
to their investment objective. For this purpose the
questionnaire analysis provided the following results:
Perceptual gap
Working on the first hypothesis of study, investors’
responses were collected for their perceived services
about mutual funds among-with their experienced
services. Perception of mutual fund investors has been
judged for quality of services provided by mutual fund
AMCs. Responses of investors were obtained on 5-point
Likert scale about their experience with mutual fund service
providers both before and after investment. Investors
were asked to give their responses on 1-5 points for
various aspects of mutual fund services, where 1 signify
minimum score and 5 signify maximum score. Average
Perceived Score (APS) of investors and Average
Experienced score (AES) were calculated to find out
perception gap. Table 1 depicts perceptual gap which
investors actually experience once they invest in mutual
funds. Actual experience of investors which they realized
with the difference in mutual fund services through their
post-sale behavior has been measured using five
parameters namely: transparency, responsiveness, communication,
commitment and assurance. Negative results
of perception gap on all these parameters highlight the
level of dissatisfaction among investors which signify that
investors believe mutual funds have different orientation
towards customer services once the investment deal is
finalized. Analysis of these score clearly show that for all
the parameters of service, quality of mutual funds AES<
APS which highlights that investors are lured by highly
promising results with extreme service quality offered by
mutual fund AMCs while their actual experience does not
provide satisfactory results. These results explain that
although with regard to transparency significant gap is
not reflected with AES= 3.34, but significant gap which
investors encounter are in term of assurance (AES=2.42),
and commitment (AES= 2.65). These results rejects the
null hypothesis Ho: There is no difference in investors’
perceived services and actual services offered by mutual
funds and conclude that significant gap exists in investors’
perceived services and actual services offered to
them.
Perception towards MF’s working
Perception of investors towards working style of mutual
fund AMCs is a strong determinant of investors’ risk
perception. Responses of investors’ on their experience
with mutual funds ability to yield expected return, hidden
costs, AMCs ability to respond to volatility, investment
style picked by AMCs to suit investors’ objective and
AMCs ability to protect investors’ interest have been
studied in order to extract exact information on how
investors perceive the working of mutual funds. Responses
of investors pertaining to mutual funds’ working
ability are presented in Table 2.
The overall mean score of respondents (M=1.87) for
their opinion on actual returns delivered by mutual funds
do not match with expected returns, revealing that
investors agree on this statement.
Majority of investors (n=183) agree on poor working
style of mutual funds whereby they are not able to deliver
expected returns. χ 2 =35.722 is significant (p=0.003) at
1% level which highlights that investors’ knowledge and
their perception towards mutual funds ability to yield
expected returns are strongly associated. Among the
various responses on mutual funds ability to respond to
market volatility, it has been observed that although
overall investors agree that mutual funds do not perform
efficiently to tackle market volatility (M=2.05, n=180),
showing their consent but responses of investors with
very less knowledge (M=2.05) significantly differ from
investors with extensive knowledge (M= 1.1).
The result of chi-square reveal that an association exist
between investors’ knowledge and their perception towards
mutual funds’ ability to respond to market volatility
(χ 2 =42.083, p=0.003).

Table 1. Analysis of perceptual gap.
Variable
Average perceived
score(APS)
Standard
deviation
Average experienced
score(AES)
Walia and Kiran 7299
Standard
deviation
Perceptual
gap
Transparency 4.03 0.97 3.34 1.08 -0.69
Responsiveness 4.20 0.88 3.15 1.02 -1.05
Communication 4.3 0.834 2.99 1.02 -1.31
Commitment 4.24 0.85 2.65 1.07 -1.59
Assurance 4.24 0.83 2.42 1.04 -1.82
Analyses of Table 2 on hidden costs charged by mutual
funds reveal that overall investors agree that mutual
funds charge hidden costs on their investments which are
not earlier disclosed at the time of investment (M=1.92).
Majority of investors (n=153) strongly agree that mutual
funds charge hidden costs. Significance of Chi-square
provides association between investors knowledge and
hidden costs charged by mutual funds (χ 2 =30.158, p=
0.017). Further, overall mean score of investors on their
response to whether mutual funds invest funds in
accordance to investors objectives provide that investors
(n=162, M=2.16) agree. The result of χ 2 =29.042 is
significant at 5% level (p=0.024). Investors also show
their consent on agents of mutual funds are not well
informed (M=2.10, n=177) which indicates that investors
realized mutual fund investors are not informed enough
to bestow thorough information to investors. However, chi
square is not found to be significant in this case. Analysis
of investors’ responses on their perception towards mutual
funds ability to protect investors’ interest also provide
that investors agree (M = 2.19, n = 189) that mutual fund
AMCs do not take some special steps in order to protect
investors’ interest. The result of Chi-square reveals that
there is a strong association between investors’ knowledge
and their perception towards mutual funds’ working
style (χ 2 =28.846, p=0.025). Finally, investors also
positively affirm that mutual funds do not possess strong
network (M= 2.24, n=146). χ 2 =15.382 is not significant for
investors’ knowledge and investors’ perception on mutual
funds possess strong network.
Investors’ own knowledge has been assumed to play a
significant role in determining investors’ perception
towards any financial avenue. One way ANOVA has
been performed to analyze if investors’ perception differ
significantly for mutual funds working with their knowledge
on finance. The analysis of ANOVA reveals that
there is a significant difference in responses of investors,
for their perception towards mutual funds are not able to
deliver expected returns which yield F ratio of F (4.395)
=3.082, p=0.016. Further, ANOVA results are also found
significant for investors’ knowledge and their perception
towards mutual funds’ ability to respond to volatility which
yield F ratio of F (4.395)=2.623, p=0.034. However,
ANOVA is not found to be significant for hidden costs,
investors’ objective, AMCs ability to protect investors’
interest and MFs possess strong network that provides
there is no significant difference in means of less
knowledgeable or extensive knowledge investors. As the
second objective of study was to test null hypothesis Ho:
Differences in investors’ knowledge does not influence
their perception towards performance of mutual funds,
which has been rejected by the results that highlighted
investors’ knowledge has shown significant association
with their perception towards mutual funds’ performance.
Risk ambiguity and choice
Relationship between risk and return is assumed to be
high which provides that higher the risk, higher the return.
For this purpose, investors were given few statements
with 1-5 scale where 1 signify the minimum level and 5
signify the maximum level. Results of investors’
responses on risk in mutual funds have been presented
in Table 3 Analysis of investors’ responses on risk in
mutual fund reveals that majority of investors (n=184)
have shown their positive node to accept risk if it is
clearly disclosed (M=2.13, σ=0.84). ANOVA results for
knowledgeable investors’ responses vary significantly for
willingness to assume disclosed risk which yield F ratio of
F (4.395)=4.040, (p ≤ 0.01). However, investors preferring
to take extreme low risk (n=41) and extreme high
risk (n=30) are found to be very few. Majority of investors
have shown their intermediate preference for assuming
risk level (n= 148) (M=2.95, σ=1.08). F ratio of F
(4.395)=33.96 (p ≤ 0.001) signify that investors’
knowledge definitely influence their decision to assume
risk level in investment avenue.
Results of investors’ responses on AMCs ability to
estimate and control risk in mutual fund reveals that
investors do not have very high degree of notion about
AMCs ability to estimate market risk (M= 3.18, σ=1.13). A
very small group of investors (n= 50) have shown
complete faith in AMCs ability to estimate risk. Similar
results are found for investors’ notion on AMCs ability to
control risk (M=3.14, σ = 1.19). ANOVA results for AMCs
ability to estimate risk in mutual funds, yield F ratio of F(4,
395)= 11.234 (p ≤ 0.001) which signify that investors with
updated knowledge understands that AMCs have ability
to estimate risk present in mutual funds whereas

7300 Afr. J. Bus. Manage.
Table 2. Investor’s knowledge and perception towards mutual funds ability.
Variable Mean Χ 2
Actual return does not match with expected returns
Very less knowledge 1.59
Some knowledge
Moderate knowledge
Good knowledge
1.87
1.937
2.0
35.722*
(df:16, p=0.003)
Extensive knowledge 1.30
Mutual funds are poor to respond to market volatility
Very less knowledge 2.05
Some knowledge
Moderate knowledge
Good knowledge
2.04
2.07
2.16
42.083*
(df:16, p=0.003)
Extensive knowledge 1.1
High hidden cost
Very less knowledge 1.96
Some knowledge 1.98
Moderate knowledge 1.89
Good knowledge 1.85
Extensive knowledge 2.1
30.158**
(df:16, p=0.017)
Funds not invested according to investor's objective
Very less knowledge 2.15
Some knowledge
Moderate knowledge
Good knowledge
2.14
2.22
2.09
29.042**
(df:16, p=0.024)
Extensive knowledge 2.10
AMCs are not able to protect investors interest
Very less knowledge 2.15
Some knowledge 2.06
Moderate knowledge 2.27
Good knowledge 2.19
Extensive knowledge 2.60
*p< 0.01 ** p

Table 3. Risk ambiguity.
Walia and Kiran 7301
Total 1 (%) 2 (%) 3 (%) 4 (%) 5 (%) M F p
Willingness to take risk 23.3 46 25.8 4.3 0.8 2.13 33.963 0.000*
Level of risk 10.3 22 37 23.3 7.5 2.95 4.070 0.003*
Worried about risk in mutual funds 11 23 35.5 25.8 4.8 2.90 5.370 0.000*
AMCs ability to estimate risk 8 20 29.8 29.8 12.5 3.18 11.234 0.000*
AMCs ability to control risk 10 21 27.5 28 13.5 3.14 8.722 0.000*
Probability of lose in MF 8.3 23.8 41.5 22.8 3.8 2.90 4.255 0.002*
Lose due to down trend in stock market 4.3 9 18.3 37.8 30.8 3.81 1.618 0.169
Gain due to uptrend in stock market 0.8 5.5 18.3 41.5 34 4.02 3.467 0.008*
Credibility of claims in mutual fund
advertisement
6.3 29.3 42.5 18.5 3.5 2.83 5.805 0.000*
Confidence of annual returns 4.5 20 34.3 31.8 9.5 3.21 12.033 0.000*
Confidence of expected total returns 4.3 18.3 33.8 30.8 13 3.30 10.278 0.000*
Overall risk in mutual funds 2.5 14.5 38.8 28.5 15.8 3.40 12.234 0.000*
Table 4. Results of multiple regression analysis for risk perception (DV).
Dependent variable Multiple R R 2 Adjusted R 2 F probability Durban Watson statistics
Risk level 0.668 0.446 0.439 0.000 1.65
Independent variable B Β
Standard
error
t-value
Significance
of t
Tolerance/VI
F
Age -0.567 -0.378 0.06 -9.45 0.000 0.878/1.138
Investors’ knowledge 0.237 0.223 0.047 5.03 0.000 0.718/1.392
Income 0.229 0.187 0.051 4.525 0.000 0.827/1.209
Credibility of advertisement 0.207 0.176 0.046 4.510 0.000 0.925/1.082
Worried about risk -0.131 -0.127 0.04 -3.286 0.001 0.938/1.066
Dependent variable Multiple R R 2 Adjusted R 2 F probability Durban Watson statistics
Overall risk in MF 0.598 0.358 0.348 0.000 1.814
Independent variable B β
Standard
error
t-value
Significance
of t
Tolerance/VI
F
Probability of lose 0.304 0.295 0.048 6.310 0.000 0.748/1.337
Age 0.239 0.172 0.06 3.971 0.000 0.868/1.152
Worried 0.149 0.157 0.046 3.257 0.000 0.699/1.43
Income -0.144 -0.126 0.051 -2.825 0.005 0.815/1.227
Downtrend in stock market 0.142 0.155 0.040 3.534 0.000 0.845/1.183
Investors’ knowledge -0.126 -0.128 0.046 -2.708 0.007 0.729/1.37
mutual fund possess above average risk (M=3.40,
σ=1.045) as very few investors consider it to be least
risky (n=9) and extreme risky (n=63). Finally, analysis of
ANOVA results reveal that investors’ perception towards
overall risk in mutual funds also differ significantly for
different categories of investors’ knowledge, which yield F
ratio of F(4.395)=12.234, p=0.000. As for majority of
responses studied for risk perception of investors, there
have been significant differences in investors’ knowledgewise
risk perception, null hypothesis of Ho: Differences in
investors’ knowledge does not influence their risk
perception is rejected.
Further, to understand investors’ perception towards
assuming risk in mutual funds and presence of overall
risk in mutual funds, multiple regression analysis has
been used. The detail results are provided in Table 4

7302 Afr. J. Bus. Manage.
Figure 1. Level of risk.
which provides that risk level assumed by an individual
investor depends upon age, investors’ knowledge, income,
credibility and worries about risk. Analysis of these
results provides R=0.668 (R 2 =0.446) and adjusted R 2
=0.439 which is significant at 0.1% level (p=0.000). The
inter-dependent nodes of risk taking decision are presented
in Figure 1. Durbin Watson statistic of 1.65 that
tests whether adjacent residuals are correlated is found
satisfactory. β= -0.378 highlight that age is a strong
predictor in investors’ decision on level of risk they wish
to assume, whereas β=0.223 also highlight a significant
impact of investors’ knowledge on their willingness to
assume a specified risk level. High t values for all the
predictor variables highlight their significant impact on
criterion variable. The tolerance for each variable is >
0.878 (1.138) which indicate that there is no problem of
multi collinearity. Finally, multiple regressions has also
been carried out to examine the relationship between
how investors perceive overall risk in mutual funds and a
set of predictor variables that included probability,
age, worries, income, downtrend in stock market and investors’
knowledge. R=0.598 (R 2 =0.358) and adjusted
R 2 =0.348 which is significant at 0.1% level (p=0.000).
Figure 2 presents the relationship nodes that finally set
the investors risk perception for mutual funds. Durbin
Watson statistic (1.814) has also been examined to test
whether adjacent residuals are correlated, and is also
found to be satisfactory. Further, standardized β=0.295
for probability to lose and β=0.172 for age also provide
that these predictor variables have most significant
impact on investors’ risk perception towards mutual funds
risk. Similarly, high t value for probability (t=6.310) and
age (t=3.971) provide that predictor variables have
significant impact on criterion variables. The tolerance
values highlight the correlation between the predictor
variables whereas VIF is an alternative measure of
collinearity in which high values reveal strong relationship
between predictor variables. The tolerance for each
variable is > 0.748 (1.337) which indicate that there is no
problem of multi collinearity (overlap between dependent

Figure 2. Risk perception.
variables).
The multivariate test statistic reveals multiple correlation
coefficient (R) is 0.705 (R 2 =0.497) and adjusted
R 2 = 0.491 for investors’ confidence in expected total
return from mutual funds. The value of R 2 measures
variability in the outcome by predictor variable which
leads to the connotation that 49.7% of the variance in
confidence about total return can be predicted from
investors’ belief in AMCs ability, age, credibility and
worries. The results indicate that all the predictor variable
risk estimation by AMCs (p= 0.000), risk control by AMCs
(P= 0.000), credibility (P=0.000), worries (P= 0.000) and
age (P= 0.002) yield significant results. The standardized
Walia and Kiran 7303
β=0.38 reveals that risk estimation by AMCs contribute
maximum to the model which indicates that a unit change
in this predictor variable has a large effect on criterion
variable. Similarly, high t = 8.378 indicate that predictor
variable has large impact on criterion variable. The tolerance
values highlight the correlation between the predictor
variables whereas VIF is an alternative measure of
collinearity in which high values reveal strong relationship
between predictor variables. The tolerance for each
variable is > 0.616 (1.623). Analysis of multivariate
statistic for investors’ confidence in annual return from
mutual funds reveal that R=0.704 (R 2 =0.496) and adjusted
R 2 =0.490 provide that 49% variance in investors’

7304 Afr. J. Bus. Manage.
Table 5. Results of multiple regression analysis for confidence in MF returns (DV).
Dependent variable Multiple R R 2 Adjusted R 2 F probability Durban Watson statistics
Confident about TR 0.705 0.497 0.491 0.005 1.79
Independent variable B β
Standard
error
t-value
Significance
of t
Tolerance/VIF
Risk estimation by AMC 0.35 0.38 0.042 8.378 0.000 0.616/1.623
Risk control by AMC 0.218 0.247 0.039 5.565 0.000 0.640/1.562
Credibility of advertisement 0.161 0.142 0.043 3.722 0.000 0.875/1.143
Worried about risk -0.138 -1.40 0.039 -3.567 0.000 0.826/1.21
Age -0.174 -1.20 0.055 -3.141 0.002 0.869/1.174
Dependent variable Multiple R R 2 Adjusted R 2 F probability Durban Watson statistics
Confident about AR 0.704 0.496 0.490 0.000 2.002
Independent variable B β
Standard
error
t-value
Significance
of t
Tolerance/VIF
Risk estimation by AMC 0.267 0.297 0.04 6.636 0.000 0.636/1.571
Risk control by AMC 0.210 0.246 0.039 5.375 0.000 0.613/1.632
Credibility of advertisement 0.225 0.203 0.042 5.375 0.000 0.893/1.120
Age -0.246 -0.175 0.053 -4.611 0.000 0.893/1.120
Probability to lose money -0.165 -0.157 0.039 -4.189 0.000 0.907/1.103
confidence can be predicted from investors’ trust in
AMCs working, credibility, age and probability (Table 5).
These results are found significant at 0.1% level (p=
0.000). For multiple regression between investor’ confidence
in annual returns from mutual funds as criterion
variable and predictor variable provide Durbin Watson
statistic of 2.002 which is quite satisfactory. The standardized
β=0.297 reveals that risk estimation by AMCs
contribute maximally to the model which indicates that a
unit change in this predictor variable has a large effect on
criterion variable.
Similarly, high t = 6.636 for risk estimation by AMCs
indicate that predictor variable has large impact on criterion
variable. As step-wise regression has been used, t
value is found significant for all the predictor variables.
The tolerance for each variable is > 0.636 (1.571) which
indicate that there is no problem of multi-collinearity.
CONCLUDING REMARKS
This study was conducted to understand investors’ perception
towards presence of risk in mutual funds and
further extend it to examine how investors’ knowledge
influence risk perception of investors. The results of this
empirical research has provided that investors have
experienced a significant change in services offered by
mutual funds, after they actually invest their funds in a
particular scheme. Investors have revealed that AMCs
deviate from their promises for assurance and
commitment towards RoI and they do not get expected
returns. Further as mutual fund investment is subject to
market risk, it gets affected by the stock market volatility.
Investors’ own knowledge influence their perception for
assuming presence of risk in mutual funds.
Research results have provided that risk ambiguity
prevails among investors because of differences in
investors’ updated knowledge on financial market behavior.
Thus, although, the perception gap among mutual
fund investors is a result of their perceived notions about
mutual fund investment where they are lured by
overwhelming promising solutions whereas the actual
performance of mutual fund AMCs is subject to multiple
constraints and risk ambiguity prevails among mutual
fund investors because of lack of the differences in
individuals’ knowledge.
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African Journal of Business Management Vol. 5(17), pp. 7306-7315, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM10.1289
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Earnings management and the auditing value in China
Yi-Pei Liu 1 and Yu-Shu Cheng 2 *
1 Department of Accounting, Providence University, Taichung, Taiwan, No. 200 Chung Chi Rd., Taichung 43301, Taiwan.
2 Department of Accounting, Kainan University, Taoyuan, Taiwan, No.1 Kainan Rd, Luchu Shiang,
Taoyuan 33857, Taiwan.
Accepted 29 December, 2010
Auditing has been identified as an area of immense importance for the development of China's stock
market. Auditing not only provides reliable information for users, but, more importantly, it must
coordinate the potential interests among the public, central and local state, and the nation. This study
investigates the association between the auditing value and earnings management risk (EMR) induced
by security regulation. It is hypothesized that, from the perspective of risk premiums, the auditing value
increases as the EMR increase. Using a sample of 4,594 Chinese listed firms during 2001 to 2006, we
find that auditing value is positively associated with EMR. We also find that different types of security
regulation affect the auditing value. The results are robust to different model specifications and
alternatives sample. Apart from providing some new evidence in the important area of auditing value,
we also reveal interesting implications for auditing profession, regulators, entrepreneurs, and
investors.
Key words: Earnings management, auditing value, security regulation, risk premium.
INTRODUCTION
The value of an audit has been an important issue.
Enhancing the value of an audit increases transparency
and facilitates public investors to better monitor firms.
Understanding the factors that are associated with the
value of an audit is a vital concern for regulators,
investors, and the accounting profession. The primary
objective of this study is to provide a refined analysis to
examine the relationship between the auditing value and
earnings management risks from the perspective of risk
premiums. We focus on the following three questions: 1)
does the regulation of special treatment or particular
transfer designation affect the value of an audit? 2) Does
the economic consequence of the regulation of delist
affect the value of an audit? 3) Does the economic
consequence of the regulation of right offerings affect the
value of an audit?
In emerging market, the value of an audit plays an immense
role in the Chinese capital market compared with
that in advanced economies. Three factors motivated this
study. First, in that almost all listed firms in China are
carve-outs or spin-offs from large state-owned
*Corresponding author. E-mail: cyushu@gmail.com. Tel: 886-3-
3412500/7915.
enter-prises (SOEs), the China Securities Regulatory
Commis-sion (CSRC) requires that all listed firms have
their annual reports audited by certified public accounts
(CPAs) so as to safeguard national recourses from misappropriation
and embezzlement; provide more reliable
information for decision makers. Second, according to the
statistics done by CSRC, the number of listed firms
reached 1,434 in 2006 and was 102.42 times that of
1991; the stock market value of listed firms reached RMB
8,940.4 billion dollars, and was 820.22 times that of 1991,
which stimulated the strong demand for audit service.
However, a lower quality of financial reporting and the
absence of an investor protection, compared with the
advanced economies, are obstacles to foreign investments.
This means the audit is valued if the audit can
improve quality of financial statement. In other words, in
attesting the quality of accounting information, audit
services thus think of an external monitoring role on
behalf of the owners/shareholders (Fan and Wong,
2005).
Finally, for the Chinese security regulations, previous
studies documented that the major earnings management
incentives in Chinese listed firms are regulationinduced
compared to the market-based or contractedbased
motivation in U.S. firms (Aharony et al., 2000; Haw
et al., 2000; Chen and Yuan, 2004; Yu et al., 2006). To

date, however, there has been little research to further
study the relationship between the auditing value and
earnings management risks from the perspective of
information value. Also, because of the uniqueness of the
capital market and the auditing profession in China, it is
of a great interest to study on how the value of an audit
respond to government’s security regulations in such an
emerging and developing economy.
We conduct an empirical analysis on a sample of 4,594
firm-year observations from 2001 to 2006. Multivariate
regression is applied to examine our research questions.
We find that, 1) the value of an audit is positively associated
with earnings management risk; 2) the regulation
of special treatment or particular transfer designation
positively affects the value of an audit; and 3) the regulations
of and delisting and right offerings positively
affects the value of an audit.
This study contributes to the literature on transitional
economies in the followings two ways. First, this study
empirically identifies the auditing value of different
security regulations under China’s gradual privatization
process. Since it is not easy to measure the value of an
audit, little research studies the auditing value issue. This
study is new, in that it demonstrates that the unintended
economic consequences of different security regulations
affect the value of an audit. My findings suggest that the
value of an audit depends on earnings management
risks, while earnings management risks depends on the
security regulation, which implies the government’s
regulatory mechanism is the key driver of the auditing
value. This result supports the suggestion by Wallace
(1980) that the audit is valued if the audit can reduce the
noise and bias of financial information resulting from
uncertainty. Second but not least, transplanting western
institutions, for example, rigorous enforcement of financial
reporting requirements, in the post-socialist societies
is a vital part of the transition from a planned economy to
a market economy. Studying how the value of an audit
respond to security regulation helps us to understand this
exciting but often bumpy process.
Institution settings
Incentive to avoid trading restriction and being
delisted
To protect the interests of investors and to maintain an
orderly market, in 1998, the CSRC introduced a unique
form of regulation—the special treatment (ST) designation.
When a listed company suffers “abnormality in [its]
financial situation” or “other situation abnormality,” and
investors can not judge the company’s prospects and
their interests would be damaged, the company’s stocks
will be implemented with special treatment. Once a firm is
designated an ST firm, its trading is regulated. For example,
the firm is required to provide audited semi- annual
Liu and Cheng 7307
financial reports, and the company’s stock-price fluctuation
is subject to a daily 5% stop-buying and stop-selling
limit; in other words, the price volatility is within ±5%.
Moreover, ST firms are pressed to improve their
financial situation with effort. If their financial situation
gets worse, the regulation gets tighter. For example, any
listed firm with three consecutive years of regulation is
classified as a particular transfer (PT) firm. PT shares are
allowed to trade only on Fridays. To prevent insider
manipulation, the price increase in a PT share cannot
exceed the 5% limit for any trading day. However, the
price of a PT share is allowed to fall without limits. If the
PT firms make a profit with an unqualified audit opinion in
the following half of the year, on the contrary, they can
apply to have their stocks relisted. If the PT firms are still
unable to revitalize themselves within the six-month tolerance
period they have to show a profit, on the contrary,
they will be deleted from the stock exchanges—delisting.
Delisting means the listed firms lose the valuable “shell.”
ST and PT regulations reduce the value of the shell to
listed firms. To avoid being delisted or being labelled with
ST or PT status, the listed firms have strong incentives to
manage their earnings upward to keep losses off the
books.
Incentive for rights offerings
Since the CSRC and other related regulatory authorities
have adopted a restrictive quota system to regulate the
Chinese stock market (Pistor and Xu, 2005), almost all
Chinese listed firms were under-capitalized at their IPOs.
In order to sustain the current operation and future
expansion, a listed firm needs to raise additional capital
immediately after its IPO. A listed company may issue
corporate bonds or ask the bank for a loan, if the company
obtains approval from the Central Bank, the State
Planning Commission, and other authorities concerned.
However, listed firms prefer to raise new equity capital
rather than to borrow because regulators seldom approve
listed companies’ requests to issue bonds and bank
loans restrict firms in many ways (Haw et al., 2000).
Moreover, listed firms are not responsible for dividends
and principal, and they view equity financing as cost free
(Chen et al., 2008). Therefore, rights issues are the most
important way to raise additional capital in the current
regulatory environment. This provides listed firms with
strong incentives to manage earnings to meet the profitability
requirement. In fact, most listed firms have had
rights issues within three years of the firms’ listing.
To be eligible for rights issues, a listed firm has to meet
several requirements. In 1993, firms had to be profitable
for two consecutive years before they could issue rights.
Since the CSRC recognized the first profitability requirement
was loose and most firms qualify to offer rights, the
CSRC tightened the regulation by raising the minimum
profitability requirement in September 1994. The CSRC

7308 Afr. J. Bus. Manage.
required firms to be profitable for three consecutive years
and the three-year average ROE must be more than 10%
before the firms could issue rights. In January 1996, the
CSRC further toughened the profitability requirement,
stating that firms must have more than 10% ROE for
three consecutive years before the firms could issue
rights. This led to a significant drop in the number of firms
that issued rights in 1996. The CSRC then lowered the
requirement in March 1999, stating that firms have to
maintain, at a minimum, a reported ROE of 6% for three
consecutive years, and the average ROE over these
three years must be no less than 10% before the firms
could issue rights. In March 2001, the CSRC further
lowered the standard, requiring that firms must have an
average ROE above 6% for three consecutive years.
Since the CSRC depends on ROE to review a listed
firm's application for rights offerings, listed firms have
strong incentives to manage earnings above those
regulatory thresholds.
LITERATURE REVIEW AND HYPOTHESIS
DEVELOPMENT
Earnings management induced by profitability
regulation
Earnings management has been prevalent in Chinese
listed companies. Prior studies suggested that Chinese
listed firms have strong incentives to manage their
earnings to meet regulatory standards to gain the right for
an IPO, to raise new equity capital through rights
offerings and to avoid trading restriction, or being
delisted. For example, Aharony et al. (2000) showed that
SOEs attempt to manage earnings to boost their chances
of being selected for IPOs. To avoid delisting, Lee and
Xue (2003) found that firms increase the discretionary
accruals to defer the occurrence of losses before the loss
year. In the loss year, the firms will adopt the opposite
earnings management behaviour to take a big bath. Similarly,
Ding et al. (2007) provided evidence that ST and PT
firms tend to undertake a higher degree of earnings
management by using non-operating items to avoid being
delisted.
In addition, numerous studies also document the
earnings management behaviour in response to the 0%
rule, the 6% rule, and the 10% rule. When listed firms
boost their earnings to meet these rules, the reported
ROE is likely to be only marginally above the regulatory
threshold (referred to as marginal ROE). Once the
regulatory threshold is reached, any additional opportuni-
stic behaviour in reported profit will increase only
theexpected cost, not the expected benefit. As research
settings differ, this prediction of earnings management
behaviour is analogous in spirit to the compensation plan
research findings about the effect of the bonus plan’s
lower and upper bounds on earnings management
(Healy, 1985).
For example, Jiang and Wei (1998) showed that the
percentage of firms with an ROE of just above 10% from
1994 to 1997 is increasing, and offer suggestions to curb
the obvious earnings management behaviour. Xia and
Yang (2002) took 1,088 listed companies in 2000 as a
sample, and showed that the listed firms whose ROEs
are within 6 to 7% or within 0 to 1% range manage
earnings to meet regulatory benchmarks for offering
stock rights and for avoiding delisting, respectively (we
refer to firms whose marginal ROEs are within 0 to 1%, 6
to 7% or 10 to 11% under different regulatory environments
as “borderline firms”). Consistent with these
findings, Chen et al. (2001) examined the association
between earnings management induced by profitability
regulations and modified audit opinions (MAOs) over the
period 1995 to 1997. The researchers found there is a
significant association between receiving MAOs and
reporting profits marginally above the target levels
specified in stock delisting and rights offering regulations.
This means earnings management for meeting the regulatory
profitability requirements increases the frequency
of receiving MAOs. Haw et al. (2000) found that firms
whose ROEs are within 10 to 11% have higher abnormal
accruals and non-operating income than other firms. The
researchers also found that the borderline firms’ earnings
response coefficient is lower than that of other firms and
that the borderline firms that conducted a rights issue
later had less managed earnings than those firms that did
not. Chen and Yuan (2004) provided evidence that there
was a heavy concentration of ROEs in the area just
above 10% for the period 1996 to 1998, and that listed
firms use excess non-operating income to reach the 10%
threshold. Furthermore, Yu et al. (2006) used a
distribution approach and documented that earnings
management exists at ROE thresholds, namely, at 10%
for the period 1994 to 1998, 10 and 6% for the period
1999 to 2000 and 6% for the period 2001 to 2002. They
further showed that earnings management at these
thresholds was very rampant and that non-core income
was the major means used in such earnings management.
In short, the Chinese earnings management behaviour
is primarily induced by the profitability regulation.
For regulators, auditors, investors, and the public, this
behaviour represents higher earnings manipulation risk
when the listed firms are ST firms, PT firms, and
borderline firms.
Earnings management risk and the auditing value
Wallace (1980) argued that the audit is valued if the audit
can reduce the noise and bias of financial information
resulting from uncertainty and then improve the input
data quality by means of the reduction of the risk
premium. Consistent with these arguments, Balsam et al.
(2003) and Ferguson et al. (2004) indicated that audit can
serve a very important role in improving information
credibility. Nevertheless, the value of an audit will also

affect the utility of financial audits. To define the concept
of auditing value, we consider a simplified version of the
“hiring or not hiring auditor problem’’. The value of an
audit is computed on the basis that the choice is between
having no audit available and requiring the entrepreneur
to hire an auditor who will provide the specified audit. The
entrepreneur can decide to hire or not hire an auditor.
Though the entrepreneur is the only one that knows a
firm’s expected (monetary) real value, he is not sure how
much the firm’s end-of-period value will be reported
through accounting information system.
When no auditor is hired, we assume that a entrepreneur’s
assets x face two states of the world: in state o
the asset is overstated; in state u it is understated. The
end-of-period values are (x + z) and (x - z), respectively.
The probabilities of overestimated and underestimated
types are q and (1 - q), respectively.
Now, let q and (1 - q) equal 1/2, then the expected
utility of x is equal to the expected value of the risks in
terms of utilities, that is:
1
E −
2
{ u(
x)
} = [ u(
x + z)
+ u(
x z)]
(1)
The corresponding risks premium is equal to π ( , ~
1 x z )
,
that is:
~ 1 2
π 1 , z ) = σ
2
( x z1λ1 ( x)
When mandatory audits are introduced, an entrepreneur’s
assets x still face two states of the world: in state
o the asset is overstated; in state u it is understated.
According to DeAngelo’s (1981) theorized analysis, the
value of an audit to clients of audit services is defined as
the joint probability that an auditor will (a) discover the
breaches or errors in client’s accounting system and (b)
report the breaches. This implies hiring an auditor is able
to decrease the noises/variances of the accounting
information, and increase the precision of information.
Therefore, the end-of-period values are ( x + sz ) and (
x − sz ), respectively, each with probability q and (1 - q).
The symbol s denotes the outcome of hiring an auditor
(0≤s≤1). The notations s=0 and s=1 indicate an audit can
completely reduce the uncertainty of the accounting
information and can not reduce any uncertainty of the
accounting information, respectively.
Now, let s equal 1/2; q and (1-q) equal 1/2, then the
expected utility of x is equal to the expected value of the
risks in terms of utilities, that is:
1 1 1
E −
2 2 2
{ u(
x)
} = [ u(
x + z)
+ u(
x z)]
(2)
(3)
Liu and Cheng 7309
The corresponding risks premium is equal to ) ~ π 2(
x,
z , that
is:
~ 1 2
π 2 , z ) = σ
2
( x z2λ2 ( x)
We assume an entrepreneur is risk-averse and he has
the same preferences whether hiring or not hiring an
λ x)
= λ ( x)
= λ
( 2
auditor, that is, 1
for all x . Since the
2
2
variances σ z 2
σ are lower than z1
, the corresponding risk
premiums, ceteris paribus, satisfy
(4)
π x, ~ z ) < π ( x,
~ z )
1(
2
for every risk z ~ . Accordingly, we define the differences
π ( , ~
between 1 x z )
and π ( , ~
2 x z )
as the value of an audit
( a V ), that is:
V a
where,
1 2
= π 1(
x,
~ z ) − π ~
2 ( x,
z ) = λσ
2
2 2
σ = σ z1
−
σ
2
z 2
From the definition of Va, we can clearly find that the
value of an audit is a function of risk premiums and that
the value of an audit depends on the riskiness of firm’s
end-of-period value and the entrepreneur’s aversion to
risk.
Observation: The value of an audit increases as the
2
riskiness of end-of-period value ( σ ) increase. Differen-
2
tiating with respect to σ , we obtain:
dV 1
= λ > 0
2
dσ
2
The preceding result indicates that an increase in firm’s
riskiness (for example, earnings management risk) is
likely to increase the incremental variance of firm’s endof-period
value and the incremental value of an audit.
Observe that if firm’s earnings management risk
increases, then the variance of firm’s end-of-period value
increases from
2
σ to
2
σ d (
(7)
(5)
(6)
2 2
σ d > σ
), and thus the
d
π (
entrepreneur’s risk premium increases form π to
d
π ≥ π
). Furthermore, the value of an audit increases
from Va to Vd and the value of an audit (Vd) is greater
than Va, that is:
d a
a
Vd = π − π > Va
= π − π
(8)

7310 Afr. J. Bus. Manage.
This observation implies that the riskier the firm’s end-ofperiod
value the greater is the incentives to hire an auditor
so as to avoid as much firm-specific risk as possible.
In turn, hiring an auditor suggests that the audited
accounting information is more useful for entrepreneur
than non-audited accounting information. Consequently,
the value of an audit increases as riskier payoffs
increases.
In that ST, PT, and borderline firms represent higher
earnings management risk in Chinese stock market, and
in that the value of an audit increases as the firm’s riskiness
increase, the following hypothesis can be advanced:
H1: The auditing value is positively associated with
earnings management risk.
H1a: There is a positive association between the auditing
value and the special treatment or particular transfer
designation.
H1b: There is a positive association between the auditing
value and reporting marginal ROE (0%, 1%).
H1c: There is a positive association between the auditing
value and reporting marginal ROE (6%, 7%) and (10%,
11%).
METHODOLOGY
Regression model and variable definitions
On the basis of previous studies (Simunic, 1980; Firth, 1997;
Crasewll and Francis, 1999; Abbott et al., 2003), we develop the
following model to test our hypothesis:
LNFEE = b0 + b1 STPT + b2 DELIST + b3 RIGHT6% + b4
RIGHT10% + b5 BIG4 + b6 TOP10 + b7 OPIN1+ b8 OPIN2+ b9
LNTA + b10 REC + b11 LEV + b12 AREA1 + b13 AREA2 + b14 AREA3
+
b15 AREA4
In this study, our dependent variable is the value of an audit.
Wallace (1980) suggested auditing is an economic service in
essence. In addition, economists have argued that the demand for
a product/service relies on the perceived customer utility (value),
and the customer perceived value is the maximum price the
customer will pay. That is, the higher the customer perceived value,
the higher the actual auditing value. This means that the perceived
customer value shall be the central role in audit pricing. Therefore,
it is reasonable to use audit fees to proxy the value of an audit. We
use natural log audit fees (LNFEE) to proxy the value of an audit.
The test variables of interest are STPT, DELIST, RIGHT6%, and
RIGHT10%. We use STPT, which is a dummy variable that take a
value of 1 if the listed firm is labelled as ST or PT shares and 0
otherwise. We code DELIST as 1 if a reported ROE is between 0
and 1%, and 0 otherwise. The variables, STPT and DELIST, are
designed to test H1a and H1b, that capture the effect of the delisting
buffer mechanism. The next dummy variables, RIGHT6%, and
RIGHT10%, are used to test H1c and capture the effect of earnings
management induced by regulatory requirements on ROE for rights
offering. RIGHT6% is coded 1 if a reported ROE is between 6 and
7%, and 0 otherwise. RIGHT10% is coded 1 if a reported ROE is
between 10 and 11%, and 0 otherwise. Positive signs are expected
for the test variables STPT, DELIST, RIGHT6%, and RIGHT10%.
Following Simunic (1980), Firth (1997), Crasewll and Francis
(1999), and Abbott et al. (2003), we control for individual client
characteristics through the following variables. LNTA is defined as
the natural log of total assets and is used to controls for auditee
size. The next four variables serve as client risk proxies. REC
represents the proportion of total assets in accounts receivable and
is used to control for client’s inherent risk in an engagement. LEV is
measured by total book value of debts to assets and is used to
capture the risk of a client failing, which potentially exposes the
auditor to loss. Large debts expose the auditor to significant audit
risk in the event of default. OPIN1 and OPIN2 measure the impact
of audit opinion on audit fees. We code OPIN1 as 0 when client
receive an unqualified opinion, and 1 otherwise. We code OPIN2 as
0 when client receive an unqualified opinion or an unqualified
opinion with explanatory notes, and 1 otherwise.
In addition to using the afore control variables, we include two
variables, BIG4 and TOP10, as additional controls to capture the
respective effects of auditor size on audit fees. Audit firms were
divided into Big 4 or non-Big 4. We further divide non-Big 4 into top
10 and non-top 10 domestic auditors because the major audit
suppliers in the China capital market are domestic auditors (Aini,
2004; Peng and Liu, 2008). The variable BIG4 is coded 1 if the
client’s financial statement is audited by Big 4 auditors and 0 otherwise.
TOP10 is coded 1 if the client’s financial statement is audited
by top 10 domestic auditors and 0 otherwise. Similar to prior
studies, we expect audit fees to be positively related to client size,
client risk, and auditor size.
Finally, there are likely to be variations in audit fees across clients
in different geographical location. Liu et al. (2003) and Chen et al.
(2007) suggested imbalanced economic development between
geographical regions results in different price level, wherein the
audit fee would be higher if the client is located in a more developed
region. To control for the impact of difference in economic
development level on audit fees, we include four dummy variables
(AREA1, AREA2, AREA3, and AREA4) based on the geographical
region in which the firm operates. Table 1 defines the dependent,
test and control variables in detail.
Sample selection and data collection
Our sample starts with the entire population of A-shares of listed
Chinese firms on the Shenzhen and Shanghai stock exchanges for
and covers a period of six years from 2001 to 2006. In view of the
regulatory nature of financial institutions, banking, finance, and
insurance firms, they are not included in the study. We exclude the
firms that issue both A- and B-shares; that issue both A- and Hshares
since they are different from A-share firms in terms of their
information environment, reporting requirements, and information
dissemination process. We also exclude the data in the listing year
due to distinguish our study from the IPO earnings management.
Furthermore, we drop the observations with missing values in
either dependent variable or independent variables. Finally, we
delete the observations with extreme variable values (0.5% at both
tails). After applying various filters, our final sample consists of
4,594 firm-year observations. Table 2 provides the distribution of
sample firms by year. They are not clustered in any particular year
and are well spread out.
Listed firms' audit fee data are obtained from the China Stock
Market and Accounting Research (CSMAR) Audit Opinion and Fees
database developed by the Shenzhen GTA Information Technology
Co, while financial data are collected from the China database of
the Taiwan Economic Journal (TEJ) and company financial reports.
EMPIRICAL RESULTS
Descriptive statistics
Descriptive data for the variables used in the study are

Table 1. Definitions of variables.
Liu and Cheng 7311
Variable Description
LNFEE Natural log of audit fees
STPT A dummy variable, 1 if the listed firm is designated as a special treatment or particular transfer firm by CSRC,
and 0 otherwise;
DELIST A dummy variable, 1 indicates 0 ≤ ROE ≤ 1%, and 0 otherwise;
RIGHT6% A dummy variable, 1 indicates 6% ≤ ROE ≤ 7%, and 0 otherwise;
RIGHT10% A dummy variable, 1 indicates 10% ≤ ROE ≤ 11%, and 0 otherwise;
LNTA Natural log of total assets;
REC Accounts receivable divided by total assets;
LEV Debt ratio (total book value of debt divided by assets);
OPIN1 A dummy variable, 0 if the listed firm receives an unqualified opinion, and 1 otherwise;
OPIN2 A dummy variable, 0 if the listed firm receives an unqualified opinion or an unqualified opinion with explanatory
notes, and 1 otherwise;
BIG4 A dummy variable, 1 if financial statements audited by Big 4 auditors, 0 otherwise;
TOP10 A dummy variable, 1 if financial statements audited by top domestic auditors, 0 otherwise;
AREA1 Geographical region, 1 if the auditee’s address is in Shanghai, Beijing, Tianjin, Guangdong or Zhejiang, and 0
otherwise;
AREA2 Geographical region, 1 if the auditee’s address is in Fujian, Jiangsu, Shandong or Liaoning, and 0 otherwise;
AREA3 Geographical region, 1 if the auditee’s address is in Heilongjiang, Jilin, Xinjiang, Hainan, Hubei or Hebe, and 0
otherwise;
AREA4 Geographical region, 1 if the auditee’s address is in Anhui, Sichuan, Guangxi, Chongqing, Hunan, Jiangxi, Inner
Mongolia, Henan, Shanxi, Yunnan, or Tibe, and 0 otherwise.
Table 2. Sample distribution by year.
Year 2001 2002 2003 2004 2005 2006 Total
Number of Obs. 719 781 800 809 804 681 4,594
Percent 15.65 17.00 17.41 17.61 17.50 14.84 100
provided in Table 3. The mean (median) audit fee paid is
RMB $ 418,714 (RMB $ 350,000). For the test variables,
on average, 10.93% of the sample firms (STPT) were ST
or PT firms. With respect to reported ROE, 10.73% of the
sample firms (DELIST) were between 0 and 1%, 8.51%
of the sample firms (RIGHT6%) were between 6 and 7%,
and 3.05% of the sample firms (RIGHT10%) were
between 10 and 11%. For the control variables, only
1.96% of the sample firms (BIG4) were audited by Big 4
auditors, while 41.73% of the sample firms (TOP10) are
audited by top 10 domestic auditors. With regards to the
geographical region where the firm operates, 33.46% of
the sample firms (AREA1) were located in the five more
developed Chinese regions (Shanghai, Beijing, Tianjin,
Guangdong or Zhejiang).
We also perform correlation analysis for all the relevant
variables (not reported here). The correlation matrix reveals
that audit fee (LNFEE) is positively correlated with
the test variables. Among independent variables, few
variables are highly inter-correlated (above 0.5). Variables
with high significant correlations include OPIN1 and
STPT (0.4849), and OPIN1 and OPIN2 (0.6925). These
statistically significant correlations, however, have not
created any serious problem of multicollinearity, as
regression diagnostics which are discussed further for the
main analyses do not indicate the existence of any such
problems.
Univariate analysis
Table 4 presents the univariate results of audit fee. The
mean and median value of audit fee (at RMB $ 489,812
and 406,452) for ST or PT firm (STPT) is significantly
higher than that (RMB $ 409,992 and 350,536) for non-
ST or non-PT firm. Similarly, the mean and median audit
fees of firms within reported marginal ROE (RIGHT6%,
RIGHT10%) are all significantly larger than that of firms
without reported marginal ROE. The mean (median) audit
fees of firms that receive dirty opinion (OPIN1, OPIN2)
are significantly higher than that of firms receiving clean
opinion. Also, the mean (median) audit fees of firms that
audited by Big 4 (BIG4) and top 10 domestic auditors
(TOP10) are significantly higher than that of firms audited
by non-Big 4 and non-top 10 domestic auditors. Finally,
the mean (median) audit fees of firms that were located in

7312 Afr. J. Bus. Manage.
Table 3. Descriptive statistics.
Panel A: Descriptive statistics for continuous variables
Variable name Mean Median Standard deviation 25 th percentile 75 th percentile
FEE 418,714 350,000 231857.38 300,000 500,000
LNFEE 12.8376 12.7657 0.4436 12.6115 13.1224
LNTA 13.8214 13.7951 0.8235 13.3281 14.3320
REC 0.1944 0.1657 0.1415 0.0875 0.2712
LEV 0.6953 0.4067 13.1242 0.2692 0.5559
Panel B: Mean, median, and frequencies for dichotomous variables
Variable name Mean Median
Number of firms
coded “1”
Number of firms
coded “0”
STPT 0.1093 0 502 4092
DELIST 0.1073 0 493 4101
RIGHT6% 0.0851 0 391 4203
RIGHT10% 0.0305 0 140 4454
OPIN1 0.1184 0 544 4050
OPIN2 0.0605 0 278 4316
BIG4 0.0196 0 90 4504
TOP10 0.4173 0 1557 2947
AREA1 0.3346 0 1537 3057
AREA2 0.1802 0 828 3766
AREA3 0.1667 0 766 3828
AREA4 0.2536 0 1165 3429
the more developed geographical region (AREA1) are
significantly higher, compared to other regions. To
summarize, results of univariate test of STPT, RIGHT6%
and RIGHT10% above are consistent with the prediction
that the auditing value increases as the firm’s earnings
management risks increase. However, results of univariate
test of DELIST are mixed. One possible explanation
is that Table 4 results based on univariate tests do not
adequately control for other factors affecting the auditing
value. Further, we return to this point where we use a
multivariate test to control other factor affecting the
auditing value, as well as, further exploring this result by
partitioning the sample according to firm’s incentives of
earnings management.
Multivariate regression results
Table 5 reports the multivariate regression results. As
shown in Table 5, a good linear fit is achieved in the
regression. The adjusted R-square for the fee models
range from 31.15 and 35.90%, which indicates a
moderate explanatory power of models. The F statistic is
statistically significant indicating meaningful relationships
between the dependent and independent variables. In
terms of regression diagnostics, all the variance inflation
factors (VIFs) values are less than 10 (not reported here),
indicating nonexistence of between independent variables
(Hair et al., 1998).
For the test variables of interest, the coefficient of
STPT is positive and highly significant (p < 0.01), thus
providing support for our H1a. The coefficient of DELIST is
generally positive and significant for models 2 and 4; but
not significant for models 1 and 4. The result partly
supports H1b. The variables RIGHT6% and RIGHT10%
are significantly positive (p < 0.01), thus providing support
for our H1c. These results indicate the higher the level of
earnings management risks, the greater variances of
firm’s end-of-period value, ceteris paribus, the greater
payoffs of risk premiums, and thus the higher value of an
audit. In other words, the value of an audit increases as
the earnings management riskiness increase. We believe
that by controlling for other factors affecting the auditing
value, multivariate tests provide more reliable evidence
than univariate tests reported in Table 4.
For the control variables, all are significant and in the
expected direction. The coefficients for LNTA, REC, LEV,
OPIN1, and OPIN2, are all positive and significant, indicating
that auditors tend to charge more for larger clients
(LNTA) and those with weaker financial condition (REC,
LEV, OPIN1 and OPIN2). The coefficients on BIG4 and
TOP10 are both positive and significant, which indicates
that Big4 can earn a significant audit fee premium compared
to non-Big4; domestic top 10 can earn a significant
audit fee premium compared to non-top10. The coefficients
on the geographical region variables (AREA1,
AREA2 and AREA3) are generally significant as well. The
results suggest that clients located in a more developed

Table 4. Univariate test.
Dummy variable
Liu and Cheng 7313
Audit fee
Mean Median Difference
D=1 (n1) D=0 (n0) D=1 (n1) D=0 (n0) t statistic |z|statistic
STPT 489,812(502) 409,992(4092) 406,452(502) 350,536(4092) 79,820***(7.3213) 55,916***(5.7508)
DELIST 402,663(493) 420,644(4101) 387,333(493) 350,553(4101) -17,981(1.6272) 36,780(0.5386)
RIGHT6% 472,968(391) 413,667(4203) 401,935(391) 350,514(4203) 59,301***(4.8493) 51,421***(5.6571)
RIGHT10% 467,736(140) 417,173(4454) 403,000(140) 350,608(4454) 50,563**(2.5422) 52,392***(4.3682)
OPIN1 474,538(544) 411,216(4050) 392,683(544) 350,557(4050) 63,322***(6.0037) 42,126***(4.7661)
OPIN2 499,597(278) 413,504(4316) 403,077(278) 350,582(4316) 86,093***(6.0239) 52,495***(5.0636)
BIG4 918,163(90) 408,734(4504) 705,000(90) 350,553(4504) 509,429***(21.6658) 354,447***(10.5348)
TOP10 503,067(1557) 358,894(2947) 444,458(1557) 339,474(2947) 144,173***(23.7770) 104,984***(21.3230)
AREA1 490,482(1537) 382,631(3057) 399,615(1537) 348,227(3057) 107,851***(15.2465) 51,388***(12.6535)
AREA2 404,249(828) 421,894(3766) 353,468(828) 350,697(3766) -17,645**(-1.9834) 2,771(0.4367)
AREA3 385,645(766) 425,331(3828) 349,839(766) 359,847(3828) -39,686***(-4.3328) -10,008***(2.9220)
AREA4 383,717(1165) 430,604(3429) 351,014(1165) 360,476(3429) -46,887***(-5.9858) -9,462***(4.0143)
regions have higher audit fees on average, than
clients in other regions.
Sensitivity analysis
We conduct a number of sensitivity analyses to
confirm the robustness of our results. First, to
further learn whether different regulatory environments
affects the auditing value, we partition the
sample into three groups based on firm’s return
on equity (ROE) and perform separate regressions
on the three samples We orderly define the
listed firms whose ROEs are within [0%, 6%], [6%,
10%] and [>10%] as Group I, Group II, and Group
III. Second, we vary the criterion for the two
variables DELIST and RIGHTS by incrementally
increasing the cut-off point of marginal ROE 1% at
a time to capture the effect of variation in our
definition of marginal ROE.
The results of our sensitivity analyses (not
reported here) show that DELIST begin to lose
significance when marginal profitability range was
set at 3% (above the requirement) and TOP10
and OPIN1 were in control. In addition, the adjustted
R-square for the model decreases gradually
(from 35.26 to 34.67%). Estimated coefficients on
other variables remained qualitatively similar
throughout the variation range from 2 to 5%.
Similarly, we find the same pattern when marginal
profitability range was set at 2% (above the
requirement) and BIG4 and OPIN1 were in
control.
Next, for Group II, RIGHT begin to lose significance
when marginal profitability range was set at
8% (above the requirement). The adjusted Rsquare
decreases gradually. Likewise, for Group
III, RIGHT begin to lose significance and the
adjusted R-square decreases gradually when
marginal profitability range was set at 14% (above
the requirement) and TOP10 was in control.
These results imply that our primary results
reported in Table 5 are robust to the sensitivity
tests. Also, our primary results are relatively
insensitive to variation in the definition of marginal
profitability range. What’s more important,
management appears to have carefully selected
profitability levels to report so as to maximize the
benefit of earnings management, which is
analogous to Healy’s (1985) compensation plan
research findings, that is, once the required profit
level is reached, any increase in reported ROE by
earnings management will increase its expected
cost, but not its expected benefit.
CONCLUSIONS AND IMPLICATIONS
The accounting profession in China has achieved
remarkable progress since its reestablishment in
the 1980s. An important issue on the Chinese
stock market is the role of auditing. Unlike the
advanced economies, the Chinese domestic audit

7314 Afr. J. Bus. Manage.
Table 5. Multivariate regression results.
Variable
Model 1 coefficient
(t-statistic)
Model 2 coefficient
(t-statistic)
Model 3 coefficient
(t-statistic)
Model 4 coefficient
(t-statistic)
Intercept 9.1368***(92.1258) 9.2618***(96.5212) 9.1482***(92.2135) 9.2737***(96.5751)
Test variable
STPT 0.2573***(12.5326) 0.2546***(12.8478) 0.2633***(13.0158) 0.2634***(13.4874)
DELIST 0.0137(0.7729) 0.0281*(1.6597) 0.0156(0.8780) 0.0302*(1.7600)
RIGHT6% 0.0992***(5.0227) 0.1105***(5.7976) 0.0972***(4.9257) 0.1080***(5.6706)
RIGHT10% 0.1419***(4.4598) 0.1276***(4.1538) 0.1409***(4.4274) 0.1263***(4.1082)
Control variable
LNTA 0.2429***(34.5575) 0.2311***(33.9175) 0.2421***(34.4386) 0.2303***(33.7780)
REC 0.1604***(3.9558) 0.1461***(3.7344) 0.1719***(4.2754) 0.1605***(4.1360)
LEV 0.0018***(4.2850) 0.0017***(4.2936) 0.0017***(4.1396) 0.0017***(4.1360)
OPIN1 0.0873***(4.4389) 0.0999***(5.2572)
OPIN2 0.1063***(4.1170) 0.1154***(4.6265)
BIG4 0.5587***(14.1603) 0.5595***(14.1755)
TOP10 0.1871***(23.4739) 0.1866***(23.4012)
AREA1 0.3543***(15.1443) 0.2816***(12.3472) 0.3546***(15.1528) 0.2822***(12.3608)
AREA2 0.2241***(8.9847) 0.2138***(8.8847) 0.2246***(9.0022) 0.2144***(8.9035)
AREA3 0.1901***(7.5455) 0.1820***(7.4859) 0.1888***(7.4927) 0.1806***(7.4230) ***
AREA4 0.2245***(9.3794) 0.2153***(9.3236) 0.2249***(9.3942) 0.2157(9.3316)
Observation 4594 4504 4594 4504
Adjusted R 2 0.3119 0.3590 0.3115 0.3581
F statistic 161.1827*** 198.8320*** 160.8753*** 198.0864***
market is characterized by newly formed audit
firms. Meanwhile, auditors are subject to economic
incentives and the discipline of markets and
regulations. This study is motivated by a need to
understand whether the auditing value is positively
associated with earnings management risk;
whether the security regulations of special treatment,
delisting, and right offerings affect the value
of an audit.
Based on a sample of 4,594 Chinese listed
firms, we find that the value of an audit increases
as earnings management risk increase. We also
find that results suggest that, 1) the value of an
audit is positively associated with earnings
management risk; 2) the regulation of special
treatment or particular transfer designation
positively affects the value of an audit; and 3) the
regulations of and delisting and right offerings
positively affects the value of an audit. These
results suggest that the unintended economic
consequences of different security regulations
stimulate the strong demand for audit service.
This study provides a unique test of the informational
value of audits in the Chinese stock market.
Our findings strongly suggest that the audit is
valued if the audit can reduce the noise and bias
of financial information resulting from uncertainty,
which is consistent with Wallace’s (1980), Balsam
et al. (2003) and Ferguson et al. (2004). In particular,
as society becomes more complex, decision

makers are more likely to receive unreliable information.
The most common way for investors to obtain reliable
information is to have an independent audit. Decision
makers can then use the audited information on the
assumption that is reasonably complete, accurate, and
unbiased, which is helpful to make a right decision. To
sum up, we provide evidence in favour of the informational
role of auditing. Audit can serve a very important
role in improving information credibility.
From the perspective of information hypothesis and risk
premium, this study investigates the auditing value in
China. Future research should further explore the
Chinese auditing value from the perspective of insurance
hypothesis and monitoring hypothesis.
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African Journal of Business Management Vol. 5(17), pp. 7316-7324, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM10.1296
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Impact of organizational commitment on job
satisfaction and employee retention in pharmaceutical
industry
Atif Anis 1 , Kashif-ur-Rehman 1 *, Ijaz-Ur-Rehman 2 , Muhammad Asif Khan 3 and
Asad Afzal Humayoun 4
1 Iqra University Islamabad, Pakistan.
2 Shaheed Zulfikar Ali Bhutto Institute of Science and Technology, Pakistan.
3 Credit Department, National Bank of Pakistan, Rawalpindi, Pakistan.
4 Foundation University Islamabad, Pakistan.
Accepted 27 January, 2011
The purpose of this study is to investigate the relationship between employee retention, job
satisfaction, perceived supervisory support and compensation by considering the organizational
commitment as mediating variable in pharmaceutical industry in Pakistan. For this purpose, primary
data collection method was used. A total of four hundred and fifty (450) questionnaires were sent to
employees of six pharmaceutical companies. Out of the total, three hundred and twenty (320) usable
questionnaires were included for data analysis. Structural Equation Modeling (SEM) was carried out by
the means of AMOS 18.0 for model testing purpose. The results signify that positive and significance
relationship exists between compensation, Supervisory Support, and organizational commitment. The
results further conclude that organizational commitment has strong and positive relationship with
employee job satisfaction and employee retention.
Key words: Compensation, supervisory support, organizational commitment, employee satisfaction, employee
retention.
INTRODUCTION
Resource based view (RBV) is now one of the most
important concept for the organizations (Barney and
Wright 1998; Holland, Sheehan and Cieri 2007). According
to this concept there are three types of resources
that work as pillar for the organization. These are organizational
capital, human capital, and physical capital. The
importance of human capital is increasing because it can
give the competitive edge to the organizations due to its
uniqueness (Holland et al., 2007). The importance of
human capital is on the increase, so the importance of
attracting and retaining the employees this argument is
considered because of competitive advantage which a
firm gets due to its employees (Holland et al., 2007). To
retain the employees Human Resource (HR) department
*Corresponding author. E-mail: drkashif@iqraisb.edu.pk
becomes active and make policies for employee
betterment such that employee would be satisfied with
the organization and stay with the firm for longer time.
This shows that it is not just retention of employees but
also retention of valued skills (Acton et al., 2003). If an
organization retain its employees this will improve the
communication among employees and improve their
commitment and workforce support for organization.
The birth rate in the countries is decreasing therefore
labour becomes the concern for the organizations in the
near future. The number of employees leaving the
organizations is more than the employees joining. The
war of talent will start in the near future because of the
shortage of labour (Ferguson and Brohaugh, 2009;
Holland et al., 2007). The firms are trying to attract and
retain the employees. The talented people always have
options in their career so that this is the concern of firms
to keep them (Ferguson and Brohaugh, 2009). It is the

primary apprehension of the firm to acquire and manage
the human capital in the way that it supports the business
plan that is necessary for the firm. As the human capital
is the main component of any organization (Kennedy and
Diam, 2010; Molina and Ortega, 2003; Acton et al., 2003;
Chapman, 2009; Holland et al., 2007), therefore, the firm
has to use his human capital in the way that they can
perform the job efficiently by using their core skills. In this
context, firm have two options; whether to hire new
employees, train them and make them accustomed to the
working conditions and the environment of the firm or try
to retain the existing employees those who are aware
with the company policies, environment and working conditions
(Molina and Ortega, 2003). It is a strategy adopted
by the organization to keep its high profile employees for
longer period and for better performance (Gberevbie,
2010). If organization fails to keep competent employees
and they have dissatisfied employees with them it will
hamper their productivity and quality (Chiboiwa, Samuel
and Chipunza 2010). Retention is crucial especially for
those employees who are related with the operations.
Organization must reduce the turnover of their employees
because it put burden on the organization in terms of
money and human resource (Samuel and Chipunza,
2009).
Employer has to bear the cost when an employee
leaves the organization, because of loss of human capital
and hiring of new employees (Lockwood, 1999). The cost
of an organization has to bear in case of leaving of an
employee is almost equal to more than one year salary
and benefits of the employee. It means it has a significant
impact on economic condition of the organization. It is not
only the loss of money and resources also the loss of
knowledge and experience for an organization which
hampers the performance of the organization (Ramlall,
2004; Acton et al., 2003). The dissatisfaction with the job
assigned is an important determinant of the employee’s
failure rates to keep them intact with the present job. The
work structure is major determinant of job satisfaction
and commitment of employees with their jobs (Mulinge
and Muller, 1998). The job satisfaction also affect the
quality of the services employees are providing
(Crossman and Abou-Zaki, 2003). It furthermore relates
to the turnover and the position assigned to the employees
on their return, as well as the accuracy of their
expectations and influences their job satisfaction (Vidal et
al., 2007).
Research on compensation evidently shows a relation
between the rewards a firm offers and those individuals
that are fascinated by the compensation into working for
the firm, and those employees who will continue to work
for the industry. In recent years, the compensation got
the importance due to the economic conditions of employees
as well as the organization. The compensation is
very crucial component for retaining of employees and for
job satisfaction. It comprises on the largest part of the
employee retention procedures. Organizational
Anis et al. 7317
commitment is loyalty to the organization and mobilization
of all employees in the development of its goals,
purposes, and infrastructure (Kim et al., 2005). It is
discussed under three heads affective commitment, normative
commitment and continuance commitment (Aube,
Rousseau and Morin, 2007). Affective commitment
describes the emotional attachment and involvement of
an individual with an organization, continuance means
perceived cost of leaving organization and normative is
perceived cost to remain in the organization (Meyer et al.
2002). The organizational commitment is correlated with
the job satisfaction and both are important factors for
employees leaving their job (Hussami, 2008).
This study analyzes the impact of supervisory support
and compensation on the job satisfaction and employee
retention while using the organizational commitment as a
mediating variable in medicine industry in Pakistan. This
study also shows the relationship between dependent
variables, job satisfaction and employee retention. This
study also depicts that how much the job satisfaction
influence the employee retention. Previous researchers
describe the relationship between organizational
commitment and employee retention or job satisfaction
but no study covers the relationship with both as
dependent variables.
LITERATURE REVIEW
Job satisfaction
Job satisfaction is a topic which is concerned by both the
people, those who are working in organizations and for
the people who study them. It is the variable which is
studied most frequently in organizational behaviour
research, and it is also a fundamental variable in both
research and theory of organizational experience range
from job design to supervision (Hong et al., 2005). As Job
satisfaction is a major concern for the organizational
research. On the other hand organizational performance
and employee satisfaction are also the key components
which are affected by this (Willem et al., 2007). What
employee feels and perceived about its job and what are
their experiences on work, does they feel positive or
negative about job, this all relates to job satisfaction (Kim
et al., 2005; Willem et al., 2007). Job satisfaction is the
extent to which the employee is satisfied with his present
work due to how many his needs and wants satisfied
(Finn, 2001). Job satisfaction can also be explained as
‘‘the agreeable emotional condition resulting from the
assessment of one’s job as attaining or facilitating the
accomplishment of one’s job values’’ (Yang, 2009).
Job satisfaction in traditional model mainly focuses on
what an individual feels about his/her job or pleasure
feeling about job (Hussami, 2008; Crossman and Abou-
Zaki, 2003). Job satisfaction and dissatisfaction not only
depends on the nature of the job, it also depend on the

7318 Afr. J. Bus. Manage.
expectation what’s the job supply to an employee
(Hussami, 2008). Lower convenience costs, higher organizational
and social and intrinsic reward will increase job
satisfaction (Mulinge and Mullier, 1998; Willem et al.,
2007).
Job satisfaction is complex phenomenon with multi
facets (Fisher and Locke, 1992; Xie and Johns, 2000), it
is influenced by the factors like salary, working environment,
autonomy, communication, and organizational
commitment (Lane, Esser, Holte and Anne, 2010; Vidal,
Valle and Aragón, 2007; Fisher and Locke, 1992; Xie and
Johns, 2000). An important aspect of job satisfaction is
that when people have to make a choice where they want
to work it also influences their intent to stay with the
organization at current position (Lane, Esser, Holte and
Anne, 2010). If employees are more satisfied with their
job it will enhance their ability of creativity and productivity,
it is also directly correlated with the customer
satisfaction (AL-Hussami, 2008). In the past much of
work has already been done by the researchers on the
organizational commitment and the job satisfaction and
they also developed the relationship between job satisfaction
and the organizational commitment (Yang, 2009;
Lane et al., 2010; Namasivayama and Zhaob, 2007) that
job satisfaction leads to organizational commitment.
There is also compelling evidence to the organizational
commitment impact on job satisfaction (Namasivayama
and Zhaob, 2007). As previous researches showed
relationship between organizational commitment and job
satisfaction (Yang, 2009). Wong et al. (2001) concluded
that if there is lack of satisfaction and commitment in an
organization it would increase the turnover intention of
employees. According to Al-Hussami (2008) the low
wages and less job satisfaction are the major components
that are affecting the retention. The supervisory
support, lack of respect and motivation are also the
attributes of the job dissatisfaction.
The previous analysis showed that there is positive
correlation existed between job satisfaction and organizational
commitment (Schwepker, 2001; Namasivayama
and Zhaob, 2007; Al-Hussami, 2008; Wong et al., 2001).
While in individualistic culture there is greater probability
that the job satisfaction influence organizational commitment
greatly (Wong et al., 2001). It might be possible
that employee is not satisfied with his/her job but remain
loyal to their organizations. Generally, if an employee is
satisfied with supervisor, coworkers, pay policies and
future promotion s/he will be committed to their organizations
and satisfied with their jobs (Reed, Kratchman and
Strawser, 1994). Wong et al. (2001) described that there
are three relationships among organizational commitment,
job satisfaction and employee turnover intentions,
1) job satisfaction impact on organizational commitment
and in the end this will affect employee turnover, 2) job
satisfaction used as a mediator between organizational
commitment and turnover intention, 3) impact of job satisfaction
and organizational commitment on each other and
their affect on turnover intention. This study mainly
focuses on the organizational commitment impact on job
satisfaction and employee retention. Both the organizational
commitment and the job satisfaction are interrelated,
but of discernible, attitudes. Organizational commitment
is supposed to provide the people with constancy,
thoughts of belonging and durable (Lane et al., 2010;
Reed et al., 1994) than job satisfaction because on the
other hand job satisfaction is associated with immediate
work environment (Reed et al., 1994).
Compensation
Different people interpret compensation differently. In this
paper compensation, reward, recognition, and wages are
terms used in different situations (Zobal, 1998). The compensation
is defined by American Association is “cash
and non-cash remuneration provided by the employer for
services rendered” (ACA, p. 9). In organization’s point of
view, the retention of employees is the major concern
and compensation and benefits is one of the best initiatives
which a company can acquire to retain employees.
The compensation includes salary and wages, bonuses,
benefits, prerequisites, stock options, bonuses, vacations,
etc. While setting up the packages, the following
components should be kept in mind. This compensation
and reward system also increases employee performance
(Deckop et al., 2006; Moncarz et al., 2009;
Zsidisin et al., 2003). The financial and non-financial
compensation are given to employees for accomplishment
of desired goals and against their behaviour.
Reward can be spontaneous and formal. The pay for
performance is the form of reward which is given on
performance based (Zobal, 1998).
Compensation is very valuable tool for retention and
turnover. It is also a motivator for an employee in commitment
with the organization which in result enhances
attraction and retention (Zobal, 1998; Moncarz et al.,
2009; Chiu et al., 2002). It also works as communicator
when it is given to employee against his services which
shows how much an employee is valuable for its organization
(Zobal, 1998). As the important components of
compensation are base salary, merit pays, discretionary
rewards or bonuses, which attract best employees (Chiu
et al., 2002). Top employees are motivated by doing
high-quality work. Actually, all employees are motivated
to do good work. No one awaken in the morning and
thinks, “I want to be unsuccessful at my job today.”
However, top performers in any organization have a
tendency to have the talents you’re looking for and are
basically motivated (Carroll, 2009). Compensation also
shapes the culture of an organization. Culture may be
individualistic or collectivistic; it depends upon the organizational
characteristics and members of the organization
(Kuhun, 2009; Zobal, 1998). Compensation is one of the
most important tools for attracting and retaining

employees. It is used to attract the potential candidates,
because applicants want to be aware of it while applying
for vacancy (Kuhun, 2009; Boyd, 2000; Zobal, 1998; Chiu
et al., 2002; Moncarz et al., 2009; Lawler, 1994). Those
organizations which have a high-wage system will have
better recruitment and retention of employees as
compare to others. Efficient wage system influences the
employees for longer retention, because if an employee
gets better reward internally he would like to stay until his
self-interest fulfilled there. Employee can switch if gets
better opportunity in the external environment (Moncarz
et al., 2009; Shaw et al., 1998).
Organizational commitment
Organizational commitment is a “psychological stabilizing
or helpful force that binds individuals to courses of action
relevant” to the organization (Carrie`re and Bourque,
2009). Individuals with higher levels of organizational
commitment have a sense of belonging and identification
with the organization that increases their desire to pursue
the organization's goals and activities, and their willingness
to remain a part of the organization (Meyer and
Allen, 1991). Moreover, organizationally committed
individuals are far less likely to engage in absenteeism
and turnover (Golden and Veiga, 2008).
Initially conceptualized as a one-dimensional construct,
organizational commitment is now known to be
multidimensional in nature. The most common forms of
organizational commitment studied and reported on in the
academic literature are affective (emotional attachment to
the organization), continuance (perceived costs associated
with leaving the organization) and normative (feelings
of obligation towards the organization) (Carrie`re and
Bourque, 2009; Rego and Cunha, 2008). Each of these
components contributes to strengthening the likelihood
that the employee will remain in the organization, but the
nature of each mind-set differs from the others.
Employees with a strong affective bond remain because
they want to do so. Those with strong continuance commitment
stay because they feel they have to. Normatively
committed employees remain because they feel they
ought to (Rego and Cunha, 2008; Parish Cadwallader,
Busch, 2008). This means that a given employee can be
affectively, normatively and instrumentally committed to
the organization.
According to Meyer and Allen (1991) the affective
commitment (AC) “refers to the employee’s emotional
relationship to, recognition with, and participation in the
organization” (employees stay with a firm because they
want to), continuance commitment (CC) “refers to a
consciousness of the costs connected with leaving the
organization” (employees stay with a firm because they
need to), and normative commitment “reflects a feeling of
obligation to continue employment” (employees stay with
a firm because they ought to). These three components
of commitment help to define the overall organizational
commitment.
Supervisory support
Anis et al. 7319
The mentoring is used for development-orientation
(Scandura and Williams, 2004). When a supervisor
provides mentoring, the relationship affects the protégés
skill development and intentions to remain with the
employer (McManus and Russell, 1997). On the other
hand non-supervisory mentor may increase mentee’s
confidence by providing access to outside organization
(Scanduraa and Williams, 2004). The immediate supervisor
support is vey important in organizational change.
Although the support of supervisor is not very crucial in
satisfaction but it has positive impact on satisfaction
(Griffin, Patterson and West, 2001). According to
Chakrabarty, Oubre, and Brown (2008) “perhaps the
finest way in which supervisors can portray himself as a
role model is to personally demonstrate proper techniques
so that employee could understand how job should
be done.” Through this way, the skills of subordinate can
be enhanced. The supervisor has positive impact on
developing skills on-the-job performance work attitudes
and career expectation of protégés. He/she also has
control on work assignments (Scanduraa and Williams,
2004). In case of lower quality of relationships between
subordinate and supervisors may exert pressure on
individual which decreases his efficiency for work and
enhances unwillingness to work hard because of extra
control or simply marginalize and ignore the subordinate
(Golden and Veiga, 2008).
Supervisors and subordinates share valuable information,
while they are interacting with each other. Supervisor
may engage in supervising or other socio-emotional
relations on the other hand subordinate by making extra
effort with greater dedication and completing supervisor’s
goals and by displaying organizational commitment. The
exchanges of valued resources will payback both of them
in the form of benefits (Golden and Veiga, 2008). In
organizing the working environment supervisor is a
crucial component of an organization it is also the key
component to pass on the information to the employees
(Patterson, Griffin, West, 2001). Supervisors also
exchange the positional resources with the subordinate,
which include material and non-material things (Golden
and Veiga, 2008). Theory recommends that, as philosophy
of reciprocal relation affect employees’ observation
of their organization, thinking of reciprocal relation will
also relate the interpersonal relationships that employees
develop with their supervisors (Smith, 2005). Employee
will be more committed to the organization and also more
committed with the supervisor if he/she perceives that the
supervisor will be supportive (Shanock and Eisenberger,
2006; Smith, 2005). Literature that supports social and
organizational culture indicate that whenever subordinate
is properly supported by supervisor this will generate
positive outcomes both for organization and employee

7320 Afr. J. Bus. Manage.
Compensation
Supervisory
Support
Figure 1. Research model.
(Shanock and Eisenberger, 2006). It is also beneficial for
supervisor; because more competent and more supportive
the supervisor is, the more likely employee and
supervisor retain their jobs (Smith, 2005). Longer the
employee retains the relationship between employee and
supervisor develops and prior studies also support this
because supportive supervision enhances impact on both
organizational commitment and job retention (Smith,
2005).
Hypotheses:
H1: Compensation has positive relationship with the
organizational commitment.
H2: Supervisory support has positive relationship with the
organizational commitment.
H3: Organizational commitment has positive relationship
with the job satisfaction.
H4: organizational commitment has positive relationship
with employee retention.
H5: Job satisfaction has a positive relationship with
employee retention.
The summary of the hypotheses is given in Figure 1. This
study is useful for the organizations that they could retain
their valuable employees and could excel and get
competitive advantage in the market with these crucial
and valuable employees that are the assets for the
organizations.
So many studies already conducted on employee
retention but this study describes the new relationship
between all these variables. Here, job satisfaction and
employee retention both are considered as dependent
variable and this paper also explain the relationship
between these two variables, while using organizational
commitment as mediating variable between dependent
variables and independent variables.
Organizational
Commitment
METHODOLOGY
Sample and Data
Job Satisfaction
Employee
Retention
The data was collected from the Pharmaceutical Industry of
Pakistan through survey questionnaire. The survey was used to
analyze the job satisfaction and employee retention in this particular
industry. Total four hundred and fifty (450) questionnaires were personally
administered to frontline employees of six pharmaceutical
companies. Out of total, three hundred and twenty (320) usable
questionnaires were included for data analyses. The survey utilized
the non-probability sampling method of frontline employees of
organizations.
The survey consisted of thirty four (34) questions. All the questions
were measured at 5-point Likert Scale. Through this survey
data regarding independent variables, supervisory support and
compensation, dependent variables job satisfaction and employee,
retention and mediating variable organizational commitment is
collected to check the employee behavior in pharmaceuticals
industry. The questions were adapted from previous studies in
other to main the content and construct validity of the survey
instrument.
Measure
The dependent and independent variables were measured at 5-
point Likert scale. The organizational commitment was measured
by eighteen items used by Vandenberghe et al. (2004). These
items are widely used for measuring organizational commitment.
The scale used to measure the supervisory support consisted of
five items and it was adapted from the study of Baptiste, (2008).
The chosen scale to assess compensation was adapted from
Moncarz et al. (2009) and Chiu et al. (2002).
The five-item scale was used to measure compensation practices
and employee perception towards an organization. The job
satisfaction was measured at eight items used by Baptiste, (2008).
To assess the employee retention the items were adopted from
(Milman, 2003).
RESULTS
The model is tested using the structural equation

0.79
0.91
0.14
0.08
0.18 0.39
Figure 2. Estimated Path Diagram of Research Model.
COM= Compensation; SS= Supervisory Support; OC= Organizational Commitment SAT=Job
Satisfaction; ER= Employee Retention
modeling techniques. The path diagram of the estimated
research model is shown in Figure 2. Structural equation
modeling is a very useful technique in social sciences for
analysis. This modeling is also known as causal
modeling, or path analysis, which hypothesizes causal
relationships among variables and tests the causal
models with a linear equation system. Causal models can
involve either manifest variables, latent variables, or both.
It is close to casual relationship that is common in social
sciences theorizing.
The results of above hypotheses test of the relationship
between constructs including compensation, supervisory
support (independent variables), organizational commitment
(mediating variable), and job satisfaction and
employee retention (dependent variables) are shown in
Table 1. Table 1 shows the Beta value is 0.144 between
COM and OC and the relationship is evident from the
analysis that if there is one degree change in COM there
would be 14.4% change in OC. The value of Beta
between SS and OC is 0.184 which shows that if there is
one degree change in SS it brings 18.4% change in OC.
The value of Beta between OC and SAT is 0.727 which
shows that if there is one degree change in OC it brings
72.7% change in SAT, The results in Table 2 further
signifies that Beta value between OC and ER is.3854
that’s depicts that if there is one degree change in OC it
brings 38.54 change in ER whereas, employee satisfaction
(SAT) accounts 20.16% change in employee
retention The analysis highlights the relationships
between COM, SS, OC, SAT, ER are positive and
statistically significant (P

7322 Afr. J. Bus. Manage.
Table 1. Hypotheses testing based on Regression weights.
Paths Estimate S.E. C.R. P Label
OC

organization. It means that satisfied employee is more
loyal to its organization and therefore employee is
unlikely to switch job and work hard for the organization.
This study is carried out in multinationals organizations in
Pakistan, but it can be generalized if number of industries
as well as number of respondents increased. Recommendation
for future research is carry out this study in
other sectors of the economy by incorporating more
sample size .The purpose of such study would be to
resolve how job satisfaction and employee retention is
viewed by the employee of other industries settings
compared to the employee in this study. Further, their
impact on firm performance can be observed because
the ultimate objective of the firm is to increase the
productivity and performance.
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African Journal of Business Management Vol. 5(17), pp. 7325-7334, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM10.1414
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Optimal order quantity under advance sales and
permissible delays in payments
Mei-Liang Chen 1 and Mei-Chuan Cheng 2 *
1 Department of Marketing and Logistics Management, Hsin Sheng College of Medical Care and Management, Longtan,
Taoyuan 325, Taiwan.
2 Department of International Business, Hsin Sheng College of Medical Care and Management, Longtan,
Taoyuan 325, Taiwan.
Accepted 21 January, 2011
In order to attract more customers, it is a common practice for retailers to provide advance sales, for
example, Maxim’s Bakery in Hong Kong, Amazon.com, Movies Unlimited and Toys R Us. Similarly,
suppliers often allow their retailers a permissible delay in payment in order to increase sales. Advance
sales and trade credit policies provide numerous benefits for companies, including gaining additional
discriminative customers and increased profit due to interest earned from payments received from
committed customers prior to the start of the regular selling period. This article establishes an
inventory model for retailers who simultaneously receive a permissible delay in payments from
suppliers while offering advance sales to customers. We first present the model and then provide a
simple method of obtaining the optimal order quantity and advance sales discount rate which achieves
the maximum total profit per unit of time for the retailer. Finally, several numerical examples are used to
illustrate the procedure.
Key words: Inventory, advance sales, trade credit, advance sales discount rate.
INTRODUCTION
Permissible delay is a common phenomenon in retailing,
where a supplier permits the retailer a fixed time period to
settle the total amount owed. This provides an advantage
to the retailer as they can earn interest on the accumulated
revenue received during the period of permissible
delay. At the same time, permissible delay can also
confer benefits to the supplier since the policy may attract
new customers who consider it to be a type of price
reduction.
Permissible delay in payments has been widely discussed
in the literature. Chang et al. (2003) established
an economic order quantity (EOQ) model for deteriorating
items, in which the supplier provides a permissible delay
to the purchaser if the order quantity is greater than or
equal to a predetermined quantity. Ouyang et al. (2006)
developed a general EOQ model with trade credit for a
retailer to determine the optimal shortage interval and
*Corresponding author. E-mail: rosma725@gmail.com.tw.
replenishment cycle.
Goyal et al. (2007) introduced a new concept where the
supplier charges the retailer progressive interest rates if
the retailer exceeds the period of permissible delay, and
established necessary and sufficient conditions for the
unique optimal replenishment interval. Ho et al. (2008)
proposed an integrated inventory model with retail price
sensitive demand and trade credit financing. Chang et al.
(2009b) formulated an integrated vendor–buyer inventory
model with retail price sensitive demand, where the credit
terms are linked to the order quantity. Chen and Kang
(2010) developed integrated models with permissible
delay in payments for determining the optimal replenishment
time interval and replenishment frequency. There
are also many relevant articles related to trade credit,
including Goyal (1985), Dave (1985), Mandal and
Phaujdar (1989), Aggarwal and Jaggi (1995), Hwang and
Shinn (1997), Jamal et al. (1997), Liao et al. (2000),
Sarker et al. (2000), Teng (2002), Huang (2003), Chang
and Teng (2004), Chung and Liao (2004), Ouyang et al.
(2005), Teng et al. (2005) and Chang et al. (2009a) and

7326 Afr. J. Bus. Manage.
the research that they cite. However, none of the models
presented in the above literature incorporates advance
sales.
Along with environmental transformation and market
competitiveness enhancement, advance sales have
gradually become one of the newest sales models.
Advance sales policies are widely used by retailers today,
including Maxim’s Bakery in Hong Kong, Amazon.com,
Eslitebooks.com, Movies Unlimited, Toys R Us and
Electronics Boutique. Customers who accept advance
sales must prepay the entire discounted purchase
amount prior to the regular sale season. Alternatively,
customers can purchase the product at the regular price
during the regular sale season.
Models have since been developed which incorporate
advance sales policies. You (2006) addressed a service
inventory control problem in which a firm sells products
through an advance booking system, with the aim of
optimizing product price to maximize the total expected
profit.
You (2007) developed an advance sales system where
a firm sells perishable inventory using a reservation
system during the sales season over a limited planning
time interval. You and Wu (2007) investigated the problem
of ordering and pricing over a finite time planning
horizon for an inventory system with advance sales and
spot sales. They sought to develop a solution procedure
to determine the optimal advance sales price, spot sales
price, order size and replenishment frequency. Tsao
(2009) considered retailer’s promotion and replenishment
policies with an advance sales discount under the
supplier’s and retailer’s trade credits and presented an
algorithm to simultaneously determine the optimal
promotion effort and replenishment cycle time.
In this paper, we develop an inventory model where the
supplier offers trade credit and the retailer provides
advance sales. It is conceivable that customers who are
unwilling to buy the product at the regular price may
choose to do so with the price discount. Thus, by
providing advance sales, the retailer is likely to gain
additional demand during the advance sales period.
Moreover, incorporating advance sales not only reduces
financial risks, it also increases interest earned from
payments received from committed orders prior to the
regular sale season. Our aim is to determine the optimal
advance sales discount rate and the optimal length of the
regular selling period in order to maximize the total profit
per unit of time.
Notation
The mathematical model in this paper is developed on
the following notation
p : Unit selling price
c : Unit purchase cost
h : Unit holding cost per unit of time excluding
interest charges
s : Ordering cost per order
I : Interest charges per $ investment in stocks per unit
c
of time
I e : Interest earned per $ per unit of time
M : Permissible delay in settling account
t : Advance selling period
p
: Advance sales discount rate (all products are % off
during the advance sale period) with 1 c / p , a
decision variable
*
: Optimal discount rate during the advance sale period
T : Regular sale period, a decision variable
*
T : Optimal regular sale period
Z ( T,
) : total profit per unit time, which is a function
of T and
*
Z : maximum total profit per unit of time, i.e.,
*
Z
Z(
T
Assumptions
*
*
, )
The mathematical model in this paper is developed on
the following assumptions
1. The replenishment occurs instantaneously at an infinite
rate.
2. Shortages are not allowed.
3. Customers who accept the advance sales offer must
pre-pay for the committed orders prior to the start of the
regular sale period.
4. No order cancellation or refund is permitted.
5. The demand rate, D, depends on the selling price, p ,
and the relationship between demand and price is linear
and given by
D ( p ) = a – b p
where a and b are positive constants. We also assume
that the demand rate is always positive. That is, p < a /
b.
METHODOLOGY
The proposed model incorporates both advance selling and
permissible delay policies. The supplier permits the retailer a fixed
time period to settle the total account, while the retailer allows
advance sales that induces customers to commit to their orders at a
discounted price prior to the beginning of the regular sale season.
Figure 1 displays the behavior of reservation level and inventory
level over time. In the advance sale period ( 0,
t p ] , all products are
% off. The reservation level changes at a rate of D( p p)
.

Inventory Level
D ( p ) T
0
D ( p � � p ) t
p
Figure 1. Advance sales offered by the retailer.
t p
t p � T
Fig . 1 advance sales offered by the retailer .
Moreover, during the period from time tp to tp + T, the inventory level
changes at a rate of D(p).
The objective here is to maximize the retailer’s total profit per unit
of time. The total profit per unit of time of the retailer consists of the
following elements:
1. sales revenue per unit of time
= { ( 1�
� ) p D ( p � � p)
t p � p D ( p)
T } ( t p � T )
= { ( 1�
� ) [ a � b(
1�
� ) p]
t � p ( a � b p)
T } ( t � T ) ,
p p
p
2. Cost of placing an order per unit of time = ( t T )
s p � ,
3. cost of purchasing per unit of time
= { c D ( p � � p)
t p � c D ( p)
T } ( t p � T )
= { c [ a � b ( 1�
� ) p]
t p � c ( a � b p)
T } ( t p � T ) ,
4. cost of carrying inventory (excluding interest payable) per unit of
time
2
= h D(
p)
T [ 2 ( t p � T)
]
2
= h ( a � b p)
T [ 2 ( t p �T
) ] ,
5. Interest payable per unit of time for the items in stock; and
6. Interest earned per unit of time.
Regarding interest payable and earned (i.e., costs of (e) and (f)), we
have two possible cases based on the values of T and M, namely,
(i) T � M and (ii) T � M . These two cases are depicted in
Figure 2.
Case 1: T � M
In this case, the permissible payment time expires at or after the
time at which the inventory is depleted completely. Thus, the retailer
Chen and Cheng 7327
Time
pays no interest for items in inventory. However, the retailer utilizes
the sales revenue received during both the advance sale period
and the permissible period to earn interest. Therefore, the interest
earned per unit of time is:
2
p I e{
D(
p �� p)
t p / 2 � D(
p ��
p)
t p M � D(
p)
T
� ( M � T ) D ( p)
T}
( t p � T )
=
2
p I e{
[ a � b(
1�
�)
p]
t p / 2 �[
a � b(
1�
�)
p]
t p
� ( M � T ) ( a � b p)
T}
( t p � T )
Case 2: T � M
M � ( a � b p)
T
The retailer earns interest on sales revenue received during the
advance sale period and the permissible period. Thus, the interest
earned per unit of time is:
2
2
2
/ 2
2
p I e { D(
p �� p)
t p / 2 � D ( p ��
p)
t p M � D(
p)
M / 2}
( t p �T
)
2
p e
p
p
p
2
= I { [ a �b ( 1�
�)
p]
t / 2 �[
a �b
( 1�
�)
p]
t M � ( a �b
p)
M / 2}
( t �T
)
.
On the other hand, after paying the total purchase amount to the
supplier, the retailer still has some inventory on hand. Hence, for
the items in inventory, the retailer faces a capital opportunity cost.
The opportunity cost per unit of time is:
2
cI cD(
p)
( T � M ) [ 2 ( t p �T
)] �
2
cI c ( a � b p)
( T � M ) [ 2 ( t p �T
)] .
Therefore, the total profit per unit of time of the retailer is:
/ 2

7328 Afr. J. Bus. Manage.
Z(
T,
where
Z
1
( a ) T = M
Inventory level
D ( p ) T
0
D ( p � � p ) t
p
t p
t p � T t p � M
( a � b p ) M
Figure 2. Graphical representation of inventory system.
if T � M ,
� (1)
( T , � )
if T � M ,
t p t M t p � T
p �
.
Time
Time
� [ a � b(
1�
� ) p]
[ ( 1�
� ) p � c � p I eM ] ��[
b(
p � c)
� a
� b ( 1�
� ) p]
� pT
� s � h ( a � b p)
T
2 2
� pI e[
a �b(
1��
) p]
( t p � T ) 2
2
p I ( 2M
�T
) T 2�
( t �T
)
2
/ 2
�� b . (2)
e
p

and
Z 2 ( T , )
[ a b(
1
) p]
[ ( 1
) p c p I eM ] [
b(
p c)
a
2
b ( 1
) p]
pT
s h ( a b p)
T
/ 2
2
2
cI c ( a b
p)
( T M)
2 pI
e[
a b(
1
) p]
( t p 2M
T)
2
I ( a b
p)
M 2
( t T
)
p e
p
. (3)
Note that Z 1(
M , ) Z 2 ( M , ) . Hence, for fixed ,
Z ( T,
) is continuous at point T M .
RESULTS
Here, we present the solution procedure and determine
the optimal solution to the two cases in discussed earlier.
*
*
Our aim is to determine T and which maximize the
total profit per unit of time Z ( T,
) . Firstly, for fixed T ,
we take the first-order partial derivative of Z ( T,
) with
respect to and derive
Z ( T,
) Z 1(
T,
) Z 2 ( T,
)
t
p p
p
t p b I e p ( t 2M
)
2b
p
a 2b
p bc
. (4)
T
2
Further, we let
b I e p ( t p 2M
)
f ( ) 2b
p
a 2b
p bc
, (5)
2
and find that
d f ( )
2b
p 0 . (6)
d
Therefore, f ( ) is a strictly decreasing function for
[
0,
1
c / p]
. Moreover, we have
b I e p ( t p 2M
)
f ( 0)
(
a bc)
2b
( p c)
c , (7)
2
and
2
Chen and Cheng 7329
Equations (7) and (8) become
f ( 0)
A
2b(
p c)
c and f 1 c / p
A
,
respectively. We then derive the following result:
Lemma 1: For any given T,
*
(a) if A 2b( p c)
c , then 0 ;
*
(b) if A 0 , then 1
c / p ;
(c) If 0 A 2b(
p c)
c , then
*
[ p ( 4 2I
M I t ) 2bc
2a]
( 4b
p)
.
b e e p
The proof is given in Appendix A.
*
Note that 0 implies that customers are willing to
pay for their orders at the regular price prior to the
beginning of the regular sale season. In addition,
*
*
1
c / p ( ( 1 ) p c ) indicates that the retailer
gains no profit during the advance sale period since the
optimal unit selling price for the advance sale
*
period, ( 1
) p , is the same as the unit purchase price,
c . In reality, it is unlikely for either of these two cases to
occur. Hence, we focus on the case in which the optimal
discount rate is
*
[ p ( 4 2I
M I t ) 2bc
2a]
( 4b
p)
(that
b e e p
*
is, 0 and
*
( 1 ) p c ), which means that
customers commit to their orders at a discounted price
during the advance sale period. That is,
0 A 2b(
p c)
c .
Henceforth, we assume the condition
0 A 2b(
p c)
c holds throughout the rest of this study.
For fixed
*
, in order to find the optimal selling
*
period T , we first take the first-order partial derivative of
*
Z ( T,
) in Equation (2) with respect to T and obtain
b I e p ( t p 2M
)
f 1 c / p
(
a bc)
. (8) G 1( T )
*
* h
s [ a b(
1
) p b(
p c)
] pt
p ( a b p)
( 2(8)
t p T)
T
2
2
* 2
p I e
b p I
2
e
For convenience, we let A ( a bc)
b I e p ( t p 2M
) / 2 . ( a b p ) ( t p T
) ( t p 2M
) t , (10)
p
2
2
1
*
d Z 1 ( T,
)
d T ( t
p
1
T)
2
hT
( a b p)
( 2t
p
2
p I
T )
2
* 2
b p I e t p
( t p
2
2M
)
We let
*
*
s [
a b(
1
) p b(
p c)
] pt
e
( a b p ) ( t
p
p
T
)
(9)
2

7330 Afr. J. Bus. Manage. (10)
and find that,
d G1(
T)
(
h p I )( a b p)(
t p T)
0.
d T
e (11)
Hence, G 1( T ) is a strictly decreasing function for
T [ 0,
M ] . Moreover, we obtain
G 1(
0)
* 2
p I e
2 b p I e
s ( a b p ) t p ( t p 2M
) t p
2
2
*
*
[ a b
( 1
) p b
( p c)
] pt
, (12)
and
2
G 1( M )
h
p I e
s ( a b p)
( 2t
p M ) M ( a b p ) ( t p M )
2
2
* 2
b p I e
*
*
( t p 2M
) t p [ a b ( 1
) p b ( p c)
] p t . (13)
p
2
For convenience, we let
T
1
t
p
t
2
p
p
* 2
p I e
2 b p I e
1 ( a b p ) t p ( t p 2M
) t p
2
2
*
*
[ a b
( 1
) p b
( p c)
] pt
, (14)
and
h
p I e
2
2 ( a b p)
( 2t
p M ) M ( a b p ) ( t p M )
2
2
* 2
b p I e
( t p 2M
) t p
2
*
*
[ a b
( 1
) p b
( p c)
] pt
(15)
p
It is obvious that 1 2 . Let T 1 denote the optimal
*
value of T which maximizes Z ( T,
) .We then derive
the following result:
Lemma 2:
* *
*
2 s 2b
p ( p p c)
t p b
p
( a b p)
( h p I )
The proof is given in Appendix B
*
Subsequently, for fixed , we take the first-order
*
partial derivative of Z ( T,
) in Equation (3) with
respect to T and obtain
*
d Z 2 ( T,
)
d T
( t
p
1
T)
2
2
c
*
*
s [
a b(
1
) p b(
p c)
] pt
hT
I c
( a b p)
( 2t
p T)
( a b p ) ( T M )( T M 2t
p )
2
2
p I e
2 * 2
[( a b p)
( t p M ) b p(
t p 2t
pM
) ] (16)
2
We let,
G 2 ( T )
*
* hT
s [ a b(
1
) p b(
p c)
] pt
p ( a b p)
( 2t
p T)
2
c I c
p I e
2
( a b p ) ( T M )( T M 2t
p ) [( a b p)
( t p M )
2
2
* 2
p(
t 2t
M)
] , (17)
b p p
p
(a) If s 1,
then T 0 .
1
(b) If s 2 , then T1 M .
(c) If 1 s 2 , then
e
2
I ( t
e
p
and find that,
2M
) t
p
*
2
pt
1
p
h p I
e
p
p I
d G 2 ( T)
(
h c I c )( a b p)(
t p T)
0.
d T
e
t
2
p
1
2
.
(18)
Hence, G 2 ( T ) is a strictly decreasing function for
T [ M,
)
.We obtain
*
* h
2
lim G 2 ( T)
s [
a b(
1
) p b(
p c)
] pt
p ( a b p)
lim ( 2t
pT
T )
T
2
T
c I c
( a b p ) lim ( T M )( T M 2t
p )
2
T
p I e
2 * 2
[( a b p)
( t p M ) b p ( t p 2t
pM
) ] , (19)
2
and
G 2 ( M )
*
* h
s [ a b(
1
) p b(
p c)
] pt
p ( a b p)
( 2t
p M ) M
2
* 2
p I e
b p I
2
e
( a b p ) ( t p M ) ( t p 2M
) t p
2
2
G ( M ) s . (20)
1
2

where � 2 is defined as above. Let T 2 denote the
*
optimal value of T which maximizes Z ( T,
� ) . We
have the following result:
Lemma 3:
(a) If s � � 2 , then T � M .
(b) If s � � 2 , then
T
2
� �t
p
��
� �t
��
2
p
�
c I
c
2
*
( M � 2t
) M � 2�
p t
p
h � c I
c
p
�
2
p I
e
( t
p
� M )
* *
* 2
2 s � 2�
b p ( � p � p � c)
t � ( � 2 ) ��
p � b p I e t p M t p
�
�
( a � b p)
( h � c I c )
��
.
The proof is given in Appendix C
Combining Lemmas 2 and 3, we obtain the following
main result:
Theorem
For 0 � A � 2b(
p � c)
c (that is,
*
� � [ p ( 4 � 2I
M � I t ) � 2bc
� 2a]
/ ( 4b
p)
),
we have:
b e e p
*
(a) If s � � 1 , then T � 0 and
*
*
Z Z 1(
0,
� )
� .
T 1
*
(b) If � 1 � s � � 2 , then � T and
*
*
Z Z 1(
T1,
� )
� , where T 1 is the same as Lemma 2
*
(c) If s � � 2 , then T � M
*
*
Z Z 1(
M,
� )
*
� Z ( M,
� )
� .
(d) If s � � 2 , then 2
2
*
T � T and
where T 2 is the same as Lemma 3 (b).
2
1
2
and
*
*
Z Z 2(
T2
, � )
� ,
Proof. This result immediately follows from Lemmas 2
and 3 and the fact that;
*
*
Z ( M,
� ) � Z ( M,
� ) .
1
2
Once we obtain the optimal advance sales discount rate
*
*
� and the length of the regular sale period T , the
optimal order quantity is as follows:
*
Q
* � D( p �� p)
t p � D(
p)
T
*
� [ a �b(
1��
) p]
t
p
*
� ( a � b p)
T
*
Numerical examples
Chen and Cheng 7331
The following numerical examples are given to illustrate
the aforementioned solution procedure.
Example 1: This example is based on real data provided
by a retailer in Taiwan in relation to one of their items.
The supplier offers a permissible delay period of 30 days
(M = 1 month). The retailer offers customers an advance
sales period of 30 days ( t � 1 month ). The interest
earned per $ per year is 12% (interest rate per month,
I � 0.01000) and the interest charged per $ investment
e
in stocks per year is 10 % (interest rate per month, I c �
0.008333). In addition, p =$ 280 / unit, c =$ 182 / unit, a
= 800, b = 2.5, h �$
30/
unit / month and
s � $ 500/order.
Under these parameters, we find that
0 � A � 334.
5 � 2b(
p � c)
c � 89180;
hence,
*
� � 0.
1111.
Further, since s � 500 � � 1 � 2558 . 03 ,
from the Theorem, we obtain the optimal value of T as
T 0 . Thus, the optimal solution is
1 �
* *
( T , � ) � ( 0,
0.
1111)
and the maximum total profit per
* * *
unit of time is Z � Z ( T , � ) � 12138. The
*
optimal order quantity is Q � 177 . 75 units.
1
Example 2: We consider the same parameters as in
Example 1, except with the following: I � 0.
00100 and
p = $ 260 / unit. Under these parameters, we find that
0 � A � 344.
025 � 2b(
p � c)
c � 70980 ; hence,
*
� � 0.
0354 . Further, since
� � . 87 � s � 500 � � � 7039 . 37 , from the
1
230 2
Theorem, we obtain the optimal value of T as
T 0.
0576 . As a result, the optimal solution is
1 �
* *
( T , � ) � ( 0.
0576 , 0.
0354 ) , the maximum total profit
* * *
per unit time is � Z ( T , � ) �
p
Z 11477 . 4
*
and the optimal order quantity is Q � 181 . 63 units.
Conclusion
In this article, we considered an inventory model with
price-dependent demand. In our model, the retailer
provides advance sales whereby customers can commit
orders at a discounted price prior to the beginning of the
regular sale season. Further, the supplier allows the
retailer a specified credit period to settle the balance
1
e

7332 Afr. J. Bus. Manage.
during which no interest accrues. Advance sales offers
two benefits. Firstly, the retailer can gain additional
demand by implementing advance sales. Moreover,
advance sales increases the amount of interest earned
since interest is earned on payments received from
advance sales orders prior to the regular sale season.
We provide a Theorem to determine the optimal advance
sales discount rate and the optimal length of the regular
sale period for which the total profit per unit of time is
maximized. Finally, numerical examples were given to
illustrate the solution procedure.
In the future research, our model can be extended in
several ways. For instance, it could be of interest to
consider the situation where the retailer determines when
to start advance sales. In addition, the model may be
generalized to the price-dependent demand in which
price is a decision variable.
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APPENDIX
Appendix A:
The proof of Lemma 1.
Chen and Cheng 7333
(a) Since f (� ) is a strictly decreasing function for � �[
0,
1�
c / p]
, f ( 0)
� �A
� 2b
( p � c)
c � 0 implies f ( � ) � 0
� Z ( T,
� ) p t p f ( � )
for all � �[
0,
1�
c / p]
. Therefore, � � 0 . Hence, for a given T , Z ( T,
� ) is a decreasing
� � t p � T
function of � . That is, a smaller value of � results in a larger value of Z ( T,
� ) . Thus, the maximum value of Z ( T,
� )
*
occurs at the boundary point � � 0 that is, � � 0 .
(b) Conversely, f �1 � c / p�
� �A
� 0 implies f ( � ) � 0 for all � �[
0,
1�
c / p]
since f (� ) is a strictly decreasing
� Z (T , � ) p t p f ( � )
function for � �[
0,
1�
c / p]
. Thus,
� � 0 , which means, for a given T , Z ( T,
� ) is an
� � t � T
increasing function of � . That is, a larger value of � leads to a larger value of ( T,
� )
p
Z . Therefore, the maximum value
*
of Z ( T,
� ) occurs at the boundary point � �1
� c / p i.e., � �1
� c / p .
(c) 0 � A � 2b(
p � c)
c implies f ( 0)
� 0 and f �1 � c / p�
� 0 . Since f (� ) is a strictly decreasing function in
� �[
0,
1�
c / p]
, by Intermediate Value Theorem, we can find a unique value � such that f ( � ) � 0 . Consequently,
� Z ( T,
� )
the point � which satisfies f ( � ) � 0 not only exists but also is unique. Solving f ( � ) � 0 (that is, � 0 ), we
� �
*
can obtain the optimal solution of � , which is given by � � [ p ( 4 � 2 I M � I t ) � 2b
c�
2a]
/ 4b
p .
Appendix B:
The proof of Lemma 2.
b e e p
(a) Since G 1( T ) is a strictly decreasing function for T � [ 0,
M ] , G 1(
0)
� s � � 1 � 0 implies G 1(
T ) � 0 for all
*
d Z 1(
T,
� ) G 1(
T)
*
T � [ 0,
M ] . Thus, we obtain � � 0 . Therefore, Z 2
1(
T,
� ) is a decreasing function of T ,
d T ( t � T)
*
that is, a smaller value of T causes a larger value of ( T,
� )
the boundary point � 0
T . That is, T 0 .
1 �
p
*
Z . Hence, the maximum value of ( T,
� )
1
Z occurs at
(b) Conversely, G 1(
M ) � s � � 2 � 0 implies G 1(
T ) � 0 for all T � [ 0,
M ] because G 1( T ) is a strictly decreasing
*
d Z 1(
T,
� ) G 1(
T)
*
function for T � [ 0,
M ] . Thus, � � 0 . Therefore, Z 2
1(
T,
� ) is a increasing function of T ,
d T ( t � T)
*
which means a larger value of T causes a larger value of ( T,
� )
occurs at the boundary point T � M . That is, T � M .
1
p
*
Z . Hence, the maximum value of Z ( T,
� )
(c) � 1 � s � � 2 implies G 1(
0)
� 0 and G 1(
M ) � 0 . Since G 1( T ) is a strictly decreasing function in T � [ 0,
M ] , by
the Intermediate Value Theorem, we can find a unique value T such that G ( T ) � 0 . Consequently, the point T which
*
d Z 1(
T,
� )
satisfies G 1(
T ) � 0 not only exists but also is unique. Solving G 1(
T ) � 0 (that is, � 0 ), we obtain the
d T
1
1
1
1

7334 Afr. J. Bus. Manage.
optimal value of T as
Appendix C
The proof of Lemma 3
T
1
� �t
p
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2
p
* *
* 2
2 s � 2b�
p ( � p � p � c)
t p � b�
p I e ( t
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( a � b p)
( h � p I )
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) t
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(a) Since G 2 ( T ) is a strictly decreasing function for T �[ M,
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, G 2 ( M ) � s � � 2 � 0 implies G 2 ( T ) � 0 for all
*
d Z 2 ( T,
� ) G 2 ( T)
*
T �[ M,
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.Thus, we have � � 0 . Therefore, Z 2
2(
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d T ( t � T)
*
which means a smaller value of T causes a larger value of ( T,
� )
occurs at the boundary point T � M i.e., T � M .
2
p
*
Z . Hence, the maximum value of Z ( T,
� )
(b) Since G 2 ( T ) is a strictly decreasing function for T �[ M,
�)
, G 2 ( M ) � 0 (i.e., s � � 2 ) and lim G 2( T)
� 0 , by
the Intermediate Value Theorem, we can obtain a unique value T such that G ( T ) � 0 . Consequently, the point T
*
d Z 2 ( T,
� )
which satisfies G 2 ( T ) � 0 not only exists but also is unique. Solving G 2 ( T ) � 0 (i.e., � 0 ), we obtain
d T
the optimal value of T which is given by:
T
2
� �t
p
��
� �t
��
2
p
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c I
c
2
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2
* *
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( M � 2t
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�
�
.
h � c I c
( a � b p)
( h � c I c )
��
2
T��
e
2
�
��
1

African Journal of Business Management Vol. 5(17), pp. 7335-7341, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM10.1581
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
The students’ degree of preference for residence hall
facilities and amenities, study of a developing country
Fatemeh Khozaei 1 *, Ahmad Sanusi Hassan 1 and T Ramayah 2
1 School of Housing Building and Planning, Universiti Sains, Malaysia.
2 School of management, Universiti Sains, Malaysia.
Accepted 15 June, 2011
The main purpose of this study was to explore the degree of university residence hall students’
preferences for some facilities and amenities. With a case study of a developing country, this paper
also aimed to determine whether the mean score of these preferences differed significantly with regard
to students’ gender, nationality, race and study level. Structured questionnaires were administrated to
850 residence hall students, and 752 questionnaires were usable out of these numbers. The result of
the study indicated that free internet access, lockable storage space and mirror inside student’s room,
water machine and variety of food in food stall were the 5 most preferred facilities in the residence
halls. Additionally, this study highlighted the importance of some specific facilities such as kitchen,
laundry monitoring system and 24 h available taxi from students’ perspective. It was found that
students had a great interest to these facilities as well. The research further uncovered a significant
difference among male and female students, race and study level on their degree of preferences.
Undergraduates, Chinese, and female students reported greatest preferences for all types of facilities
and amenities. No significant difference was found in the preference mean scores of students from
different nationalities.
Key words:Facilities and amenities, university residence hall, gender, students’ preferences, race, nationality,
study level.
INTRODUCTION
In the next few years, probably the university organizers
will be faced with strong competition from off campus
housing market as the marketing of student housing is
jointed not only with the availability but also the quality of
these residential facilities. Student’s increasing expectations
to nicer and more home-like accommodations
(Roche et al., 2010) as well as demand for up-to-date
facilities (Ryan, 2003) beside the availability of off
campus housing with better provided facilities and
amenities and affordable price of hiring and sharing
private off campus accommodation, are the factors that
can drive students from the on campus to off campus
accommodations. Consequently, in near future the low
monthly fee might not be a strong motivator to keep
university students in on campus residence halls. Even
*Corresponding author. E-mail: fatemeh.rd08@student.usm.my
with ignoring of the financial benefits that universities
might achieve from residing of large number of students
in the residence halls, it is difficult to take no notice to the
positive impacts of living on campus on the students
(Araujo and James, 2010; Pike, 2009; Turley and
Wodtke, 2010; Flowers, 2004 ). Hence, there is a challenge
for residence hall organizers to provide students
with campus housing that not only provides them with
benefits of living on campus but also have the
characteristics of off campus accommodations such as
adequate facilities and amenities.
Borrowing from the studies on housing satisfaction it is
proved that convenient living facilities is one of the
predictors of housing satisfaction (Ge and Hokao, 2006).
In a study, Mohit et al. (2010) showed that residential
satisfaction is highly correlated with neighbourhood
facilities. Similarly, Salleh (2008) also found that central
facilities in the neighbourhood as well as educational
facilities are two of the most important predictors of

7336 Afr. J. Bus. Manage.
satisfaction for low cost housing residences in Penang,
Malaysia.
Taking previous studies into consideration, lead us to
take a specific notice on the importance of facilities on
residential settings. Hence it make sense that provision of
proper facilities is one the key factors that makes the
residence hall environment more desirable for students.
Besides If the students are satisfied with their residence
hall they might even experience less depression, and
less mobility problems.
In spite of the key role of provided facilities on
residence halls; studies tend to ignore the students’
preferences for different types of facilities. Hence, to fill a
part of gap in literature, the main goal of this study was to
uncover some aspects of students’ preferences toward
facilities and amenities in residence halls. There are three
questions for this study:
1. What is the degree of students’ preference for specific
facilities in residence hall?
2. What are the most 5 preferred facilities and amenities
for students?
3. Is there any difference between gender, nationality,
race and study level in the facilities and amenities
preferences?
The finding of this study could be useful in planning of
residence hall facilities from several perspectives: firstly
understandings of the students’ housing preferences can
aware the university organizers of their customer real
needs and requirements. This can lead to a better future
planning, design and management of these residences.
Secondly highlighting the importance of some specific
facilities for students which are not very common in many
of residence halls such as (laundry monitoring system,
kitchen and indoor pool for female students) in the
context of developing countries, can enhance the
knowledge about the current students’ perspective about
availability of such facilities in residence halls. It can
reveal that of how these facilities are desired to be
available in the students’ residence hall. And lastly, the
comparison of students with different background on their
preferences emphasizes on students differences and
similarities. Whether difference in design and management
of residence halls for male and female students
must be taken into account or not, can be revealed to
some extent with the result of such a study.
MATERIALS AND METHODS
The goodness of measure
The current study is a part of a vast research on student housing
preferences. This vast research aimed to examine the university
student’s preferences toward different aspects of their residence
hall environment such as location, facilities, amenities and so forth.
For the means of the study an instrument was developed which
was named as SAPI (student accommodation preferences index),
Khozaei et al. (2011) revealed in a study the development and
validation of this instrument).
The study conducted at residence halls of the Universiti Sains
Malaysia (USM) located at Penang Island, Malaysia. The survey
was distributed among students who were living in these university
residence halls in the first semester of 2010-2011. These residence
hall of USM were mostly occupied by undergraduates and a
minority of graduate students. Data was collected using a selfadministrated
questionnaire. Students were asked to indicate their
preferences rating a four point scale from not at all (1) to very much
(4) on each statement. 10% of total residence hall student’s
population were sampled, 850 students responded and returned the
questionnaires and 752 questionnaires were usable out of this
numbers.
Collected data was analysed using PASW Statistics 17. It was
proved that SAPI is a valid and reliable measurement instrument
and consists of 6 factors which are facility and amenity, visual,
convenience of student’s room, location, social contact, and
security (Khozaei et al. 2011).
The current study concern with the facility and amenity (amenity
is defined as facilities that make the life of students more pleasant
and comfortable) factor which consisted of 22 items. The factor
loading for each item is represented in Table 1. Internal consistency
of measures was assessed using the Cronbach’s alpha. The
alpha yielded a high reliability coefficient for the factor which was
0.92 (Khozaei et al., 2011).
Profile of respondents
Table 2 represents the demographic background of respondents.
As descriptive statistic revealed that of the study group, 242
students (32.2%) were male and 510 of them (67.8) were female.
The majority of respondents were ranged between 18 to 23 years
old (41.0%) and the minority aged above 30 years old. The greatest
number of students were Malaysian (83.3%) followed by (8%)
Indonesians, (4.4%) Iranians (1.1%) Iraqis and 5.5% from the other
nationalities. 369 number of students were Malay (49.1%), 273
Chinese (36.3%) followed by 36 Indian (4.8%) and 74 students
(9.8%) were from other ethnics. 83.0% of respondents were
undergraduate students and the rest of respondents were graduate
students.
RESULTS
As stated previously, this study aimed to investigate the
residence hall students’ level of preferences for specific
types of facilities and amenities. Mean and standard
deviation of the students’ preferences for each item is
reported in the Table 3. Most of the items revealed a
mean score above 3. Recalling that 4 point Liker scale
was used in this study, simply it is recognizable that the
majority of students desired to have the stated facilities
and amenities in their residence hall “mostly” or “very
much”. However 8 of the items indicated a mean of
higher than 2.
Free internet access reported as the most preferred
facility in the residence hall (mean 3.70, SD .63). This
pointed out the importance of access to internet from
students’ perspective. it might be due to the key role of
internet on different aspects of the students life such as
research, study and communication, research and study
The availability of lockable storage space inside the room
(Mean 3.53, SD .66) was reported as the second highest

Table 1. Facility and amenity factor loading and reliability.
Items of facility and amenity Factor loading Cronbah alpha
ATM machine 0.717
Photostat and printing services 0.714
Water machine 0.690
Storage rooms for unused staffs 0.625
Small library 0.616
24 h study room 0.611
Vending machine 0.552
Lift 0.539
Free internet access 0.539
Laundry with washer and dryer at each floor 0.538
Mirror in the room
Hot water in the bathroom
0.516
0.516
0.92
Lockable storage space inside the room 0.515
Visual tour in website 0.503
Laundry monitoring system 0.499
Fitness room 0.498
Small mart 0.495
24 h Taxi for emergency use 0.483
Pin board in the room 0.429
Variety of food in food stall (Chinese Malay Indian) 0.427
Kitchen 0.358
Indoor pool (specially for female) 0.340
preferred facility. The next three important facilities were
mentioned as mirror in the room (Mean 3.50, SD 0.69),
water machine (Mean 3.43, SD .77) and variety of food in
food stall (Mean 3.40, SD .80).
In addition the students showed a great desire for
facilities of pin board in the room (Mean 3.35 SD .74),
Laundry with washer and dryer at each floor (Mean 3.33
SD .82), ATM machine (Mean 3.31 SD .92), big storage
space inside the wall of the room (Mean 3.24 SD .77) ,
photostat and printing services (Mean 3.20 SD .92), 24 h
study room (Mean 3.17 SD .93), small mart ( Mean 3.12
SD .90), lift (Mean 3.08 SD 1.05) fitness room (Mean
3.07 SD .91) laundry monitoring system ( Mean 3.05 SD
.91) as well as storage room for unused stuffs (Mean
3.00 SD .91) as indicated by mean score of higher than
3.
Besides, the facilities that might be generally found in
the majority of university residence halls, this study also
examined the students’ preferences for facilities such as
kitchen, laundry monitoring system, 24 h taxi for
emergency uses and indoor pool for female students.
Among these facilities, students had the highest
preference for laundry monitoring system (Mean 3.05, SD
.91). This system is used by some universities from
developed countries. With this system, students are able
to check the availability of washing machines and dryers
online through the internet. This system can easily help
students to manage and save their time and instead of
Khozaei et al. 7337
queuing for using washing machines and dryers, they can
use the machines in less crowded hours. The students’
desire for having the kitchen in residence hall (M 2.95 SD
0.99) and 24 h available taxi (M 2.95 SD 0.94) were also
respectively high.
Further it was of interest to understand whether male
and female students differ significantly on their preferences.
Accordingly an independent sample t test was
conducted. Significant differences were found between
male and female students on facility and amenity preferences.
These facilities and amenities were more important
for female students than their male counterparts.
Table 4 presents the result of the independent-samples t
test.
A series of 1 way ANOVA were performed to examine
students’ preferences in base of nationality, race, and
study level. No significant differences were found between
mean score of students from different nationalities.
However a significant difference was found between race
and facility and amenity preferences. Post hoc comparisons
using the Tamhanes’T2 test indicated that the
mean score for Chinese students (M=71.49, SD=8.76)
was significantly higher than the Malay students
(M=68.68, SD=12.64). Table 5
The result of study also indicated a significant
difference between study level (undergraduate, master by
research, master by course work, PhD students) and
facility and amenity preferences. Post hoc comparisons

7338 Afr. J. Bus. Manage.
Table 2. Demographic characteristics of participants.
Variable Valid percent
Gender
Male
Female
32.2
67.8
Age
Nationality
Race
Study level
using the Tukey HSD test indicated that the mean score
for undergraduate students (M=70.19, SD=11.50) was
significantly higher than the PhD students (M=62.54,
SD=11.94).
DISCUSSION
This study examined the degree of students’ preferences
for some facilities and amenities in residence halls. This
study which is a part of a vast study on student housing
preferences conducted at the Universiti Sains Malaysia
residence halls. The data collected for development of
Student accommodation preferences index (SAPI)
(Khozaei et al., 2011) was used for the means of study.
SAPI is an instrument for study of students’ housing
stated preferences. In fact studies on housing
preferences can be categorized into two main categories;
stated preferences and revealed preferences. Revealed
preferences studies concentrate on residences’ current
housing choice. It is supposed that the residences’ desire
can be understood by their purchase or selected residence.
In the other hand stated preference studies “are
based on intended choices or hypothetical choices”
(Coolen and Hoekstra, 2001).
It is obvious that the stated preferences studies are
more applicable in the context of on campus housing
18-20 41.0
21-23 44.0
24-26 6.3
27-29 3.6
above 30 5.2
Malaysian 88.3
Indonesian 0.8
Iranian 4.4
Iraqis 1.1
other 5.5
Malay 49.1
Indian 4.8
Chinese 36.3
other 9.8
Undergraduate 83.0
Master by research 2.5
Master course work 7.4
PhD 7.0
while the revealed preferences studies might lead to a
better understanding of the off campus housing
preferences”
The result of this study revealed that among all facilities
and amenities, free internet access, lockable storage
space and mirror in students’ room, water machine and
variety of food in food stall were the most 5 highest
preferred facilities and amenities in the residence hall.
Access to the internet was reported the highest preferred
facility in the residence halls. The result of this study
supports the studied that emphasizes on the importance
of access to internet for today’s life. In fact in recent years
several studies have examined the impor-tance of access
to internet among different people of society such as
students, travellers and firm staffs. In the for example
context of university residence halls, khozaei et al. (2010)
found that better access to internet was one of the
reasons that students preferred a specific resi-dence hall
to others. the other study showed that “overall Internet
use for academic purposes has increased” and students
have positive opinions about the Internet's utility for
academic work (Jones et al., 2008). Ogan et al. (2008) with
study of undergraduate students found that “respon-dents
to the survey went to the Internet daily, on average for
4.4 h. Overall, students saw the Internet as having a
positive impact on their lives”. In a evaluated the importance
of some amenities in hotel rooms among male and

Table 3. Mean and standard deviation for facility and amenity preferences.
Descriptive Statistics N Mean Standard deviation
Free internet access 752 3.70 0.63
Lockable storage space inside the room 752 3.53 0.66
Mirror in the room 752 3.50 0.690
Water machine 752 3.43 0.77
Variety of food in food stall 752 3.40 0.80
Pin board in the room 752 3.35 0.74
Laundry with washer and dryer at each floor 752 3.33 0.82
ATM machine 752 3.31 0.92
Big storage space inside the wall of the room 752 3.24 0.77
Photostat and printing services 752 3.20 0.92
24 h study room 752 3.17 0.93
Small mart 752 3.12 0.90
Lift 752 3.08 1.05
Fitness room 752 3.07 0.91
Laundry monitoring system 752 3.05 0.91
Storage rooms for unused stuffs 752 3.00 0.91
Hot water in the bathroom 752 2.96 1.04
Kitchen 752 2.95 0.99
Vending machine 752 2.95 0.90
24 h Taxi for emergency use 752 2.95 0.94
Small library 752 2.93 0.98
Visual tour in website 752 2.80 0.90
Water tap inside the room 752 2.71 1.03
Indoor pool (specially for female) 751 2.61 1.08
Khozaei et al. 7339
Table 4. Differences between male and female student on their facility and amenity preferences independent-samples t-test
calculation).
Male (n=241) Female (n=510) t p
Mean SD Mean SD
Amenity and facility preferences 66 12.95 71.02 11.08 -5.193 .000
Table 5. One way ANOVA on nationality, race and study level.
Analysis of variance
by nationality
Analysis of variance
by race
Analysis of variance
by study level
ANOVA
Sum of Squares df Mean Square F Sig.
Between Groups 72.517 4 18.134 1.431 .242
Within Groups 9461.332 747 12.679
Total 9533.849 751
Between Groups 2475.747 3 825.249 5.898 .001
Within Groups 104516.464 747 139.915
Total 106992.210 750
Between Groups 3100.147 3 1033.382 7.430 .000
Within Groups 103892.063 747 139.079
Total 106992.210 750
Where df = Degree of freedom, and sig. = significance.

7340 Afr. J. Bus. Manage.
female respondents. With study of 534 travellers they
found that high speed internet access was one of the top
three important technology amenities for both male and
female respondents.
The second highest preferred facility was the availability
of a lockable storage space (for example, safe box)
inside the room. This preference reveals the students’
essential need to keep their valuable stuffs like; money,
identity card, passport in a safe place which is not reachable
by others. In spite the importance of such a facility
many of universities ignore to provide it in students’ room.
The next three important facilities were mentioned as
mirror in the room (Mean 3.50, SD 0.69), water machine
(Mean 3.43, SD 0.77) and variety of food in food stall
(Mean 3.40, SD0 .80). It is interesting to note that the
needs for two vital facilities of water machine and variety
of food in food stalls stands after preference for internet,
lockable space and mirror inside the room. It might be
due to the fact that the current students are different from
previous generations in their needs and requirements.
Students bring this life style to residence hall. As
Vasquez and Rohrer (2006) asserted “Because modern
residence hall students are concerned with maintaining
their technological needs, today they bring a variety of
appliances to school: televisions, computers, printers,
stereos, microwaves, cell phones, mp3 players, DVD
players, video game systems, and digital cameras, to
name a few”. Access to internet can fill the absence of at
least some of their house facilities such as TV.
In addition the students showed a great desire for
facilities of pin board in the room, Laundry with washer
and dryer at each floor, ATM machine, big storage space
inside the wall of the room , photostat and printing
services, 24 h study room, small mart, lift, fitness room,
laundry monitoring system as well as storage room for
unused stuffs as indicated by mean score of higher than
3. Some scholars have emphasized on the facilities that
can support students’ study in residence hall; “adequate
physical facilities that support the educational process
contribute in important ways to student learning. Proper
lighting, soundproofing, and furnishings, for example, can
transform a student room from a mere place to sleep into
a most adequate and private study facility. Alternate
places to study within the residence hall are most helpful
as well as typing rooms, music listening rooms, reference
libraries, seminar rooms, classrooms, faculty offices, and
other facilities that meet the daily needs of students
“(Riker and Decoster, 2008). This study shows that
beside other facilities students had a great desire for
availability of facilities such as 24 h study room and
Photostat and printing services that eases their study in
residence hall.
Besides, the facilities that might be found in the
majority of university residence halls, this study also
examined the students’ preferences for facilities such as
kitchen, laundry monitoring system, 24 h taxi for emergency
uses and indoor pool for female students. The
preferences for all of these items were respectively high.
Today, many residence hall buildings provide common
areas where kitchens, laundry rooms, study halls, and
living spaces for students provide a greater level of
comfort and services (Wisbey and Kalivoda, 2008).
The result of several 1 way Anova didn’t reveal a
significant difference between mean score of students
from different nationalities. However a significant
difference was found between race and study level on
facility and amenity preferences. It was found that the
mean score for Chinese students was significantly higher
than the Malay students. In addition the mean score for
undergraduate students was significantly higher than the
PhD students.
The current study expands the knowledge about
students’ facilities and amenities requirements. Knowing
what various facilities and amenities students want from
their residence hall is the key to attracting enrolment and
satisfaction of students. It is required to be aware of
students’ perspective as the customers of these buildings
to provide a better set of facilities and amenities in
residence hall.
ACKNOWLEDGEMENT
This paper was supported by the postgraduate research
grant scheme (PRGS), Universiti sains Malaysia
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African Journal of Business Management Vol.5 (17), pp. 7342-7349, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM10.1597
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
An empirical study on factors that affect the transition
time between capability maturity model integration
(CMMI) levels in Saudi Arabia
Fahad H. Alshammari* and Rodina Ahmad
Department of Software Engineering, Faculty of Computer Science and Information Technology, University of Malaya
50603. Kuala Lumpur, Malaysia.
Accepted 31 March, 2011
During recent years, software process improvement (SPI) has been more concerned by a software
industry. Numerous studies have been made in development of SPI standards and models, or to
identify factors that affect SPI success. However, these studies did not provide answers to questions
about the factors that affect the transition time between capability maturity model integration (CMMI)
levels, and why there are obvious differences in the organizations’ transition time between CMMI levels.
The objective of this research is to identify the factors that can affect the transition time between CMMI
levels. The study conducted 10 interviews in 7 different Saudi’s software companies to extract the
factors and compare these factors with what are in the literature to avoid redundancy, based on that,
the study designed a questionnaire. It sent out 117 requests to participants, of which 46 responded
from 12 companies. The study asked the participants to rank each factor on a five-point scale (high,
medium, low, zero and not sure) to determine the effect of each factor. It identified 21 factors that are
considered effective factors on the transition time between CMMI levels. Also, the study identified two
new factors (turnover of staff and imposed partner) which were not identified in the literature.
Key words: Software process improvement, capability maturity model integration (CMMI), factors, transition
time, empirical study.
INTRODUCTION
During recent years, Issues associated with software
quality are widely diffused to affect the development cost
and time (Sommerville, 1996; Okay and Semiz, 2010).
The software industry has been more concerned about
Software Process Improvement (SPI). Software quality
has become more critical as software pervades our dayto-day
lives (Paulk et al., 1994). The decrease of transition
time between CMMI levels can lead organisations to
business benefits. A group of Fellows of the Royal
Academy of Engineering and British Computer Society
demonstrated that despite spending 22 billion pounds on
Information Technology projects in the UK during
2003/2004, there are still some projects that failed to
deliver on time (The Royal Academy of Engineering,
2004). Therefore, in general, time is still a main issue
*Corresponding author. E-mail: fhd_hmd@siswa.um.edu.my.
which affect an organization’s business benefits. SPI has
some models and Capability Maturity Model Integration
(CMMI) is one of the reference models, concerned with
organizations quality. CMMI can be described as a collection
of best practices gathered from the experiences
with software-capability maturity model (SW-CMM), and
other standards and models (SEI, 2007). However, there
are obviously different times, in the organizations’ transition
time, in order to move from one level to another.
Despite Software Engineering Institute (SEI) has
specified an average transition time between CMMI
levels, there is still an obvious deviation in various
software organizations in terms of their transition time
between CMMI levels. The effort put into these models
and standards can assist in producing high quality
software, reducing cost and time, and increasing
productivity (Butler, 1995; Pitterman, 2000; Yamamura,
1999). However, little attention has been paid to the
effective implementation of these models and standards

(Goldenson and Herbsleb, 1995). Therefore, the
transition time between CMMI levels still needs more
investigation. Thus, the main objective of this study is to
investigate the factors that affect the transition time
between CMMI levels in Saudi Arabia, and in light of that,
applying the factors in an empirical study over Saudi's
companies. This paper presents the results of an empirical
study aimed at identifying and investigating the
factors which has an effect (positively or negatively) on
transition time between CMMI levels based on the perceptions
and experiences of practitioners in developing
country, that is, Saudi Arabia. The research was limited
to the companies which already achieved CMMI level 3
or companies which have a CMMI level 2 and already
started ways to achieve CMMI level 3. The investigation
has several interesting findings which enabled the study
to identify and explain the relative factors which affect the
transition time between CMMI levels in Saudi Arabia. The
study has analyzed the experiences, opinions and views
of practitioners in the literature (that is, case studies,
reports and journal papers, etc.). The study has also
conducted a study on factors that have an impact on the
transition time between CMMI, and critically analyzing
and discussing each factor which affects the duration/
transition time between CMMI levels. Our results may
provide feasible and timely advice to SPI decision makers
in designing appropriate strategies to accelerate the
transition time between CMMI levels.
LITERATURE REVIEW
In the last decade, numerous studies have been done
into the transition time between CMMI levels. Jackelen
(2007) started a CMMI program with the goal of achieving
the CMMI Level 2 and satisfaction process areas within
five months. After the analysis of the current status of the
company, the top management decided to extend the
plan’s schedule of the program for one month. The paper
discussed how it was possible to achieve CMMI Level 2
in six months. The factors identified in this study were:
Management Commitment, Experienced Staff, Consultant,
Training, Awareness, and Quality Environment.
Guererro and Eterovic (2004) explored a case study that
achieved the moving from CMM Level 1 to CMM Level 2
in 10 months which would have been achieved in 19
months on the average time according to SEI data
(2004). They analyzed ten factors that affect the adoption
of CMM. These factors were: Training, Developer’s
Involvement, Maintaining Momentum, Group Focus,
Frequency of Process Assessments, Champions, and
Visibility into the SPI process. Balla et al. (2001), Iversen
and Ngwenyama (2006) and Akmenek and Tarhan
(2003) have described an achieving of CMM-Level 3 in 7months
time which would have been achieved in 19
months according to SEI (2004). Identified factors were:
Management Commitment, Awareness,
Staff Involvement, Training, Experienced Staff,
Alshammari and Ahmad 7343
Consultations, and Quality Environment. Olson and
Sachlis (2002) discussed the moving from CMM-Level 1
to CMM-Level 3 in 14 months which would have been
completed in 38 months based on the time average
according to SEI data (2004). Identified factors were:
Management Commitment, Staff Involvement, Training,
Consultant, Implementation Plan, and Process Documentation.
Zeid (2004) has explained how the organization,
ITSoft moved from CMM Level 2 to CMM Level 3 in a
short time (two months) and from CMM Level 1 to CMM
Level 2 in 9 months. Identified factors were: Training,
Experienced Staff, Quality Environment, Implementation
Plan, Process Documentation, and Metrics and Measurement.
It is important to conduct empirical research in
order to provide more certainty that explores these
factors that affect the transition time between CMMI
levels, since an empirical research enables rigorous
experimentation by encouraging multiple analysis from
multiple perspectives using different approaches, and
helps to compare what was believed to what was
observed (Harrison et al., 1999; Perry et al., 2000).
Therefore, empirical research helps researchers move
towards well-founded decisions (Perry et al., 2000). An
empirical investigation of SPI implementation factors will
provide SPI practitioners with valuable insights through
planning of SPI strategies (Niazi et al., 2006). A good
understanding of the transition time factors of CMMI
should help organisations accelerate in moving between
CMMI levels. The decrease of transition time between
CMMI levels can lead organisations to business benefits.
RESEARCH DESIGN
Research approach
In this study, people who are already involved in software
development industry were identified, to extract factors which are
having a high impact on transition time between CMMI levels. For
this purpose, the study has done the following:
i. Conducting a face to face meeting, to extract the factors that
affect the transition time between CMMI levels without any
suggestions from the researchers.
ii. Factors filtration, to identify and avoid redundancy of factors
which have different name with the same meaning between
practitioners and literature review.
iii. Survey design, designing a questionnaire in favor of this study in
order to collect the data from respondents.
iv. Distribution stage, to distribute and apply the questionnaire into
Saudi Arabia.
v. Data analysis, according to data, which are collected from
respondents.
vi. Results, to find out the findings and to determine the effective
factors from the data set.
Study scope
In this research, the study scope would be on the companies which
already adopted CMMI and achieved CMMI level 3 or companies
which have CMMI level 2 and have started procedures to achieve
CMMI level 3.

7344 Afr. J. Bus. Manage.
Population and sample profile
Software organizations and companies are considered as the target
population for this study. This population includes companies that
develop either software or combined software and hardware
products for a wide variety of markets. According to the study and
the scope, it had sent out 117 requests to participants, of which,
only 46 responded from 12 companies distributed over Saudi
Arabia. This means the response rate was (39.32%).
However, we have high confidence in the accuracy and validity
of the data. Forty-six practitioners voluntarily participated in this
study. It was important to ensure that no particular practitioner was
over-represented (Coolican, 1999).
This research addressed the issue of over-representation by
using a sample of companies of varying complexity, size, business
nature, application type, etc. A similar approach has been used by
other researchers (Baddoo, 2001; Baddoo and Hall, 2002, 2003;
Niazi et al., 2006).
Data instrumentation
In this study, a questionnaire as a main instrument to gather survey
data from companies was used. A survey research method can use
one or more data elicitation techniques such as interviews and self
administered questionnaires (Lethbridge, 2005). It is deemed suitable
for eliciting quantitative and qualitative data from respondents
(Lethbridge, 2005). A questionnaire was pre-tested by 7 SPI
personnel in domestic software companies and 4 graduate students
at the University of Malaya.
Guielford (1965) suggested that reliabilities of Cronbach’s α is
high if Cronbach’s α is over 0.70. Therefore, in our analysis, the
pre-test of the expert questionnaire appeared as a high average
Cronbach α of 0.799; this indicated that the questionnaire was
acceptable and internally consistent.
The study used e-mail, telephone calling and face to face meeting
sessions. Because of the possibility of illustrating the objectives
of the research and different terms used in the questionnaire, and
clarifying the purpose of different questions included in the questionnaire,
and also ensuring data validation before the end of each
survey session, the survey session duration was about 45 min.
Effective factor
This study defined effective factor as a measure of the extent to
which the factor has an effect on the transition time between CMMI
levels and whether it adds value to the transition time of CMMI
based on the perceptions and experiences of practitioners who
have been involved in the area of SPI at their respective organisations.
In order to describe the notion of effective factor on transition
time of CMMI, it is essential to decide on the importance of an
effective factor. For this purpose, the study has used the definition:
If the majority of respondents (≥ 50%) consider that factor has a
high effect on transition time of CMMI then it treats that factor as an
effective factor.
A similar approach has been done in the literature (Niazi and
Babar, 2009; Niazi et al., 2005; Rainer and Hall, 2002). Rainer and
Hall (2002) identified important factors in SPI with the criterion that
if 50% or more participants consider that a factor has a major role in
SPI efforts then that factor should be considered as having a major
impact on SPI.
Data collection
According to the research objectives and available resources,
although, depending on what has been suggested by Alam (2011),
the study has used a survey research method to gather data on
Saudis practitioners’ perspective of the factors that affect the
transition time between CMMI levels. A survey of data collection is
considered suitable for gathering quantitative and qualitative data
from a number of respondents (Kitchenham and Pfleeger, 2002). A
survey of data collection can use one or more data elicitation
techniques such as interviews and questionnaires (Lethbridge,
2005). The study has used a closed format questionnaire as a data
collection approach in conjunction with face-to-face meetings during
some stages of data collection. In order to make sure of clarifying
the research objectives, the terms used in the questionnaire, and
ensuring data were validated before completing each survey
session. The study has conducted 10 interviews in 7 different
software companies in Saudi Arabia, with flexible schedules so that
interviewees could make an appointment at any time suitable for
them (Fowler, 2002). We sent 117 questionnaires by email to those
included in our scope. A questionnaire was based on factors that
affect the transition time between CMMI levels. The study has
designed a questionnaire to gather the effective factors where each
respondent ranked each factor identified as factor which has an
effect on transition time between CMMI levels. In order to identify
the effective factors, the respondents were asked to note each factor’s
relative value (that is, High, Medium, Low, Zero, or Not sure).
FINDINGS
Factors that affect the transition time between CMMI
levels in Saudi Arabia
Table 1 shows the list of impacting factors that affect the
transition time between CMMI levels. According to the
scope of this study, Table 2 identifies the high frequency
and percentage of each factor that affect the transition
time between CMMI levels in Saudi Arabia. Table 3
shows the effective factors in the transition time between
CMMI are, training (89%), management commitment and
gap analysis, 85% to each. This indicates that, in the
Saudi practitioners’ opinion, training can play quite a vital
role in the transition time between CMMI levels. Therefore,
this result almost agrees with Olson and Sachlis
(2002), Balla et al. (2001) Iversen and Ngwenyama
(2003) and Akmenek and Tarhan (2003). Other
frequently effective factors in Saudi Arabia are turnover of
staff, review, allocation of resources, resistance to
change, separation of process and product concerns,
CMMI experienced staff, defined SPI implementation
methodology, visibility into the SPI process planning,
imposed partner, management of changement, unscheduled
events, investments of a company, management
and staff involvement, awareness, process documenttation,
frequency of process assessment, metrics and
measurement, and consultation. Table 4 shows the non
effective factors on the transition time between CMMI
which are having less impact. From the empirical study in
Saudi Arabia, the study has noted that the factors;
turnover of staff and imposed partner, are new effective
factors, whereas, the study did not find in literature and
previous studies, to best of our knowledge that, these
new factors have been identified or have been taken

Table 1. Factors that affect the transition time between CMMI levels.
Alshammari and Ahmad 7345
Factor
H
Saudi Arabia (n = 46)
M L Z N/S
Self-Motivation power
22 8 2 4 10
Turnover of staff
38 8 0 0 0
Market conditions changes
4 3 32 6 1
Cost of appraising
15 18 6 3 4
Management of changement
32 11 1 1 1
Investments of a company
29 14 1 1 1
Many roles to one person
3 1 1 39 2
Unscheduled events
31 11 1 3 0
Financial motives
8 17 11 7 3
Public holiday events
0 1 25 20 0
Imposed partner
33 10 1 0 2
Job respecting
3 6 21 16 0
Income level
13 12 21 0 0
Management commitment
39 7 0 0 0
Frequency of process assessment
26 19 0 0 1
Separation of process and product concerns 37 9 0 0 0
Management and staff involvement
29 10 0 0 7
Training
41 4 0 0 1
Review
38 8 0 0 0
Defined SPI implementation methodology
34 10 0 0 2
Awareness
29 13 3 1 0
CMMI Experienced staff
37 3 1 0 5
Communication
9 2 29 0 6
Group focus
20 18 0 0 8
Process documentation
29 17 0 0 0
Consultation
23 19 1 0 3
Metrics and Measurement
26 20 0 0 0
Allocation of resources
38 8 0 0 0
Rewards
8 17 11 7 3
Gap analysis
39 6 0 0 1
Resistance to change
38 8 0 0 0
Visibility into the SPI process planning
34 10 0 0 2
H= High; M= Medium; L = Low; Z = Zero; N/S = Not Sure.
up as effective factors on the transition time between
CMMI levels.
By using effective factor criterion, the study has
identified 21 factors that are generally considered
effective factors for the transition time between CMMI
levels. Descriptive Figure 1 shows visual description for
the identified effective factors in Saudi Arabia. Since X
axis represents the factors, Y axis represents the
numbers from 0 to 100, while red columns represent the
percentage and blue columns represent the high frequency.
Figure 2 shows visual description for 10 factors
which are non effective in Saudi Arabia. Each pie
represents the high frequency of each factor, and its
percentage.
DISCUSSION
This paper presented an empirical study on factors that
affect the transition time between CMMI levels in Saudi
Arabia. A good understanding of the factors that can
delay the transition time between CMMI levels is expected
to help organisations to identify what strategies they
need to use in order to address these factors and
accelerate the transition time from one level to another of
CMMI. The study believes that these factors can be very
useful for Saudis’ CMMI based SPI practitioners as these
can help them in planning for CMMI level 3 in their
organisations.
The results indicate that software development

7346 Afr. J. Bus. Manage.
Table 2. Identifying the high frequency and percentage of each factor.
Factor
Saudi Arabia
High frequency Percent
Training 41 89
Management commitment 39 85
Gap analysis 39 85
Turnover of staff 38 83
Review 38 83
Allocation of resources 38 83
Resistance to change 38 83
Separation of process and product concerns 37 80
CMMI experienced staff 37 80
Defined SPI implementation methodology 34 74
Visibility into the SPI process planning 34 74
Imposed partner 33 72
Management of changement 32 70
Unscheduled events 31 67
Investments of a company 29 63
Management and staff involvement 29 63
Awareness 29 63
Process documentation 29 63
Frequency of process assessment 26 57
Metrics and Measurement 26 57
Consultation 23 50
Self-Motivation power 22 48
Group focus 20 43
Cost of appraising 15 33
Income level 13 28
Communication 9 20
Financial motives 8 17
Rewards 8 17
Market conditions changes 4 9
Many roles to one Person 3 7
Job respect 3 7
organisations need to improve their training, planning,
and staff also needs training courses (for example,
introduction to CMMI, Intermediate CMMI and SCAMPI),
therefore, this kind of similar understanding was noticed
by Alam (2009) and also Alam et al. (2010). Management
commitment is one of the factors that have the most
importance for any organization as identified by Alam et
al. (2010) and Ponnu and Chuah (2010). Thus, management
may delay the transition from a particular CMMI
level to a higher one if there is one or more of the
following points:
i. If the management has identified projects for the CMMI
and others for the important work.
ii. If limited its role in contracting with a consultant and a
follow-up an evaluation without efforts to improve the
operations.
iii. If the management was working as "let alone the
process now until we deploy the product or software to
the client, then we complete the documents later".
iv. If the management did not seriously consider the
workflow reports and then makes decisions based on
their own impressions rather than on facts.
v. If the management seeks only behind the certificate
without obtaining the real value of the application.
Turnover of staff, often resign - or said - fundamental
work team who built the company's quality system after
the end of an appraisal is to assign the task to a new
team, perhaps a newly appointed, to complete the
march. The new team needs more time in this case,
which leads to consumption of more time in the transition.
Chiboiwa et al. (2010) explained some external
influences that increase the level of staff turnover which
are; a level of payment, dissatisfaction with the reward
system in an organisation, and opportunities for

Table 3. Effective factors in Saudi Arabia.
Factor
Saudi Arabia
High Percent
Training 41 89
Management commitment 39 85
Gap analysis 39 85
Turnover of staff 38 83
Review 38 83
Allocation of resources 38 83
Resistance to change 38 83
Separation of process and product concerns 37 80
CMMI Experienced staff 37 80
Defined SPI implementation methodology 34 74
Visibility into the SPI process planning 34 74
Imposed partner 33 72
Management of changement 32 70
Unscheduled events 31 67
Investments of a company 29 63
Management and staff involvement 29 63
Awareness 29 63
Process documentation 29 63
Frequency of process assessment 26 57
Metrics and measurement 26 57
Consultation 23 50
Table 4. Non effective factors in Saudi Arabia.
Factor
Saudi Arabia
High Percent
Self-Motivation power 22 48
Group focus 20 43
Cost of appraising 15 33
Income Level 13 28
Communication 9 20
Financial Motives 8 17
Rewards 8 17
Market conditions changes 4 9
Many roles to one person 3 7
Job respect 3 7
alternative employment outside the country.
Imposed partner, this factor is identified as a factor that
has a negative impact on the transition time of CMMI.
Since, the partner type in huge projects would affect the
employee's productivity and delay the documentation
processing.
Consequently, this will consume time, therefore, it will
delay the transition time between CMMI levels (this
partner is added to the organization because of his high
social situation).
Other factors identified in this study completely agree
Alshammari and Ahmad 7347
with Balla et al. (2001) Iversen and Ngwenyama (2003)
and Akmenek and Tarhan (2003).
Through this empirical study, the recommendation was
that practitioners of CMMI-based SPI can design and
develop better strategies to decrease the transition time
by avoiding the factors identified in this study.
RESEARCH LIMITATION
Creating this research has faced some limitation which

7348 Afr. J. Bus. Manage.
Figure 1. Effective factors in Saudi Arabia.
Communication
8%
Figure 2. Non Effective factors in Saudi Arabia.
attributed to: Lack of the literature that investigated the
transition time of CMMI-based SPI; Most of Saudis’
companies use another software process improvement
models rather than CMMI.
CONCLUSION
This study focused on factors that affect the transition
time between CMMI levels in Saudi Arabia. It analyzed
the experiences, opinions and views of practitioners in
order to identify factors that have an impact on the
transition time between CMMI levels. The study identified
factors that are effective on the transition time between
CMMI levels. Focusing on these factors offers costeffective
opportunities in order to decrease the time spent
through the duration between CMMI levels. In order to
determine the effective factor, the study used the
following criterion:
If the majority of respondents (≥ 50%) consider that
factor has a high effect on transition time of CMMI
then we treat that factor as effective factor.
Using this criterion, the study has identified 21 factors
that are generally considered effective factors for the

transition time between CMMI levels. It has identified two
new effective factors affecting the transition time between
CMMI levels, they are; turnover of staff, and Imposed
partner. These two factors were not identified in the
literature as effective factors that affect the transition time
between CMMI levels. The study recommends that
Saudis’ organizations should focus on these effective
factors to accelerate the transition time between CMMI
levels. A good understanding of the transition time factors
of CMMI should help organisations on accelerating
moving between CMMI levels. The decrease of transition
time between CMMI levels can lead organisations to
business benefits.
ACKNOWLEDGEMENTS
Thanks in advance to the workers in this research, especially,
Dr. Rodina Ahmad and the people who supported
in many ways. Also, I want to thank University of Malaya
for the support which came from them.
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African Journal of Business Management Vol. 5(17), pp. 7350-7356, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM10.1645
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
On the exchange rates behavior by PPP: A test on
Malaysian ringgit and US dollar
Farhad Pourkalbassi 1 , Alireza Bahiraie 1 *, Aishah Hamzah 1 and Lee Chin 2
1 Institute of Mathematical Sciences, Faculty of Science, University of Malaya, 50603 Kuala Lumpur, Malaysia.
2 Faculty of Economics and Management, University Putra Malaysia, 43400, Selangor, Malaysia.
Accepted 27 May, 2011
Exchange rates are important to innumerable economic activities and the exchange rate behavior has
long been at the top of the list of research agenda in international finance. This article is another test of
the Relative Purchasing Power Parity (RPPP) to explain exchange rate behavior in short terms. The
study examine the relative form of Purchasing Power Parity theory with recent monthly exchange rate
data of US Dollar and Malaysian Ringgit starting from year 2005, which was the time Malaysia’s
currency went back to floating system after a few years pegging to US dollar since 1997 Asian Financial
Crisis (AFC). Within this study, correlation and Ordinary Least Square (OLS) methods were applied to
test the proposed RPPP model. Both the statistical and the observational results show significance
power of Relative PPP on explaining exchange rate behavior of the chosen currencies.
Key words: Exchange rate, purchasing power parity (PPP), Malaysian ringgit, US dollar.
INTRODUCTION
Exchange rate predication is one of the most challenging
and critical decisions in international finance area. Its
challenging aspect is due to its direct effect on one of the
most important goals of any firm, doing international
trade, which is exchange risk hedging. Nowadays, restricted
in current monetary system, any firm who involves
with import and export activities outside of its home
country borders will encounter a major risk called
exchange rate risk that can be a major determinant for
successfulness of business. Hence, finding and evaluating
various theories that may help and facilitate future
exchange rate prediction is toward the benefits of any
global trader and investor and has made busy a lot of
economic and financial academicians so far.
One of the major theories that explain exchange rate
determination is Purchasing Power Parity (PPP), which in
its absolute and relative forms, has been numerously
studied before. Despite all the studies that have been
done in different markets to evaluate persistency of
Purchasing Power Parity in different time horizons and to
evaluate it as a determinant factor for exchange rate, the
*Corresponding author. E-mail: alireza.bahiraie@yahoo.com.
results are contradictory. It is amazing to see contradictory
results independent of applied statistical methods
for both absolute and relative type of PPP. But, as the
studies shows, it may trust more on relative PPP as a tool
for short term exchange rate prediction probably along
with some other financial tools and theories. As it can
ignore the actual levels of exchange rate and prices in
relative forms of PPP, it can be said that being exempt of
strong assumptions; it is much easier to hold relative PPP
than absolute PPP. It should be considered that absolute
PPP is much broader than relative PPP in a sense.
Therefore, when absolute PPP holds, relative PPP
should also hold; however, absolute PPP does not
necessarily holds if relative PPP holds.
There are various questions that can be asked on this
issue in context of Malaysia. Knowing that most of the
studies regards PPP has been done in Malaysian market
before Asian Crisis on 1997, and considering that
Malaysia’s currency system is switched back to floating
system after 2005, how is the validity of PPP since 2005
for Malaysian ringgit? How significant is the relation
between price and exchange rate for Malaysia in deal
with its major trading partner US based on relative form
of PPP? How does the validity of this relation prove to be
useful for exchange rate forecasting?

In this study, relative form of PPP theory with monthly
data from 2005 to 2009, as Malaysia’s currency went
back to floating system in 2005 after a few years re-peg
to US dollar experience since 1997 Asian Financial Crisis
(AFC) was examined. In the period of 1997 to 1998,
Malaysia experienced financial crisis that affected the
whole ASEAN region and the country started controlling
the capital movement, inflation, and interest rate
movement. To prevent more reduction in value of ringgit,
government switched from floating system of currency to
fixed system. The ringgit of Malaysia was pegged to US
dollar since then, till July 2005.
PURCHASING POWER PARITY (PPP) THEORY
The theory of purchasing power parity (PPP) is a result of
Cassel (1916) research in which he states that in ideally
efficient market; identical goods should have only one
price. Based on this idea, purchasing power parity (PPP)
is a theory of exchange rate determination and a way to
compare the average costs of goods and services
between countries.
Purchasing power parity (PPP) states that there is a
proportional relationship between the prices - peroxide by
a representative basket of goods - in one country, relative
to that of another when expressed in the same base
currency. Although, there are a number of PPP specifications,
the concept that has been the focus of recent
empirical studies is long run PPP that permits short run
deviations. The concept has been the subject of much
debate both in the theoretical and econometric literature.
Dornbusch (1976) commented that most macroeconomists
have a deep-seated belief that a variant of PPP
is justified in some sense. Since it forms a cornerstone of
many macroeconomic models of trade and of exchange
rate determination, failure to support this parity empirically,
would somewhat undermine the basis for such
models.
Different literatures have investigated the empirical
validity of the PPP using different econometric methods
and using data from developed as well as developing
countries. These empirical investigations have also
expanded to emerging markets and ASEN economics. It
is interesting to know that these various empirical tests
results do not all approve or reject this theory together.
Frenkel (1981) by using standard 2SLS and GLS showed
that PPP failed to hold during 1970's, but in another study
conducted by Davutyan and Pippinger (1985), they
concluded that indeed, it held not only during the 1920's,
but also during the 1970's. More amazing is even after
recent developments in econometric techniques, result of
studies that have used these advanced methods are still
not toward one direction. Unit root tests and cointegration
analysis, is one of these new techniques that after its
introduction has widely adopted to test PPP in most of
recent studies.
Pourkalbassi et al . 7351
Debates on validity of PPP theory among different
economics based on their level of advancement, has
created a rationale on conducting some of PPP tests. In
context of Malaysia, to the best of our knowledge,
previous related researches that focus solely on Malaysia
has been done only by Gan (1991), Khoon and Mithani
(2000). Gan (1991) finds no relationship between real
effective exchange rate and relative price of tradable
goods. Similar conclusion is arrived in a later study by
Khoon and Mithani (2000) who found that Malaysian’s
real exchange rate follow a random walk implying the
invalidity of PPP. Others studies in a multi-countries
context with the inclusion of Malaysia are also limited.
Among others, Manzur (1995) finds that PPP holds
poorly in the short run but quite well in the long run in
Malaysia and four other selected South East Asian
countries. Bahmani-Oskooee (1993) and Baharumshah
et al (1997) also obtain, among other countries, a weak
evidence of long-run PPP in Malaysia. Their results are in
contrary to Kim (1993) who rejects the PPP hypothesis in
Malaysia and Singapore using the Johansen and Juselius
(1990) method.
Recently, Razzaghipour et al. (2001) use statistical
analysis to study the mean-reversion to PPP in the Asian
currencies including Malaysian Ringgit and obtain
empirical support for PPP, although not statistically
significant. Meanwhile, Azali et al. (2001) are able to
provide support for PPP between South East Asian
countries (including Malaysia) and the Japan using the
panel unit root and cointegration approach.
Kim et al (2009) in a recent study, use a time-varying
coefficient cointegration model to test for purchasing
power parity (PPP) of Southeast Asian currencies and to
track changes in purchasing power relationships over
time. From one of their main empirical findings, the
stability of the relationship between exchange rates and
price differentials is strongly rejected.
EMPIRICAL METHODOLOGY
A fundamental concept of PPP is the relation between domestic
and foreign prices. The purchasing power parity is written as:
Pd = S × Pf
which says that the domestic price level is equal to the foreign price
level multiplied by the exchange rate. Of course, the exchange rate
is defined as direct quotation. The expression can be rewritten to
say that the exchange rate should be equal to the price ratio:
S = Pd ÷
Pf
Under fixed exchange rates, the first expression could be used to
determine domestic prices. The second expression gives us the
‘equilibrium’ exchange rate under floating rates.
It is often convenient to write PPP in logarithmic form, to get, in
this case, a linear expression for the exchange rate:

7352 Afr. J. Bus. Manage.
ln S = ln P − ln P
d f
Or, using small letters for logs;
s = pd − p f
The basic assumption is that goods arbitrage will equalize the
prices of domestic and foreign goods. PPP comes in different
forms. Going to the extreme, the study has the law of one price. To
get to the law-of one price for all goods it need:
All goods (includes services) should be tradable
No tariffs or transportation costs
Taxes should be the same
Tastes must be the same, leading to identical domestic and foreign
consumption baskets
The productivity level and growth should be the same.
If these conditions hold, the study talks about absolute PPP
(APPP). These are of course, extreme assumptions. The study
might assume that the deviations are given once and for all. A
constant deviation can be represented with a constant term (a). In
addition, it can assume stochastic stationary deviations (ε). The
PPP equation for explaining the exchange rate becomes:
ln S = a + ln P − ln P + ε
d f
where (ε) is a stochastic term with mean zero, E( ε ) = 0 . The study
differs between APPP, PPP (the more general form) and later
relative PPP.
Over the years, people have tried a number of different price
indexes. Here is a list: CPI, WSP (whole sale prices), export over
import prices (=Terms of Trade), unit labor costs, indexes consisting
of only tradables, indexes consisting of only non-tradables.
The Economist even publishes a Big-Mac index.
A version of PPP is relative PPP, which builds on comparing
inflation rates and rates of depreciations instead:
∆ ln S = ∆ ln P − ∆ ln P
d f
If the domestic inflation increases faster than the foreign one, the
outcome is depreciation of the exchange rate. Making the same
assumptions as for PPP regarding constant and stochastic
deviations the relation becomes:
∆ ln S = a + ∆ ln P − ∆ ln P + ε
d f
The main difference between PPP and relative PPP is that the
former assumes that price levels tend to move together in the long
run. Under relative PPP, the price levels can move independent of
each other in the long run, and only the inflation rates are assumed
to move together. Absolute PPP does not hold empirically unless
there is a study for long periods (20 years) or augment the equation
with other variables like the interest rate differentials and oil-prices.
Still, it will be a long run relation (of course the study has to allow for
a constant term and dummies for tax changes). Relative PPP holds
often among fixed exchange rates in the sense that these countries
have the similar inflation rates. Countries with fixed exchange rates
cannot have different inflation rates for a long time. For floating
exchange rates, the relationship is mostly weak.
Hence, in the study , th e last equation to test whether relative
PPP holds on span of data was used. To test the validity of relative
Purchasing Power Parity as a prediction tool in short time, the study
calculates the amount of PPP-implied for the time series. Based on
relative PPP theory, the study found that:
∆ ln S = ∆ ln P − ∆ ln P
This formula in simple form based on inflation data and can be
expressed as:
∆ S = Id − I f
The formula explains that expected percentage change in
exchange rate should be equal to inflation difference between
domestic (home) country and foreign country if relative PPP holds:
To apply above formula, the study need to figure out inflation rates
from the time series data of price levels. The inflation equation
based on price level is:
By applying this equation, the study figures out monthly inflation
rates for Malaysia and US on our span of data (to calculate inflation
of each month, each month’s CPI should be deducted by CPI of
previous year at same month). Then by applying relative PPP
equation and determined inflation rates, the study estimate PPPimplied
exchange rates for Malaysia and US.
EMPIRICAL RESULTS AND ANALYSIS
Data set
d f
S − S
∆ S = I − I → × 100 = I − I
t t−1
d f
St
−1
d f
St−1
→ St = St−1 + × ( Id − I f )
100
Inflation
CPI − CPI
CPI
t t−1
= ×
t−1
100
In order to have enough sample observation to validate
the relative PPP in short term, the study use monthly
data. Therefore, it selects forty five samples of observations
starting from year 2005 on the pair of currencies.
Data for this study are obtained from various sources. For
inflation rate, that is, percentage change in Consumer
Price Index (CPI), it extracts the required data from
International Financial statistics (IFS) CD- ROM. Also, for
price level or price index data, the study use same
database from IFS. For actual monthly exchange rate, it
obtains required data from PACIFIC Exchange Rate
Service which offers a trustable database service for
academic research and teaching purposes. For the
purpose of this study, the three macroeconomic data: a)
CPI (Consumer Price Index) percentage changes as the

Table 1. Estimated PPP-implied exchange rate.
Pourkalbassi et al . 7353
No. Date Actual MYR/USD Inf MY Inf US PPP-Impl MYR/USD No. Date Actual MYR/USD Inf MY Inf US PPP-Impl MYR/USD
1 Jul-05 3.7866 2.93 3.17 3.79 24 Jun-07 3.4457 1.45 2.69 3.36
2 Aug-05 3.7601 3.65 3.64 3.79 25 Jul-07 3.4406 1.63 2.36 3.42
3 Sep-05 3.7691 3.47 4.69 3.71 26 Aug-07 3.4846 1.92 1.97 3.44
4 Oct-05 3.773 3.09 4.35 3.72 27 Sep-07 3.471 1.83 2.76 3.45
5 Nov-05 3.7784 3.31 3.46 3.77 28 Oct-07 3.3736 1.92 3.54 3.41
6 Dec-05 3.7792 3.22 3.42 3.77 29 Nov-07 3.357 2.3 4.31 3.31
7 Jan-06 3.7514 3.25 3.99 3.75 30 Dec-07 3.334 2.39 4.08 3.30
8 Feb-06 3.7266 3.24 3.60 3.74 31 Jan-08 3.2674 2.28 4.28 3.27
9 Mar-06 3.7034 4.76 3.36 3.78 32 Feb-08 3.2238 2.66 4.03 3.22
10 Apr-06 3.6613 4.55 3.55 3.74 33 Mar-08 3.1865 2.76 3.98 3.18
11 May-06 3.6105 3.91 4.17 3.65 34 Apr-08 3.1624 3.05 3.94 3.16
12 Jun-06 3.6652 3.90 4.32 3.60 35 May-08 3.2155 3.81 4.18 3.15
13 Jul-06 3.6687 4.1 4.15 3.66 36 Jun-08 3.2577 7.69 5.02 3.30
14 Aug-06 3.6754 3.28 3.82 3.65 37 Jul-08 3.2499 8.51 5.6 3.35
15 Sep-06 3.673 3.27 2.06 3.72 38 Aug-08 3.3323 8.5 5.37 3.35
16 Oct-06 3.6779 3.07 1.31 3.74 39 Sep-08 3.4447 8.21 4.94 3.44
17 Nov-06 3.6434 2.96 1.97 3.71 40 Oct-08 3.5225 7.63 3.66 3.58
18 Dec-06 3.5502 3.05 2.54 3.66 41 Nov-08 3.5883 5.71 1.07 3.69
19 Jan-07 3.5076 3.24 2.08 3.59 42 Dec-08 3.5539 4.39 0.09 3.74
20 Feb-07 3.4959 3.14 2.42 3.53 43 Jan-09 3.5732 3.91 0.03 3.69
21 Mar-07 3.49 1.55 2.78 3.45 44 Feb-09 3.6356 3.71 0.24 3.70
22 Apr-07 3.4371 1.55 2.57 3.45 45 Mar-09 3.6749 3.52 -0.38 3.78
23 May-07 3.4031 1.45 2.69 3.39
indicator of the inflation rate for each country. b)
Price level or Index that is the same Consumer
Price Index but not in percentage or differential
format. c) Actual exchange rate for each country,
was chosen.
Results via correlation testing and observation
The study calculates the PPP-implied exchange
rate on the span of data by applying the proposed
relative PPP equation.
Table 1 shows the actual value of exchange
rate along with the PPP-implied exchange rate. It
shows the comparison of differences in the inflation
rate of home country (Malaysia) and foreign
country (USA), which is assumed to be equal to
the percentage change in exchange rates, and the
actual percent change in the exchange rate.
Same result has been shown in Figure 1 to
reveal the relation between actual and PPPimplied
exchange rates observably. According to
Figure 1, it seems that the study have satisfactory
results for supporting relative PPP, even though it
notices some deviations. To have a deeper
analysis on deviations, the study goes through
equations further presented to figure out percent
deviation of actual exchange rate from the
theoretically calculated PPP-implied exchange
rate:
data points
i= 1
Arithmetic Mean =
number of data points (n)
n
∑

7354 Afr. J. Bus. Manage.
Figure 1. Actual exchange rate vs. estimated PPP-implied rate.
Table 2. Percent deviation and percent error of PPP-implied exchange rate.
Date % Deviation % Error Date % Deviation % Error Date % Deviation % Error
Jul-05 6.24 0.09 Oct-06 3.42 1.66 Jan-08 8.64 0.08
Aug-05 5.54 0.79 Nov-06 2.52 1.8 Feb-08 10.13 0.12
Sep-05 5.91 1.59 Dec-06 0.01 3 Mar-08 11.43 0.2
Oct-05 5.99 1.42 Jan-07 1.18 2.3 Apr-08 12.27 0.08
Nov-05 6.06 0.22 Feb-07 1.53 0.97 May-08 10.62 2.08
Dec-05 6.08 0.24 Mar-07 1.74 1.16 Jun-08 8.86 1.28
Jan-06 5.37 0.04 Apr-07 3.27 0.37 Jul-08 8.96 2.99
Feb-06 4.72 0.36 May-07 4.33 0.39 Aug-08 6.5 0.53
Mar-06 4.06 2.03 Jun-07 3.1 2.55 Sep-08 3.06 0.14
Apr-06 2.98 2.1 Jul-07 3.2 0.6 Oct-08 0.77 1.61
May-06 1.66 1.08 Aug-07 1.9 1.3 Nov-08 1.04 2.76
Jun-06 3.2 1.81 Sep-07 2.29 0.61 Dec-08 0.1 4.98
Jul-06 3.24 0.24 Oct-07 5.17 1.07 Jan-09 0.63 3.17
Aug-06 3.44 0.7 Nov-07 5.83 1.42 Feb-09 2.31 1.74
Sep-06 3.31 1.26 Dec-07 6.55 1.03 Mar-09 3.3 2.78
Error = PPPImplied exchange rate - Actual exchange rate
Error
Percent Error = 100
Actual Exchange Rate ×
Deviation = PPPImplied exchange rate - Arithmetic Mean
Deviation
Percent Deviation = 100
Actual Exchange Rate ×
Through the stated formulas, the percent deviation and
percent error in PPP-implied exchange rate and actual
exchange rate are calculated and summarized in Table 2.
Regarding the deviations from PPP, there are mainly
three points to be explained. First, deviations in prices
can take place because of shipping costs and tariffs.
Since international trade involves shipping goods across
national borders, prices may differ due to shipping costs
or tariffs. Second, it is because of temporary deviations,
which result from the differential speed of adjustment
between financial-asset markets and goods markets or
real relative price changes. Relating to this factor, the

Table 3. Statistical results (Number of observations: 45).
Pourkalbassi et al . 7355
Variable Mean Variance S.D.
Actual MYR/USD 3.528493333 0.033502534 0.183036973
PPP-Implied MYR/USD 3.547777778 0.03941284 0.198526672
Correlation matrix:
Actual MYR/USD PPP-Implied MYR/USD
Actual MYR/USD 1 0.957325 (0.0000)
PPP-Implied MYR/USD 0.957325 [0.0000] 1
different speeds in the changes of price and the exchange
rate are pointed out, which are caused by some
exogenous factors. Moreover, the exchange rate tends to
adjust to important economic factors more promptly,
while prices lag behind. It is said: ’periods with important
economic news will be periods when PPP deviations are
large.’ Using this point, Jacob A. Frankel demonstrated
’The Collapse of Purchasing Power Parity during the
1970s’ in 1981. Third, it is the appearance of deviations.
They result from comparing the current exchange rates
with price set in the past or using national price indexes
when countries consume different baskets of goods.
They reveal that there is a lag between order and delivery
in international trade, and price indexes are not directly
comparable internationally since tastes of consumers in
different countries are different.
Test of relative PPP via statistics and hypothesis
Besides these casual observations, to have a more
objective analysis, the study uses the statistical methods.
Using the differentiated equation:
S
S S Inf Inf
100
t −1
t = t −1
+ × ( MY −
US )
The study defines that if PPP theory holds, the real
exchange rate should be equal to PPP-implied exchange
rate. However, as has already been noticed, there are
deviations the relations cannot be exactly equal. By using
the hypothesis testing of correlation between them, it can
be decided on statistical significance of these
relationships:
H0: ρ=0 there is no correlation between the real rate and
the PPP-implied exchange rate
Ha: ρ≠0 there is no correlation between the real rate and
the PPP-implied exchange rate.
If there is statistically significant correlation between the
real exchange rate and the PPP-implied exchange rate,
the study will reject Ho from this hypothesis.
The Table 3 shows the result of statistical test on the
pair of currency with confidence level of 95%. Pearson
correlation between the real exchange rate and the PPPimplied
exchange rate is 0.957325 and significance (2tailed)
is 0.000 [using p = 0.05 level]
Since there is a high positive correlation between the
real exchange rate and the PPP-implied exchange rate,
Ho can be rejected. The risk that will be taken in rejecting
Ho is very low, which is 0.000 using 0.05 level of p.
Therefore, the study concludes that, there is statistically
significant correlation between the actual exchange rate
and the PPP-implied exchange rate on the pair of
currencies.
SUMMARY AND CONCLUSION
Exchange rates are important to innumerable economic
activities. Tourists care about the value of their home
currency abroad. Investors care about the effect of
exchange rate fluctuation on their international portfolios.
Central banks care about the value of their international
reserves and open positions in foreign currency as well
as about the impact of exchange rate fluctuation on their
inflation objectives. Governments care about the prices of
exports and imports and the domestic currency value of
debt payments. Markets care both directly and indirectly,
since exchange-rate shifts can affect all sorts of other
asset prices. Exchange rates often swing wildly on a daily
basis for reasons that apparently have connection to
economic and financial variables. In this study, a simple
test of the relative Purchasing Power Parity (RPPP) to
explain the exchange rate behavior in short time was run.
The study concludes that, since there are high correlations
between the real exchange rate and the PPPimplied
exchange rate, there is statistically significant
correlation between the actual exchange rate and the
PPP-implied exchange rate. So, it can be said that there
is a statistically significant correlation between the
change in the exchange rate and the percentage change
in the price level of two countries. Therefore, PPP can
serve to explain the changes in the exchange rate
between two countries significantly. Further, the study
explained that there are many factors that cause deviations
from PPP, and large deviations can be considered
as invalidity of PPP. Some factors are permanently
avoidable, such as, freight costs for international trade,

7356 Afr. J. Bus. Manage.
but some are not avoidable to a certain period such as
the effect of big economic news. Considering these
aspects, the study cannot deny that it has different results
by using different data, periods, countries and methodlogies.
However, PPP can still be used as a basis for
economic policy decision, because it can bear satisfactory
results for certain countries or periods.
REFERENCES
Azali M, Habibullah MS (2001). Does PPP hold between Asian and
Japanese economies? Evidence using panel unit root and panel
cointegration. Japan World Econ., 13: 35-50.
Baharumshah AZ, Ariff M (1997). Purchasing power parity in
Southeast Asian countries economies. Asian Econ. J., 11: 141-
153.
Bahmani-Oskooee M (1998). Do exchange rates follow a random
walk process in Middle Eastern countries?. Econ. Letters., 58(3):
339-344.
Gan BW (1991). On the deviations from purchasing power parity: the
case of the Ringgit effective exchange rate. Appl. Econ., 23: 1461-
1471.
Cassel G (1916). The present situation of the foreign exchanges.
Econ. J., 26: 62-65.
Davutyan N, Pippenger J (1985). Purchasing power parity did not
collapse during the 1970s. Am. Econ. Rev., 75(5): 1151-1158.
Dornbusch R (1976). Expectations and Exchange Rate Dynamics. J.
Pol. Econ., 84: 1161-1176.
Frenkel JA (1981). The collapse of purchasing power parities during
the 1970's. Eur. Econ. Rev., 16: 145-165.
Johansen S, Juselius K (1990). Maximum likelihood estimation and
inference on cointegration with application on demand for money.
Oxf. Bull. Econ. Stat., 52: 169-210.
Kim BJC (1993). Test of the long-run purchasing power parity: the
case of some Pacific-Rim countries. In: Pan Pacific Business
Association (Eds.). Proceedings of the Pan Pacific Conference on
A Business, Economic, Technological and Educational Exchange.
Beijing, pp. 370-372.
Kim BH, Kim HK (2009). The purchasing power parity of Southeast
Asian currencies: A time-varying coefficient approach. Econ.
Model., 26: 96-106.
Khoon GS, Mithani DM (2000). Deviation from Purchasing Power
Parity: Evidence from Malaysia, 1973–1997. Asian Econ. J., 14:
71-85.
Manzur M, Ariff M (1995). Purchasing power parity: new methods
and extensions. Appl. Finan. Econ., 5: 19-26.
Razzaghipour A, Fleming G, Heaney R (2001). Deviations and mean
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1997. Appl. Econ., 33: 1093-1100.

African Journal of Business Management Vol. 5(17), pp. 7357-7366, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.019
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
The Effect of tourism web page design on browser's
attitude and visit intention
Yu-Shan Lin
Department of Information Science and Management Systems, National Taitung University, Taiwan (R.O.C).
E-mail: ysl.nttu@gmail.com. Tel: +886 89 353805. Fax: +886 89 356418.
Accepted 31 March, 2011
This study investigated the influence of different types of web page design on browsers’ attitudes,
figured out if information-processing styles play moderating roles, and examined the relationship
between attitude towards the web page and visit intention. This research specifically designed three
web pages, created in different types, words only, pictures only, and a combination of words and
pictures. Respondents were undergraduate students, and answered questionnaires online. This
research found no significant difference between high and low need for cognition (NFC) individuals in
terms of attitude towards the web page when the web page was presented in words design. A higher
level of attitude was associated with high PFA individuals when the web page presented in pictures
design. Individuals with high NFC and high PFA were significantly different from the other groups when
the web page presented in combination design. At last, a positive correlation existed between attitude
towards the web page and visit intention.
Key words: Attitude towards the web page, visit intention, web page design, information processing styles.
INTRODUCTION
The prevalence of network technology increases the proportion
of internet users each year. The internet has
become the main channel for seeking and disseminating
information. Many people browse the internet to obtain
information they want. According to the 2007 statistics of
the Taiwan Tourism Bureau, 73% of visitors to Taiwan had
seen official advertisements promoting Taiwan tourism on
the Internet before choosing to visit Taiwan (a percentage
that trailed those who had seen such advertisements on
TV, radio, magazines, or books) (Tourism Bureau, 2008).
A 2008 survey showed that 76% of visitors to Taiwan had
seen advertisements or reports promoting Taiwan tourism
on the Internet before they visited Taiwan (Tourism
Bureau, 2009). The survey results demonstrate the
growing importance of the internet to travelers in seeking
relative tourism information. Therefore, designing
effective websites is a key ingredient to creating ideal
tourists.
Irrespective of countries, tourism bureaus, or other
tourism promotion organizations, creating attractive
websites is a very important way to pull a large number of
potential tourists. A successful website can reach millions
of people in every corner of the world at very little cost.
For example, Taiwan Tourism Bureau invites F4, a popular
Taiwanese boy band, to promote Taiwan to Japanese
and Korean with their boyish charm, and hopes to cash in
on the band’s popularity to promote Taiwan’s tourism
industry. The F4 project is expected to cost the Taiwan
Tourism Bureau US$ 2.7 million, which covers the production
fee and the budget to buy air time in both Japan
and Korea. Although achieving certain effect, in comparison,
it seems that designing an appealing website or
web page will obtain better and remarkable economic
benefit.
Research motive and objectives
A travel decision requires large amounts of reference
information, but a lengthy web page introduction may not
draw attention. Users may have diverse preferences
about web page information displays. This study

7358 Afr. J. Bus. Manage.
investigates the influence of different types of web page
designs on browsers’ attitudes and visit intentions,
utilizing three research questions:
i. Do different web page displays lead to different
attitudes towards the web page?
ii. Do information-processing styles play moderating roles
in the influence of different types of web page designs on
browsers’ attitudes towards the web page?
iii. Is there a positive relationship between attitude
towards the web page and visit intention?
Understanding how viewers perceive web pages is
imperative. This understanding is essential for securing
and incorporating user input in the design process to
ensure effective design. Without this understanding, presenting
information on web pages will continue “in a way
that is intuitive for designers but not for end users”
(Proctor et al., 2002). Research findings should help to
design effective web pages that are more likely
processed by certain individuals because the design is
consistent with individual processing preference.
LITERATURE REVIEW
Web page design
Professional analysts and designers generally agree that
well-designed user interfaces improve web performance
and appeal, helping to convert “tourists” or “browsers” to
“residents” and “customers” (Marcus and Gould, 2000).
Researchers across disciplines agree that visual
representation in appropriate graphs could contribute to
information comprehension, problem solving, and effective
communication (Kosslyn, 1989; Schapira, Nattinger
and McHorney, 2001; Edwards et al., 2002; Tuch et al.,
2009; Blanco et al., 2010; Ganguly et al., 2010). Page
layout is the visual presentation of the web page by
means of background color, white space, horizontal and
vertical scrolling, font-size, and color, and other design
elements. The layout affects ease of use and quick
identification of page components (Becker and Mottay,
2001). Other dimensions include background music,
interaction, interface design (such as animation), etc.
Although there are many dimensions of a web page or
message design, this study only discusses the word
(verbal) and picture (visual) design of tourism web pages.
Internet marketing possesses great multimedia ability,
using words, pictures, images, and sounds. Hanna and
Millar (1997) reported that following the initial welcome
page, photographs of destinations are the most popular
website content. Standing and Vasudavan (2000) considered
that one of the major weaknesses of the Western
Cape site of South Africa is the reliance on a text description
with few photos. Photographic images of places
and attractions help form expectations regarding tour
tours during the pre-travel stage (Markwell, 1997). Photographs
on web pages are thus important in tourism
marketing.
Many tourism web pages use long descriptions to introduce
destinations, offering browsers plentiful information,
such as accommodations, traffic, shopping, entertainment,
events/activities, etc. Potential tourists form
preliminary concepts through reviewing introductions on
web pages. However, appropriately arranging web page
contents is very important to the designer in charge of
marketing. Some previous researches have touched on
the issue, focusing on various products. Adelaar et al.
(2003) explored the effects of media formats on emotions
and impulse buying intent. The results indicated that displaying
the text of lyrics had a greater effect on impulse
buying intent than showing still images of the music
video. In addition, different media formats caused emotional
responses that explain the participant’s impulse
buying intent to buy the CD. Unexpectedly, the still
images and video did not necessarily generate more
buying intention than combinations of the text and music.
Therefore, research recommends that electronic commerce
and marketing managers explore innovative ways
of integrating visual and verbal media formats for eliciting
an effective consumer response. Martin et al., (2005)
found that subjects prefer web sites with medium level
complexity, rather than high or low complexity. High
sensation seekers who prefer complex visual designs,
and low sensation seekers who prefer simple visual
designs, prefer medium complexity web sites. High needfor-cognition
subjects evaluated web sites with high
verbal and low visual complexity more favorably.
According to the above researches, effectiveness of web
page presentation modes is different according to product
categories. This study focuses on the web page for tourist
attraction, and conceptualizes the web page design as
stimuli to present in verbal (words), visual (pictures), or
combined form.
Information processing styles
Individual differences among message recipients may
lead to wide variations in the way people respond to
advertising appeals (Moore et al., 1995). The field of
attitude research has long acknowledged individual
difference as a major variable that causes variations in
attitude (Underwood and Shaughnessy, 1975). Sojka and
Giese (2001) investigated individuals’ preferences for the
visual as opposed to verbal information and explored how
those preferences relate to processing styles of personality
traits. They used the Style of Processing scale
(Childers et al., 1985) to test for preferences towards
verbal or visual information. Results showed that individuals
with a high need for cognition prefer to process
verbal information while individuals with a high need for
affect prefer to process visual information. Ruiz and

Sicilia (2004) used compact camera ads to consider
whether individuals differ in their propensity to rely on
affective, cognitive, or both systems to process information.
Three ads were very informational, very emotional,
and very informational and emotional at the same time.
Their research suggested that persuasive appeals tend to
be more effective when the nature of the appeal matches,
rather than mismatches, the individual personality-type
preferences for processing information. Results showed
that informational and informational-emotional advertising
appeals, which match consumer’s processing style
(thinking and thinking-feeling processors, respectively),
can generate more positive attitudes towards the brand,
purchase intention, and brand choice. Sojka and Giese
(2006) used different sweater (with fictitious brand name
“Enue”) ad styles (visual and verbal version) and a beach
resort ad (combination visual/verbal version) to test the
role of affect and cognition in processing visual and
verbal information. They suggested that high-affect
individuals (affective processors) respond more favorably
to a visual ad than the other groups, and individuals high
in both affect and cognition (combined processors),
respond more favorably to a combination visual/verbal
ad. In addition, an interesting question arises for products
such as clothing, perfume, and alcohol, advertised primarily
through visual means. Although occasionally, some
of these product categories might use a verbal appeal
(for example, beer that tastes great but is less filling), in
many cases, products such as clothing, perfume, and
alcohol are shown primarily in a visual format. Branded
clothing, such as Tommy Hilfiger, GAP, or Ralph Lauren,
and certain athletic wear (most notably Nike) often
feature a picture of the clothing with only the brand and
logo on the page. Although these pictures might be very
effective for individuals with high affect, what about highcognition
individuals. Are these advertisers effectively
reaching all intended audiences, or are there more effective
means to reach individuals with high cognition (Sojka
and Giese, 2006)? Therefore, different product categories
may be different in the relationship between visual/verbal
advertisements and their effectiveness, considering the
processing styles of audiences.
This study explores the relationship between visual/
verbal designs of tourism web pages and their effectiveness,
considering the processing styles of browsers. As
mentioned earlier, visual materials, such as photographs
of a destination, play an important role in tourism
marketing. Similarly, tourism information presented in text
is also essential.
Research has typically referred to personality classifications
that focus on the cognitive style (tendency to
engage in and enjoy thinking about) as the need for
cognition (NFC) (Cacioppo and Petty, 1982). Cohen et al.
(1955) defined the NFC as “a need to structure relevant
situations in meaningful, integrated ways.” A variety of
factors may contribute to involvement (for example,
situational and decision factors, personal needs, goals,
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and product characteristics), but individual and personality
characteristics such as a person’s need for
cognition, appear to be another important source of
consumer involvement. Research has identified an
individual’s need for cognition as one of the precedent
variables contributing to message involvement and
hence, the motivation to process ad messages (Andrews
et al., 1990).
Cacioppo and Petty (1982) developed the NFC scale
for researchers to distinguish between high and low NFC
individuals. Persons scoring high on the Need for Cognition
Scale, intrinsically enjoy thinking, whereas persons
scoring low on the scale tend to avoid effortful cognitive
work (Haugtvedt et al., 1992). Several studies have
validated the NFC scale with a variety of techniques
(Cacioppo and Petty, 1982, 1984; Cacioppo et al., 1983;
Lassiter et al., 1991; Petty et al., 1985; Srull et al., 1985).
More positive responses are found to be obtained in
high NFC individuals with factual appeals or more
information-dense ads and those with high-quality arguments
(Geuens and De Pelsmacker, 1998). Additional
research found that individuals with a high need for
cognition (cognitive processors), as opposed to a low
need for cognition, preferred verbal information (Martin et
al., 2005; Sojka and Giese, 2001; Venkatraman et al.,
1990) and enjoyed the problem-solving challenge presented
in verbal symbolism (Brennan and Bahn, 2006). NFC
individuals’ preference for verbal stimuli should reflect a
higher level of attitude towards the web page than would
be expressed by those low in cognition. On the contrary,
a web page with very few words that is mainly visual,
results in a similar attitude of both low and high NFC
individuals towards the web page, because it does not
present any information to process. Hence, the following
hypothesis is proposed:
H1: A higher level of attitude towards the web page (Awp)
is associated with high need for cognition (NFC)
individuals, compared with low NFC individuals, when the
tourism web page presents a word (all-verbal) design,
and no differences appear when the tourism web page
presents a picture (all-visual) design.
However, cognition represents only one processing style.
Individuals may also differ in their tendencies to process
affective or emotional stimuli (Raman et al., 1995). Conceptualized
as a complementary construct to the need for
cognition, the need for affect is an individual’s tendency
to engage in and enjoy processing feelings (Giese et al.,
1999). The Preference for Affect (PFA) scale (Sojka and
Giese, 1997) measures affective processing situations.
Larsen and Diener (1987), using the Affect Intensity
Measurement (AIM) scale (Larsen, 1984), demonstrated
that some people, compared with others, consistently
experience emotions with greater strength when exposed
to emotionally provocative stimuli. However, these individual
differences in emotional intensity tend to disappear

7360 Afr. J. Bus. Manage.
when confronting high and low affect intensive individuals
with a non-emotional stimulus (Larsen et al., 1987).
Individuals scoring high on the affect intensity measure
responded with greater emotional intensity to advertisements
with an emotional appeal (Moore and Harris, 1996;
Moore et al., 1995). Sojka and Giese (2001) found that
individuals with a high need for affect prefer to process
visual information. Martin et al. (2005) also found that
high sensation seekers prefer complex visual designs,
and low sensation seekers prefer simple visual designs.
Therefore, if individuals with high affect are truly adept at
processing visual stimuli, they might prefer a visual web
page. PFA individuals’ preference for visual stimuli should
reflect a higher level of Awp than would be expressed by
those low in affect. Hence, the following hypothesis is
proposed:
H2: A higher level of attitude towards the web page (Awp)
is associated with high PFA individuals, compared with
low PFA individuals, when the tourism web page presents
a picture (all-visual) design, and no differences appear
when the tourism web page presents a word (all-verbal)
design.
Following Sojka and Geise’s (1997) classification, it is
possible to identify four types of individuals according to
cognitive and affective processing styles. They suggested
that cognitive and affective processing systems are
independent, but can operate interactively. They conceptualized
the relationship between affect and cognition as
a biaxial grouping of four quadrants. Feeling processors
with high affect/low cognition rely on affect to make
decisions. Thinking processors with high cognition/low
affect generally prefer to think rationally and tend to rely
heavily on cognitive information. Combination processors
with high affect and high cognition are comfortable using
either processing style. Passive processors are low on
both cognitive and affective processing styles. Their
processing type is unclear.
Ruiz and Sicilia (2004) suggested that persuasive
appeals tend to be more effective when the nature of the
appeal matches the individual personality-type
preferences for processing information. For combination
processors, advertising appeals based on information
and emotions, obtained better results. Informationalemotional
advertising appeals, which match consumer’s
processing style (combination processors), can generate
attitudes that are more positive towards the brand,
purchase intention, and brand choice. Similarly, this work
proposes that a web page presenting in combined words
and pictures (verbal and visual), which matches the processing
style of combination processors (high NFC/high
PFA), can generate a higher level of attitude towards the
web page (Awp). Hence, the following hypothesis is
proposed:
H3: A higher level of attitude towards the web page (Awp)
is associated with individuals with high NFC and high
PFA, compared with the other processor groups, when
the tourism web page presents a combination (words and
pictures) design.
Website effectiveness
To measure advertisement effectiveness, past research
used attitude towards the ad, attitude towards the brand,
and purchase intention (Ruiz and Sicilia, 2004). Singh
and Dalal (1999) conceptually and empirically showed
how home pages are similar to ads. The measures of
website effectiveness can borrow from the measures of
advertisement effectiveness. Martin et al. (2005) used
brand attitudes, website attitudes, and purchase intentions
to make website evaluations. Singh et al. (2005)
suggested that the proposed model (Feelings→
Evaluations→ Attitude towards Web Page→ Behavioral
Intentions) provides an adequate means to characterize
web page perception. The current study uses attitude
towards the web page (Awp) and visit intention (VI) to
measure web page effectiveness.
Researchers have widely investigated the stages of
attitude formation after exposure to a stimulus (for
example, advertisement). Although there are various
arguments on the different stages of attitude formation,
this work only explores the effect of attitude on intention.
Singh et al. (2005) used fourteen, and Appiah (2006)
used eleven, 7-point semantic differential scales to measure
attitude towards the web page. Bruner and Kumar
(2000) and Stevenson et al. (2000) used three, 7-point
semantic differential scales to measure attitude towards
the website. This research adopts the latter measures.
Finally, this study tests the relationship between
attitude towards the web page and visit intention. Singh
et al. (2005) empirically proved that attitude towards the
web page has significant effect on behavioral intentions.
Therefore, we believe that attitude towards a web page
will affect browser’s visit intention. Hence, the following
hypothesis is proposed:
H4: Attitude towards the web page (Awp) has a significant
effect on visit intention (VI).
RESEARCH METHOD
Research framework
Figure 1 presents the research framework of this study. The
independent variable is tourism web page design, including three
types of web page design: words, pictures, and combined words
and pictures. The dependent variables are attitude towards the web
page (Awp) and visit intention (VI). The moderating variable is
information-processing style, including NFC and PFA.
This work proposes that the levels of attitude towards the web
page (Awp) are associated to the different information processing
styles (NFC or PFA) of subjects exposed to various tourism web
page designs (words, pictures, or combined words and pictures).
While the tourism web page design matches the information
processing style, it presumably generates a higher level of attitude

Figure 1. Research framework.
towards the web page. Subjects’ attitudes towards the web page
(Awp) supposedly have a significant effect on their visit intention (VI).
In other words, a higher level of attitude towards the web page
generates a higher degree of visit intention.
Stimulus materials: Web pages
This research specially designs three fictitious web pages since
people may have their own perceptions of real destinations, even if
they have never visited those places. Choosing existing web pages
(such as web pages of any tourism bureau) as the stimulus
materials, may give some cues for recognizing places, even after
carefully removing names of places and pictures of noted sights.
The places introduced in the three web pages should demonstrate
common characteristics to avoid any possible bias, so we
chose a simple theme of island tourism. The common characteristics
include the sea, a sandy beach, marine life, and sea
activities.
The three web pages were created in different types. Web page
type refers to the basic web page design, either textual or pictorial.
The first web page consisted of words only. The second web page
was composed of pictures only without any objective information.
The third web page contained both words and pictures, including
objective descriptions and relevant pictures. The three web pages
were the same size; presented in one page with no need to scroll
down. The first page contained nearly 560 words, the second, six
pictures, and the third, about 280 words with three pictures.
Measures
Information
The moderating variable and information-processing style included
NFC and PFA. NFC was measured via the scale developed by
Cacioppo et al. (1984). An 18-item, nine-point scale, the Need for
Cognition scale, measures the extent to which individuals seek out
and use cognitive information for decision processing across all
situations. In previous testing, the coefficient alpha for this scale
was 0.90. PFA was measured with the scale developed by Sojka
and Giese (1997). The 13-item, nine-point scale, measures
affective processing, and the coefficient alpha of the scale was
0.9136 and 0.8721 of different samples in Sojka and Giese’s study.
The dependent variables related to the concept of web page
promotion effectiveness, were attitude towards the web page and
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visit intention. Each was assessed using nine-point scales. “I like
the web page”, “I think it is a good web page”, and “I think it is a
nice web page” are used for measuring Awp (Bruner and Kumar,
2000; Stevenson et al., 2000). The degree to persons would
consider visiting a destination, the likelihood that they would visit
the destination, and their willingness to visit the destination were
used for measuring VI (Xing and Chalip, 2006).
Pretest
An online questionnaire system was developed specifically for this
study. A pretest was conducted before the actual experiment.
Subjects (not included in the main experiment) were asked to
answer the online questionnaire individually. One purpose of the
pretest was to test if the questionnaire was easy to understand and
if any ambiguous descriptions required some modifications. The
end of the questionnaire included an open-ended question about
unclear parts. Feedbacks from the subjects were used to fine-tune
the design of the online questionnaire. The other purpose of the
pretest was to test the consistency and stability of the measured
items in the questionnaire.
The first pretest consisted of 18 samples. A week later, a second
test included the same samples in the first pretest. Data from the
two pretests were checked by test-retest reliability. The correlation
of every item was between 0.477 and 0.946. The P-value was
almost less than 0.01 except for item 15 of NFC and item 6 of PFA,
showing high stability of the translative items of the questionnaire.
This study tested the consistency of dimensions using
Cronbach’s α. Cronbach’s α is a coefficient for testing internal
consistency, and consistency is higher when the coefficient is
higher. The Cronbach’s α of the two dimensions of information
processing styles, NFC and PFA, are between 0.962 and 0.977.
The high coefficients show high consistency of the two
dimensions.
Procedure
Participants in this study were undergraduate students, majoring in
Information Management or Computer Science and Information
Engineering. They were chosen not only because they are
considered heavy internet users, but also because the unity of
samples is necessary in our experimental design. Subjects used

7362 Afr. J. Bus. Manage.
PCs in a computer classroom to ensure a consistent high network
speed for all and used the same internet browser (that is, Internet
Explorer 8) to answer the online questionnaire. First, they were
tested by the NFC and PFA scales. Subjects then browsed one type
of web page design randomly to avoid the order effect when
browsing all three types at the same time, rated the web page
according to its verbal and visual contents (a manipulation check
confirming the stimuli are perceived as verbal, visual, or a
combination visual-verbal web page), and responded to questions
concerning their Awp and VI. At the end of the questionnaire,
participants were asked to provide their personal information, such
as gender, habits of using the Internet, etc.
Data analysis
SPSS 14 for Windows was used to perform statistical analyses. The
analysis methods mainly included descriptive statistics, ANOVA,
and regression analysis.
Reliability analysis tests were conducted on all scales. The
Cronbach’s α of NFC was 0.914, similar to Cacioppo et al. (1984)
result (α = 0.9). The Cronbach’s α of PFA was 0.918, similar to
Sojka and Giese’s (1997) result (α = 0.9136). The Cronbach’s α of
Awp was 0.909, slightly lower than Stevenson et al.’s (2000) result (α
= 0.93). The Cronbach’s α of VI was 0.929, higher than Xing and
Chalip’s (2006) result (α = 0.88).
DATA ANALYSIS AND RESULTS
Sample analysis
Three-hundred and three (303) students answered the
questionnaire, but the valid sample was 264. Those samples
with incomplete answers were sieved out from the
data pool. The ratio of valid samples was 87.1%.
Questionnaire A consisted of 64 valid samples (tested
web page of words design), 72 valid samples in Questionnaire
B (pictures design), and 128 valid samples in
Questionnaire C (combination design). The last questionnaire
had the most samples because they would be
divided into four groups. The descriptive statistics of
personal information are further listed.
Samples included 75.8% for males, and about 24.2%
for females. Ninety percent (90%) of samples had used
the internet more than four years, revealing subjects’
familiarity with the Internet. 81% of subjects accessed the
internet seven days per week, and surfed on the internet
every day. Overall, 40% of subjects accessed the internet
more than six hours per day, 17% for three hours, 13%
for four hours, and 11% for five hours. More than 80% of
subjects were heavy internet users.
Manipulation checks reinforced that participants perceived
the all-words web page to be “verbal”, the allpictures
web page to be “visual”, and the combination
(words and pictures) web page to be medium verbal/
visual (M(verbal wp) = 1.27; M(visual wp) = 6.08; M(combination wp) =
3.67).
Test of hypotheses
This study used dichotomous partitioning for the NFC and
PFA scales. One major concern in the decision to use a
median split was because of size, although previous
research has used median splits (Mantel and Kardes,
1999; Zhang, 1996), tripartite partitioning (Geuens and
De Pelsmacker, 1999), and quartile splits (Moore et al.,
1995).
Test of hypothesis 1
1. Questionnaire A (words): High vs. low NFC: The
median was 0.64 in NFC scores and was the partition of
high and low individuals. Low NFC individuals rated an
average of -0.58 and high NFC individuals rated 0.15 in
the nine-point scale (ranging from -4 to 4). The mean
difference for NFC was not statistically significant (p =
0.089 > 0.05). This means that attitude towards the web
page was not different between high and low NFC
individuals when the tourism web page was presented in
words (all-verbal) design. Thus, the first half of H1 is not
supported.
2. Questionnaire B (pictures): High vs. low NFC: The
median was 0.62 in NFC scores and was the partition of
high and low individuals. Low NFC individuals rated an
average of -0.22 and high NFC individuals rated -0.52 in
the nine-point scale (ranging from -4 to 4). The mean
difference for NFC was not statistically significant (p =
0.45 > 0.05). This means that attitude towards the web
page was not different between high and low NFC
individuals when the tourism web page was presented in
pictures (all-visual) design. Thus, the latter half of H1 is
accepted.
Test of hypothesis 2
1. Questionnaire B (pictures): High vs. low PFA: The
median was 0.96 in PFA scores and was the partition of
high and low individuals. Low PFA individuals rated an
average of -0.76 and high PFA individuals rated 0.02 in
the nine-point scale (ranging from -4 to 4). The mean
difference for PFA was statistically significant (p = 0.044
< 0.05). This means that attitude towards the web page
was different between high and low PFA individuals when
the tourism web page was presented in pictures (allvisual)
design. Thus, the first half of H2 is accepted.
2. Questionnaire A (words): High vs. low PFA: The
median was 1 in PFA scores, but values of rank 31 to 35
were all 1. We considered the distance before and after
(rank 30 and 31, rank 35 and 36) and the size of high and
low groups at the same time. The partition of high and
low individuals was 1.12. Low PFA individuals rated an
average of 0.15 and high PFA individuals rated -0.63 in
the nine-point scale (ranging from -4 to 4).
The mean difference for PFA was not statistically
significant (p = 0.069 > 0.05). This means that attitude
towards the web page was not different between high and

low PFA individuals when the tourism web page was
presented in words (all-verbal) design. The latter half of
H2 is accepted.
Test of hypothesis 3
1. Questionnaire C (combination of words and pictures):
(1) High NFC, high PFA;
(2) High NFC, low PFA;
(3) Low NFC, high PFA;
(4) Low NFC, low PFA
Subjects were divided into four groups. The NFC score
was used first to do a median split (0.7), and then the
median of PFA (1.66) was used to separate again. High
NFC/high PFA individuals rated an average of 1.33, high
NFC/low PFA individuals rated 0.11, low NFC/high PFA
individuals rated 0.37, and low NFC/low PFA individuals
rated -0.3 in the nine-point scale.
The mean difference for groups was statistically signif-
icant (p = 0 < 0.05). This means that attitude towards the
web page was different among the four groups when the
tourism web page was presented in a combination (words
and pictures) design.
To figure out the detail difference situation, a post hoc
test of multiple comparisons was processed. The result
showed that the high NFC/high PFA group was
significantly different from the other three groups. The
mean difference displayed that the high NFC/high PFA
group had the highest level of attitude towards the web
page, followed by the low NFC/high PFA group, the third
was the high NFC/low PFA group, and the low NFC/low
PFA group was the lowest level. Thus, H3 is supported.
Test of hypothesis 4
(1) Questionnaire A: Samples (n = 64) of Questionnaire A
were considered to test H4 first. The mean of VI was 0.49,
and the mean of Awp was -0.22. Then, the correlation of VI
and Awp was calculated. The coefficient of the Pearson
correlation was 0.573. The result showed a moderate
relationship between VI and Awp because the coefficient
was greater than 0.4. The dependent variable was VI,
and the independent variable was Awp. The regression
analysis result showed that the adjusted R square was
0.317, which means 31.7% of the variance was explained
by Awp. The result of ANOVA showed the regression
model was statistically significant (F (1,62) = 30.279, p =
0.000 < 0.05). The result of the coefficient estimation
showed that the estimated Beta of Awp was0.573 (t =
5.503, p = 0.000). This shows that the higher level of Awp,
the higher level of VI. H4 is supported. (2) Questionnaire
B: Samples (n = 72) of Questionnaire B were considered
to test H4. The mean of VI was 0.33, and the mean of Awp
was -0.37. Then, the correlation of VI and Awp was
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calculated. The coefficient of the Pearson correlation was
0.845. The result showed a moderate relationship
between VI and Awp because the coefficient was greater
than 0.7. The dependent variable was VI, and the
independent variable was Awp. The regression analysis
result showed that the adjusted R square was 0.710,
which means 71% of the variance was explained by Awp.
The result of ANOVA showed the regression model was
statistically significant (F (1,70) = 175.201, p = 0.000 <
0.05). The result of the coefficient estimation showed that
the estimated Beta of Awp was 0.845 (t = 13.236, p =
0.000). This shows that the higher level of Awp, the higher
level of VI. H4 is supported.
(3) Questionnaire C: Samples (n = 128) of Questionnaire
C were considered to test H4 first. The mean of VI was
0.51, and the mean of Awp was 0.39. Then, the correlation
of VI and Awp was calculated. The coefficient of the
Pearson correlation was 0.936. The result showed a high
relationship between VI and Awp because the coefficient
was greater than 0.7. The dependent variable was VI,
and the independent variable was Awp. The regression
analysis result showed that the adjusted R square was
0.874, which means 87.4% of the variance was explained
by Awp. The result of ANOVA showed the regression
model was statistically significant (F (1,126) = 883.911, p
= 0.000 < 0.05). The result of the coefficient estimation
showed that the estimated β of Awp was 0.936 (t =
29.731, p = 0.000). This shows that the higher level of
Awp, the higher level of VI. H4 is supported.
(4) The whole (Questionnaire A, B, and C): All samples (n
= 264) were considered together to test H4. The mean of
VI was 0.46, and the mean of Awp was 0.03. Then, the
correlation of VI and Awp was calculated. The coefficient
of the Pearson correlation was 0.779. The result showed
a high relationship between VI and Awp because the
coefficient was greater than 0.7. The dependent variable
was VI, and the independent variable was Awp. The
regression analysis result showed that the adjusted R
square was 0.606, which means 60.6% of the variance
was explained by Awp. The result of ANOVA showed the
regression model was statistically significant (F (1,262) =
405.55, p = 0.000 < 0.05). The result of the coefficient
estimation showed that the estimated Beta of Awp was
0.779 (t=20.138, p=0.000). This shows that the higher
level of Awp, the higher level of VI. H4 is supported.
Besides H1, other hypotheses are accepted. H1 is
partially accepted; the first half is not supported, but the
latter half is accepted.
DISCUSSION
This research finds no significant difference between high
and low NFC individuals in terms of attitude towards the
web page when the tourism web page is presented in
words (all-verbal) design. The first half of H1 is not

7364 Afr. J. Bus. Manage.
supported. The result is different from previous research
suggesting that individuals with a high need for cognition,
as opposed to a low need for cognition, prefer verbal
information (Martin et al., 2005; Sojka and Giese, 2001;
Venkatraman et al., 1990). One possible reason is that
the information quantity offered by the words web page is
not enough to make a difference. The other reason may
be that all-verbal information cannot draw attention no
matter whether viewers are high or low NFC. Although
high NFC individuals are relatively fond of thinking and
prefer verbal information theoretically, a tourism web
page full of words is not attractive. As mentioned previously,
photographs of places and attractions help form
expectations during the pre-travel stage, playing a key
role in introducing tourism web pages. However, when
the web page is only composed of pictures without any
written description, NFC individuals, irrespective of high
or low NFC, show a much lower level of attitude towards
the web page and no differences appear between them.
This is because they are not adept at and not interested
in processing visual stimuli.
The statistical analysis of the first half of H2 shows a
significant difference between high and low PFA
individuals. A higher level of attitude towards the web
page is associated with high PFA individuals, compared
with low PFA individuals, when the tourism web page
presents in pictures (all-visual) design. This proves that
high PFA individuals prefer visual designs and are adept
at processing visual stimuli. This finding supports previous
research suggesting that individuals with a high
need for affect prefer processing visual information (Sojka
and Giese, 2001) and high sensation seekers prefer
complex visual designs, and low sensation seekers prefer
simple visual designs (Martin et al., 2005). When the
tourism web page presents in words (all-verbal) design,
PFA individuals, irrespective to high or low PFA, show a
much lower level of attitude towards the web page and no
differences appear between them. This is because they
are not good at and not interested in processing verbal
stimuli.
Findings for H3 show that individuals with high NFC and
high PFA are significantly different from the other groups
(high NFC/low PFA, low NFC/high PFA, and low NFC/low
PFA) when the tourism web page presents in combination
(words and pictures) design. They show a higher
level of attitude towards the web page, compared with the
three other processor groups. The findings are the same
as Sojka and Giese’s research (2006) suggesting that
individuals, high in both affect and cognition respond
more favorably to a combination visual/verbal ad. The
result is similar to the findings of Ruiz and Sicilia (2004),
which suggested that persuasive appeals tend to be
more effective when the nature of the appeal matches the
individual personality-type preferences for processing
information. Therefore, the combination web page,
designed in verbal and visual formats simultaneously,
matches browser’s processing style (combination
processors), and generates attitudes that are more
positive towards the page.
H4 focuses on the relationship between attitude towards
the web page and visit intention. The result shows a
positive correlation between the two variables. Whether
data are tested in subgroups or the whole, a high relationship
exists between attitudes towards the web page
and visit intention, except for the subgroup of Questionnaire
A (moderate relationship). We conclude that attitude
towards the web page has a significant impact on visit
intention, namely, higher level of Awp, then a higher level
of VI. The result is similar to the findings of Stevenson et
al. (2000), Bruner and Kumar (2000), and Poh and Adam
(2002). They proved that attitude-toward-the-website has
a positive impact on purchase intention. Because the web
pages in this study are tourism introductions and not
actual products, the behavior intentions change from
purchase to visit. In short, when individuals form attitudes
that are more favorable towards a web page introducing
tourism attraction, they will show stronger intention to visit
the place.
Theoretical and practical implications
Results of this study, show a higher level of attitude when
individuals are exposed to web pages, congruent with
their information processing styles, in terms of affect. The
result cannot apply to NFC subjects because no
differences in attitude towards the web page are found
between high and low NFC individuals. The lack of visual
attractiveness in a highly informational web page (just a
list of written descriptions about tourism introduction) provokes
a lower level of attitude towards it. The result
illustrates that an all-verbal web page design is less
attractive.
Individuals high in affect may prefer pictures and
individuals high in affect and cognition prefer web pages
that contain both visual and verbal elements for them to
process. The current study proves this argument (H2 and
H3). The findings of this study offer additional support that
cognitive and affective processing systems can operate
not only independently, but also interactively (combination
processors). High NFC and high PFA individuals show
the highest level of attitude towards the web page when
viewing the combined verbal and visual design, verifying
previous research results in advertisements in web page
design, especially applied to tourism marketing.
The two classifications of information processing styles,
cognition and affect, are powerful tools for segmenting
consumers, which can guide marketing personnel or
website designers in the web page type best suited to
different groups of browsers. Therefore, various types of
web page designs can exist in different websites for
specific processor groups. In other words, web page
design should be customer-oriented or, more precisely,
browser-oriented. A country, a place, a scenic spot, or

any tourism promotion organization can create more than
one website to introduce their tourism attractions to
different segments. For example, create a website full of
pictures for browsers high in affect, and design another
website which contains both visual and verbal materials
for browsers high in affect and cognition simultaneously.
One website that fits all browsers is no longer enough to
attract and satisfy various browser demands. The attitude
towards a web page makes a great impact on visit
intention. Designing suitable web pages for specific
groups of browsers is an important way to attract them to
pay a visit.
LIMITATIONS
Web pages or message designs include many dimensions,
but this study only discusses the words (verbal)
and pictures (visual) design of tourism web pages.
Although this matches our research theme, it is still a
limitation of the study.
Some moderating variables may not be included in this
study, such as scenic spots introduced, different travel
types supplied, browser characteristics, etc. This work
focuses on the relationship between web page design
and attitude towards the web page, moderated by
information processing style (NFC and PFA). This is
another limitation.
To avoid the order effect, every participant only views
one type of web page design. Therefore, attitude towards
the web page and visit intention of the three different
groups are not comparable to determine which type of
web page design is most attractive to browsers.
FUTURE RESEARCH
As mentioned in the literature review, there are many
dimensions of web page design, such as message
framing, background color, font style, organization of text
and graphics, etc. Studies may add these dimensions to
the framework to see if some other designs perform
better for browsers with specific information processing
styles.
This study does not research passive processors (low
NFC/low PFA). What types of web page or what
combination of pictures and words will be more effective
for them? Further studies could explore this issue.
Future research should include a greater quantity of
web pages and more actual web pages, as they may be
more realistic for respondents, but should consider controlling
existing knowledge or familiarity of respondents
towards places introduced on web pages. Additional
research should experiment with different styles of
combination visual/verbal web pages and use text and
pictures in varying degrees; large picture/small text and
small picture/large text to further explore the interaction of
affect and cognition in response to visual and verbal
Lin 7365
stimulus.
Another issue for advanced research is involvement.
How do the various aspects of involvement; involvement
with a tourism web page or involvement with tourist
attraction, influence the connection between affect/
cognition and visual/verbal elements?
Investigating the mentioned issues can contribute to
tourism marketing theory and to practically applying
internet tourism marketing.
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African Journal of Business Management Vol. 5(17), pp. 7367-7374, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.039
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Evaluation of corporate social responsibility
performance standards
Grigoris Giannarakis 1 *, and Nikolaos Litinas 1 , Nikolaos Sariannidis 2
1 Department of Shipping Trade and Transport, University of the Aegean, Korai 2A, 82100, Chios, Greece.
2 Department of Financial Applications,Technological Education Institute (TEI) of West Macedonia,
Kila 50100 Kozani – Greece,
Accepted 30 May, 2011
Based on a global corporate social responsibility (CSR) standards, a comparative framework have been
produced in order to evaluate corporate social performance in national level. The nine CSR standards
are UN Global Compact, Global Reporting Initiatives guidelines, Ethibel Sustainable Index, Dow Jones
Sustainability Index, Global 100, FTSE4Good, Accountability Rating, SA8000 and World Business
Council for Sustainable Development. The procedure of analysis includes weight factors that reflect the
importance of each standard. In total, 98 countries out of 133 countries made available by the World
Economic Forum, implement at least one CSR standard. The results of the top 20 countries are
presented here. The findings show significant difference in CSR standards among the countries, which
indicate the different perceptions of the companies or needs of each country.
Key words: Corporate social responsibility, performance, standard.
INTRODUCTION
The concept of CSR and CSR performance measurement
has gained increasing attention from numerous
business-analysis authors, businesses, non governmental
organizations (NGOs) and other bodies. Different
concepts of CSR have been elaborated in order to identify
the role of business in relation to society. CSR is a
constantly changing concept which means different
things to different sectors and countries (Palazzi and
Starcher, 1997; Fafaliou et al., 2006). The World
Business Council for Sustainable Development (WBCSD)
describes CSR as “the commitment of business to contribute
to sustainable economic development, working with
employees, their families, the local community and
society at large to improve their quality of life”. Carroll
(2000) supports the idea that CSR is a multi-construct
model where companies should concentrate on multiple
stakeholders based on “if we do less than this, we should
not call it social performance”. The Commission of the
European Communities (2001) mentions that, CSR
means the implementation of stakeholders’ expectations
*Corresponding author. E-mail: ggianaris@aegean.gr. Tel: +30
22710 35200. Fax: +30 22710 35229.
in business operations on voluntary basis. Stainer (2006)
emphasizes that companies should focus, at least, on the
most important stakeholders identifying their concerns.
Stainer (2006) defines the concept of performance in
the field of CSR as the ability to achieve their objectives
in a resourceful manner and consistently. In addition, “on
the one hand, a domain of responsibility defines the
parameters of performance that are relevant and on the
other hand, performance defines a domain of responsibility”.
Organizations should concentrate their efforts both
on performance attainment and stakeholder satisfaction
even if the development of a performance measurement
model for its evaluation is becoming a very difficult procedure
(Panayiotou et al., 2009). Carroll (1991) introduces
the term corporate social performance in order to
embrace the concept of CSR and responsiveness. With a
performance perspective, companies must integrate
social goals and initiatives in their decisions. Companies
operating in different sectors and countries have
differences in the amount of their environmental and
social impact (Krut and Munis, 1998; Morhardt et al.,
2002; Palazzi and Starcher, 1997) which makes the performance
measurement a complex procedure. Globescan
(2005) reveals that in a sample of the general public from
various countries, different countries face different

7368 Afr. J. Bus. Manage.
social priorities. Even though the countries of the
European Union seem to be homogenized in many ways,
there are factors that differentiate each member
(Lazarides and Drimpetas, 2010). Each country has a
different history, a culture and traditions that could affect
the economic activity or the thoughts of individuals.
Additionally, the structure of the economies is affected by
numerous factors such as the role of the companies, the
economic policies that have been developed, the market
structure, the different law system etc. (Secchi, 2004). In
general, companies should adapt their CSR strategies to
the countries where they operate and understand the
different cultural values in each of them (Sundaram and
Black, 1992; Hofstede, 1980). Palazzi and Starcher
(1997) mention that the response to stakeholders’
expectations can be affected by the culture and country
where the company operates and this influences the CSR
pricnciples and actions. It is obvious that each country
has different social priorities and companies owe a duty
to adapt their notion of CSR to specific challenges; thus,
it is difficult to devise a broadly accepted performance
measurement methodology.
A number of CSR standards have been established in
order to homogenize the different aspects of CSR in each
country and sector. This would help to make the aspects
more reliably comparable. The development of CSR
standards represents a new framework of corporate
governance. They provide instructions for what areas,
and how a responsible company should act with regards
to its stakeholders’ expectations. However, there still
remain a vast number of standards that take into account
regional, national and sectoral characteristics in order for
companies to correspond to specific challenges.
The task of the study is to evaluate the corporate performance
concerning widely accepted CSR standards at
a national level. A national CSR standard index is constructed
by the number of companies that satisfy specific
CSR standards such as Global 100 most Sustainable
Corporations in the World, Accountability Rating,
FTSE4Good, Dow Jones Sustainable Index (DJSI),
Ethibel Sustainable Index (ESI), implementation of Global
Reporting Initiative (GRI) guidelines and SA8000, membership
in WBCSD and UN Global Compact (UNGC). It
focuses on countries that are provided by World
Economic Forum formatting a Global Competitive Index
(GCI). This study contributes to the literature in several
ways:
i. creates an aggregated score for each country
ii. investigates companies’ behavior in regards to CSR
standards from different part of economies and cultures
iii. promotes a dialogue about CSR standards and the
performance and
iv. concentrates on national level
The literature review of CSR performance measurement
and CSR standards is analyzed further. The methodological
aspects are also presented, from whence
the findings and concluding remarks are made.
LITERATURE REVIEW
CSR performance measurement
Carroll (2000) states that the assessment of CSR performance
is an important issue both for business and
society and it is the central concern of the following
authors; Hino (2006), Graafland et al. (2003, 2004),
Jollands (2006) and Krajnc and Glavic (2005).
Goodpaster (2003) notes the difficulties of making subjective
measurement of CSR performance could probably
lead to different perceptions of outcomes. By assessing
CSR performance, companies have the opportunity to
identify both their strengths and weaknesses, modify their
strategies and define opportunities for improvement (Kok
et al., 2001; Sirgy, 2002). There are five different approaches
to assess CSR performance: measurements based
on the analysis of the contents of annual reports,
pollution indices, perceptual measurements derived from
questionnaire based surveys, corporate reputation indicators
and data produced by measurement organizations
(Igalens and Gond, 2005). Maignan and Ferrell (2000)
arrange similar measurement approaches into three main
categories: expert evaluations, single- and multiple-issue
indicators and surveys of managers, while Turker (2009)
proposes approaches such as reputation indices and
databases, single- and multiple -issue indicators, content
analysis of corporate publications scales measuring CSR
at the individual level, and scales measuring CSR at the
organizational level. Hino (2006) recommends using
measurement approaches, namely, survey methodology,
reputation index and rating, and content analysis of documents.
In regards to the multiple indicators approach,
there is no single way of assessing CSR performance
(Wolfe and Aupperle, 1991), as different rating methods
are available. However, there are cases of companies
that prefer internal evaluation procedure for their performance
in order to protect valuable internal information
that could affect their competitiveness advantages.
Gjolberg (2009) introduces a CSR standards performance
measurement on national level using different
standards and initiatives such as DJSI and FTSE4Good,
Global 100 Most Sustainable Corporations, membership
in UNGC and WBCSD, sustainability reporting practices
in KPMG Sustainability Reporting Survey and the Global
Reporting Initiative and certification by ISO14001. A
national CSR index of CSR standards is elaborated by
Gjolberg (2009) for each of the twenty countries in order
to measure the performance of corporate practices and
activities.
CSR standards
A CSR standard provides transparency and evidence of
accountability. It embodies two types of challenges: the

first challenge concerns the society’s expectations and
the second one incorporates the implementation activities
in order to satisfy these expectations. However, none of
the proposed CSR standards can satisfy these challenges
simultaneously (International Institute for Sustainable
Development, 2004). The attainment of the standard
means the adoption of specific initiatives as regards the
standards’ guidelines (King et al., 2005). Most of the
companies implement a combination of standards in
order to improve their operational procedures and to
ascertain what society expects from businesses.
Numerous national and local or regional standards exist
such as Corporate Responsibility Index for UK companies,
Hellenic network for CSR for Greek companies,
Eco-Management and Audit Scheme for European companies,
Maala index and Institute Ethos for Malaysian
and Brazilian companies respectively. The globalization
of transport, communication, trade and economies forces
companies, in most cases, to select global standards in
order to attract investors and the global acceptance of
their initiatives. The standards of different organizations
are so numerous that top managers encounter problems
which ones to adopt. The selection of the CSR standard
depends not only on the internationalized orientation of
the companies but also on the comprehensiveness of the
local expectations and needs of society. The global
standards in most of the cases are more demanding than
the local ones, while the regional or local standards seem
to adapt CSR to particular conditions of the country or
region where companies operate (Muller, 2006). Companies
might consider both universal and local or regional
challenges in the field of CSR in the countries where they
operate. Most of the time such dilemmas are confronted
by multinational companies which operate in different
countries with different economic structures and cultural
traditions, thus, they incorporate in the CSR procedure
not only global standards but also national or regional
ones. Larger companies tend to integrate CSR activities
in their operations because they are more visible to
stakeholders and the cost of CSR standards, code
conducts and social reports is relatively small compared
with that of small or medium size companies (Werther
and Chandler, 2005; Graafland et al., 2003).
Description of CSR standards
This is a presentation of the most well recognized CSR
standards. The Accountability Rating rates the sustainable
development of the world’s largest companies in four
main categories, strategic intent, governance and
management, engagement and operational performance.
Each of the categories has equal importance to the performance
score. The assessment procedure includes two
stages: the first one consists of binary questions along
with sector specific questions and the second stage
incorporates more complex questions. The rating is
Giannarakis et al. 7369
based on Fortune Global 100 as published by Fortune
magazine in July. The DJSI is one of the most reliable
SRI indexes. The assessment procedure covers criteria
including economic, environmental to social aspects of
sustainable development. It incorporates both general
and sector specific criteria. The main source of information
for the assessment is the SAM questionnaire which
is completed by companies. A number of studies have
investigated the relationship between DJSI and macroeconomic
variables (Hotia et al., 2008; Sariannidis et al.,
2009, 2010). In regards to the FTSE4Good, it assesses
the CSR in five areas, working towards environmental
sustainability, developing positive relationships with
stakeholders, up-holding and supporting universal human
rights, ensuring good supply chain, labor standards and
countering bribery. FTSE4Good is excluded in the
assessment procedures of companies that generate
revenue from tobacco producers or production of nuclear
war. The importance of FTSE4Good in CSR has been
explored (Collison et al., 2009) while extensive literature
exists for FTSE4Good and economic performance
(Currana and Moran, 2007; Capelle-Blancard and
Couderc, 2009).The Global 100 index provides a list of
the top 100 most socially and environmentally aware
companies from a total of 3,000 developed and emerging
market stocks. However, it does not include indicators
from all aspects of CSR as the environmental indicators
make up the majority of total number of indicators. The
ESI evaluates the social performance covering multiple
stakeholders such as employees, customers, supplies
and the environment. A series of sectors are excluded
from the evaluation procedure such as armament, gambling,
nuclear energy, tobacco, hazardous chemicals and
genetically modified organisms.
The SA8000 standard provides the opportunity for companies
to measure their own performance and responsibly
manage their supply chains concerning the human
rights of workers developed by Social Accountability
International. The SA800 was created to enforce other
international agreements such as International Labor
Organization (ILO) conventions, the Universal Declaration
on Human Rights, and the UN Convention on the
Rights of the Child. The SA8000 covers the following
area: compensation, discipline, child labor, forced labor,
health and safety, freedom of association, discrimination,
working hours and management systems. The impact of
SA8000 standard has been analyzed and compared in
regards to other standards (Mathews, 2004; Ciliberti et
al., 2009). Members of UNGC follow ten universally
accepted principles in the areas of human rights, labour,
environment and anti-corruption that include in for major
categories human resources, labour, anti-corruption and
the environment. Several studies examine the role of
UNGC in the corporate governance and general in the
CSR field (Arevalo and Fallon, 2008; Gupta, 2007). As
regards the WBCSD, members can share CSR initiatives
working with governmental and non-governmental

Table 2. Companies and countries commitment to CSR standards.
Giannarakis et al. 7371
CSR standard Countries Companies 1 st rank 2 nd rank 3 rd rank
SA8000 55 2135 Italy India China
UNGC 90 978 Spain France Brazil
WBCSD 37 196 USA Japan Germany
GRI guidelines 44 597 Spain USA Brazil
DJSI 24 267 UK Japan France
Global 100 24 100 UK USA Canada, Australia
Accountability Rating 18 100 USA Germany France
ESI 16 127 USA Japan France
FTSE4Good 11 67 USA Japan UK
Source: Authors (2010)
members of UNGC. The Spanish companies make up
12% of UNGC, while in second place are French
companies with 9% and in the third place, Brazilian companies.
The Spanish companies are placed in the first
rank concerning GRI guidelines with USA’s companies in
the second place with 9% and Brazilian companies with
8%. Looking at the WBCSD, USA companies are placed
in the first place of rank with 19% while Japanese and
German companies are placed in the second and third
place with 12 and 7% respectively. Concerning the
Accountability Rating, USA’s companies are placed first
with 31%, in the second and third place, Dutch and
French companies can be found with 14 and 10%. As
regards the SRI of ESI and FTSE4Good, USA companies
are the majority with 27 and 29% respectively while
Japanese companies are ranked in the second place with
19 and 16%. In the Global 100 standard UK companies’
presence is 21% while the Dutch companies’ presence is
12%.
In Figure 1, there is a presentation of CSR standards
performance of the first 20 countries taking into account
the modified GCI. Nine European countries are included
among the first twenty countries while six of them belong
to Asia. USA and Canada represent North America and
Brazil which is the only country of the South America.
Even if Switzerland is the most competitive country with
regards to the GCI, it is ranked in the sixteenth place of
CSR performance standard. Italy seems to present
exceptional CSR performance, first in rank among 98
countries while it is placed in the forty eighth place of
competitiveness. Italian companies try to implement CSR
initiatives even while the business environment does not
encourage this trend. Chinese companies try to attain
both the financial development and CSR taking the third
place of performance; however, the concept of CSR has
been confused by the Chinese companies. The high
performance of Chinese companies is contrary to surveys
which conclude that the development of CSR is not
satisfactory (Kolk et al., 2010). In the fourth place of
performance is Spain, even though the implementation of
CSR is still moderate and there is no consensus in their
orientation towards CSR as shown by Mele (2004) and
de la Cruz Déniz and Suárez (2005). In France, the
government’s CSR policy plays an important role in CSR
(Fairbrass, 2008), thus, the rank of CSR performance
standard in eighth place is characterized justified.
Pakistan’s CSR standard performance is ranked in ninth
place as opposed to Naeem and Welford (2009) where
Pakistani companies fail to engage in their operation
many aspects of CSR. The multinational companies in
Pakistan use the CSR as a competitive tool (Ali et al.,
2010). The Dutch classification in eleventh rank is justified
by the fact that both Dutch government and individual
companies are active in the field of CSR challenges and
international initiatives (European Commission, 2007;
Heyder and Theuvsen, 2009). United Arab Emirates
(UAE) is distinguished by the political stability in the
Middle East area and CSR is an important business topic
and the national performance is ranked in the fifteenth
place. The financial crisis in Greece seems not to cause
Greek companies to behave with a social responsibility
towards their stakeholders, eighteenth rank; however
Greek companies are presented with low level of
effectiveness on CSR (Metaxas and Tsavdaridou, 2010).
In the twentieth place of CSR performance is Vietnam
where the relationship of Vietnamese government and
companies is important for the promotion of CSR (Uriarte,
2008).
Table 3 describes the number of countries in each
continent presenting the mean and standard deviation of
each one. The high standard deviation of each continent
except Africa suggests that further analysis of the
standard performance is crucial. The case of Africa
shows that there is a more homogeneous performance
than in other continents. The different national
performance, even if they are on the same continent, is
probably due to the fact that both cultural and legal
traditions still play a significant role in relations between
business and society (Sobczak and Martins, 2010).
In this study, Italy, Germany, Greece and USA present
exceptional or satisfactory performance results. However,
Gjolberg (2009) concludes that these companies have a

7372 Afr. J. Bus. Manage.
0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95 1
Modified GCI concerning Switzerland
Figure 1. National index of CSR standards performance (Authors, 2010).
Table 3. Descriptive statistic of companies for each continent.
Continent Number of companies CSR standards performance mean Std. Deviation
EU 33 167,4528 427,36403
Asia 28 136,0124 278,48255
Africa 16 14,6210 33,06961
South America 10 70,9607 147,53728
North America 9 92,6514 156,14135
Oceania 2 104,3505 129,77255
Total 98 115,5142 298,64041
Source: Authors (2010).
negative score concerning the CSR standards. In
Gjolberg’s (2009) results, Switzerland is placed first,
while in this study, the CSR standard performance is simply
satisfactory. Gjolberg (2009) places Sweden, Finland
and Norway as high performance countries; however, this
study evaluates them in 24 th , 29 th and 31 th rank of performance
respectively. Finally, in both studies, UK, France,
Australia and Spain attain positive CSR performance.
Conclusions
The assessment of CSR performance has received great
attention by scientists, practitioners and organizations.
The study aims to measure and evaluate the CSR
standards performance of companies at a national level
presented by GCI. The evaluation procedure is based on
nine global standards that cover all aspects of CSR
where a national index for each country is created. CSR
standards recommend ethical rules of business conduct
regarding CSR aspects. The evaluation of CSR performance
at a national level is a complex procedure as
companies should adapt their social responsibility to
specific needs and trends of societies where they
operate; however, there is a need for companies to certificate
by well recognized CSR standards in order to implement
acceptable CSR initiatives globally. A standard is
a mean for companies to demonstrate their engagement

to CSR clearly and reliably.
The study constructs a national CSR standards performance
index which indicates the CSR trend of countries
that are provided by GCI. Dutch, Italian, French and
Japanese companies are generally known as socially
responsible and this fact which is reflected in the rank
classification. The high performance of Pakistan, China,
Greece and Vietnam could be characterized as a surprise.
The differences among the countries’ performance
is probably own to the fact that companies prefer to
select regional or local standards to satisfy the specific
challenges of each country. Most of the Gjølberg’s (2009)
findings are not consistent with this study showing the
adoption of GCI rather than GNP in order to correct and
weight the results and that the adoption of three new
standards such as Accountability Rating, ESI and
SA8000 play a crucial role in the classification of CSR
standards performance. Further studies are needed in
order to specify which CSR standards should be included
in a national CSR standards performance and how
regional or local standards are internationally oriented.
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2010-11.pdf

African Journal of Business Management Vol. 5(17), pp. 7375-7385, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.064
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Integrating codesign into new product innovation:
Consumer-driven online game optiomization design
Chi-Shun Liao
Hsin Sheng College of Medical Care and Management, 418 Gaoping Sec., Jhongfong Rd., Longtan Township, Taoyuan
County, Taiwan 32544, R.O.C. E-mail: naylor.shun@msa.hinet.net.
Accepted 13 May, 2011
This article issues an introductory argument that codesign techniques can bridge theory and practice
for online game designs, by providing content and methodological knowledge that guides the design
process. To address the complexity and challenges of online game designs, a game designer should
adopt new approach that is suitable for individual consumers and rely on consumer codesign efforts to
transform users’ perceptions into online game elements. This study suggests a unique method that
enables managers to understand new online game service codesign structures and make service
design decisions that integrate optimum individualized designs.
Key words: Codesign, online games, innovation, massive multiplayer online role-playing games (MMORPGs).
INTRODUCTION
Consumers can play key roles in shaping the development
of new products. For example, an increasingly
popular method involves consumers in the early stages of
the new product development (NPD) process by inviting
them to suggest ideas for innovative products and services
(Kristensson et al., 2008). Consumers increasingly
appreciate the opportunity to design their own products
and express their self-images more effectively, which
increases consumption value. However, most product
specification processes suffer from one key weakness:
the design team lacks an adequate understanding of the
customer (Reinertsen, 1997). Most manufacturers create
a new technology and then attempt to find markets for it,
which means that they ignore what customers want from
a new product or service. Through collaborative codesign,
a manufacturer might instead, establish a dialog
with customers, help them express their needs, and
identify precise products that fulfill those needs.
The codesign concept requires manufacturers to
interact with consumers to obtain specific information that
they can use to define and translate consumers’ needs
and desires into concrete product specifications (Berger
et al., 2005). In adaptive codesign, consumers act as
designers, creating unique products from an array of
design options presented by the product manufacturer. In
this case, firm–customer interaction and adaptation, add
value. Codesign thus constitutes a foundation of a new
kind of value creation that adopts the paradigm of customer
integration (Piller et al., 2003). Yet, most studies of
consumer codesign focus on managerial practices that
support the partnership (Berger et al., 2005; Spina et al.,
2002; Zirpoli and Caputo, 2002) or identify prerequisites
for the successful involvement of suppliers in NPD
activities (Jayaram, 2008; Petersen et al., 2003; Valk and
Wynstra, 2005; Song and Di Benedetto, 2008). However,
to the extent that these processes integrate consumers’
preferences and demands with the innovative ideas
created by professional designers, they might achieve a
two-way communication path with greater utility. In collaborative
design processes, customers enter the value
creation process by defining, configuring, matching, or
modifying an individual solution (Chen and Tseng, 2007).
When codesign activities occur on dedicated interfaces,
they also allow for the joint development of products and
solutions, as demonstrated in studies that focus specifically
on product development (Chen and Tseng, 2007;
Spina et al., 2002; Zirpoli and Caputo, 2002).
In this context, the interactive nature of the internet
enables consumers to make informed service choices
more conveniently through service heterogeneity in
online environments, presents a challenge, because
consumers want to create unique designs that meet their
own specific needs. The customer-driven development of
new services is crucial for initiating new online game

7376 Afr. J. Bus. Manage.
markets for example. Because the nature of information
and communication services that support online games
varies greatly, different service designs meet different
consumer needs, and the required customer may
centricity prompt designers to turn to customer codesign.
Accordingly, industrial customers often regard designers
as sources of customized innovation.
Take the online gaming context as another example.
The popularity of massive multiplayer online role-playing
games (MMORPGs) has increased dramatically
(Meredith et al., 2009). In these genres, a vast number of
players interact in a fully developed multiplayer universe
that exists in an advanced, detailed virtual game world
(Wikipedia, 2010). However, little research investigates
these online gaming communities, despite some
prelimnary insights from various perspectives such as
psychological, sociological, and economic research
(Griffiths et al., 2004). This study aims to analyze how
consumers’ needs may drive the development of a
special class of innovative designs, namely, online game
services.
The design of a MMORPG, though not necessarily
exceptional compared with general ideas about service
design, offers several peculiarities that are worth
investigating. For example, as a dynamic developer of
new service features, an MMORPG must confront fierce
competition, demand for complex services, and a virtually
unmatched need for constant refinement and innovation.
To succeed, the MMORPG must be relatively easy for
consumers to use and easily integrate transformed processes
to attain and maintain a competitive advantage.
These attributes reveal that a unified discussion of the
design and production of MMORPG is inherently
challenging. Because of differences in players, delivery
media, and expected production values, the production of
online games also is an expensive, time-consuming, and
technically nontrivial undertaking (Dudley, 2003). Game
designers who rely on current technology must employ a
design model that limits the scope, quality, quantity, and
complexity of interactivity among players. This boundary
circumscribes both the type of games designers can
create and the resultant game’s market penetration
(D'Amora et al., 2006). Yet, design efforts persist, without
the benefit of a thorough understanding of how designers
might obtain and employ various types of consumer
information in their current and future processes (May-
Plumlee and Little, 2006). As customers continue to
demand increasing levels of performance, functionality,
and customization, firms can turn to them as sources of
both components and innovation. Because consumers
are interested in more options and personalized services,
the use of collaborative codesign might enable a firm to
establish communication with individual consumers, such
that they can express their needs and identify precise
services that would fulfill them.
Finally, this study suggests the use of conjoint analysis
(CA) during the innovation process to determine optimal
designs. This approach can identify consumers’ beliefs
about the relative contribution of certain attributes and
preference orderings for objects that represent various
attribute combinations. With CA, every combination of
attributes is a kind of service idea, and the tester is the
stimulus; these combinations provoke the overall assessment
values consumers have for a certain stimulus (Liao
and Lee, 2010). Therefore, the game designer generates
innovative ideas and puts them into practice in the
shortest possible time, then, consumers base their
evaluations on the combination of product attributes and
choose services that will offer them the maximum benefit.
This study of codesign technology attempts to
understand consumers’ preferences for online games to
enhance consumer effectiveness and help designers
meet individual consumer demands.
LITERATURE REVIEW
The role of codesign in new product development
Even the most ingenious invention fails if it does not meet
the needs of customers. Most firms assign a few
employees to work closely with customers, cocreate, and
innovate, particularly in customized designs of products
built for particular customers (Seybold, 2006). Few
companies have made customer codesign a core
competency or the starting point for all their new business
initiatives, though customer-led innovation remains one of
the most predictably successful NPD processes. Therefore,
firms need a better understanding of the process by
which designers transform information about customer
requirements into final design specifications (Bailetti and
Litva, 1995). Korsakien÷ (2009) argues that customers
should be cocreators and coproducers, because they are
more creative and valued, and offer more easily implemented
NPD ideas (Kristensson et al., 2008). Therefore,
designers should collaborate with and learn from customers,
as well as adapt to their individual and dynamic
needs.
The purpose of codesign is to make it easy for customers
to design their own ideal solutions, such that they
leverage their own knowledge and learn what is possible.
When the customer participates in the production of a
good or service, its end value increases, because the
customer can tailor the service. Such codesigns appear
increasingly popular in innovation (Vargo and Lusch,
2004); however, a paucity of research considers the
theory and practice underlying consumer codesign, for
either new products or new services. In particular, the
theoretical foundations of codesign success (for example,
methodology, critical processes) are uncertain.
Traditional approaches to innovation assume that
subject matter experts, invent, and design innovative products
to meet needs that customers may not have even
realized (Seybold, 2006). Codesign instead, encourages

consumers to participate with the trained designer and
use different components to construct personal products.
In turn, it has spread across industries (Berger et al.,
2005; Spina et al., 2002). For example, codesigning
online games may lead to more memorable experiences
that entice customers. They expect to cocreate game
service, just as they codesign the virtual worlds they
inhabit while playing the game. Through trial and error,
players build a model of the underlying game based on
empirical evidence (Wright, 2006). As they refine this
model, they begin to master the game world. Thus,
players create value simply by spending time in virtual
worlds.
The codesign process studied herein includes service
design options and computer modeling to help customers
select the options they prefer, which should foster an
engaging experience because it involves novelty, creative
expression, and an advanced technology interface. An
online game design process that relies on conjoint
analysis can also enable the consumer to choose the
game’s drama, scenes, character roles, incidental music,
player-versus-player options, armor, and skills. To ensure
maximum efficiency, the analysis also reveals which
realistic service attributes may be codesigned and
communicated more easily for realistic evaluations.
Online game service attributes and evaluative criteria
Customer assessments of service products comprise two
dimensions: core and supplementary (Anderson and
Narus, 1995). The core elements represent responses to
the customer’s need for a basic benefit; for example,
online games offer user interfaces, hotels offer lodging,
and credit cards offer revolving credit. The supplementary
service instead refers to the features that promote the
core service (for example, an online game provides an
invoice archive, and secures payment methods).
Customers primarily purchase the core services; the
supplementary services enhance their receipt of that core
service by adding value. Through synergy between the
core and supplementary services, the provider increases
overall value for customers (Goyal, 2004). Therefore,
services should represent a strong consideration for
online designers, in that consumers assess services
according to what they consider most important.
Online games’ core services include essential characteristics
(for example, game drama, scene, arms, character
roles, game rules), whereas, the supplementary services
refer to player-versus-player options, small maps, and so
forth. Luo et al. (2006) also identify attributes that
correlate with online game services: character role,
equipment, trade history, players’ historical request
records, account information retrieval, rules, and coin
trading. In addition, Chen et al. (2007) show that consumer’
preferences for online game items depend on the
joint influence of several product attributes: visual image,
Liao 7377
community communication, control form, uniqueness,
stability, interest, incidental music, and duration. Therefore,
the joint effects of various service attributes on the
final decision to use a specific service item require
consideration. When consumers use an online game,
according to Griffiths et al. (2004), they consider profession
and deity alignment, help guides, forums, combat,
character roles, magic, exploring, strategic thinking,
player-versus-player options, and social contact with
others. These services become manifest in preferences,
expectations, and quality assumptions that may be
ingrained or generalized as product prejudices. Although,
various studies use aspects of excessive and addictive
online gaming, as well as demographic factors of specific
online games (Meredith et al., 2009), few consider
customer codesign, which prevents them from including
more attributes. Furthermore, most existing studies imply
that consumers value core and supplementary services,
consistent with services research. Therefore, this study
addresses the combined influence of the following services
during the codesign process: game drama, scene,
task, character role, arms, player-versus-player option,
skill, armor, incidental music, and small maps.
METHODS
Conjoint analysis (CA) is a systematic, solution-oriented experimentation
process that designs, tests, and modifies alternative
ideas, products, or services. It assumes that a product can be
described in terms of a set of multidimensional attribute profiles and
that consumers’ decisions reflect their preferences for and overall
judgment of that set of profiles (Huang and Fu, 1995). To make
decisions, consumers must make trade-offs, because one product
does not contain all their favored attributes. The results of a CA thus
include a hypothetical product, or a particular combination of
attributes and levels, most preferred by consumers, which can be
especially useful for developing new products that mimic a hypothetical
“best” product. Most conjoint studies thus pertain to new
product design (Beane and Ennis, 1987; Green and Srinivasan,
1990), and many commercial applications derive from early CA,
mostly in the form of new product or concept evaluations,
repositioning, competitive analyses, and market segmentation.
Conjoint analyses alter the structural design of a certain factor to
create different combinations of multiple attribute standards.
Therefore, every combination is a product idea, and the tester is the
stimulus. The combinations provoke overall assessments of value
for a certain stimulus. When the respondent evaluates the
systematically varied stimulus, the use of adaptive modeling, using
part-worth models, can reveal how much each element contributes
to the overall stimulus ratings. Thus, the total utility of any defined
stimulus equals the sum of its parts, formulated as:
P
Z j = ∑
i=
1
f ( y
i
ji
)
; for
j = 1,
2,....,
n
, (1)
Z j
Where is the consumer’s preference rating for the jth stimulus;
f i is a function that represents the part-worth of each of j different
y ji
y ji
levels of the stimulus object for the ith attribute; and is the
level of the ith attribute for the jth stimulus object. In practice,

7378 Afr. J. Bus. Manage.
i ( ji ) y f
y ji
can be estimated for only a few levels of
, depending
on the research design, and the part-worths for intermediate levels
y ji
of can be obtained through linear interpolation.
The part-worth function is represented by a piecewise linear
curve that approximates any arbitrary shape of the preference
function. Furthermore, X denotes a particular alternative that can
be described as an ordered p-tuple of p attributes, such that
( 1, 2 ,......, p ), X X X X =
X ( i 1,
2,
… , p)
where i =
represents the
level of the alternative X on the ith attribute. The component utility
X ,
of i i ( i ) X U
then can be defined as:
U X ) = U ( X ) + U ( X ) + ...... + U ( X
i ( i i i1
i i2
i ik
Where
i ( im X U
),
),
(2)
m = 1, 2, …, k, is the utility of X with respect to
the mth level of the ith attribute. The additive model posits that the
total utility for an alternative X, U(X), can be expressed as:
( ) ( 1 ) 2 ( 2 ) 3 ( 3 ) ...... p ( X U
X U X U X U X U + + + + =
1 p
Equation (1) provides a means to estimate the importance and
contribution of each attribute to the total utility of an alternative, as
expressed in Equation (3). Large utilities reflect the most preferred
levels, and small utilities get assigned to the least preferred levels.
The attributes with the largest utilities are the most important for
predicting preference and represent the optimum product design.
EMPIRICAL APPLICATION
The empirical process consists of four steps: (1) determine the
attributes and levels, (2) compile the stimuli (profiles of attributes) to
present to respondents, (3) create the sampling design, and (4)
determine reliability and validity.
Selecting and defining factors and levels
With regard to the selection of service factors and levels, this study
considers several key principles. First, the factors and levels must
be communicated easily to support a realistic evaluation. Second,
the factors and levels must be realistic, meaning that the attributes
should be distinct and represent a concept that can be implemented
(Hair et al., 2006). Third, all selected factors must have high levels
of consumer attribute recognition and cover a broad spectrum, to
introduce sufficient potential heterogeneity into the factor choice.
Therefore, this study first conducted focus group interviews with
consumers, who detailed the accessories and evaluation standards
they considered when assessing online games. Three focus groups
with different consumers (N = 38 total) also revealed primary
attributes. Next, interviews with several professional designers, who
had significant MMORPG design experience and worked for game
brands, indicated design directions for MMORPG accessories.
Therefore, this study identifies important service attributes that
affect usage decisions associated with MMORPGs in Table 1. For
each attribute, the specific levels represent the characteristics of
service differentiations available in the market. The respondents
also considered the importance of each attribute in their evaluation
criteria. For each specific attribute, respondents indicated its degree
of importance, in their opinion (1 = very unimportant, 7 = very
)
(3)
Table 1. Attributes and levels for the conjoint analysis.
Attributes Levels
War
Drama
Action
Science fiction
Scene
Task
Character role
Arms
Player-versus-player option
Skill
Armor
important).
Small map
Incidental music
Design stimuli
Battlefield
Grassland
Forest
Village
Assassination
Treasure
Adventure
Combat
Warrior
Elf
Angel
Assassin
Gun/sword
Bow and arrow
Hammer
Staff
Open
Faction
Defense
Flight
Attack
Shield
Metal armor
Present
Absent
Rock music
Light music
Dance music
An innovative service design must contain the service’s critical attributes.
This study addresses 10 important attributes of MMORPGs;
using the technology provided by the designer, consumers can
select the levels of attributes that would result in an optimum

A
Liao 7379
Figure 1. Example of evaluation form, describing possible MMORPG profiles; a) drama: War. Scene: Village. Task: Treasure. Character role: Angel. Arms: Staff. Player-versus-player
option: Faction. Skill: Defense. Armor: Metal Armor. Small Map: Present. Incidental music: Light music; b) drama: Science fiction. Scene: Forest. Task: Assassination. Character role:
Warrior. Arms: Bow and arrow. Player-versus-player option: Open. Skill: Defense. Armor: Metal Armor. Small Map: Present. Incidental music: Rock music.
service. For the experimental design, this study adopts an
orthogonal array method, as developed by Bose and Bush
(1952), to identify a subset of stimuli that then structure the
interviews. Orthogonal arrays build on the Greco-Latin
square notion and develop even more highly fractionated
designs, in which all main effects can be estimated on an
un-confounded basis, assuming interaction effects can be
neglected. An orthogonal array also identifies a subset of
28 stimuli that provide the structure for the data collection
interviews (partition stimuli appear in Figure 1). Therefore,
the respondents evaluate 28 MMORPG profiles, which
consisted of the 10 attributes in Table 1, and each attribute
had one correspondent level. If respondents assigned 10
points to a profile, they would likely select this MMORPG in
their next choice. If respondents assigned 0 points, they
would probably never select the MMORPG.
Sampling design
B
The data collection relied on survey questionnaires. The
sample consisted of 320 undergraduate students. To
ensure that questionnaire items were clearly articulated, a
pilot test of the survey instrument included 30 MMORPG
players; their responses suggested several minor modifications
to the survey questions. Of the 480 questionnaires
distributed through a convenience sampling method, 340
were returned, though 20 invalid questionnaires had to be
eliminated, leaving 320 valid questionnaires. The retrieval
rate was 70.8%, and the valid return rate was 66.7%. As
the respondent characteristics in Table 2 reveal, approximately
70% of the respon-dents were women, and more
than 39.4% of the sample spent 1 to 3 h daily online. They
were very familiar with online games: 23.8% of the respondents
indicated they had at least four years of experience
with these games, and 76.6% used online games at home.

7380 Afr. J. Bus. Manage.
Reliability and validity
Table 2. Characteristics of Respondent MMORPGs.
Measure Items Percent (%)
Gender
Male
Female
30
70
Age(years)
Place of playing online games
Years of online game experience
Hours per day playing online games
The reliability measure relies on the Cronbach’s α coefficient, calculated
for all items to assess the internal consistency of the model
variables. According to Price and Mueller (1986), a standard
coefficient α of 0.60 or higher is generally acceptable. The value of
the Cronbach’s α for the observed stimuli is 0.947, which indicates
that this study achieves good consistency. The validity test
considers both external and predictive validity (Cattin and Wittink,
1982). In conjoint studies, internal validity usually pertains to the
strength of the model, which represents the utility prediction tool for
the system. External validity relates to the model’s strength, in
terms of the extent to which it applies to and across populations
outside the system (Hu, 1994). Using holdout stimuli to compare the
actual and predicted preference judgments, this study reveals that
most survey respondents (262) achieve sufficient measures of
validity. Predictive validity, computed independently for each
respondent, relies on a preference model of the product–moment
correlations between each respondent’s 28 calibration profile
evaluations and the predictions, according to the calibration model
of interest and the mean for each preference model across the 320
respondents. The mean correlation shows the conjoint model is the
most effective in terms of predictive ability (r = 0.926).
ANALYSIS AND RESULTS
The means for the MMORPG attributes for all ten items
are in Table 3. All respondents attach relatively high
levels of importance to the ten product attribute variables.
With respect to drama, they prefer “style,” “challenge,”
and “appearance.” On the scene attribute, they all prefer
“appearance” and “factuality.” For the character role (or
23 1.3
Home 76.6
Internet Cafe 20.3
Friend’s 3.1
5 31.2
5 15.6
arms), they choose “appearance” and “function,” and for
the player-versus-player option, they prefer “social
contact,” “factuality,” and “function.” “Function” is the most
often selected skill; for the armor attribute, they reveal a
preference for “function,” “appearance,” and “factuality.”
With regard to the small map (or incidental music),
respondents prefer “function” and “factuality,” and for the
task, they want “challenge” and “factuality.”
Attributes and evaluation criterion fit analysis
To identify the main evaluation criterion on which respondents
base their perceptions of attributes, this exploratory
research identifies eight relevant attributes of six evaluative
criteria. A group of respondents rated, on a sevenpoint
scale, each of the attributes according to the six
evaluative criteria. The position of each attribute in the
perceptual space then represented the average factor
score for that attribute. The vectors inserted into the
reduced perception space, which depicts both the
attribute group centroids and overlaps among groups,
enable the researcher to project group means on each
vector to reflect the relative prominence of the predictor
variable for that group. This perceptual map then reveals
that each attribute gets projected onto each evaluative
criterion vector, which reveals the degree of similarity and
quality direction of a particular evaluative criterion, as
illustrated in Figure 2. Dimension 1 contains three attribute
vectors—challenge, style, and social contact—that

Table 3. Summary statistics of the MMORPG service attributes.
Liao 7381
Attribute E.C Mean SD Mean SD Mean SD Mean SD Mean SD
Drama Scene Task Character role Arms
Factuality 4.76 2.13 5.34 1.83 4.78 1.82 5.19 1.95 5.18 1.96
Function 4.74 1.84 4.85 1.82 5.13 1.71 5.47 1.82 5.88 1.60
Appearance 5.34 1.80 5.63 1.69 4.59 1.91 5.92 1.64 5.62 1.70
Style 5.55 1.78 5.16 1.74 5.61 1.67 4.95 1.92 5.20 1.88
Challenge 5.54 1.70 5.0 1.86 5.69 1.64 5.17 1.78 5.27 1.88
Social contact 4.92 1.87 4.83 1.92 4.81 1.94 5.14 1.95 4.36 2.06
Player-versusplayer
option
Skill Armor Small map Incidental music
Factuality 5.33 1.82 5.30 1.92 5.22 1.87 5.10 2.03 5.01 2.02
Function 5.17 1.89 5.78 1.63 5.70 1.67 5.28 1.95 4.69 2.08
Appearance 4.67 1.96 5.45 1.68 5.40 1.77 5.04 1.85 4.19 2.13
Style 4.63 1.93 5.35 1.82 4.93 1.96 4.13 2.07 4.52 2.09
Challenge 4.75 1.92 5.36 1.87 5.04 1.89 4.03 2.07 4.23 2.13
Social contact 5.27 1.93 4.47 2.05 4.30 2.03 3.91 2.12 3.80 2.22
Note: E.C.= evaluation criterion.
cluster relatively closely together. The dimension thus can
be designated the sense-seeking group. Dimension 2
focuses mainly on the attribute vector of appearance,
function, and factuality; it represents sensibility
preferences.
The map in Figure 2 clearly indicates that consumers
regard task as the best element if they reside in the
sense-seeking group. It has high attribute popularity,
challenge, good social contact, and excellent style. The
next most popular attributes are appearance, function,
and factuality. The other attributes are distant from the
direction of this evaluative criterion vector, so they are
considered of inferior quality and constitute the group that
is more similar. That is, consumers believe the other
attributes do not achieve sufficient value with respect to
the three evaluation criteria, so they issue negative
evaluations.
Conjoint analysis
As noted, CA reveals the best design for personalization,
and it converts preference ratings into utilities for
hypothetical products. Utilities can be divided into the
part-worth utilities associated with each attribute level of
the service, such that the utility value represents a
respondent’s overall preference for a particular service
profile. A part-worth indicates the preference or utility
associated with a specific level of an attribute, estimated
for each respondent in a conjoint study. The utilities then
are the values predicted by the regression, and the partworth
utilities are the regression coefficients. In this way,
CA reveals the relative importance of each attribute by
considering how much difference each attribute makes to
the total utility of a product. In addition to assisting in the
development of new services, these results can assist the
design of personalized MMORPG services. For example,
as Table 4 shows, the most suitable personalized service
for respondent 1 is game 1 (science drama; village scene
and combat tasks; elf, staff arms; open; with flight skill;
shield armor; small map; rock music), according to this
person’s following attribute values: drama (9.65), scene
(25.60), task (18.70), role (6.19), arms (7.69), playerversus-player
option (2.04), skill (13.24), armor (0.51),
map (2.78), and music (13.55). Scene is the most important
attribute for predicting the preferences of respondent
1 but appears as less important for most other
respondents.
Although CA features individual respondents, the goal
generally is to summarize across a group to obtain output
similar to that in Table 5. The procedure represents the
partial utility values for each level of each attribute and a
percentage measure of their importance at both individual
and aggregate levels. Such a summary thus shows that
the most important overall attribute is game scene
(15.31%), followed by game arms (13.83%), task
(13.30%), and role (12.93%). Intermediate importance
marks music (11.06%), drama (9.19%), skill (8.58%),
small map (6.58%), player-versus-player option (4.65%),
and armor (4.52%). According to Table 5, the most
preferred combination of attributes across all respondents
is a science blended drama MMORPG that uses a forest
scene, features an adventure task and assassin role, has
guns/swords, is open to interactions, includes flight skills
in the MMORPG design, and provides a small map. This
combination gives consumers the highest total value.

7382 Afr. J. Bus. Manage.
Table 4. Utilities for subject 1.
Online
games
Utility Drama Scene Task
Character
role
Arms
Player-versusplayer
option
Skill Armor
1 6.41 Science Village Combat Elf Staff Open Flight Shield Present Rock
2 6.40 Action Grassland Combat Warrior Gun/Sword Faction Defense Metal Armor Absent Light
3 5.97 Action Grassland Adventure Elf Bow and arrow Open Defense Metal Armor Absent Light
4 5.71 Science Battlefield Treasure Elf Gun/Sword Faction Flight Metal Armor Absent Rock
5 5.56 Action Village Adventure Elf Bow and arrow Faction Attack Metal Armor Absent Light
6 5.54 Action Forest Combat Assassin Hammer Open Flight Metal Armor Present Light
7 5.19 War Forest Treasure Elf Gun/Sword Open Attack Shield Present Light
8 5.05 Action Village Adventure Angel Gun/Sword Open Defense Shield Absent Rock
9 4.89 War Grassland Assassination Assassin Staff Open Attack Metal Armor Absent Rock
10 4.82 Science Forest Assassination Warrior Bow and arrow Open Defense Metal Armor Present Rock
11 4.81 Science Village Treasure Angel Bow and arrow Open Defense Shield Present Light
12 4.76 War Grassland Adventure Warrior Bow and arrow Faction Flight Shield Present Rock
13 4.75 Science Forest Assassination Angel Staff Open Flight Metal Armor Absent Rock
14 4.73 War Battlefield Assassination Angel Hammer Open Flight Shield Absent Light
15 4.50 War Forest Combat Angel Hammer Faction Attack Metal Armor Absent Rock
16 4.41 Action Grassland Treasure Angel Bow and arrow Open Flight Metal Armor Absent Dance
17 4.29 Science Forest Adventure Assassin Staff Faction Flight Shield Absent Light
18 4.06 Science Village Assassination Angel Hammer Open Flight Shield Absent Dance
19 4.05 Action Battlefield Treasure Assassin Hammer Faction Defense Shield Present Rock
20 3.91 Science Village Treasure Warrior Hammer Faction Attack Shield Absent Dance
21 3.87 Action Forest Assassination Elf Staff Faction Defense Shield Absent Dance
22 3.85 War Battlefield Combat Assassin Bow and arrow Open Defense Shield Absent Dance
23 3.69 War Village Treasure Angel Staff Faction Defense Metal Present Light
24 3.56 Science Battlefield Assassination Angel Bow and arrow Faction Attack Shield Present Light
25 3.35 War Village Assassination Assassin Gun/Sword Faction Flight Metal Armor Present Dance
26 3.27 Science Grassland Combat Angel Gun/Sword Faction Attack Shield Present Dance
27 3.23 Science Grassland Adventure Elf Hammer Open Defense Metal Armor Present Dance
28 2.07 Action Battlefield Adventure Warrior Staff Open Attack Metal Armor Present Dance
DISCUSSION
Many designers believe that MMORPG innovation
begins with a new service idea; in turn, most innovation
studies focus on new concept generation.
Yet the diversification of demand, increasing
speed of innovation, and proliferation of choice
appears to require codesign between consumers
and service designers. Designers recognize that
consumers with great purchasing power increasingly
attempt to express their personalities
through their service designs. By extending the
Small
Map
Incidental
music
scope of attribute research and combining it with
conjoint analysis techniques, this study provides
an effective service codesign method that can
help designers understand the nature of their own
services, as well as the preferences and demands
of their consumers.

Table 5. Utilities for subject 1
Liao 7383
Online games Utility Prayer-versus-prayer option Skill Armor Small map Incidental music
1 6.41 Open Flight Shield Present Rock
2 6.40 Faction Defense Metal armor Absent Light
3 5.97 Open Defense Metal armor Absent Light
4 5.71 Faction Flight Metal armor Absent Rock
5 5.56 Faction Attack Metal armor Absent Light
6 5.54 Open Flight Metal armor Absent Light
7 5.19 Open Attack Shield Present Light
8 5.01 Open Defense Shield Absent Rock
9 4.89 Open Attack Metal armor Absent Rock
10 4.82 Open Defense Metal armor Present Rock
11 4.81 Open Defense Shield Present Light
12 4.76 Faction Flight Shield Present Rock
13 4.75 Open Flight Metal armor Absent Rock
14 4.73 Open Flight Shield Absent Light
15 4.50 Faction Attack Metal armor Absent Rock
16 4.41 Open Flight Metal armor Absent Dance
17 4.29 Faction Flight Shield Absent Light
18 4.06 Open Flight Shield Absent Dance
19 4.05 Faction Defense Shield Present Light
20 3.91 Faction Attack Shield Absent Dance
21 3.87 Faction Defense Shield Absent Dance
22 3.85 Open Defense Shield Absent Dance
23 3.69 Faction Defense Metal armor Present Light
24 3.56 Faction Attack Shield Present Light
25 3.35 Faction Flight Metal armor Present Dance
26 3.27 Faction Attack Shield Present Dance
27 3.23 Open Defense Metal armor Present Dance
28 2.07 Open Attack Metal armor Present Dance
The important attributes to consider when designing
MMORPGs include drama, scene, task, character role,
arms, player-versus-player options, skill, armor, small
maps, and incidental music. With regard to the drama, it
is important that consumers perceive a unique style when
playing the game, that it provides special challenge, and
that they consider the appearance of the game attractive.
The scene should be bright and aesthetically pleasing.
The task design should emphasize a challenge, and its
style should be centralized and unique. Regarding the
character role attribute, consumers demand that the
game and their images fit perfectly, such that the game
covers their images in full and provides an attractive
appearance, as well as centralized, firm factuality and
individual capability functions. The design of the arms
should focus on function, whereas the player-versusplayer
option should be fast in terms of factuality and
social contact. With regard to skills, players should be
able to combat the enemy effectively and adopt different
actions, with flashy moves that can attract others’
attention. The games should also offer armor functionality
that provides different forms of protection while still
appearing attractive. Finally, the design of the small map
should ensure a location function, and the incidental
music should be dulcet and inspire functions. Users
regard these attributes of game design as particularly
important, and designers should exploit them to improve
their game offerings.
An online game service–centered view of the exchange
also implies that the goal is to customize offerings,
recognize the consumer as a constant co-producer, and
strive to maximize consumer involvement to better fit his
or her needs. In codesign, ideas provide useful sources
of information to game designers, who should use
customization to design the best services for individual
consumers, decrease the risk of design failure, and
promote consumer loyalty to and satisfaction with the
product. This study provides a unique idea for
understanding the new service customization structure
and making online game design decisions integrated with
optimum individualized design. Designers should
carefully consider the level of consumer involvement and

7384 Afr. J. Bus. Manage.
Figure 2. Perceptual maps of online game attribute sets.
control over the final service; this study provides an initial
blueprint for understanding the potential implementation
of customer codesign for the game industry.
LIMITATIONS AND FURTHER RESEARCH
This study involves only one type of online game
(MMORPG), so the findings may not be valid for other
types. Another concern is that the self-selected group of
respondents consists of more serious and engaged
players, who may not reflect the MMORPG population in
general. However, customer codesign provides an appropriate
approach to study new modes of cooperation that
are relevant well beyond specific NPD niches. Because
the codesign process involves a high level of consumer
input and stimulation, some participants expressed
concern about their ability to act as designers and put
together an online design on their own. Further understanding
therefore requires codesign research that not
only considers collaborative methods but also the psychology
underlying them and their behavioral outcomes.
Online games tend to be characterized by high player
turnover, great similarity within game forms, and a poor
understanding of the need for relationships. As a result,
game designers need to develop incentive models and
install design models to move from innovation attributes
to the provision of more integrated, customized solutions.
In conjoint analysis, the relatively significant data
requirements for estimating individual utilities become
increasingly burdensome for respondents. A hybrid
model approach might offer a simple but robust approach
that uses self-explicated data to obtain a preliminary set
of individualized part-worths for each respondent. Research
should continue to use hybrid models as practical
alternatives to traditional conjoint.

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African Journal of Business Management Vol. 5(17), pp. 7385-7391,4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.109
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Measuring the impact of multiplier, to determine the
Keynesian model of income, in open economy, in the
context of Pakistan
Naveed Iqbal Syed*, Muhammad Sohail Tahir and Shamim A. Sahibzada
Department of Management Sciences, Shaheed Zulfiqar Ali Bhutto Institute of Science and Technology, H-8/4,
Islamabad, Pakistan.
Accepted 27 May 2011
The main objective of this study is to measure the impact of Keynesian four sector open economy
multiplier model in the context of Pakistan's economy and to suggest to the government how the size of
multiplier could be increased. For this purpose, 19 years time series data have been collected for
different components of the aggregate demand function of the Keynes model. Stationarity of the data
was checked by Augmented Dickey-Fuller (ADF) unit roots test. Next, the regression analysis is applied.
By Keynesian multiplier model, multiplier (K) value is obtained for each year and on the basis of
multiplier value, national income equilibrium is determined. Overall, the mean value of multiplier (K) is
equal to 0.841088 times. The significance of the model R 2 ( 0.970894) indicates that 97.08% of the
dependent variable are explained by the independent variables. This is because of the fact that there is
significant unbiasedness in the data and adjusted R 2 =0.963133 which is closer to the R 2 . The
consumption, investment and government expenditure have a significant impact on national income,
whereas the t value of net export (X) is less than two which is insignificant and may be because of
recession and fluctuation in the pattern of international demand. The coefficient of variation, t-statistic,
R 2 , and adjusted R 2 lies within the acceptable ranges. For policy recommendations, government must
provide incentives to develop industrial base in the country. Expenditure dampening policy should be
encouraged to discourage imports of luxury and unnecessary imports. Simultaneously expenditure
switching policies should be adopted by the government to find out substitutes to the expensive
imports like ethanol could be developed to decrease oil imports. The scope of the government
expenditures should be increased. The transfer payments systems like Benazir Income support
programme (BISP), Bait-ul-Mall scheme and Zakat should be improved.
Key words: Marginal propensities, multiplier, national income, John Maynard Keynes, recession, expenditure
dampening, expenditure switching.
INTRODUCTION
Economic phenomena are very complex in its nature but
are always unique in its application. Although the laws of
economics are not like natural laws, with minor changes,
model developed in one country could be easily applied
in another country or economy (Alam, 2009). The
provisions for minor adjustments are given because all
*Corresponding author. E-mail: naveediqbalshah@gmail.com.
Tel: +92-51-4863363-65. Fax: +92-51-4863367.
economic models or laws are true under ceteris paribus
conditions.
A basic proposition of the Keynesian theory is that the
equilibrium level of income and output depends upon the
economy’s aggregate spending for output. If the
aggregate spending is not sufficient to call forth the level
of output that require the employment of all variables like
workers for its production, unemployment results, and
production of goods and services falls below its potential.
If the aggregate spending is just sufficient, full employment
results, and production reaches its potential. If

7386 Afr. J. Bus. Manage.
aggregate spending, exceeds the required level, inflation
results. However, at any level of output, from that which
calls for the full employment of the labour force to that
which imposes idleness on a large part of the labour
force, it is a possible equilibrium level.
A major task of macroeconomics is the explanation of
what determines the economy’s aggregate output of
goods and services. In any time period, that output may
be equal to what can be produced with full uitilsation of
the economy’s resources or it may be something below
this. What it actually is can only be ascertained by
measurement (Alam et al., 2010). Conceptually, the
expenditure and income approaches to measurement
yield the same figure for the value of the economy’s final
output of goods and services. This total figure is broken
down to provide a framework for the use to determine
aggregate demand or expenditure function. Our expenditure
sides are the amount accounted for the expenditure
of the consumer, business, government and the rest of
the world; and the aggregate supply side are the amount
devoted to the payment of taxes, purchases of consumer
goods and services and saving.
National income determination has been a long outstanding
issue to both researchers and practitioners.
Keynes (1930) devises a comprehensive measure to
determine national income equilibrium in his famous
concept of closed and open economy, and how the increments
in national income will take place due to different
injections into the income stream like Investment (I),
government expenditures (G), and exports (X).
The main objective of this study is to measure the
impact of Keynesian four sector open economy multiplier
model in the context of Pakistan's economy and to suggest
to the government how the size of multiplier could be
increased. For this purpose, 19 years time series data
have been collected for different components of the
aggregate demand function of the Keynes model. The
main research question is: are there any significant
impacts of multipliers like investment, government expenditures
and exports on the Keynesian model (or national
income)? Literature review is followed by the introduction
section, which further leads to research objectives,
questions, hypothesis, data collection techniques,
methodology, specification of the model, discussion,
conclusion, and recommendations for the government.
LITERATURE REVIEW
According to Hassan (1960), the Keynesian-type income
multiplier has little relevance for an underdeveloped
country having extremely low elasticity of output; any
boost in autonomous investment is likely to result in the
rise in prices. This assumption of Hasan (1960) is not
true in its applied nature. Keynesian model is equally
applicable to all countries irrespective of its nature of
development. To fill this gap, we have applied Keynesian
model on a developing country like Pakistan, and the
study of Behrman (1975) supports our point of view. He
considered a nine-sector model with capacity creation
and utilization, import, export, price and wage determination.
Consumption-savings decisions are estimated for
households and nonprofit institutions, businesses, and
the government. Many aspects of government fiscal and
monetary policies are endogenous. In its specification,
the effort is made to overcome the common shortcomings
encountered in Keynesian-based national income
determination models for developing economies. The
developing countries are far from homogeneous. In terms
of almost any relevant feature, the range across countries
is enormous. Further, the suggested modifications reflect
characteristics not necessarily common to all developing
countries, but at least to a significant number of them.
Husain and Abbas (2000) report long run relationship
among money, income, and prices. Their analysis further
suggests one way causation from income to money,
implying that, probably, real factors rather than money
supply has played a major role in increasing Pakistan’s
national income. Although real income had increased in
real and monetary term but significant increase in national
income is due to inflation too. So, for national income
determination, we have taken real instead of nominal
income and other related variables. Almost same study
conducted by Holst and Sancho (1992) set a method for
analyzing the varying composition of income and
production with a social accounting matrix. Their method
was designed to show the structural components of
income and expenditure in the economy as these affect
relative incomes. It was shown that, for any defined model
of nominal income determination, a structure can be
specified which captures the affects of external shocks on
the distribution of income. It does not consider real
income determination affect such as taking into consideration,
inflation. Both studies of Husain and Abbas
(2000), Holst and Sancho (1992) did not consider the real
value or adjustment for inflation in their studies.
According to Hussain (1994), economist usually derives
multiplier for shifts in IS-Investment Saving curve and
multipliers are confined to goods market. Values of multipliers
change when the money market is brought into
consideration. Romer (2000) considered recent
development works to the disadvantage of IS-LM. This
observation suggests that it is time to revisit the question
of whether IS-LM values of multipliers will further change
when supply side is added to the IS-LM demand side
model. But this model is still suitable not only for goods
market but also for services and other segment of the
society because open/four sector model of income
determination gives better solution to all sector of the
economy. To overcome this gap, all sector of the economy
like consumption, saving, investment, taxes, government
expenditure, exports and imports are included in the
present study.
Torre et al. (2002) showed that in an economy showing

strategic complementarities and spillovers, equilibrium is
not usually unique, and certain equilibriums are inefficient.
In the Keynesian model, there is a concept of
stable equilibrium and short run fluctuations like deflationary
and inflationary gaps which could be resolved by
fiscal policy tools.
As shown by the study of Chumacero et al. (2004) and
Andini (2007), a problem of deficient effective demand
arises because the marginal propensity to consume
(MPC) is lower than one. The condition implies that the
amount of aggregate monetary savings increases as the
aggregate monetary production-income level increases. If
MPC is less then one, then the remaining part is saved.
Saving according to Keynesian model are leakages out of
the income stream which ultimately becomes injections in
the form of investment through multiplier effect. This gap
is addressed in this study by including different multipliers
like investment, government expenditures and exports.
Already, Ahmad (2008) and Feizi (2008) in their studies
emphasized the importance of Keynesian model of
income determination in the open economy, with the
introduction of a new instrument of Islamic interest free
system. In their studies, exchange rate was used as an
alternate to the interest rate because of prohibition of the
interest rate in Islamic system. Keynesian model, on the
other hand, believes that investment is autonomous, that
is, does not depend upon interest rate. It means interest
rate has no influence on the Keynesian model so their
model could directly be applied to Islamic economy.
Tcherneva (2008) argued in his study that Keynes had
a targeted demand approach to full employment. Modern
policies, aim to “close the demand gap,” were inconsistent
with the Keynesian approach on both theoretical and
practical grounds. Aggregate demand tends to boost
inflation and erode income distribution that is why true full
employment is not possible via traditional pro-growth,
pro-investment aggregate demand stimuli. This was well
understood by Keynes, who preferred targeted job creation
during expansions. But even in recessions, Keynes
did not campaign for wide-ranging aggregate demand
tools; because, different policies have different employment
creation effects. There was significant proof to argue that
Keynes had an “on the spot” approach to full
employment, where the problem of unemployment is
solved via direct job creation, irrespective of the stage of
the economic cycle these aspects are covered in this
study by adding multipliers and injections instrument in
the model.
According to Benassy (2006) and Cogan et al. (2009),
models used in practice to evaluate fiscal policy stimulus
proposals are not forceful. The multiplier effect, by which
an increase in government spending can create an
increase in consumption, is attributed to price or wage
rigidities. Government spending multipliers in an alternative
empirically estimated and widely cited new
Keynesian model are much smaller; the estimated stimulus
is extremely small just when needed most, and GDP
and employment effects are large, with private sector
Syed et al. 7387
employment impacts likely to be even smaller. According
to Polyzos et al. (2008), changes in the regional income
brought about by increases in state spending are associated
to the government spending multiplier, or to the
marginal tendency of the economy for consumption and
the marginal tendency for imports or exports per region.
In the latter study, a new variable location quotient is
used which does not exist in the actual Keynesian model.
Based upon the findings of Hussain (1994), Romer
(2000), Chumacero et al. (2004), Benassy (2006), Andini
(2007), and Cogan et al. (2009) that injections multiplier
needs to be addressed in a particular situation from
country to country because the basic structure of the
multiplier remains same, the circumstances like marginal
propensities to save, tax and imports are different in
structure and size. Based upon these findings, the main
research question is generated to be answered.
Research objectives
The main objective of this study is to measure the impact
of Keynesian four sector open economy multiplier model
in the context of Pakistan's economy and to suggest to
the government how the size of multiplier could be
increased.
Research questions
Q: Are there any significant impacts of multipliers like
investment, government expenditures and exports on the
Keynesian model (or national income)?
Research hypothesis
H0: There are no significant impacts of multipliers like
investment, government expenditures and exports on the
model Keynesian model (or National Income).
METHODOLOGY/ MODEL
1. Taking log
2. Taking real value (adjusting for inflation)
3. Stationarity – ADF-unit root test
4. Coefficient of variation
5. Regression analysis
6. Keynesian multiplier and national income formulae
Data collection
Mainly, the secondary data is used in this research study from the
period of 1990 to 2009, taking annualized data and average data
where actual annualized data was not available. The data was
taken from World Bank, State Bank of Pakistan, Economic Survey
of Pakistan, Pakistan Development Review, Federal Bureau of
Statistics Pakistan, Federal Board of Revenue, and International
Monetary Fund.

7388 Afr. J. Bus. Manage.
Analysis
Table 1. Unit root test. ADF Test Statistic for different variables.
Variable ADF K Significance (%) Critical value
Y -3.9985* (1) 1 -3.8877
C -3.2985* (1) 5 -3.0521
I -3.0885* (1) 10 -2.6672
G -5.7985* (1)
X -5.402* (1)
M -3.40 (1)
*MacKinnon critical values for rejection of hypothesis of a unit root.
This is originally Keynes (1930) model of income determination in
different sector of the economy. In this particular research paper,
we are using it to determine equilibrium level of national income in
four sector economy in Pakistan. This model has been used by
Zind (1999). Secondary data from 1990 to 2009 has been taken to
determine multiplier first and ultimately national income equilibrium
in four sector economy model in the special case of Pakistan. All
dependent and independent variables are taken on annual basis.
The data is converted into real terms by dividing it by retail price
index (RPI) of the respective years. First, stationarity of the time
series data is checked by Augmented Dickey-Fuller (ADF) unit roots
test, using e-views software package. All data was transformed into
natural log before applying the Augmented Dickey Fuller Unit Root
test.
The following further analysis is done to complete the study. To
examine relationship between national income and other independent
variables, the ordinary least square estimation technique is
applied.
In the second analysis, Keynes (1930) technique was used to
determine four sector multiplier and national income equilibrium.
Specification of the empirical model
This is the original Keynes (1930) model of income determination in
an open economy, used by Zind (1999) in his research paper to
determine multiplier and income in six member states of the Gulf
Cooperation Council (GCC):
Y= α+ C+I+G+(X-M) + UT (1)
Where, α = constant; Y = national income; C = consumption; I =
investment; G = government expenditure; X = exports; M = imports;
UT= error term.
Equation 1 is the aggregate demand or expenditure function of
Keynesian model which consider on one side of the equation Y as
national income or gross domestic product (GDP) and other side of
the equation is broken down components of Y, consumption C,
investment I, government expenditures G, exports X and imports M.
Equation 2 indicates that the national income is a dependent
variable and C, I, G, X, M are independent variables respectively:
Y= ƒ (α+ C+I+G+(X-M) + UT) (2)
Where, α = constant; Y = national income; C = consumption; I =
investment; G = government expenditure; X = exports; M = imports;
UT= error term.
Equation 3 is the four sector (open economy) National income
equilibrium determination function:
Y=
1 (Ca-cT+I+G+X- Ma)
1- c+m
(3)
Where, c = marginal propensity to consume (MPC); m = marginal
propensity to import (MPM); Ca = autonomous consumption (could
be calculated as C = Ca + cY); T = taxes; I = autonomous investment;
G = government expenditures; X = exports; M = imports; Y =
national income; Ma = autonomous imports (could be calculated as
M = Ma + mY).
Equation 4 determines the multiplier of four sector economy.
Multiplier gives the multiple times of change in national income due
to injections in the economy. Multiplier could be negative or positive
depending upon the circumstances:
K=
1
1-c+m
Where, K = multiplier; c = marginal propensity to consume; m =
marginal propensity to import.
1-MPC = MPS (5)
Where, MPC = marginal propensity to consume; MPS = marginal
propensity to save.
Equation 5 is being derived on the assumption that
MPC+MPS=1.
Unit root test
In the time series data, unit roots exist subject to stochastic trends,
which is why examining the stationarity of a time series is important.
The Augmented Dickey Fuller (Fuller, 1979) was employed to check
the non-stationarity of the series.
The rejection of null hypothesis means that the series are
stationary.
This hypothesis can be rejected by providing strong evidence
against it. Table 1 reports the results of the ADF test. Since the
ADF test statistic for different variables like national income
consumption, investment government expenditure, imports export
absolute values are greater than the critical value. The null
hypothesis of a unit root is rejected at 1% level of significance.
Therefore, all variables are stationary at first difference level.
RESULTS AND DISCUSSION
Regression analysis
To determine national income equilibrium (Table 2),
different marginal propensities are calculated like marginal
propensity to save, tax, and imports. Marginal propensities
are the first order derivative of the saving, taxes
and import equations. They explain how much saving,

Table 2. National income multiplier and equilibrium.
Syed et al. 7389
Years MPS MPT MPM K Equilibrium
1991 0.988644 0.883976 0.956779 0.36060834 517169.4
1992 0.92474 1.20386 1.188345 0.681447432 638225.2
1993 1.034163 0.977101 0.551381 2.022984597 646798.9
1994 0.970779 0.991056 1.068206 0.330028519 625368.3
1995 0.875648 1.073901 1.118914 0.759205787 608671
1996 1.148897 1.301076 1.348278 0.666463798 598417.4
1997 0.900008 1.011091 1.061301 1.176749635 669419.3
1998 0.950017 1.034807 0.83014 0.355244426 492758
1999 0.887299 0.714081 0.764715 0.42263727 590054.2
2000 1.005618 0.597816 1.017636 0.701539077 848762
2001 0.956557 0.862773 0.739465 0.390808993 3801928
2002 0.97502 0.832713 0.894962 0.370000932 3696568
2003 0.937351 0.88689 0.967428 0.358208757 3870834
2004 0.888861 0.854895 0.994988 0.365130903 3867240
2005 0.779841 0.848713 1.003403 0.932596678 3929055
2006 0.81266 0.910109 1.033112 0.362860334 4303330
2007 0.920682 1.034701 1.175496 0.319399101 4598898
2008 1.006072 1.046995 1.049981 0.322263789 7080727
2009 0.842624 1.121845 1.149492 1.227030393 7082817
Table 3. Average and coefficient of variation.
Variable K Equilibrium
Average value 0.841088 2461553
Coefficient of Variation 0.57 0.039
taxes, and imports are changed due to change in income.
While calculating marginal propensities, few results
turned out to be greater than one. These may be due to
some exogenous factor or may be due to the impact of
economic cyclical movement over the period of time, or
may be due to recession in the economy. Over all the
major portions of results are in quite acceptable range
according to the defined rules.
After calculating different propensities, four sector
multiplier (Equation 4) is calculated by using multiplier
formulae. National income equilibrium (Equation 3) is
calculated for each year over the period of time. To get
the single value of multiplier and national income equilibrium,
arithmetic mean was taken and average multiplier
and national income figures were determined (Table 3).
Overall, the value of multiplier (K) is equal to 0.841088,
which indicates that if injections like investment (I),
government expenditure (G), and net exports (X)
increase by Rs. 100, national income will increase by Rs.
100 × 0.841088 = Rs. 84.1088. This according to the present
circumstances is quite acceptable. The value of R 2
(0.970894) in this research study(Table 4) indicates that
97.08% of the dependent variable is explained by the
independent variables. This is because of the fact that
there is significant unbiasedness in the data and adjusted
R 2 = 0.963133 which is closer to the R 2 . The absolute
values of t-statistic of C, I and G, are greater than 2 (or
1.96), which are significant so we reject the null
hypothesis and accept the alternate hypothesis that C, I,
and G have an impact on the national income.
The t-statistic of X is less than two which is insignificant
which leads to the acceptance of null hypothesis that net
exports have not any significant impact on national
income and may be because of recession and fluctuation
in the pattern of international demand.
The latter may be mainly due to the number of internal
and external factors including heavy expenditures on war
against terrorism and last year’s heavy floods in the 80
years history of Pakistan. Another reason of insignificant
value of the net exports is because of power crisis is
Pakistan, besides quotas imposed by developed
countries on Pakistani exports.
In an open economy, where imports depend in part on
the level of income, the overall expansionary effect of any
increase in autonomous spending will be dampened by
the “leakage” of some part of any expansion of income
into the purchase of imports. Assume that as a result of a
rise of income in other countries there is a rise in exports

7390 Afr. J. Bus. Manage.
Table 4. Regression model.
Y α C I G X UT
-233068.1 2.8122 11.74131 12.636 -2.468 0.029
t-Statistic (-0.18341) (3.57784) (2.90566) (1.98207) (-1.088)
Prob. 0.856935 0.002747** 0.01086** 0.056*** 0.2935
R 2 0.9708
Adjusted R 2 0.9631
P-value, *Significant at 1%, ** Significant at 5%, *** Significant at 10%
of the domestic economy.
This will cause an equal initial increase in domestic
income as production is stepped up to meet increase in
foreign spending. The MPC indicates that this initial rise
in income will induce an increase in consumption expenditures,
but the MPM reveals that some of the additional
consumption expenditures will be for imported goods.
Therefore, at the second stage of the expansion process,
domestic income raises by the amount of induced
consumption expenditures less the rise in induced consumption
expenditures for imported goods. The restricted
increase in income at the second stage leads to smallest
third-stage increase in domestic income than would
otherwise be the case, because again, part of the
increased expenditures at third stage is for imported
goods. Thus, for any given increase in autonomous
spending, the size of the multiplier is reduced when there
is a positive marginal propensity to import.
Conclusion
There is global recession and the developing country like
Pakistan is severely hit by this external factor as well as
discriminatory policy of the developed countries to
impose export quotas on a country like Pakistan. This is
also one of the major factors contributing to the low value
of multiplier.
Within the country, war against terrorism, local recession
in the economy, decrease in aggregate demand,
power crisis and floods have created major hurdles in the
pace of economic development. Although the economy is
growing but the GDP growth rate is very low. This study
could be further extended by incorporating Islamic model
of interest free economy.
RECOMMENDATIONS
Keynesian model is a demand oriented model so it needs
to find out means to increase aggregate demand of the
economy. For this, individual components of the aggre-
gate demand need to be targeted. For example, if
marginal propensity to consume increases, this could
increase the value of multiplier. MPC is percentage
change in consumption due to change in income. This is
not just the consumption of consumer goods but includes
consumption of all sectors of the economy including
industrial and agricultural. If raw materials are efficiently
utilized (or consumed), this increases employment,
potential income, standard of living, economic growth and
decreases poverty beside other multiplier impacts. The
other component of the Multiplier in Pakistan is marginal
propensity to imports. It is percentage change in imports
due to change in income. High MPM is not acceptable if
imports are either consumer goods or luxury goods. But if
imports are either raw material or machinery to produce
value added products for export purpose, then this type
of imports should always be encouraged. Government
must provide incentives to develop industrial base in the
country. Expenditure dampening 1 policy should be encouraged
to discourage imports of luxury and unnecessary
purchase of goods and services simultaneously
expenditure switching 2 policies should be adopted by the
government to find out substitutes to the expensive
imports like ethanol could be developed to decrease oil
imports, industrialist should be given incentives like in
Gujranwala and Gujrat industrialists are producing those
products which would have been imported other wise like
washing machines, water pumps, etc. The scope of the
government expenditures should be increased. The transfer
payments 3 system could be improved. In Benazir,
income support programme (BISP), Bait-ul-Mall scheme
and Zakat, the distribution of funds through debit cards is
one of the major achievements to ensure transparency.
Gawadar port could be used to increase local exports
and make Pakistan a free port to encourage other
countries to use it. This would create multiplier time’s
1 Expenditure dampening policy which is also known as expenditure reducing
policy is a decreasing the consumption of imported products to ensure the
balance of payment of a country to be improved either by imposing high rate of
direct tax or by campaigns.
2 Expenditure switching policy: Encouraging people to switch to consume
domestic products rather than imported products.
3 Transfer payments: All those payments by the governments to the citizens for
which government does not ask for any return.

positive impact on employment, poverty, government
revenue, standard of living, income, etc.
Limitations
1. This is demand oriented model.
2. This is short rum model.
3. Multiplier process works only when there is sufficient
availability of consumer goods.
4. Full value of multiplier is obtained only when various
increments in investments are repeated at regular
intervals of time.
5. The full value of the multiplier can be achieved only
when there is no change in the marginal propensity to
consume (MPC) during the process of income
propagation.
6. To consider the full value of multiplier, it is assumed
that there are no time lags between the receipt income
receipt and its spending. But in the real life this is
impossible:
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African Journal of Business Management Vol. 5(17), pp. 7391-7403, 4 September, 2011
Available Online At Http://Www.Academicjournals.Org/Ajbm
DOI: 10.5897/AJBM11.126
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Transformational leadership, employee engagement
and performance: Mediating effect of psychological
ownership
Azka Ghafoor*, Tahir Masood Qureshi, M. Aslam Khan and Syed Tahir Hijazi
University of Central Punjab, Lahore, Pakistan.
Accepted 16 May, 2011
In this study, we examined the relationship between transformational leadership, employee engagement
and employee performance. Furthermore the mediating effect of psychological ownership in the
dimensions of self-efficacy, belongingness, self-identity and accountability are studied in the
relationship of these variables with employee performance. The empirical findings of data, collected
through questionnaires from sample of 270 employees and managers of telecom companies indicated
significant relationship between transformational leadership, employee engagement practices and
employee performance. Results also supported the mediation of psychological ownership in
relationship of these variables. Managerial implications and future research directions are discussed.
Key words: Transformational leadership, employee engagement, employee performance, psychological
ownership.
INTRODUCTION
Employees’ involvement in the organization is considered
a source of development and innovation. Management
practices transformational leadership style. Transformational
leadership theory explains that encouraging
positive behavior or the leader enables followers to think
bigger (Burns, 1978). Targeting follower’s interests and
abilities, transformational leadership can enhance the
follower’s commitment towards organization (Piccolo and
Calqitt, 2006). Transformational Leadership style encourages
the culture and human resource practices that
motivate employees to participate in organizational development.
These practices engage employees into their
tasks and decision making process. Transformational
leadership leads to empowerment of employees that
improves employee’s engagement (Dvir et al., 2002).
*Corresponding author. E-mail: azkamalikucp@gmail.com. Tel:
+92-42-35880007 or +923314413872.
Following this theory organization can encourage positive
work attitude and increase the quality of work (Piccolo
and Calqitt, 2006). Practicing transformational leadership
style basically develops the feeling among employees
that they mean a lot and their betterment is the purpose
of the organization. This feeling improves their organizational
attitude and ultimately the quality of work being
performed.
The concept of employee involvement refers to the
employee interest into the tasks and jobs assigned to
him. This way when an employee is involved in his tasks
he feels psychological ownership of his job. Psychological
ownership is the feeling of employee that they have
responsibility to make decisions in the interest of the
company. (Avey et al., 2009) Psychological ownership is
referred to as psychological empowerment. It is the
sense of employee that he can create, mold and take
decisions and mange his work his way. Empowerment of
an employee can base on self-esteem, locus of control
and the information available to employee (Spreitzer,

7392 Afr. J. Bus. Manage
1995). Employees feel themselves that they can influence
the organization by raising their voice; it is a job
enrichment theory (Spreitzer, 1996). They feel themselves
empowered to take decisions in executing tasks
and feel themselves accountable for taking any risky
steps associated with the tasks. When employees are
secured to take any decision on their own responsibility
with the support of the organization, the level of commitment
in the organization will increase. Also employee is
given opportunity to involve and he feels psychological
ownership towards his actions and their consequences,
employees develop the sense of belongingness. These
feelings develop interest and responsibility in employees.
This enables them to effectively perform their tasks.
When employees is responsible towards his task he
takes every decision with much attention and involvement
this increases the chances of best outcomes. When
employee is satisfied he develops the sense of security.
Job satisfaction is defined as the state of mind that
develops the feeling that employees all job related needs
are being met (Evans, 2001).
When employee performs all his tasks with responsibility
and interest, he strives to go better and bring
effective and efficient outcomes. Today’s working environment
employees have to face certain situations.
These situations are related to their work tasks and ask
for quick responses. Employees do not effectively
perform any challenging tasks given to them because of
the lack of association with work. Employees are selected
after much consideration. They are trained extensively to
bring best practices in the organization. Top management
lacks to develop the psychological well being of
employees. Physical performance depends on the psychological
state of employees. Employees having blurred
identity in terms of work and weak sense of belongingness
are not motivated to improve their work. The feeling
of dissatisfaction holds them back from performing right.
Current study draws the motives of (1) The relationship
between transformational leadership and employee
performance. (2) The relationship between employee engagement
and employee performance. (3) The mediation
of psychological ownership between transformational
leadership and employee performance. (4) The
mediation of psychological ownership in the relationship
of employee engagement and employee performance.
LITERATURE REVIEW
Transformational leadership style
Leadership is broadly discussed topic in literature. Its
antecedents and consequences have greater impact on
organizational outcomes and performance. Scholars,
such as (Bass, 1988, 1990 ; Hartog et al., 1997) contributed
in the literature of leadership and its prominent
styles of transactional and transformational leadership
style. Transactional leadership style is defined as the
exchange of rewards and targets between employees
and management (Howell and Avolio, 1993) leaders fulfill
employee needs of rewards when targets are met (Bass,
1990; Howell and Avolio, 1993; Humphreys, 2002) it is
defined as the transaction of needs fulfillment from both
sides of the organization and employees (Pounder,
2002). Transformational leadership style focuses on the
development of followers and their needs. Managers
exercising transformational leadership style focus on the
development of value system of employees, their motivational
level and moralities with the development of their
skills (Ismail et al., 2009) transformational leadership acts
as a bridge between leaders and followers to develop
clear understanding of follower’s interests, values and
motivational level (Bass, 1994) it basically helps
follower’s achieve their goals working in the organizational
setting; it encourages follower’s to be expressive
and adaptive to new and improved practices and
changes in the environment. (Bycio et al., 1978) Burn’s
(1978) transformational theory and Bass’s (1985)
transformational leadership theory explained these characteristics
of leadership style. Transformational theory
proposed by Burns (1978) explains that transformational
leadership style supports mutual understanding between
employees and management while Burn’s (1985) theory
explained that interaction between employees and
management is managed in ways that ultimately leads
employees beyond their self interest in support of
organizational targets.
Transformational leadership is discussed based on two
important characteristics of individualized consideration
and intellectual stimulation. As discussed by Bass and
Avolio (1994) intellectual stimulation is the enhancement
of the followers ability to think own his own related to his
work tasks. Intellectual stimulation is defined as the ability
of an individual to be logical, rational and able to intelligently
adopt from certain situations (Dionne et al., 2003).
Logical thinking and intelligent evaluation of environment
helps employees create new ideas. Stimulating employee’s
intellectuality encourages them to take risk in order
to bring new practices and ideas that help improve
performance (Yammarino and Dubinsky, 1994). Kahn
(1992) discussed that organizational support to employee
develops intellectual stimulation in employee to solve
issues and difficulties. Organizational support and encouragement
motivate employees to think about the
improvement of their own abilities and organizational
processes.
Another characteristic of transformational leadership is
individualized consideration. Literature defines individuallized
consideration as the consideration of employee’s
individuality. Transformational leaders link priorities of
every follower’s with the development of the organization

(Bass and Avolio, 1994). Leaders focus on the
development and training of employees that create
promotion opportunities Avolio et al., 2004). The
outcomes of these characteristics depend on the ability of
the leader to stimulate and direct followers in order to
achieve desired outcomes (Bass, 1994; Bass and Avolio,
1994; Avolio et al., 2004).
Social support from the mangement motivate
employees perform better (Maslach, 2003). Employee’s
involvement in their work tasks increases when managerial
support in available; employees become more
innovative and involved in their work tasks (Gilson, 2008).
Transformational leadership is previously studied in the
context of performance and development. Findings of
these studies show that transformational leadership style
and organizational desired outcomes are highly interrelated
(Bartram and Casimir, 2007; Kildas et al., 2007).
Transformational leadership is also considered the
source of culture development that supports follower’s
dvelopment and individual consideration (Lockwood,
2007). Transformational leadership develops culture that
focuses on improvement of employee performance and
development of abilities (Evans, 2001). Development of
abilities enhances confidence level of employees
(Bandura, 1997). Employee’s involvement and development
improves employee’s confidence hence improving
creativity level (Amabile, 1988).
Transformational leadership style makes employees
more confident and creative. The use of creativity and
innovation helps achieve organizational goals (Locke and
Latham, 1990). Employees managed with transformational
leadership style are given empowerment to a
certain level. This level of empowerment helps follower’s
achieve their goals on time (Lashley, 1999).
Transformational leadership is studied in relation with
positive organizational outcomes such as quality of
performance of employees (Humphreys, 2002). Transformational
leadership style improves the quality of overall
operations in the organization (Pounder, 2002). Intellectual
stimulation encourages employees to think over the
improvement areas and bring best results. All the
dimensions of transformational leadership together direct
towards the improvement of performance (Shin and
Zhou, 2003). Transformational leadership improves
employee performance because of the increased level of
satisfaction that is developed between employees and
management. Transformational leadership has positive
relationship with employee level of satisfaction (Scarpello
and Campbell, 1983). Individual satisfaction towards his
job shows positive impacts on his performance and
reduces absenteeism (Breaugh, 1981) turnover (Arnold
and Feldman, 1982) and enhances sense of citizenship
towards organization (Organ, 1988). Transformational
leadership has positive relationship with citizenship
behaviors and sense of belongingness.
Employee engagement
Ghafoor et al. 7393
Employee engagement is defined differently in academic
researches and among practitioners; basically it is psychological
traits and behaviors (Macey and Schneider,
2008). Employee engagement is defined in terms of other
well-known constructs like organization commitment and
citizenship (Saks, 2006). It is also defined as the emotional
and intellectual commitment of employee towards
organization (Baumruk, 2004; Shaw, 2005; Richman,
2006) engagement is the amount of effort one exerts in
work tasks (Frank et al., 2004).
Employee engagement is based on organizational culture,
communication style, managerial styles, leader-ship
style, trust and respect factors, in order to develop
engaging culture workplace must develop the environment
that supports these factors (Lockwood, 2007).
Leadership development of culture and employee
engagement practices is associated in this way.
Employee engagement is the psychological phenolmena
as defined in past literature it is based on two
psychological components attention and absorption.
Attention is the amount of time individual gives to his role
and job to think over it while absorption is the focus of
individual towards his role and his performance in that
role (Rothbard, 2001). Engagement is the energy that
individual puts into his work, involving himself to improve
performance (Maslach, 2003) the degree to which
employee is involved in his work roles, it is the active use
of individuals thinking, emotions and behaviors (Saks,
2006) engagement is the willingness of employee to get
involved into his work tasks. It is appositive attitude
developed in employee when he finds organizational and
cultural support. Engagement is defined in the dimensions
of vigor, dedication and absorption (Schaufeli et al.,
2002).
Employee engagement is discussed in terms of other
close variables that support the human resource practices
of employee engagement. Employee engagement
can be defined in terms of empowerment. Psychological
Empowerment is the perception of employees that they
can adjust their work roles to accomplish their tasks and
make important decisions regarding work tasks (Yulk and
Becker, 2006) engagement is defined as the level of
energy and decisions making that employees takes on
his account to solve work related issues (Maslach, 2003).
Saks (2006) Studied the consequences of employee
engagement; it is an individual level phenomenon that
indirectly affects the performance or success of organization
by delivering positive individual level outcomes.
Engagement brings outcomes like reduced burnout,
satisfaction, commitment and higher performance
(Maslach, 2003) employees feel belongingness to
organization with lower intentions to leave (Schaufeli and
Bakker, 2004) good health and its positive effects on the

7394 Afr. J. Bus. Manage.
performance is also studied in the past (Sonnentag,
2003).
Employee engagement is considered to be a construct
of involvement of employee in his work tasks (Saks,
2006) transformational leadership practicing engagement
of employees is related to psychological state development
that involves self-efficacy and attaining the targeted
goal.
Psychological Ownership
Previous literature supports that people with sense of
possession of any object are motivated to take better
care of it and maintain the object; this sense of
possession is an organizational behavior to better
understand individual’s motivation (Avey et al., 2009).
Psychological ownership is a phenomena in which
employee develops feeling of possession for the target
(Dyne and Pierce, 2004). Psychological ownership is the
perception of an individual that outcome of ownership is
actually what he desires and this sense reflects what he
thinks and beliefs about that outcome of ownership
(Pierce et al., 2003). Psychological ownership is considered
positively related to other organizational behaviors
like character strength and psychological well being
(Wright and Cropanzano, 2004).
Psychological ownership can be measured, developed
and invested in individuals; this study shows citizenship
behavior support through dimensions of self efficacy,
belongings, self identity and accountability (Pierce et al.,
2003).
Self efficacy is the confidence of an individual that he
can perform certain tasks by implementing his abilities
correctly (Bandura, 1997) while White (1959) argued that
feeling of ownership is linked with the individual need to
be effective and need to control one’s actions. The feeling
to control one’s actions is a component of individual
psychology that results in self efficacy (Bandura, 1997)
this sense of controlling and owning the actions to do
particular tasks develops sense of psychological ownership.
Accountability is considered another dimension of
psychological ownership in a sense that accountability is
the right to hold others responsible and hold one’s self
responsible (Lerner and Tetlock, 1999) possession of an
object moves individual to protect or defend that object as
ownership right (Hall, 1966) accountability is also defined
as the burden sharing or knowledge sharing practices of
an individual that he considers his responsibility towards
others while stewardship and self-sacrifice are considered
higher levels of psychological ownership. (Avey et
al., 2009) the clear sense of role and responsibilities build
accountability. When an individual feels himself accountable
he develops the sense of responsibility towards his
work.
When individual feels belonged to certain environment
or work setting he develops psychological ownership.
Belongingness is psychological need rather then a
physical need. It is the sense of security to be associated
with some possession. The belongingness in terms of
psychological ownership in organization develops when
employees feel belonged to their work and organization
(Avey et al., 2009)
Self identity is defined as the possession or symbols by
which individuals define themselves (Rousseau, 1998;
Belk, 1988) employees identify themselves from both
intangibles and tangibles symbols. Psychological
ownership is the ownership of tangible, work setting and
intangible, ideas and objects (Isaacs, 1933) intangibles
as mission or purpose of organization (Rousseau, 1998)
and tangibles like physical work setting and possession in
use to execute tasks. Psychological ownership is linked
with self-identity, self-adjustment and well being (Kasser
and Ryan, 1993). Self identity as totality of possession; is
totality of one’s being, “What is mine is myself” (Sartre,
1943/1969).
Shamir, House, and Arthur (1993) explain this behavior
as people do certain tasks because they are associated
or identify themselves with those tasks. In terms of
organizational identity individuals has the sense of
meaningfulness of him and feels connected to the
organization and its operations (Ashforth and Mael, 1989)
thus this connection and definition of one’s self in terms
of his work develops psychological ownership.
Possession of tangible and intangible build up around
and psychological ownership are linked with self-concept
of individual (Furby, 1978). Also to consider here is the
distinction of employee belongings and identity. As explained
in literature employee may feel identity because
of belongingness to the organization but development of
the feeling of belongingness not necessarily develops
identity with the object or organization (Avey, Avolio,
Crossley, and Luthans, 2009) thus belongingness and
identity are separate and related constructs of psychological
ownership. When employees identify themselves
through organization, the target of organization becomes
their own targets (Belk, 1988) these targets become
meaning of employee self efficacy and responsibility
towards his actions (Avey, Avolio, Crossley, and Luthans,
2009). This explains that psychological ownership is
developed on the dimension of self efficacy, accountability,
belongingness and self identity.
Employee engagement is developed when transformational
leadership is strong. When organization is itself
striving to develop bonding with employee’s psychological
ownership develops. Psychological ownership can
positively impact organization and its outcomes through
transformational leadership (Avey, Avolio, Crossley, and
Luthans, 2009) transformational leadership in this regard
plays as the base for psychological state development of

the employees.
When employees are engaged in their work their
commitment and comfort with work increases. Employee
engagement is related to the commitment of employee
and how hard they work (Lockwood, 2007).
Previous literature has also studied employee engagement
relationship with dimensions of psychological
ownership. When employee is engaged in his work tasks,
the need to develop certain skills and competencies
arises. The ability to perform better is based on the
equipped state of the employee to be able to take
decisions and perform better (Alamahamid, McAdam,
and Kalaldeh, 2010) acquirement of required competencies
and skills develop confidence of employee (Chiu,
Hsu, and Wang, 2006)self efficacy is defined as the
confidence of an individual in his abilities to perform
certain tasks (Bandura, 1997) employees equipped with
needed skills and abilities have higher level of self
efficacy (Hsu, Ju, Yen, and Chang, 2007)this self efficacy
is the dimension of psychological ownership (Avey,
Avolio, Crossley, and Luthans, 2009).
When employees are encouraged to take part in their
work related decision making and increase their involvement
they become responsible for their own tasks and
performance (Bandura and Schunk, 1981) responsible
employees show much attention to their work and tasks.
Employee responsibility is discussed as accountability on
self and other accountability towards tasks in literature.
This accountability is the dimension of psychological
ownership (Avey, Avolio, Crossley, and Luthans, 2009).
When employees are engaged in their activities and
decision making, feeling of belongingness develops; the
sense of belongingness develops commitment and
ultimately improves performance in terms of competitive
advantage (Stairs, 2005)employee sense of belongingness
improves his perception about his work and
organization and develops association with his work. The
sense of belongingness is discussed in terms of the
dimension of psychological ownership that ultimately
improves performance (Avey, Avolio, Crossley, and
Luthans, 2009).
Previous literature supports positive outcomes of organization
derived from engagement and involvement of
employees in organizational related tasks. Employee
engagement is related to outcomes like success, betterment
of performance in organization (Bates, 2004;
Harter, Schmidt, and Hayes (2002).
Employee engagement reduces negativity among
employees. Employee’s involvement in tasks develops
ways of improvement and positive intentions of employees.
Employee engagement in terms of dedication
towards work reduces the burnout intentions of employees
(Gonza´lez-Roma, Schaufeli, Bakker, and Lloret,
2006).
Employee engagement develops employee’s behaviors
Ghafoor et al. 7395
and emotions. Once employees are equipped with
willingness behavior and positive attitude they draw out
positive results. In literature engagement is defined as a
separate variable that is based on emotional, behavioral
and cognitive abilities of employee that determine
performance (Saks, 2006).
Involvement of employees in work develop loyalty
factor in them. Loyal employees and staff leads to
success of organization (Roehling, Roehling, and Moen,
2001)when employees strive for success of organization
they improve their performance. Employee engagement
is the deciding factor of success of organization; Engagement
is positively related to higher satisfaction, loyalty of
employees and performance (Lockwood, 2007)more
engaged workforce brings better performance and
results.
Employee engagement leads to individual level outcomes
of loyalty and satisfaction. These outcomes
ultimately lead to organizational results. Corporate results
show strong bonding between concept of engagement
and workers performance to business outcomes
(Ferguson, 2009).
Psychological ownership is the development of
employee’s mental state. Psychological it is considered a
positive source of performance of individual; employees
with feeling of ownership are more satisfied with their
work and show more interest in organization (Avey,
Avolio, Crossley, and Luthans, 2009) when employees
show greater interest in their work they perform better.
Psychological ownership is discussed in terms of
citizenship behavior. This behavior develops sense of
employee as family to organization. Psychological ownership
provides base to the development of competitive
advantage and performance as citizenship behavior
develops, also ownership is related to individual level
outcomes like performance (Pierce, Kostova, and Dirks,
2003) competitive advantages of firm leads to high performance
and success (Barney, 1995) while citizen-ship
behavior develops social capital that leads to sustainable
organizational advantages (Bolino, Turnley, and
Bloodgood, 2002).
Psychological ownership develops bonding in the
hierarchal levels of organization. Development of ownership
privileges creates psychological contracts between
employees and organization; employees show more
interest in the investment and performance of organization
(Rousseau and Shperling, 2003) When employees
are interested in the investment of the organization they
desire best investment. Employee working in the mutual
investment relationship is more committed to their employers
and strives for better performance (Tsui, Pearce,
and Porter, 1997). The desire of the betterment of organization
encourages employees to give their best to the
organization.
Psychological ownership develops influencing

7396 Afr. J. Bus. Manage.
Figure 1. Conceptual model.
behaviors; attitude and motivation (Dyne and Pierce,
2004). Motivation and commitment are strongly related
(Meyer, Becker, and Vandenberghe, 2004). Psychological
ownership develops employee’s abilities to understand
and perceive about their environment. Employee’s
satisfaction, trust and belongingness factors develop
strong sense of association, self identity. While higher
level of employee involvement develops creativity, self
efficacy and sense of responsibility in employees.
Previous literature showed relationship between
transformational leadership and performance. Transformational
leadership style and its practices are studied
in the context of employee increased performance and
decreased negativity. Literature explains the relation
between transformational leadership and psychological
impacts of efficacy, hope, resilience and optimism (Avey,
Hughes, Norman, and Luthans, 2008) also the antecedents
and consequences of psychological ownership are
studied; study explained the dimensions of psychological
ownership and its outcome as satisfaction and commitment
of employees (Avey, Avolio, Crossley, and Luthans,
2009). Positive and negative impacts of these variables
are studied in relation to other variables in different
settings.
Current model studies the relationship between
employee engagement and employee performance.
Transformational leadership practices employee engagement
in the work setting (Figure 1). This involvement of
employees develops confidence, responsibility and
belongingness in employees (Gill, Flaschner and Bhutani,
2010). Also the mediating effect of psychological
Ownership in terms of its dimensions- self-efficacy,
accountability, self-identity and belongingness is studied
in the relationship of engagement and performance.
When employees are engaged in their work tasks they
develop confidence and sense of belongingness. This
psychological outcome of employee engagement
strengthens their sense ownership. When employees
consider work and organization as possession, sense of
responsibility increases and employees feel committed to
their work. This commitment and force of inner need of
self development and belongingness increases individual
performance of employee.
Hypotheses are developed to study the affect of employee
engagement, transformational leadership and
employee performance. The mediating affect of
psychological Ownership is studied in the relationship of
transformational leadership, employee engagement and
employee performance.
H1a: Employee engagement is positively related to
employee performance.
H1b: Transformational leadership is positively related to
employee performance.
H2a: Psychological Ownership mediates the relationship
between transformational leadership and employee
performance.
H2b: Psychological ownership mediates the relationship
between employee engagement and employee
performance.
METHODOLOGY
Our study is applied and co-relational study focusing the

Table 1. Means, standard deviation and correlations.
Ghafoor et al. 7397
Variable Mean SD EP EE TL PO
Employee Performance (EP) 5.39 0.90 (0.737)
Employee Engagement (EE) 5.10 1.13 0.256** (0.845)
Transformational Leadership (TL) 5.40 0.94 0.200** -0.073 (0.815)
Psychological Ownership (PO) 5.09 0.96 0.436** 0.774** 0.132* (0.746)
n= 270.
**Correlations are significant at the 0.01 level; *Correlation is significant at the 0.05 level.
() Cronbach’s Alpha, Reliability values are given in bold parenthesis.
telecommunication sector of Pakistan. This study highlights the
impact of leadership styles and human resource practices on the
behavioral development of telecommunication sector employees.
The reasons direct towards the behavioral development of employees
that is why telecommunication sector is selected to study
gather the quantitative data in order to study behavior based
variables. The study context revolves around the variable of
psychological ownership that plays a great role in the development
of employees.
The sample includes all the telecommunication service providers
currently operating within Pakistan and providing international
services. Elements of our study were employees and managers.
Employees included all the officers, technicians, engineers and
heads of areas while managers were of the middle and lower level.
Few upper level managers were also included in the sample. The
data was collected from a total sample of 270 respondents directly
linked with telecommunication sector.
Measures
Transformational leadership
Measures used to collect data from sample of different telecommunication
sector organization is based on Likert-style questionnaire
items (1, “Strongly Disagree”; 2, “Disagree”; 3, “Somewhat
Disagree”; 4, “Neutral”; 5, “Somewhat Agree”; 6, “Agree”; 7,
“Strongly Agree”). A total of 5 items were used to collect data for
this variable. These included (1) “My supervisor acts in ways that
build my respect” (2) “My supervisor talks to us about his/her most
important values and beliefs” (3) “My supervisor expresses his/her
confidence that we will achieve our goals”. The Cronbach alpha for
these 5 items was satisfactory (.815), indicating that these items
together can form a reliable measure to collect and test data.
Employee engagement
In order to study human resource practices a large number of well
established scales are used. In our study we selected 8 items to
study the impact of employee engagement of employee’s behavior
and performance. Likert style questionnaire was developed on
scale items (1, “Strongly Disagree”; 2, “Disagree”; 3, “Somewhat
Disagree”; 4, “Neutral”; 5, “Somewhat Agree”; 6, “Agree”; 7,
“Strongly Agree”). This questionnaire included items (1) “my leader
helps me know what type of requirements he has from me”, (2) “My
suggestions are considered”. The Cronbach’s alpha value (.845)
showed that all the items collectively present a reliable measure for
this variable.
Psychological ownership
In our study, psychological ownership is studied in the context of its
dimensions- self efficacy, belongingness, self identity and accountability.
In order to collect data for this variable the scale of
Psychological Ownership (Avey, Avolio, Crossley, and Luthans,
2009) was used. 8 items were selected from this questionnaire to
be studied on the likert style scale (1, “Strongly Disagree”; 2,
“Disagree”; 3, “Somewhat Disagree”; 4, “Neutral”; 5, “Somewhat
Agree”; 6, “Agree”; 7, “Strongly Agree”). The scale items included
(1) “I am confident I can make a positive difference in this organization”,
(2) “I am totally comfortable being in this organization”, (3)
“I feel being a member in this organization helps define who I am”.
The Cronbach’s alpha value for these items (.746) is satisfactory
which means all these items together form a reliable measure for
this variable.
Employee performance
We studied employee performance as dependent variable. 8 items
questionnaire based on likert style (1, “Strongly Disagree”; 2,
“Disagree”; 3, “Somewhat Disagree”; 4, “Neutral”; 5, “Somewhat
Agree”; 6, “Agree”; 7, “Strongly Agree”). Some of these items
include (1) “Targets given to employees are met on time”, (2)
“Employees quality of performance has improved over time”. In
order to test the reliability of measure Cronbach’s alpha value
(.737) was used which showed satisfactory results.
RESULTS
Means, standard deviation of each variable and the
correlation of the variables studied are presented in Table
1. Empirical findings in this table present that dependent
variable; employee performance is significantly, positively
related to independent variables, employee engagement
(mean = 5.10, p < 0.01) and transformational leadership
(mean = 5.40, p < 0.01). Employee performance is also
significantly, positively related to mediating variable,
psychological ownership (mean = 5.09, p < 0.01).
Employee engagement and psychological ownership
(mean = 5.09, p < 0.01) are also positively, significantly
related. Transformational leadership and psychological
ownership is also positively, significantly related to psychological
ownership (mean = 5.09, p < 0.01). Reliability

7398 Afr. J. Bus. Manage.
Table 2. Multiple regression analysis.
Step
β
Model 1
R
Model 2
2 ∆R 2 P Value β R 2 ∆R 2 Step 1:
P Value
Employee engagement 0.256*** 0.065 0.065 0.000 0.204** 0.206 0.017 0.019
Transformational leadership 0.200*** 0.040 0.040 0.001 0.145** 0.210 0.021 0.009
Step 2:
Psychological ownership 0.436*** 0.190 0.190 0.000
*p < 0.05, ** p < 0.01, *** p < 0.001, n = 270.
values of Cronbach’s alpha are given against each
variable.
Because of the significance shown between dependent
variable and independent variables, independent variable
and mediating variable and mediating variable and
dependent variable, from the results we further calculate
mediation. As discussed by Baron and Kenny (1986)
assumptions satisfied about the significance between
variables validate the mediation analysis. The measures
in data collection for each variable showed a reliable
Cronbach’s alpha values which shows that all the
measures used were reliable to collect data for respective
variables.
Regression analysis was conducted on the data to find
out the relationship significance and the impact of mediator
on the relationship between independent variables
and dependent variables.
Figure 1 presents the relationship of independent and
dependent variables. The relationship between employee
engagement and employee performance is significant (β
= 0.256, p < 0.001).
These findings show the first hypothesis, employee
engagement is positively related to employee
performance is accepted.
The relationship between variables, transformational
leadership and employee performance, is also significant
indicating that positively, significant relationship exists
between these variables. Hence proving the second
hypothesis of the study, transformational leadership is
positively related to employee performance, is accepted
on the basis of empirical findings (β = 0.200, p < 0.001).
Multiple regression analysis show that employee
engagement (β = 0.204, p < 0.01) is insignificant. Hence
the mediation of psychological ownership approves
between employee engagement and employee
performance as can be seen in Table 2. These findings
accept the third hypothesis of mediation, psychological
ownership mediates the relationship between employee
engagement and employee performance.
Multiple regression analysis conducted on second independent
variable showed that transformational leadership
with mediation (β = 0.145, p < 0.01) is also insignificant.
Mediation exists between these variables as well hence
accepting the fourth mediation hypothesis, psychological
ownership mediates the relationship between transformational
leadership and employee performance.
DISCUSSION
Transformational leadership style is widely used in
organizations today. Previous literature reveals positive
impact of transformational leadership style and its
respective practices on organizational outcomes.
Transformational leadership is positively related to performance
in terms of improved quality of outcome (Ismail et
al., 2009). The study on transformational leadership is
related to other positive outcomes such as creativity
ultimately improving performance (Shin and Zhou, 2003).
An individual’s creativity is enhanced by the level of self
efficacy that he has (Bandura) in order to learn and
create process that are unique and effective individuals
go for acquisition of knowledge (Amabile, 1988) the
acquisition of knowledge and development of confidence
of a person in his own abilities drives his level of self
efficacy (Bandura and Schunk, 1981) Transformational
leadership style concludes creativity and innovation
(Gong, Huang, and Farh, 2009) also the study of transformational
leadership style with other outcomes and
managerial practices concludes that it has positive effect
on performance (Avolio, Zhu, Koh and Bhatia, 2004).
Transformational leadership is positively associated
with commitment of employees with work and organization
even when they are at distance from their supervisors
and leaders. The positive impact of empowerment
supports this relationship (Avolio, Zhu, Koh and Bhatia,
2004) this shows that the development of behavior takes
place when transformational leadership style is practiced
and employees are given sufficient level of empowerment
in their work to engage.
Transformational leadership and its respective practices
are also studied in the concept to reduce the

negativity in the organization. Transformational leadership
style and the enhancement of empowerment in
terms of greater involvement in tasks advancement in
employees reduce the negative factors that may affect
performance, also that the positivity improves
performance of employees (Avey, Hughes, Norman and
Luthans, 2008). Transformational leadership not only
enhances positive outcomes but also reduces the effect
of negative aspects associated with employee satisfaction
and performance. Transformational leadership
enhances satisfaction level of employees in their work
setting by improving organizational citizenship behavior
(Breaugh, 1981). Organizations exercising
transformational leadership style and practicing follower’s
development showed employees less intentions to leave
the organization; reduction in absenteeism and intention
to leave direct towards the improvement of performance
(Arnold and Feldman, 1982). Ferguson (2009) discussed
that transformational leadership style reduce the negative
effects of work stress in the organization that ultimately
improves the performance.
When organizations exercise effective empowerment
among employees the perception of employee develop
healthy because they are more engaged to their work.
Management practices, leadership and perception of employees
towards their work and responsibilities develop
empowerment in employees (Yulk and Becker, 2006)
empowerment of employees develop the level of
accountability towards the tasks that he performs. This
shows that when employee is engaged in his tasks the
level of affective empowerment ultimately improves the
effectiveness of the organization based on individual’s
performance. Previous literature supports positive
relationship between empowerment, accountability, performance,
focus and precision (Thoms, Dose, and Scott,
2002) when employees are given empowerment he
performs his tasks with more accuracy and attention
(Fandt, 1991). Where transformational leadership is said
o have positive relationship with other outcomes. It is also
positively associated with the development of self
identity. Employee develop sense of association with
their organization when the level of trust and satisfaction
with work increases (Driscoll, 1978). This discussion
shows that transformational leadership style has positive
relationship with desired organizational outcomes such
as increased performance, satisfaction, enhanced sense
of belongingness, citizenship and self efficacy. This
discussion also supports that employee develop sense of
association with the organization that helps them define
their identity. Negative relationship of transformational
leadership with desired outcomes is also studied. Transformational
leadership has not effect on the creativity of
the employees (Jaussi and Dionne, 2003). Empirical
findings of our study however showed strong positive
relationship between transformational leadership and
Ghafoor et al. 7399
psychological performance; transformational leadership
and employee performance. Hypothesis drawn on this
relationship is approved in context of the study conducted
in Pakistan.
Employee engagement is a global construct and is
studied in the relationship of employee commitment, performance
and association with organization (Ferguson,
2009) Practicing transformational leadership style
improves employee engagement in the work setting that
reduces stress level of employee (Gill, Flaschner, and
Bhutani, 2010) stress in the work setting play a negative
role in the development of employee and performance.
When stress level reduces, performance of employee
increases.
Previous literature supports the positive effect on
employee quality of work because of empowerment.
When employees are involved in their tasks they feel
psychological empowerment (Stander and Rothmann,
2010). Quality of services of the employees improves
when employees are involved in their work (Ismail, et al.,
2009) involvement given to employees brings improvements
from employee’s side as the sense of responsibility
increases. Ultimately an employee helps himself
improve the way of performance that brings self efficacy.
Employee engagement and transformational leadership
are closely studied in the context of working environment
and studies conducted on organizational settings.
Association of transformational leadership and employee
engagement are also supported in the literature with
highly positive results. Transformational leadership
develops and enhances employee involvement in the
organization (Avey, Hughes, Norman, and Luthans,
2008). Employee involvement showed positive impact on
employee performance; employee involvement is also
positively related to employee commitment (Avolio, Zhu,
Koh, and Bhatia, 2004) employee commitment is
positively associated with employee performance in
terms of greater accountability and trust (Dose and
Klimoski, 1995). This discussion shows that employee
engagement and employee engagement and involvement
discussed in terms of leadership style both show positive
relationship with employee performance and positive
outcomes in the organization. Findings of this study show
that employee engagement practices have positive
relationship with employee performance thus proving the
second hypothesis of our study.
When employee is satisfied with his job, his trust
towards organization and his performance increases.
Behavioral intentions and outcomes depend on the power
being given to employee, also the quality of relationship
between hierarchal levels improve performance (Harris,
Wheeler, and Kacmar, 2009) when behavior of employee
is positive towards his own performance and his attitude
is positive towards his organization the level of
commitment of employee increases. When employee’s

7400 Afr. J. Bus. Manage.
behavior is positive they will interact with other hierarchal
levels positively creating harmony in the environment and
improving overall performance and effectiveness of
organization.
Previous literature supports that employee job insecurity
plays negative impact on the employee engagement.
In his study Stander (2010) studied the impact of
insecurity among employees on employee’s engagement.
When employees are not mentally in position of
satisfaction from their job they cannot participate in the
organization properly. This shows that proper engagement
of employees and the satisfaction of employees
towards job develop psychological state of employees
that helps them participate well in their tasks.
Also other factors that lead to the performance improvement
and quality enhancement are addressed in
previous literature along with leadership styles and empowerment
of employees. When employees are allowed
to take decisions and perform their tasks according to
their own setup, the level of innovation and creativity
improves (Gumusluoglu and Ilsev, 2009) innovation and
creativity is developed through self efficacy of employees.
Job self efficacy and support of organization contributes
to employees creative performance (Gong, Huang, and
Farh, 2009) self efficacy creates psychological ownership
that improves performance.
Self concept of the employee is supported by his
identity and association with his work and organization.
When employees are involved in their work the level of
empowerment and self determination of employees
improves moral identity (Zhu, 2008) when employees are
engaged in their tasks they feel a certain level of
psychological empowerment. This develops the self
concept and determination in employees. Moral identity
improves employee commitment to their work.
Responsibility and self identity are psychological
factors studied in the context of positive orientation of
employees in the sense of ownership. James (2009)
studied the relationship of psychological ownership with
positivity in the employee behavior also including the
sense of belongingness of employee. Employee ownership
is studies in terms of prevention and promotion of
employee in the organization. Both these factors
compliment employee sense of association to his job and
organization. This association predicts employee loyalty
that ultimately causes commitment and high performance
(Chen, Tsui, and Farh, 2002) Psychological ownership
brings self efficacy, belongingness, and self identity in the
employee that develops the sense of commitment.
Employees with high level of commitment show better
performance (Khan, Ziauddin, Jam, and Ramay, 2010).
The perception of employees about their job develops
the sense of citizenship towards organization. Organizational
citizenship behavior predicts effective commitments
of employees (Shore, Barksdale, and Shore, 1995).
Employees who feel close association with their job are
more satisfied. Hence the sense of job responsibility is
high in terms of these employees (Piccolo and Calquitt,
2006) when employees feel their responsibility- accountability
towards their job they actually strive for
development of self- self efficacy. Commitment is
supported by the factors of satisfaction, belongingness
and trust of employees when these two factors are
satisfied the level of employee commitment increases.
Literature shows significant relationship between job
satisfaction and organizational commitment (Azeem,
2010). Previous studies findings support the positive
impact of psychological ownership on organizational
outcomes. Our study tested the relationship of employee
engagement and transformational leadership with the
mediation effect of psychological ownership. Findings of
our study showed that psychological ownership mediate
the relationship of both employee engagement and
transformational leadership with employee performance.
Based on the above discussion the proposed model of
this study is supported. Thought this study conducted in
Pakistan telecommunication sector showed partial
mediation of psychological ownership in the relationship
of transformational leadership and employee performance,
mediation between employee engagement and
employee performance is insignificant thus proving full
mediation.
Managerial implications and recommendations
This study has important implication in the areas where
employees are not developed psychologically. Also in the
areas where employees feel lack of belongingness to
their organization. In order to remove this perception of
insecurity towards job, lack of belongingness and blurred
self identity proposed model will help improve employee’s
satisfaction towards their job. Development of
psychology of employees on the basis of self-identity,
belongingness, self-efficacy and responsible attitude all
lead to positive outcomes. Employees with higher level of
these dimensions will prove to be more effective and
participative in the work environment. Supported by
above discussion and empirical findings of this study
employee engagement and employee performance are
perfectly mediated by impact of psychological ownership.
This shows that employee given employee involvement
and engagement improve performance. Also psychological
development of employee is positively related to
employee performance and engagement. Thus another
important implication is promotion of employee engagement
in their work tasks and organizational environment
that ultimately helps employees improve performance.
Transformational leadership style in relationship with
employee performance does not show perfect mediation

of psychological ownership. Thus telecommunication
industry of Pakistan should focus on the leadership
practices. Employee’s needs and interest should be
identified and employees should be guided towards the
development of positive psychological being. Management
support as effective leader can improve
performance and develop positive attitude in work setting.
Support of organization will improve performance and
confidence in employees. Management should exercise a
sufficient level of empowerment in work settings allowing
effective employees engagement. With organizational
support and sense of belongingness employees will feel
comfortable taking any step regarding issues also they
will feel themselves responsible to their tasks. This will
develop employees psychologically about their work, its
importance, their own identity, responsibilities and
belongingness to their work. Employees association and
bonding with organization will determine commitment and
performance.
Conclusion
The aforementioned discussion and empirical testing
concludes that leadership style and human resource
practice, employee engagement, significantly affects the
dimensions discussed in the context of psychological
ownership. Transformational leadership develops selfefficacy
in employees to move further also transformational
leadership style supports the development of
identity. Employees are more comfortable when they are
supported and guided by proper leadership. Employee
engagement on the other hand makes employees more
accountable and enhances the sense of belongingness.
Employee engagement practiced under transformational
leadership develops the positivity in behavior that leads
to trust and satisfaction that enhances sense of belongingness.
The sense of ownership is supported by the
perception of citizenship of employees. Once employees
feel themselves as part of the organization their self
identity with organization improves. This identity and
association with organization develops commitment in
employees and their performance increases. The above
discussion also supports the direct impact of employee’s
satisfaction and sense of belongingness to the quality of
relationship between employees and organization. Both
transformational leadership style and employee engagement
practices develop sense of ownership in employees.
They feel responsible for their actions; develop
confidence in their abilities, sense of self-identity and
sense of belongingness to their work and organization.
Limitations and future research directions
This study focused on only one human resource practice,
Ghafoor et al. 7401
employee engagement. Exercising human resource
practices under different leadership styles create different
outcomes. This study only focuses on transformational
leadership style while other leadership style such as
transactional leadership style also supports significant
effects on employee performance and organizational
effectiveness. This study focused the dimensions proposed
by (Avey, Avolio, Crossley, and Luthans, 2009) in
the study of psychological ownership. There can be other
psychological factors developed through employee
engagement and leadership style, such factors are not
identified.
There are other factors that are developed by behavior
of employee’s engagement like empowerment (Avey,
Hughes, Norman, and Luthans, 2008) and negative
factors like stress and conflict (Gill, Flaschner, and
Bhutani, 2010). This study lacks the justification of these
variables in relation to psychological ownership. This
study is conducted in telecommunication industry of
Pakistan. The difference of practices in different industries
and cultural affects may impact on the results
accordingly.
Future research should study the relationship of other
transformational leadership practices with given dimensions
of psychological ownership. Also future research
should explore and study other dimensions of psychological
ownership transformational leadership practices.
Psychological ownership leads to more outcomes that
should be addressed in future. Other psychological
factors and causes of their development through
leadership style should be identified.
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African Journal of Business Management Vol. 5(17), pp. 7404-7409, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.137
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Financial competitiveness evaluation on sporting
goods listed enterprises: A China study
Feng Ran 1 * and Xiaoling Zhang 2
1 Institute of Physical Education, Chongqing University, Chongqing 400045, China.
2 Department of Building and Real Estate, Faculty of construction and Land Use, The Hong Kong Polytechnic University,
Hong Kong.
Accepted 29 April, 2011
The sporting goods listed enterprises faces more severe financial challenges in the global financial
crisis. An effective approach for evaluating the financial competitiveness level is essential for meeting
this challenge to improve the sustainable competitiveness of the sporting goods production industry.
This approach starts from setting up a coherent conceptual and analytical framework covering different
aspects, including profitability capability, debt paying capability, and operation capability. In this paper,
an evaluation system for the integrated index competitiveness evaluation system (IICE) is presented
and aimed at studying the financial competitiveness of the sporting goods listed enterprises. This is
based on 10 indicators drawn from previous literatures in consultation with a group of experts in this
field. Principal component analysis (PCA) is applied to assist in identifying the principal components
for evaluating the financial competitiveness of the sporting goods enterprises. The findings lead to
suggestions for further study into investigating effective business strategies for improving the financial
competitiveness for sporting goods listed enterprises in China.
Key words: Competitiveness, financial, evaluation system, sporting goods listed enterprises.
INTRODUCTION
According to the World Federation of Sporting Goods
Industries, China has become the largest sporting goods
production base, producing some 70% of the world’s
sporting goods. In China, sporting goods, including
sportswear and equipment, take up 80% of China’s
sports industry. Recently, the successful holding of the
Beijing Olympic Games and Guangzhou, the Asian
games, has enormously boomed the rapid development
of the sporting goods industry. Driving by the tremendous
business opportunities, internationally renowned brands
like Nike and Adidas have expanded investment in China.
Meanwhile, the domestic manufacturers such as Li Ning,
Anta and 361°, are experiencing stronger growth in
Chinese market. It is believed that the enhancement of
the competitiveness of a sporting goods company is one
of the most important strategic tasks in the sports
industry. The challenge to win in the competitive battle
*Corresponding author. E-mail: ranfong1973@sina.com. Tel:
+86-0 13308250808.
has become essential in modern business, while the
dynamically growing competitive environment and the
global financial crisis have forced the sporting goods
companies to pay more attention to their competitiveness
in the financial assets. However, a lot of research has
been conducted in the organizational competitiveness;
few of them have focused on the study of financial competitiveness
on the business enterprises. Therefore, it is
of prime importance to find an evaluation approach to
study the financial competitiveness of a firm in order to
conduct effective competitive strategies in the market.
This paper aims to investigate the financial competitiveness
for sporting goods listed enterprises by developing
an evaluation model. The evaluation approach is
an integration of evaluation indices, applied collectively to
reveal a theoretical competitiveness constructs, for
example the gross profit, earnings per share, return on
equity, etc. By incorporating these financial indicators, an
integrated index competitiveness evaluation (IICE)
system for sporting goods enterprises is formulated. The
IICE system can provide a theoretical basis and effective
technical assistance for decision- makers in the sporting

goods industry in the future.
LITERATURE REVIEW
Research efforts made to define the concept of competitiveness
can be found extensively. Investigations of the
topic can be conducted from the perspective at national,
industrial, firm or project level (Zhang et al., 2010). The
distinction between these four levels is made as the
analytic context is significantly different at different level.
For example, Scott and Lodge (1985) consider that
national competitiveness refers to a country’s ability to
create, produce, distribute and/or service products in
international trade, while earning rising returns on its
resources. Buckley et al. (1988) defines industrial competitiveness
as both efficiency (reaching goals at the lowest
possible cost) and effectiveness (having the right goals).
Competitiveness involves a combination of assets and
processes, where assets are inherited (for example
natural resources) or created (for example infrastructure),
and processes transform assets to achieve economic
gains from sales to customers (Department of Industry,
Science and Resources, 2001).
Ivancevich et al. (1996) define competitiveness as the
degree to which a firm can, under free and fair market
conditions, produce goods and services that meet the
demand of international markets while simultaneously
maintaining or expanding the real incomes of its
employees and owners. Traditionally, the competitiveness
of a product or service refers to its capability to
compete in the market, satisfy customers, take up market
share, and make profits for shareholders (Zhang et al.,
2010).
There are also a lot of studies about the financial
competitiveness of business enterprises. Wen (2006)
proposed an AHP-fuzzy comprehensive evaluation
method, and comprehensively evaluated the currently
enterprises’ financial competitiveness. Wang and Li
(2007) drew the overall impression of the enterprises’
competitiveness through selecting listed firms’ financial
index of the equipment manufacturing industry. Dai and
Wei (2010) developed a financial competitiveness evaluation
model based on the method of analytic hierarchy
process (AHP), which was built in the four areas of
solvency, operational capacity, profitability and development
capacity. However, it can be summarized that most
of the studies mentioned herein are confined as
qualitative research. The result of the qualitative research
is rather subjective, and less than trustworthy.
Therefore, very few of them have addressed comprehensive
financial indicators set, tailored for evaluating the
competitiveness of sporting goods listed enterprises. And
there is a lack of quantitative evaluation approach by
combining the set of indicators to assess competitiveness
of sporting goods enterprises. There is a necessity to find
out an appropriate method in this paper, to facilitate the
study in filling up the research gap.
Ran and Zhang 7405
INTEGRATED INDEX COMPETITIVENESS EVALUATION
SYSTEM (IICE)
Research method
There is no one single indicator used to measure the financial competitiveness
of the sporting goods listed enterprises. The evaluation
about the financial competitiveness is therefore, considered as a
multi-level and more complex problem, and the effects about the
enterprise financial competitiveness caused by each index are
different.
In order to develop the IICE system, the first task is to identify the
indicators that can demonstrate the financial capability and to
organise the indicators into an appropriate structure based on
principles such as ease of operation and cost effectiveness. This
then enables the principal component analysis method to be used
to extract the principal component factors and calculate the
loadings with each of the investigated cases. This is followed by the
group analysis of the sustainability level of urban land use among
the capital cities and municipalities in China. The advantages have
been identified in the application of PCA in land use changes (Li
and Yeh, 1998) and land use evaluation practice (Yu, 1993).
Indicator selection and data collection
Obviously, the financial competitiveness of the listed enterprises
has been analysed from various scale perspectives (Feng and
Wang, 2000; Wu et al., 2010). Indicators are powerful tools to
simplify, quantify, and communicate information on processes such
as society–nature interaction that are too complex to be measured,
and perceived directly (Hammond et al., 1995). A literature review
was undertaken to provide the appropriate financial indicators for
setting up the IICE system. In line with the literature review, a preliminary
indicator list has been proposed by including the relevant
indicators mentioned in the previous literatures. For example, Wang
and Li (2007) opined that ‘quick ratio’, ‘asset-liability ratio’ and ‘total
asset turnover’ can be considered as the key indicators for evaluating
the financial competitiveness for listed enterprises. Besides, the
research has also added indicators, such as, ‘net profit growth rates
‘, ‘three year capital average growth rates’ , ‘net capital profit ratio’,
‘total capital profit ratio’ , ‘total asset growth rates’ and ‘sales
income growth rates’ into the indicator system. Feng and Wang
(2000) proposed another three financial indicators, “gross profit
margin”, “earnings per share” and “current asset turnover” to
conduct the performance evaluation process for airlines with
financial ratios taken into consideration.
In order to ensure effective readability and proper expression of
their meanings, these indicators were presented to 10 business
management practitioners and academics as a pilot study. The
respondents were invited to assess whether the indicator
framework is appropriate, whether the proposed indicators are
appropriate in capturing the competitiveness of those sporting
goods listed enterprises, whether the terminology was correct, or
whether some indicators could be deleted from the list or others
could be added. Valuable comments were received and amendments
were made accordingly, which led to the confined list of three
pillars of issues and 10 indicators as shown in Table 1. The two
indicators “sales income growth rates” and “free cash flow ratio”
were deleted from the indicator framework according to the respondents’
opinions. In this context, the revised indicator list can be
classified into three major groups: profitability capability, debt
paying capability and operation capability. By communicating with
experts in the business management area, the evaluation framework
can be tailored with the specific circumstances of local areas.
The cases used for this study are those sporting goods listed
enterprises in China, including Lining, Anta, XTEP, China
Dongxiang and Peak (Appendix). The relevant data for the 10

7406 Afr. J. Bus. Manage.
Table 1. The Financial competitiveness indicator system.
Category Indicator Unit References
Profitability
capability
Debt paying
capability
Operation
capability
X1-Gross profit RMB:1000 Wang and Li, 2007; Wu et al., 2010
X2-Gross profit margin % Feng and Wang, 2000; Jin, 2003; Wu et al., 2010
X3-Earnings per share Cents Feng and Wang, 2000; Jin, 2003; Wu et al., 2010
X4-Shareholders’ equity per share Cents Wang and Li, 2007; Wu et al., 2010
X5-Return on average total
shareholders’ equity
% Wang and Li, 2007; Wu et al., 2010
X6- Current ratio % Wang and Li, 2007; Wu et al., 2010
X7-Quick ratio % Wang and Li, 2007; Wu et al., 2010
X8-Asset-liability ratio % Wang and Li, 2007; Jin, 2003
X9-Current asset turnover
% Feng and Wang, 2000; Wu et al., 2010
X10-Total asset turnover % Wang and Li, 2007; Wu et al., 2010
Table 2. Eigenvalues and variability contributions of IICE (%).
Factor Factor1 Factor2 Factor3
Eigenvalue 4.518 3.061 1.196
Percentage variability contributions 45.18 30.62 11.95
Cumulative variability contribution rate 45.18 75.80 87.75
indicators were acquired from the annual report of Lining (2007,
2008, 2009), the annual report of Anta (2007, 2008, 2009), the
annual report of XTEP (2007, 2008, 2009), the annual report of
China Dongxiang (2007, 2008, 2009) and the annual report of Peak
(2007, 2008, 2009).
PRINCIPAL COMPONENT ANALYSIS AND RESULT
OF IICE
Principal component analysis (PCA) is a popular means
for making comparisons between objects’ measures on
several dimensions or criteria, such as the welfare level
between individuals (Maasoumi and Nickelsburg 1988).
To do this, it linearly transforms a set of original variables
into a new set of variables that are uncorrelated (orthogonal)
with each other (Ku et al., 1995). The method
relies solely on the variation and co variation of the data
matrix to construct weights in the indexes, which are then
used to produce a small number of comprehensive
variables, in place of many original variables, simplify the
data structure and minimise original data information
loss. Many procedures have been proposed for
1
−0.
780*
X
8
6
−0.
785*
X
10
7
4
2
determining the number of components to be retained in
the PCA model (Jackson, 1991) and additionally,
although somewhat controversially (Sternberg, 1977), the
method can be used to help identify the concepts
underlying the data. It is also well supported by standard
statistical software and therefore, in the current context, it
provides a simple and efficient method to identify the
groups or concepts for use in evaluating the financial
competitiveness of the sporting goods listed enterprises.
The eigenvalues and eigenvectors of the PCA correlation
matrix based and the first three eigenvalues are
given in Table 2. As can be seen, the contribution rate is
calculated from the Varimax normalized factor analysis.
This suggests that PCA can be used in several different
ways in constructing the competitiveness level of the
sporting goods listed enterprises. In accordance with the
minimum “m” selection criteria (Ei > 85%), the three
eigenvalues of the cumulative variability contributions
rate E3 is 87.75%.
The values of the eigenvectors of the three components
are given in Table 3, the vectors being scaled so
that the maximum weighting is 0.927.
F = 0.
927*
X + 0.
926*
X + 0.
539*
X + 0.
502*
X + 0.
437*
X + 0.
256*
X −0.
702*
X
1
3
9
(1)

F
+
2
0.
110 *
F
+
Table 3. Factor loadings for first three principal components.
= −0.
183 * X
3
=
X
8
0.
185 *
0.
250 *
X
Variable F1 F2 F3
8
X6 0.927 -0.183 0.185
X7 0.926 -0.186 0.188
X4 0.539 0.702 -0.094
X2 0.502 0.491 0.659
X1 0.437 0.858 -0.046
X3 0.256 0.926 -0.145
X9 -0.702 0.652 0.049
X8 -0.780 0.110 0.250
X10 -0.785 0.476 -0.088
Name Solvency capability
factor
6
0.
186 *
+ 0.
476 * X
X
6
−
10
0.
188 *
− 0.
088 * X
Factor 1: Solvency capability factor
+
10
X
7
7
+
0.
702 *
0.
094 *
X
4
4
Sustainable profit making
capability factor
+
0.
491*
0.
659 *
As Formula 1 to 3, and Table 3 show, the first component
F1, is predominantly loaded with X6 (0.927) and X7
(0.926). The first principal component (Factor 1) stores
the maximum contents of the variance of the original data
set (Li and Yeh, 1998), which include the components:
X6- current ratio and X7- quick ratio
The financial competitiveness of the sporting goods
listed enterprises can be driven by several elements, including
debt management and asset management
aspects. For example, X6 and X7 has a high loading on
Factor 1, indicating that debt management capability can
greatly affect the competitiveness level of the sporting
goods listed enterprises. This is becoming even more
critical in the context of the global financial crisis. Those
who gained the capability to solve the debt capability can
become the leader in the competitive market in China.
This finding is echoed with Wu et al. (2010), who opined
that the solvency capability played a noticeable role of
spurring the growth of sporting goods listed enterprises in
China.
Factor 2: Sustainable profit making capability factor
The second principal component (Factor 2) describes the
largest amount of the variance in the data that is not
already described by the first principal component, and
so forth (Taylor, 1977). Factor 2 gives high positive
weightings to X3 (0.926), X1 (0.858) and X4 (0.702)
X
−
X
+
X
X
2
2
−
+
0.
858 *
0.
046 *
X
1
X
−
1
+
Capital management
capability factor
0.
926 *
0.
145 *
X
3
Ran and Zhang 7407
X
+
3
−
0.
652 *
0.
049 *
where; X3- earnings per share; X1- gross profit; X4-
shareholders’ equity per share.
This indicates that a sustainable profit making capability
should have a healthy shareholder structure and the
way to make profit in the market. By operating shareholder’s
equity, the sporting goods listed enterprises can
gain sufficient capital for producing sporting goods, and
the outcomes from the store market can help encourage
the sustainable business operation. This demonstrates
that it is significant for business decision makers to
allocate and manage shareholders’ resources in a
sustainable way.
Factor 3: Capital management capability factor
The third principal factor (Factor 3) has principal loadings
with X2 (0.659) and X8 (0.250), which carry much information
in the proportion of capital management capability
aspects, where; X2- gross profit margin; X8- asset-liability
ratio.
The result points to the links between the capital
management capabilities with the competitiveness of the
sporting goods listed enterprises. Capital has become
one of the most significant resources for those manufacturing
enterprises nowadays. In order to accumulate
sufficient capital, one of the efficient ways is to manage
the asset from producing and selling the sporting goods,
efficiently and sustainably. On the other hand, the gross
profit margin can indicate how, and to what extent, the
X
9
X
9
(2)
(3)

7408 Afr. J. Bus. Manage.
capital can be controlled and well managed. In this
context, the capital can always be ready for producing
enough sporting goods in the market.
Conclusions
The evaluation of the financial competitiveness of the
sporting goods listed enterprises in China is currently a
rather rudimentary, subjective issue, while the complexities
involved warrant a more sophisticated and objective
approach. The integrated index competitiveness evaluation
system (IICE) in this study has involved profitability
capability, debt paying capability and operation capability
aspects. Using the methods of principal component
analysis, three principal components were extracted and
named according to their intuitive meaning, ‘solvency
capability factor’, ‘sustainable profit making capability
factor’ and ‘capital management capability factor’. IICE
offers a theoretical basis for proposing appropriate
business strategies in order to promote and enhance the
overall competitiveness of the sporting goods listed
enterprises.
The proposed IICE system can not only help business
managers identify the status quo of the competitiveness
level in the financial aspect, but also help the industry
authorities to make relevant policy changes as well as
actions based on the assessment results. In this context,
a further research based on the findings of this paper has
to be designed to provide appropriate tools, instruments
and methodologies, to improve the competitiveness of
sporting goods enterprises. The findings in this study can
also provide relevant experiences sharing for other
industries and sporting goods industry in other countries,
which can be of interest to the international audience of
business managers or decision makers.
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APPENDIX
Data for evaluation on the competitiveness of the Sporting goods listed enterprises
Ran and Zhang 7409
Manufacturer X1 X2 X3 X4 X5 X6 X7 X8 X9 X10
Anta (2009) 2,472,894.00 42.1 50.23 203.84 26.2 5.63 5.20 0.158 1.20 0.963
Anta (2008) 1,848,573 40 35.94 179.95 20.7 9.42 8.70 0.093 1.06 0.936
Anta (2007) 999,907 33.5 25.26 166.69 24.5 8.62 7.71 0.104 0.72 0.645
Anta (2006) 313,228 25.1 8.19 13.22 84.5 0.96 0.71 0.134 2.11 1.460
XTEP (2009) 1,387,800.00 39.1 29.79 1.37 23 5.80 4.93 0.180 1.05 0.974
XTEP (2008) 1,064,300.00 24.3 26.84 1.21 34.8 4.80 4.38 0.195 0.93 0.875
XTEP (2007) 443100 31.12 15.11 2.8 94.9 1.90 1.43 0.690 1.76 1.511
XTEP (2006) 136100 11.95 3.41 2 31.3 1.20 0.79 0.641 1.17 0.926
361° (2009) 1,193,803 39.4 42.1 186.5 44.7 2.40 2.10 0.256 1.13 0.949
361° (2008) 348,028 26.4 11.9 142.3 80.5 1.25 1.03 0.385 0.92 0.845
361° (2007) 76,923 20.6 1.5 38.3 23 1.33 1.07 0.724 1.27 1.143
361° (2006) 27,058 10.3 0.7 15.4 19.2 1.26 1.08 0.067 1.07 0.955
China Dongxiang (2009) 2,399,371 45.2 25.76 129.8 20.75 12.81 12.76 0.070 0.56 0.502
China Dongxiang (2008) 1,943,762 58.5 24.12 128.6 21.67 11.84 11.07 0.079 0.49 0.456
China Dongxiang (2007) 1,000,573 58.5 15.89 134.78 21.67 18.45 18.17 0.090 0.29 0.275
China Dongxiang (2006) 535,561 62.4 7.1 19.7 174.43 2.13 1.76 0.639 1.70 1.010
Lining (2009) 3,969,864 47.3 90.75 255.3 41.3 1.70 1.36 0.468 2.65 1.560
Lining (2008) 3,220,374 48.1 69.63 182.9 39.6 1.35 1.04 0.518 2.37 1.543
Lining (2007) 2,082,846 47.9 45.83 168.5 30.1 2.22 1.70 0.373 2.00 1.564
Lining (2006) 1,508,552 47.4 28.65 135.7 23 2.74 2.23 0.354 1.68 1.469
Peak (2009) 1,159,700.00 37.5 36 143 20.9 8.40 7.80 0.130 1.01 0.910
Peak (2008) 667800 32.7 25 52 48.6 2.30 1.90 0.461 1.75 1.423
Peak (2007) 306000 30.2 11 27 41.7 1.90 1.50 0.529 1.31 1.158
Peak (2006) 177200 28.4 6 0 62.2 1.60 1.10 0.622 2.06 1.915

African Journal of Business Management Vol.5 (17), pp. 7410-7419, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.174
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
A (data envelopment analysis) DEA-based systematic
approach for selection of strategic alliance candidates:
Case by the biotechnology industry
Chia-Nan Wang 1 * and Chih-Hong Wang 2
1 National Kaohsiung University of Applied Sciences, Taiwan.
2 National Chengchi University, Taiwan.
Accepted February, 2011
Enterprises become more and more difficult to maintain success in the highly competitive environment.
This is the reason why many enterprises start searching for strategic alliance partners to strengthen
their competitive advantage. However, facing a future of uncertainty, choosing the suitable partner of
strategic alliance has become a difficult task. Based on data envelopment analysis and heuristic
techniques, this study proposes a new systematic approach, which calls alliance candidate selection.
The objective of alliance candidate selection is to assist biotech companies to evaluate the operation
efficiency and find the best candidate of strategic alliance. Realistic data are collected from
biotechnology businesses of Taiwan published stock market. Target company and 19 biotechnology
companies for decision making units were collected. This research tries to help target company to find
the right alliance partners for future integration. By analysis of alliance candidate selection, the results
show that, the predicted benefits of 3 candidates as first priority 4 ones suggested and 10 of the ones
not recommended. The results are sound for enterprises to find the future candidates of strategic
alliance by many industry peoples. Alliance candidate selection can effectively provide all the essential
analysis and recommendations to enterprises, for finding the right candidate of strategic alliance.
Key words: Strategic alliance, data envelopment analysis, biotechnology, efficiency.
INTRODUCTION
The technology policy of many countries chooses biotech-
nology for full support and development. Biotechnology
industry becomes one of the most past booming
industries in the world. No doubt, this is a new industry
and people still try to find a way up. Nevertheless, with
rapid growth of the global competition, enterprises
strongly feel that their advantage is not easy to continue
longer in the market, especial the competence strategy of
this new industry. This is the reason why many
enterprises start searching for strategic alliance partners
in order to strengthen their competitive advantage for the
ultimate success in the market. However, facing a future
of uncertainty, choosing the suitable partner of “strategic
alliance” has become a difficult task. The objective of this
*Corresponding author. E-mail: cn.wang@cc.kuas.edu.tw. Tel:
886-7-3814526 ext. 7109. Fax: 886-7-3837251.
paper is to develop an effective method to assist biotech
companies to evaluate the operation efficiency and find
the best candidate of strategic alliance. Based on the
methodology of data envelopment analysis (DEA) and
heuristic techniques, this research develops an evaluation
method which calls alliance candidate selection (ACS).
ACS will be a very effective tool by using evaluation
models to provide top managers with an effective method
to find the best partner of strategic alliance under some
certain control factors; because the merge and alliance
has been a very common strategy for business to have
more choices and fast expansion. Besides, mutual
learning is another advantage.
Most of DEA applications focused on performance
evaluation, some are in the area of mergers and
acquisitions (Sufian and Habibullah, 2009). The research
of Bhattacharyya et al. (1997) shows that, government
owned banks possess more operational efficiency than
privately owned banks, but less efficiency than foreign

anks. Camanho and Dyson (2005) enhance cost
efficiency measurement methods. The results obtained in
the case study show that, the DEA models can provide
robust estimates of cost efficiency even in situations of
price uncertainty. Lee et al. (2005) discuss a description
of a DEA model for analysis of the control performance for
a specific context for electronic data interchange (EDI) in
the context of finance and trade. Homburg (2001) investi-
gates the use of DEA for activity-based management and
pros and cons of DEA as applied to benchmark activities.
Mota et al. (1999) provide a quantitative model for
activity-based management (ABM). A real case study of a
drill factory is used to illustrate the application of the
model. Co and Chew (1997) use DEA to analyze the
performance and R&D expenditures in American and
Japanese manufacturing firms. An approach based on
DEA is proposed by Chang and Lo (2005) for measuring
the relative efficiency of an ISO 9000 certified firm's ability
to achieve organizational benefits. Luo and Donthu (2005)
use DEA and Stochastic Frontier (SF) to show that, top
100 marketers’ advertising spending in print, broadcast,
and outdoor media are not efficient and could bring in
20% more sales. Cook and Zhu (2003) use DEA for
productivity measurement of highway maintenance crews
as maximum achievable by reduction in resources without
impacting the outputs from the process. Durand and
Vargas (2003) analyze the ownership, organization, and
private firms' efficient by DEA. Forker et al. (1997)
combine nonlinear DEA and linear regression analyses,
and then demonstrate that Total Quality Management
(TQM) practices are related to performance. However,
DEA cannot only be used in performance evaluation and
can be extended more.
Some researches extend DMU combination in DEA to
study strategy. Some other researcher such as Shaffer
(1993) suggests that, mergers have the potential to
produce efficiencies. Worthington (2004) uses DEA and
the multinomial logic model to evaluate the determinants
of merger and acquisition (M&A) activity in Australian
credit unions. The results indicate that, asset size and
quality, management ability, earnings and liquidity impose
significant influences on the level of M&A. Lubatkin and
Srinivasan (1997) update the list of large mergers from
1948 through 1988 and calculate three capital market
measures of value creation. They facilitate “mergers for
efficiency,” rather than “merger for diversity.” Wang and
Wang (2005) provide an application model for merger
evaluation in high-tech business. Their study tries to build
a model to find the best merger candidate. Delmas and
Tokat (2005) use DEA to analyze how the process of
retail deregulation affects the comparative efficiency of
governance structures, which range on a continuum from
fully vertically integrated structures to market trans-
actions.
Talluri and Baker (1996) propose a two-phase
mathematical programming approach for effective partner
selection in designing a venture capital (VC) by combining
Wang and Wang 7411
the DEA and technique with an integer programming
model. Shao and Lin (2002) develop an approach to
investigate the effects of Information Technology (IT) on
the technical efficiency in a firm’s production process.
DEA and Tobit models are used to measure the efficiency
scores upon the corresponding IT investments of the
firms. To our best knowledge, there are no researches
reported, that use DEA to select strategic alliance
candidates in technology oriented business. The
remaining of this paper is organized as follows; two DEA
models are reviewed followed by the development of the
DEA-based heuristic method for strategic alliance
candidate selection (ACS). Case study and the analysis
are then demonstrated followed by the conclusion.
CONCEPT OF THE DEA METHODOLOGY
DEA was first proposed by Charnes et al. (1978) (CCR).
Its original idea comes from the measurement model of
production efficiency proposed by Farrell (1957). DEA
itself is a non-parametric method for assessing the
relative efficiency of decision making units (DMUs) based
upon multiple inputs and outputs. The primitive DEA
model adopts the concept of production in microeco-
nomics: efficiency = output / input. Banker et al. (1984)
(BCC) developed a new model from the CCR model to
understand the problems of pure technical efficiency
(PTE) and scale efficiency (SE). Both of the CCR and
BCC models are summarized as follows.
CCR model
The CCR model intends to maximize the ratio of weighted
outputs against weighted inputs. It reduces multiple
outputs to a single “virtual” output, and multiple inputs to a
single “virtual” input for each DMU. CCR is good at
analyzing the relative efficiency without setting the
weights in prior, which makes the CCR model more
objective. Assume that there are n DMU. Each DMU has
m inputs and s outputs. Let x ij represent the ith input and
y rj represent the rth output of DMU j, respectively. Let
u r
and v i represent the virtual variables of rth output and
ith input, respectively. Let
h j represent the relative
efficiency of DMU j. Where ε is a relatively small
positive number (normally set at 10 -6 ). The relative
efficiency of each DMU can be calculated by solving the
following mathematical programming problems:
Max
s
∑
r
r=
1
j = m
h
∑
u y
v x
i
i=
1
Subjected to
rj
ij
s
∑
r rj
r=
1 ≤
m
∑
u y
v x
i ij
i=
1
1
(1)
(2)

7412 Afr. J. Bus. Manage.
ur
≥ ε
> 0 (3)
v i ≥ ε
>0 (4)
r =1,2,3,….,s; i =1,2,3,…..,m; j =1,2,3,…..,n
The CCR input model can suggest improvement
directions and the values of both outputs and inputs in
order to achieve the desired efficiency value of 1, which
can be done by calculating the following equations:
x
y
* −*
ij = h j xij
− si
* + *
rj = yrj
+ sr
Where
, i =1,…,m (5)
, r =1,…,s (6)
−
s i represents the lacking quantity (slack) of the
+
sr
output and represents the redundant quantity
ij
(surplus) of the input.
x *
rj
,
y * + *
−*
,
s s
r and i
x ij yrj
represent the optimal values of , , +
sr
and,
respectively. Note that when the value of objective
j function h =1, +
s r =0 and −
s i =0 (for all r and i). That is,
DMU j achieves its optimal efficiency. Note that, CCR is
the most popular DEA model for evaluation of the total
operational efficiency.
BCC model
The difference between the CCR and BCC models is the
use of returns-to-scale. For each DMU, BCC allows
variable returns-to-scale, while CCR is characterized by
constant returns-to-scale. The BCC model has an
additional convexity condition. The input–oriented BCC
model can be written as:
Max
s
∑
u y − u
r rj
r=
1
j = m
h
∑
Subjected to
v x
i ij
i=
1
s
∑
r=
1
0 (7)
u r y rj − u0
≤ 1
m
v x
(8)
∑
i=
1
i
ij
u ≥ ε > 0 (9)
r
v i ≥ ε >0 (10)
r =1,2,3,…,s; i =1,2,3,…,m; j =1,2,3,…,n
u0 is a real number to indicate the intercept of the
production frontier. When u 0 >0, the production frontier
for this DMU is decreasing returns-to-scale (DRS). When
u 0 =0, the production frontier for this DMU is constant
returns-to-scale (CRS). When 0 u

Step A-4: Correlation analysis
Start •Business/potential connection
•Competitors
•Upstream / downstream of the
DMU selection
industry
I/O factors setting
Original raw data collection
No
Analysis of correlated
coefficient
Data Refinement
•Industrial forum
•Survey
•Brainstorming of industrial
managers
•Improper factors removal
•Data positive adjustment
DMU data table I/O variables setting
DEA calculation
Form virtual DMU
DEA calculation
for
all scenarios
Record frontier #
Completed
all DMU
Frontier # table
Results Analysis
End
Yes
Potential scenarios
combination
Scenario table
• Combine I/O data with
target company
• Create a new DMU data
table
Document Calculation
Process
Figure 1. Procedures of alliance candidate selection (ACS).
Calculate the correlation coefficient for those raw data of
all DMUs.
Step A-5: Raw data refinement
The screening and exclusion of non-effective data are
Wang and Wang 7413
A. Data Collection
B. Variables Setting
C. Calculation
D. Analysis
done in this step, such that all the remaining data are
positively correlated between the inputs and the outputs.
Both within the inputs and the outputs, if the correlation
coefficient between any two factors is very high, like more
than 0.85, these two factors are redundant and one of
them can be removed. Moreover, when the coefficient
between input and output is very low, like low than 0.15,
the two factors are low correlation and one of these

7414 Afr. J. Bus. Manage.
factors can be removed. The removing steps continue
until there are no data to be removed. When some data
are removed, note that each time the correlation analysis
step (Step A-3) is invoked to update the correlation
coefficients. Finally, the DMU Data table is the outcome of
the data collection stage.
Variables setting
Two steps are under variables setting. After the com-
pleted steps, the outcome is scenario table, which record
scenario characteristics for calculation of the variables
setting.
Step B-1: Input/Output variable setting
Since it always would have some changes following the
formation of the alliance, we set up 2 parameters to
modify the changes in input and output. The purpose of
parameter ‘k’ is for the modification of the sum of input
factors, and parameter ‘m’ is for the modification for sum
of output factors. For example, we assume the alliance
can obtain the advantage of input resources by reducing
20% (k=0.8, this means we sum input resources for two
merged companies then multiply 0.8), or obtain the
advantage of output resources by increasing 20% (m =
1.2, this means we sum input resources for two merged
companies, then multiply 1.2).
Step B-2: Potential scenarios combination
Then, combining all inputs and outputs by two
parameters, list the total combination scenarios.
Outcome: Scenario table
List the total scenarios form a scenario table.
Calculation
Five steps make up this calculation. After completing the
steps, the outcome is frontier number table, which is used
for analysis of the potential performance of virtual
alliances in the calculation.
Step C-1: DEA Calculation
According to CCR model, use DMU Data Table to
calculate the company efficiency ranking before the
formation of the alliance. The purpose is to understand
the performances of all DMUs before the alliance is
formed.
Step C-2: Form virtual DMU
Merge the inputs and outputs one by one between the i
DMU and target company to be the virtual alliance. The ‘i’
is an integer. Replace data of i DMU with data from the
virtual alliance in DMU Data Table.
Step C-3: DEA Calculation for all scenarios
The data of virtual alliance in DMU Data Table are
multiplied by the parameters for first combination scenario
in the scenario table. Then, use DEA to calculate the
efficiency ranking. If the virtual alliance is frontier, then
record in the frontier number table. Afterwards, the data of
virtual alliance in DMU data table are multiplied by the
parameters for second combination scenarios. Repeat the
DEA calculation to record the frontier number, and so on,
till all scenarios are complete.
Step C-4: Check all DMU are completed steps 2 and 3
Let ‘i’ is changed to ‘i+1’ and go back to step 2, until every
DMU has formed a virtual alliance.
Outcome: Frontier number table
Summarize the frontier number for all virtual alliances as
the frontier number table.
Analysis
Under evaluation with multiple scenarios, Norman and
Stoker (1991) proposed a suitable method for testing.
When doing the DEA evaluation, the DUMs in frontier
means these companies have the best efficiency.
Therefore, a DMU becomes a frontier in more different
scenarios, and we assume it could have more opportunity
to be the most efficient company. The ranking of efficiency
integrated several scenarios would be ranked by the
frontier numbers. Compare the results before and after
the formation of the alliance of target company to analyze
the differences. Find out the most successful opportunity
for the virtual alliances.
CASE STUDY – TAIWAN BIOTECHNOLOGY INDUSTRY
To implement the ACS model, this paper selects one target
company and 19 candidates for analysis. All data are collected from
Taiwan Stock Exchange Post System. Details are depicted as
follows.
Data collection
A win-win supplier-buyer model is vital for competitive- ness (Cho
and Soh, 2010). The strategic target company is a real company
that wants to find its strategic alliance candidate. Therefore, this
paper collects 19 candidate companies which are related to the
company following the step of ACS. According to discussion with
many managers in this industry, this paper summarized major
concerns of strategic alliance. These concerns are low cost, less
employees and high profit. According to these requirements, the

Table 1. Original raw data of inputs and outputs.
Wang and Wang 7415
Item
Capital
Input
Assets Employee RD Revenue
Output
Profit EPS Equity
Unit Million Million Person Million Million Million NTD Million
A 331 546 102 27 279 17 0.32 467
B 632 2595 240 201 1576 303 3.75 1069
C 604 1204 209 43 1012 111 1.38 871
D 498 974 232 14 347 15 0.32 619
E 350 305 19 43 39 -26 -0.64 294
F 2710 5715 450 29 2487 206 3.01 4120
G 3742 6493 1024 187 4374 299 0.92 5162
H 3644 7285 2191 89 8903 107 0.71 4449
I 2417 5821 933 193 2809 717 2.99 5007
J 1281 3029 492 101 1452 324 1.66 1799
K 1705 3058 192 75 1976 686 3.53 2724
L 993 2983 86 87 2932 610 2.78 1469
M 9800 50772 602 18 9138 373 2.11 30988
N 360 104 58 33 32 -103 -3.89 86
O 300 496 71 59 36 -92 -2.94 205
P 850 2125 350 66 1555 79 6.44 1607
Q 431 846 86 31 774 138 2.95 715
R 680 3707 155 0 2040 71 2.18 2064
S 6181 9772 19 0 1122 -110 -0.38 6599
Target
company
718 999 200 61 620 138 2.33 866
Table 2. Correlation analysis of original raw data.
Capital Assets Employee RD Revenue Profit EPS
Capital 1
Assets 0.8948 1
Employee 0.3701 0.2295 1
RD -0.0633 -0.1288 0.4151 1
Revenue 0.7486 0.7343 0.7750 0.1749 1
Profit 0.1796 0.2181 0.2248 0.5714 0.3516 1
EPS 0.0473 0.1002 0.1062 0.2805 0.2061 0.5655 1
Table 3. Correlation analysis after adjustment.
Assets Employee Revenue Profit
Assets 1
Employee 0.2295366 1
Revenue 0.7342894 0.7749449 1
Profit 0.2180533 0.2248374 0.3515596 1
DEA input factors are set to be capital, assets, employee’s number
and research and development (R&D) expense. The output factors
are set to be revenue, profit and earning per share (EPS). The
original raw data are collected and shown in Table 1. The data
source is from Taiwan Stock Exchange, Market Observation Post
System (2010). Then, correlation analysis is used to analyze the
improper factors. The correlation analysis for all factors is depicted
in Table 2. Following the ACS’s procedure, remove the factors with
the negative coefficient (such as RD) and with very high (such as
capital) or very low (such as ESP) coefficient value. After
adjustment, re-execute the correlation analysis and new results are
shown in Table 3. Obviously, the coefficients have no any violation,

7416 Afr. J. Bus. Manage.
Table 4. DMU Data table.
Item
Assets
Input
Employee Revenue
Output
Profit
Unit Million Person Million Million
A 546 102 279 137
B 2595 240 1576 423
C 1204 209 1012 231
D 974 232 347 135
E 305 19 39 94
F 5715 450 2487 326
G 6493 1024 4374 419
H 7285 2191 8903 227
I 5821 933 2809 837
J 3029 492 1452 444
K 3058 192 1976 806
L 2983 86 2932 730
M 50772 602 9138 493
N 104 58 32 17
O 496 71 36 28
P 2125 350 1555 199
Q 846 86 774 258
R 3707 155 2040 191
S 9772 19 1122 10
Target company 999 200 620 258
so the final factors of inputs and outputs are fixed to be “Assets”,
“Employee”, “Revenue” and “Profit”.
Therefore, remove some of the improper factors, the final DMU
data table is shrunk to include only 2 inputs and outputs each.
According to the assumption of DEA, all values of raw data need
to be positive, but the output factor, profit, has negative values in
some DMUs.
Therefore, following the DEA method, this research adds120
million for all DMUs’ profit to adjust the data, and then DEA might
start to work. The final DMU data table is then changed to Table 4.
Variable setting
Following the ACS’s procedure, this paper assumes that the input
resource could be reduced by 20% and output resources could be
increased by 20%. Therefore, k is 0.8 which means we would sum
the input resources for two strategic alliance companies then
multiply by 0.8 and m is 1.2, which means we would sum the input
resources for two strategic alliance companies then multiply by 1.2.
The combinations of inputs and outputs are demonstrated in Table 5
with a total of 16 scenarios. These 2 parameters could be changed
according to the expert’s assumption.
Calculation
First of all, execute the CCR for DMU data table, to understand the
DMU performance ranking prior to the formation of the alliance. The
results are shown in Table 6. Five companies have the best
efficiency. They are E, H, L, Q, and S. Secondly, start to form a
virtual company and execute a DEA calculation for every scenario.
According to ACS’s procedures, each virtual company needs to run
for 16 scenarios and in total there will be 19 virtual companies.
Three hundred and four DEA calculations were conducted (16 * 19 =
304). This research summarizes the frontiers in the frontiers number
table, which is depicted as Table 7. Since every virtual company has
a total of 16 scenarios, the ‘Successful Chance’ is defined as the
frontier number divided by 16 (total 16 scenarios). The successful
chance is illustrated in Figure 2.
RESULTS ANALYSIS
Compared with the performance ranking before and after
the formation of the alliance for all DMUs (Tables 6, 7 and
Figure 2). Some major issues are summarized as follows:
The company E, H, L, Q, and S are the best 5 efficiency
rated companies before the formation of any strategic
alliance. They are the best potential candidates for
astrategic alliance. However, after ACS calculation, the
results are different. After our calculation, the company H,
L, and Q retain the first priority. These virtual companies
have the highest opportunities (100%) to have the best
efficiency following the formation of a strategic alliance.
The company A and K are both second priority. Both of
their virtual companies have 12 frontiers. This means both
of them have a 75% opportunity to retain the leading edge
in this industry. The company E is third priority. Its virtual
company has 11 frontiers. This means company E only
has a 69% opportunity to remain the best and has the
best efficiency prior to the formation of an alliance.

Table 5. Scenario table.
Wang and Wang 7417
Scenario Sum of capital * k Sum of employee * k Sum of revenue * m Sum of profit * m
1 1 1 1 1
2 0.8 1 1 1
3 1 0.8 1 1
4 1 1 1.2 1
5 1 1 1 1.2
6 0.8 0.8 1 1
7 0.8 1 1.2 1
8 0.8 1 1 1.2
9 1 0.8 1.2 1
10 1 0.8 1 1.2
11 1 1 1.2 1.2
12 0.8 0.8 1.2 1
13 0.8 0.8 1 1.2
14 0.8 1 1.2 1.2
15 1 0.8 1.2 1.2
16 0.8 0.8 1.2 1.2
Table 6. DMU Performance ranking before alliance.
No. DMU Score Rank
5 E 1 1
8 H 1 1
12 L 1 1
17 Q 1 1
19 S 1 1
11 K 0.9284006 6
20 Target company 0.8447962 7
3 C 0.8396367 8
1 A 0.8195542 9
16 P 0.6655952 10
2 B 0.6284619 11
7 G 0.6144914 12
18 R 0.553452 13
14 N 0.5335715 14
9 I 0.5121536 15
10 J 0.5121189 16
4 D 0.453699 17
6 F 0.4238099 18
13 M 0.4138679 19
15 O 0.1838214 20
Therefore, company E will have less desire to form an
alliance, because it might reduce its performance.
The companies N, C and P are fourth priority and their
virtual companies have the success chances of 50, 38,
and 13%, respectively. Even though the results are not
perfect, if we check the performance before the formation
of an alliance from Table 6, we will find that these
companies will experience great improvement through
Table 7. Frontier number table.
Company Frontier number Rank
H+Target Company 16 1
L+Target Company 16 1
Q+Target Company 16 1
A+Target Company 12 4
K+Target Company 12 4
E+Target Company 11 6
N+Target Company 8 7
C+Target Company 6 8
P+Target Company 2 9
B+Target Company 0 10
D+Target Company 0 10
F+Target Company 0 10
G+Target Company 0 10
I+Target Company 0 10
J+Target Company 0 10
M+Target Company 0 10
O+Target Company 0 10
R+Target Company 0 10
S+Target Company 0 10
forming an alliance. This means they would have strong
desire to form alliance. For other companies, where the
frontier number is 0 after the formation of an alliance, this
means they will have no chance to achieve the highest
level of efficiency through an alliance. This research does
not recommend these companies forming an alliance.
Besides, company S had the best ranking before
forming of an alliance, but its virtual company has no
chance to be perfect. This means a good company is not

7418 Afr. J. Bus. Manage.
Figure 2. Successful chance.
always suitable for an alliance. Through calculation by
ACS, a wrong combination alliance will be easy to
distinguish. The method of ACS and the analysis are both
discussed in a forum with several industrial managers
(including the managers from target company) and their
feedback was sound. Target company is planning to use
ACS for their evaluation tool for partner selection of
strategic alliance.
ACS is recognized to effectively provide all essential
analysis and recommendations to enterprises for strategic
alliance.
CONCLUSIONS
Biotechnology is the star industry of coming era. Strategic
alliances have become a popular strategy for many
biotech companies to extend their business roadmap. The
objective of this paper is to develop an effective method to
assist biotech companies in evaluating operation
efficiency and finding the best candidate for a strategic
alliance in complicated technology conditions. Its focus is
on the realization of strategic plans and efficiency.
According to ACS, candidates will be easy to separate
into different priorities. This application design might help
top management in their decision making process for
business extension.
The results are sound for enterprises to find future
candidates for a strategic alliance. Besides, academic
researchers also can fully use this model to extend the
applications of DEA for more diversities. Furthermore,
selection of inputs and outputs are also more alternatives
for study, such as research and development expenses,
research and development manpower, etc. Future
direction should be in the consideration of the involvement
with intangible resources, for input factors or output
factors, and analysis among different industries.
Moreover, the trend of inputs and outputs could be
discussed as well.
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African Journal of Business Management Vol. 5(17), pp. 7420-7427, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.199
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Technology portfolio modeling in hybrid environment
Sattari Ardabili, Farzad
Islamic Azad University-Ardabil Branch, No. 82, Allahiari Alley, Mostafa Khomeini St., Emam Khomeini Ave. P. O. Box
56147-44464, Ardabil, Iran. E-mail: farzadsattary@yahoo.com, sattaryardabili@modares.ac.ir. Tel: +984517714090.
Fax: +984517714091.
Accepted 15 March, 2011
Technology portfolio selection is one of the critical decision making process for any manager. This
paper considers a fuzzy mixed portfolio selection with random fuzzy return and new hybrid algorithm
approach for solving it. Fuzzy set theory is applied to model uncertain and flexible information. Since
traditional technology evaluation methods is often unable to consider vague data gathered from
environment, in this paper, the returns of each technology are assumed to be fuzzy random variables.
In proposed hybrid algorithm we employ outputs of neural networks to produce initial solution for
genetic algorithm and in order to reduce the computational work. Finally, we apply the model for
investment case in carwash technologies selection. We concluded that the proposed approach can
assist decision makers in selecting suitable technology portfolios, while there is a lack of reliable
project information.
Key words: Technology portfolio, fuzzy random variable, neural network, chance programming, genetic
algorithm, hybrid intelligence.
INTRODUCTION
To employ the best function of resources is one of the
major obligations of technology managers. This issue
implicates allocating resources (asset, individuals,
facilities, equipment…) to a range of various technological
programs, and it includes a main question that
which means should be chosen to carry out development
aims (Jolly, 2003). A good technology portfolio may
enable a company to promote production profitability,
efficiency and capability of constant concordance,
international development and appropriate competitive
advantage (Cui et al., 2006). Kelly and Rice found out
that firms can attract trustworthy and consistent
associates by creating important technology portfolios
(Kelly and Rice, 2002).
For formulating and systematizing these decisions,
models of technology portfolio were designed in 1980’s,
with the aim of assisting technology managers in
undertaking such a delicate task. The main methods of
technology portfolio modeling, for certain, should take
Harris et al. (1981), Foster (1981), or Little’s models
(1981) into account. More recent approaches, regarding
the interdependences between projects, try to investigate
the impacts of risk diversification (Ringuest et al., 1999)
and to propose purchase strategies based on technology
portfolio categorization (Hsuan, 2001), and base on
qualitative approach (Akinwale and Abiola, 2007) or focus
on searching for optimized portfolios, that is, suited to the
new product development strategy of the firm
(Balachandra, 2001).
TECHNOLOGY PORTFOLIO MODELING
Portfolio selection for strategic management is a crucial
activity in many organizations, and it is concerned with a
complex process that involves many decision-making
situations (Lin and Hsieh, 2004). When a company
intents to perform beyond its investment, it can develop
its investment based on technology knowledge. Such a
company can incorporate new knowledge and own
unique technologies, which demands creating portfolio
from technological assets (Grindley and Teece, 1997).
Financial and organizational limitations can affect the
technology development of a company. This problem can
be observed particularly in small firms (Chan and Heide,
1993; Lerner, 1997). Maidique and Patch (1998) indicate
that strategy technology is a technology portfolio that a
company devises for gaining advantage in market.

Technology managers need to attract, receive and
transfer technological knowledge to other sections of
company, under a particular situation (Malik, 2002). In
addition to above mentioned points, this technology,
which plenty of studies have been undertaken on it,
influences other kind of management in the company, as
well. This management is called portfolio management
that according to the type of technology carries out major
revisions in optimal combination of assets.
One way of improving the market penetration rate of
efficient technology can be generalization of portfolio
concept into efficient and inefficient technologies, rather
than depending on only one kind of technology. Such a
conception of portfolio can contribute to diversification of
risk which is associated with investments in efficient
devices and equipments (Balachandra and Shekar,
2001).
So far, copious researches have been undertaken on
the ground of portfolio selection. And majority of them
underlie Markowitz approach and his proposed
mathematical model which was based on mean-variance
(Markowitz, 1952). This model by keeping its centrality
has been groundwork of new models of portfolio (Ehrgott
et al., 2004; Campbell et al., 1997; Elton and Gruber,
1995; Jorion, 1992).
However, investigators have proposed other models for
portfolio selection that some of them are: capital asset
pricing model CAPM (Luenberger, 1997; Lerner, 1997),
Semi-variance model (Mossin, 1966), Safety-first model
(Campbell et al., 1997) and so on. The portfolio selection
problem deals with how to form a satisfying portfolio. It is
difficult to decide which assets should be selected
because of the uncertainty on their returns (Gupta et al.,
2008).
Inadequacy of Hard or Crisp mathematical models in
covering uncertain, imprecise and vague states necessitates
employment of fuzzy principles and method (Elton
and Gruber, 1995). Particularly, incremental development
of vagueness and uncertainty sources and different
approaches for controlling them reveals the exigency of
proposing new optimized models. The information that
the decision makers obtain are usually expressed with
linguistic descriptions such as high risk, low benefit or
high rate of interest (Sheen, 2005) which were identified
by Zadeh’s Fuzzy theory (Zadeh, 1978). It was
determined that insufficient knowledge around asset
return and involved in the behavior of financial markets
treatment can be captured by means of fuzzy quantities
and/or fuzzy constraints.
Recognizing optimized point for a decision maker is
difficult task and usually due to plurality of choices, it is
time consuming. Inasmuch as such a decision making
has to do with selection or non-selection, mostly is formulated
as 0-1 function (Lin and Hsieh, 2004). Applying
integer programming to risk priority reduction (Glickman,
2008) and using linear programming with infinite
dimensions (Carlsson and Fuller, 2001) have been
undertaken in recent years, which each of them has
Farzad 7421
attempted to get the optimal answer, in a way. Therefore
discussing these two states simultaneously that combine
fuzzy random return and integer selection as a comprehensive
model can lead to better results especially in
contrast with initial models.
FUZZY RANDOM VARIABLES
In the current situations, future returns are accompanied
with lots of complexities. Because of this vagueness and
complicacy, predicting future returns through the method
of historical data is not feasible. In order to confront this
problem, researchers have suggested applying Fuzzy
sets theory (Zadeh, 1965, 2005). But even in that case,
there has also been some problems in risk calculation
which is rooted in uncertainty, furthermore a lot of models
have been proposed around the issue of portfolio that
among them Watada (1997), Carlsson et al. (2002) and
Huang’s model (2007a) can be referred. However, one of
the best ways in which the investors can manage
uncertainty is applying random and fuzzy optimal models.
In real world as well, some of the investors, faced with
uncertainty, use fuzziness and randomness simultaneously
(Huang, 2007b), that are indicator of random
returns with fuzzy parameters and environments (Tanaka
et al., 2000; Inuiguchi and Tanino, 2000).
Random fuzzy variables were introduced for the first
time by Kwakernaak (1978, 1979). The basis of this
matter in fuzzy random variable is a measurable function
from a possibility space to the set of fuzzy variables.
Fuzzy random variables are indicators of fuzzy random
phenomena, which are in fact future returns with fuzzy
values. In other words, each random fuzzy variable X ~
includes at least one random variable X as origin of X ~ .
So, random fuzzy variable X ~ is the fuzzy consequence
of uncertain design of that is the
class of all the fuzzy numbers in n
R . Figure 1 depicts
one-dimensional random fuzzy variable.
After Kwakernaak this concept was developed by
researchers like Puri and Ralescu (1986), Kruse and
Meyer (1987) and Liu and Liu (2003a). Liu and Liu
(2003b) have presented different spectra of Expected
Value Model (EVM) of fuzzy random variable, and
because of the necessity of measurability and ranking of
fuzzy random variables they introduced Numerical
Expected Value Operator. In 2001 the concepts of
optimistic and pessimistic values were proposed by Liu
(2001). The capability of fuzzy random variables, will be
more obvious when the probability distribution is
determined. The distribution of random variable of
2
X ~ N ( µ , σ )
is considered with fuzzy µ 2
and definite σ .
~ 2
For example if ξ ~ N ( µ , σ ) and µ~ is triangular fuzzy
~
variable µ = ( a,
b,
c)
, then ξ ~ n
n
Ω → F(
R ) F(
R )
is a random fuzzy variable
with normal distribution value (Liu, 2002).

7422 Afr. J. Bus. Manage.
Figure 1. Quality of one-dimensional random fuzzy variable.
Definition 1- A random fuzzy variable, is a function of ξ
from proba-bility space of
( Ω,
Α,
Ρr)
to the set of fuzzy
Cr ξ( ω ∈ B
as a measurable
variables such that { }
function of ω for any Borel set B from ℜ . For example,
if
( Ω,
Α,
Ρr)
Ω = { ω , ω ,..., ω }
is a possibility space and if 1 2 m
and m are fuzzy variables, then function
u u u ,..., , 1 2
⎧u1,
⎪
⎪
⎪u
2 ,
ξ(
w)
= ⎨
⎪.....
⎪
⎪u
m ,
⎩
if
if
if
ω = ω
1
ω = ω
2
ω = ω
m
Is clearly a random fuzzy variable (Liu and Liu, 2003b;
Liu, 2006).
For example, if η is random variable defined on the
probability space ( Ω , Α,
Ρr)
, and a~ is a fuzzy variable, then
the sum
a ~ ξ = η +
will be a random fuzzy variable
defined by
ξ ω = η ω + , ∀ω
∈Ω
~
( ) ( ) a
Definition 2- Let ξ be a fuzzy variable with µ
membership function µ . For any set A of real numbers,
the credibility is defined as (Liu and Liu, 2002):
1
Cr{
ξ ∈ A}
= ( sup µ ( x)
+ 1−
sup µ ( x))
2 x∈A
c
x∈A
Definition 3- Let ξ is a random fuzzy variable that is
(1)
(2)
(3)
defined on incredibility space
( Θ,
P( Θ),
Cr)
expected value E(ξ ) is defined as follows:
∞
0
E( ξ)
∫ Cr{
θ ∈Θ
E[
ξ(
θ)
] ≥ t}
dt −∫
Cr θ ∈Θ
E[
ξ(
θ)
]
= 0
−∞
{ ≤ t}dt
then the
provided that at least one of the two integrals is finite (Liu
and Liu, 2003c).
Portfolio model, fuzzy random variable approach
In this part the technology portfolio is formulated as
optimized issue with fuzzy objectives. Portfolio selection
problem involving the random fuzzy variable based on
the standard asset allocation problem to maximize the
total future return can be as follows (Hasuike et al.,
2009):
Maximize
Minimise
S.
t :
that
a ij
, b∈
R
z =
Var(
∑
∑ ∑
n
∑
i∈N j∈N
i
i∈N
i
i=
1
a
~
r x
ij
x
i
~
r x )
ij
i
≤ b
(4)
(5)
are real coefficients, and ij r~
is the average
of the future return rate of technology i , and they are in
the form of fuzzy random variables, it means that
r~ ij ∈ F(
R)
σ
ij . Also is the common covariance which is
considered for risk reduction in portfolio models. To date,
different methods for integrating the twofold objectives
have been devised. The objective function of the above
model can be revised in the form of integrating risk
reduction and the return average increase. For

λ is the
parameter for risk aversion. So it can be written:
undertaking this task, assume that ∈[
0,
1]
And in the case that the values of the variables are in the
form of integer, we have:
⎡ n n ⎤
n ⎡
( 1 ) ~ ⎤
Minimise λ⎢∑∑
xiσ
ij x j ⎥ + − λ ⎢−∑
µ r x i i ⎥
⎣ i=
1 j=
1 ⎦ ⎣ i=
1 ⎦
S.
t :
Where λ = 0 represents the state of the maximizing the
return and it is the optimal point with the highest return
mean. Any value between (0 and 1) is the representative
of the exchange between the return mean and variance
that will have an answer between the two ends of the
problem when λ = 0 and λ = 1.
k is the representative of the limitation of the technologies
number.
And u , l are also the representatives of the high and low
limits considered by the investor to purchase the type i
technology.
One of the dimensions of the twofold models of portfolio
is decreasing the risk, which is fulfilled by minimizing the
variance. In this study, by considering the point that the
returns of technologies are as random fuzzy LR
variables, the covariance of these variables equals
(Nather, 1997; Korner, 1997):
Cov[
X,
Y]
= Cov[
m , m ] + a [ Cov(
l , l ) + Cov(
r , r )]
l1
x
y
x
l2
− 2a
[ Cov(
m , r −l
+ Cov(
m , r −l
Y
Y
That l , m,
r are the triangular fuzzy numbers. Supposing
that the random LR variables are symmetrical, we have:
Regarding the independence assumption of
l , m,
r
it can
be written:
1 1
Var ( X ) = Var(
m)
+ Var(
l)
+ Var(
r)
6 6
And
∑∑
ij
i∈N j∈N
n
∑
i=
1
i
i
i
a x
i
ij
x = k
y ∈{
0,
1}
≤ b
ly ≤ x ≤ uy
Cov[
X,
Y]
= Cov[
m , m ] + a [ Cov(
l , l ) + Cov(
r , r )]
−2a
[ Cov(
m , l ) + Cov(
m , l
l1
x
y
x
l2
Y
i
X
Y
Y
X
X
Y
)
Y
X
X
Y
X
X
)
Y
(6)
(9)
(7)
(8)
1
Cov ( X , Y ) = Cov(
mX
, mY
) + Cov(
l X , lY
)
3
Farzad 7423
(10)
Regarding the point that both left and right ranges are
equal when the random variables are normal, it can be
written:
n n
1 ~ ~
Var [ r~
] = [ ( ~ , ~
∑∑ X i X j Cov ri
rj
) + Cov(
li
, l j )]
3
i=
1 j=
1
(11)
where i r~
j , r~
, the returns of variables i and
j l
, and i ,
~
l j
are indicators of their ranges.
The type of above model cannot be solving with common
methods so we employ Max-Min approach and nonlinear
programming methods. The nonlinear algorithm that
would be considered in this research is hybrid algorithm.
Nonlinear optimization will employ hybrid intelligence
algorithm that use neural networks outputs as the input
chromosomes (Huang, 2007b) and Max-Min
approximation can be based on Lai and Hwang (1992).
A proposed model
The objective function of the problem
In the mean and variance model of Markowitz (1952,
1959), the returns have been considered as random
variables and it has been supposed that the investors are
aiming at striking balance between maximizing the return
and minimizing the risk of investment. Thus, the returns
with the mean, and the risk with the variance portfolio
became quantitative.
The random fuzzy variables are one of the best
possible ways to encounter the simultaneous random and
fuzzy uncertainty (Li and Xu, 2009). If we suppose that
the return of technology i is a fuzzy random variable, its
membership function can be displayed in the simple
triplet (l, m, u) form, as it is shown in the following:
⎧ x − l
⎪m
− l
⎪
x − u
µ = ⎨
⎪m
− u
⎪0
⎪
⎩
l ≤ x ≤ m
m ≤ x ≤ u
otherwise
~
(12)
The reason of using triangular fuzzy numbers for the
fuzzy parameters is the augmentation of calculating
efficiency (Klir and Yuan, 1995) (Figure 2).
The return rate of each technology is in the form of
r
fuzzy triangular numbers as: i = ( mi
−α
i , mi
, mi
+ β i )
m
in which i , is the random variable with normal

7424 Afr. J. Bus. Manage.
Figure 2. Triangular fuzzy numbers.
2
distribution mi ~ N(
E(
mi
), σ i ) , i and i are also left
and right spreads, respectively. The objective function of
the problem can be reflected in the form of defining
variables of the future incomes as random fuzzy and
reducing risk.
n
r Max∑
~
=1
i
i i X
n
n n
~
Min Var(
r X ) = σ x x
(13)
(14)
where: i r
~
: The mean of the future monthly income of
technology i σ ij
which is in random fuzzy variable form. :
The common covariance
X i
⎡
⎢
0
=
⎢
⎢⎣
1
∑
i
i=
1
if
thechnolog
y
otherwise
i
∑∑
i=
1 j=
1
ij
i
i
is
purchased
We can revise the above objective function in the
following way:
Above nonlinear function (13), with replaced expected
value of distribution, can be rewritten as:
n
Max∑ =
i 1
E(
~ r
i X i
)
(15)
Because r is the random with normal distribution, we can
use normal mean for expected value. And also can be
rewriten risk objective function as a separate constraint:
Ch{ r
~
x ≤ b }( γ ) ≥1
−α
∑
i
i
i
i
(16)
where i b represents investigator target return, i is the
predetermined confidence level and γ is the pessimistic
return from technology i .
And also, because the chance of a random fuzzy event
j
α
β
α
characterized by
f ( ξ ) ≥ 0
is a function from (0, 1] to [0,
1], defined as (Liu, 2002)
Ch{
f ( ξ ) ≥ 0}(
γ ) = sup inf Pr{ f ( ξ ( θ))
≥ 0}
Cr { A}
≥γ
θ∈A
(17)
thus,
Ch{ f ( ξ ) ≥ r}(
γ ) = Pr{ f ( ξ ( θ )) ≥ r}
(18)
That for any specific r value can be calculated as follow:
Ch
~
∑ ri
xi
≤ bi}
≥ 1−
n
= Pr{ b − (
~
i
i ∑ ri
xi
i=
1
{ α ) ≥ r } ≤ α
The constraints of the problem
(19)
a) The starting up constraint: this constraint is related to
the costs of starting up the technology. The starting-up
costs should not be higher than the initial budget of
investment, that:
n
∑
i=1
Si
Si X i ≤ BI
(20)
, is the required budget for purchasing and starting up
technology i , and
BI , is the initial budget of investment.
b) The workforce constraint: this limitation represents
individuals that are skilled in working with technology i
and are needed and should be in access. By taking into
consideration that determining the exact number of
qualified individuals in work market is not possible and
judging about the amount of their skill and their number
involves some vagueness, the fuzzy numbers’ set is used
for expressing the judgment of experts.
n
∑
i=
1
~ ~
p X ≤ P
i
i
i
(21)
p~
i : The number of required qualified individuals for
working with technology i .
P i
~
: The number of available qualified individuals for
working with technologyi .
c) The return constraint: The return rate of any
technology for fulfilling investors’ objectives should be
higher than the investors’ expected return rate for
Technology i in a span of time. The expected rate is
taken into account as fuzzy, inasmuch as the vagueness
and uncertainty of the rate, in order to make every
0
0

specified ranges of return, for each technology, possible
to investigation. That:
n
∑
i=
1
r~
i is the future return rate of Technology i
~
Rexp i
r~ ~
X ≥ Rexp
i
i
is the future expected rate for Technology i
(22)
d) The volume constraint: this limitation is the
representative of total number of possible technologies.
n
∑
i=
1
X
i
= k
e) The variables constraint.
ly i
≤ x ≤ uy
y ∈{
0,
1}
i
; int
eger
i = 1,
2,...,
n
(23)
(24)
l and u are lower and upper number of one technology
type in portfolio, respectively.
Now we can formulate the model as:
Max
st :
Pr{
f
Pr{ b − (
n
∑
i=
1
n
∑
i=
1
n
∑
i
i=
1
n
∑
i=
1
S x ≤ BI
~ ~
p x ≤ P
~ ~
r x ≥ R
x = k
ly ≤ x ≤ uy
y ∈{
0,
1}
i
x ; integer
i
i
n
∑
i
i=
1
i
i
i
i
i
r
~
x ≥ f } ≥ β
i
i
i
i
n
∑
i
i=
1
~ r x ) ≥ r } ≥ α
i
expi
i
i
i = 1,
2,...,
n
The performance of the model
0
0
0
In order to test the model, investment in starting up a
huge carwash was studied. Various and related
technologies in this area included different sorts of fully
automatic, half automatic, and manual advanced
Farzad 7425
machines which were in different groups such as washing
passenger cars, trucks, tankers, trains, and water jets,
floor washers, chair washers, polishers, … and in various
spectra of models and facilities. Since it was not possible
to mention the commercial names, abbreviator signs
were used for them.
First, the rate of the expected return of each technology
and the right and left limits have been calculated.
Calculation of the right and left sides’ values, the vector
of the expected return rate, and the matrix of covariance
has been made by employing historical data and experts’
(the owners of car washes and sellers) ideas. For
gathering this data, at first the historical data of thirteen
models of car wash equipments during the past 12
months in the years 2009-2010 have been collected and
used for approximating the return rate of technologies
i j n n
and covariance matrix
a a Cov V = ( ( , )) × . Subsequently,
the experts and active individuals in this area were asked
to state their own estimation of the rate of α i and β i .
The mean of these estimates were considered as right
and left limits and the return rate of fuzzy random variable
of Technology i is
E( ri
) =
( E(
mi)
−α
i,
E(
mi
), E(
mi)
+ βi
) .
The number of technologies considered by the investor
( k = 4)
is aggregately four machines, and maximum
number of technology i and personnel, is 2 Unit, 3 people,
respectively. Also the initial budget of investment is 400
R )
million. Expected rate
( exp
has obtained 0.85 with 0.3
and 0.15 upper and lower spreads respectively from
questioners.
Hybrid intelligent system
Since it is difficult to find the optimal solution of the
proposed model (Chow and Denning, 1994) in traditional
ways, we use linear and nonlinear (hybrid) approximation
methods simultaneously. We can use the technique of
simulation (Colubi et al., 2002) and genetic algorithm
(Holland, 1975) based on random fuzzy simulation to
help find the optimal solution with hybrid algorithm. When
random fuzzy simulation is integrated into GA, the
algorithm will take a fairly long time to find the optimal
solution. In order to lessen the computational work, we
employ neural networks (NNs). NNs are famous for
approximating any nonlinear continuous functions over a
closed bounded set (Huang, 2007b). An ANN creates a
model of neurons and the connections between them,
and trains it to associate output neurons with input
neurons. The network ‘‘learns’’ by adjusting the interconnections
(called weights) between layers. When the
network is adequately trained, it is able to generate
relevant output for a set of input data (Mirbagheri, 2010).
In order of neural network modeling, we use one input
layer, one hidden layer (with 13 neurons) and two

7426 Afr. J. Bus. Manage.
Table 1. Comparisons of object values by hybrid intelligent system.
Population size m P
Crossover function f X
20 0.2 0.8 0.685879 4,4,7,13
20 0.2 0.5 0.452937 1,4,12,13
20 0.3 0.8 0.5503178 4,4,10,13
20 0.3 0.5 0.8940088 7,7,10,13
30 0.2 0.8 0.9294400 4,5,12,13
30 0.2 0.5 0.92452 5,7,12,13
30 0.3 0.8 0.946780 3,4,5,13
30 0.3 0.5 0.9543 3,4,10,12
neurons as output layer. In this research, one training
data set for uncertain objective function employed and for
training theses data, back propagation algorithm investigated.
And also, logistic sigmoid function used in hidden
layer. Also, for running genetic algorithm we define an
integer pop-size = 30 as the number of chromosomes
and initialize pop-size chromosomes randomly to produce
feasible chromosomes explicitly. Expected values and
chances were calculated by them. The probability of
crossover and probability of mutation are pc
= 0.
5 ,
pm
= 0.
3 respectively. The hybrid intelligent algorithm
was described as follows:
Step 1. Generate training input-output data for uncertain
functions like
U = max{ f
U
U
1
2
3
= Pr{ b − (
Pr{
n
i
i=
1
= E[
f ( x),
ξ]
i
∑
n
∑
i
i=
1
r~
x ≥ f } ≥ β }
r~
x ) ≥ r }
i
i
0
by the random fuzzy simulation.
Step 2. Train a neural network to approximate the
uncertain functions according to the generated training
input-output data.
Step 3. Initialize pop size chromosomes whose feasibility
may be checked by the trained neural network.
Step 4. Update the chromosomes by crossover and
mutation operations.
Step 5. Calculate the objective values for all
chromosomes by the trained neural network.
Step 6. Compute the fitness of each chromosome
according to the objective values.
Step 7. Select the chromosomes by spinning the roulette
wheel according to the different fitness values.
Step 8. Repeat the fourth to seventh steps for a given
number of cycles.
Step 9. Report the best chromosome as the optimal
solution of technology portfolio selection problem.
A run of the hybrid intelligent algorithm (1000 cycles in
0
random fuzzy simulation, 500 training data in NN, and
500 generations in GA) shows the optimal solution as
Table 1, whose objective value f = 0.
954 is highest
achieved goal value.
CONCLUSION
Because the returns of each technology in the future
cannot be represented with historical data especially in
the absence of enough data situation, in this paper, we
have considered technology portfolio selection in hybrid
environment with random fuzzy returns and linear and
fuzzy constraints to set output as integer values. To
solving randomness and fuzziness simultaneously, a
hybrid intelligent algorithm is provided to estimate
objective function with combinational constraints.
Expected values and the chance constraints were
calculated with neural network and feasible output
employed in hybrid genetic algorithm. An example is
given to illustrate the proposed fuzzy random project
portfolio selection using real data from Carwash Industry
results were showed the high fitness of model (Table 1).
ACKNOWLEDGEMENT
The author acknowledges the Islamic Azad University,
Ardabil Branch for the financial support of the research.
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African Journal of Business Management Vol. 5(17), pp. 7428-7439, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.204
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Analyzing performance of investment companies listed
in the Tehran stock exchange by selected ratios and
measures
Reza Tehrani 1 , Hamed Ahmadinia 2 * and Amaneh Hasbaei 1 *
1 Faculty of Management, University of Tehran, Tehran, Iran.
2 Department of Accounting, Faculty of Teachers Training, Shahre Ray Branch,Islamic Azad University, Tehran, Iran.
Accepted 31 March, 2011
This paper tried to analyze the performance of the investment companies listed in Tehran Stock
Exchange that had active portfolio management from 2006 to 2010 by Sharp, Treynor, and Sortino
ratios. For more profound study of their performances, this research used some of the measures,
including turnover, liquidity, size and diversification of portfolio. After gathering needed test data and
relevant statistical tests as Kolmogorov-Smirnov and Shapiro-Wilk, the results showed the distribution
of data was not normal. Therefore, the hypothesis was tested by nonparametric tests. The results of the
first hypothesis about the three mentioned above ratios and with Freidman and Wilcoxen tests showed
the companies had better controls on systematic risk than other components. The result of the second
hypothesis by using combined Anova and Multiple Anova showed portfolio turnover in the companies
had positive and significant affect in the companies performances than other measures.It is possiblefor
anyone to be able to find a company that has a high level of portfolio turnover and a high level of
performance than other companies while it has a lower level of other measures.
Key words: Investment companies, performance evaluation ratios (Sharp, Sortino and Treynor), performance
measures (liquidity, company size, turnover and being diversified in their portfolio).
INTRODUCTION
Nowadays, investment companies are working in all of
the financial markets.The main task of aninvestment
company is buying and holding other companies
securities with the aim of investing shareholders funds
into a co-portfolio consisting of sharing losses and profits
for them. Thus, the individual investors invest their funds
in securities and make a portfolio while this investment
has a lower risk and more favorable returns for their
investment. Therefore, investment companies have
enough expert individuals to invest funds (Saunders and
*Corresponding author. E-mail: hamed.ahmadinia@gmail.com.
Tel: +98-9192347013
Millon, 2005).
In this paper, we intend to examine performance of
investment companies listed in Tehran Stock Exchange.
Therefore, in this regard based on different theories of
concern with portfolio performance evaluation, at the
beginning of this research using Sharp, Treynor, and
Sortino ratios, which evaluate SD (Standard Diviasion),
systematic risk, and downside risk against the expected
return of investment, we evaluate the performance of
investment companies. These ratios werealso used inthe
following researches: (Pedersen and Ted, 2003) in
London Stock Exchange, (Bengtsson, 2007) in Nordic
and Baltic Stock Exchange, (Chaudhry et al., 2008) in
Australian Securities Exchange, (Galetsas, 2008) in
Greek Stock Exchange, (Rahdari, 2009) in Tehran

Stock Exchange, (Rao, 2010) in National Stock
Exchange of India Limited.
For more detail and precise study of the companies
performances, the following researchers: (Lin and Chang,
2004; Hyung et al., 2005; Hernandez-Perez et al., 2006;
Gonzalez and Rubio, 2007; Gomes and Kruglianskas,
2009; Hu, 2010) were studied on turnover, liquidity, size
and diversification of portfolio.
In our research we tested the ability of Iranian
investment companies in controlling systematic risk to
comparing the company risk and fluctuating level of risk
with their assets allocation in portfolio with the three
ratios:Sharp, Treynor and Sortino.
LITERATURE REVIEW
This study attempted to have a comprehensive
evaluation on portfolio performance of Iranian investment
companies. In order to achieve this goal, we divided
conceptual framework in two parts: performance
evaluation ratios and performance evaluation measures.
In each part, we mentioned relevant previous studies in
detail.
Performance evaluation ratios
Investment in securities exchange is possible by different
methods and motives. In June of 2010, management
report on working opportunity fund, presented that almost
75% of portfolio in investment companies is consisting of
venture investment and this part of portfolio is composed
by 36% common shares, 61% preferred shares and 3%
debt instruments or bonds (EVCC, 2010).
There are many theories in concern with portfolio
performance evaluation. The modern portfolio theory
assumed, the distribution of data is always normal and
the main factorin this theory is emphasized sincethe
systematic risk (β) has a significant influence on all parts
of the market. The ratios in this theory generally examine
the levels of changing risk and its effect on portfolio
performance. For instance,Treynor evaluates the effects
of changing systematic risk on the portfolio performance.
The Sharp ratio examines the effect of standard deviation
on expected return or risk within the company due to
occurring inappropriate allocation of assets in portfolio
formation.
The Sharp ratio is one of the most famous ratios in this
regard. The majority of previous studies suggested the
use of Sharp ratio in performance evaluation (Pedersen
and Ted, 2003; Goetzmann et al., 2006; Eling, 2008).
The Post modern portfolio theory was created with new
assumptions about distribution of data. This theory
Tehrani et al. 7429
emphasized that distribution of data in some conditions is
not always normal, and introduced downside risk as a
new factor for evaluating portfolio performance. By
accepting higer level of risk for your investment portfolio,
you may gain more favorable return. Thus, risk is
assumed as a positive factor. Otherwise, if changes in
level of risk doesnot have a positive effect on portfolio
return, it is identified as a negative factor. The Sortino
ratio is one of the most famous factors in this regard, and
used for performance evaluation, optimizing and
allocating assets in portfolio (Alenius, 2009).
Several studies related to these theories (Modern and
Post modern portfolio) have been done. One of the first
surveys conducted in early 2000 was (Redman et al.,
2000). They examined the risk-adjusted returns using
Sharp, Treynor, and Jensen ratios for seventy portfolios
of international mutual funds, in three time periods: (1985
through 1994, 1985-1989, and 1990-1994). The
benchmarks for comparison were the U. S. market
proxied by the Vanguard Index 500 mutual fund and a
portfolio of funds that invest solely in U. S. stocks. Based
on their research results in the period reviewed by Sharp
and Treynor ratios, it showed better performance for
these mutual funds than market performance. Also,
Jensen ratio showed a positive surplus for their
performance than the base stock return index in the
United States. In 2003 (Pedersen and Ted, 2003) also
measured risk adjusted performance evaluation with the
use of classic and modern performance evaluation ratios.
Finally, the results of relevant statistical test based on the
performance of selected companies on the London Stock
Exchange indicated that the Sharp ratio could be a
suitable ratio for performance evaluation.
In this context,the (Goetzmann et al., 2006) paper
concluded that the Sharp ratio certainly has a superior
ability in comparing with the other ratios for performance
evaluating in investment companies. In connection with
the performance evaluation ratios based on the post
modern portfolio theory (Chaudhry et al., 2008) in a study
on the Australian Securities Exchange examined
performance of selected companies in their statistical
sample. According to lack of normality in data distribution,
their research results showed that the Sortino ratio can
present ability of mutual funds, because it evaluated the
level of downside risk better than other ratios.
Unlike (Chaudhry te al., 2008) paper, (Eling, 2008) in
connection with the performance evaluation ratio like
Sharp, Sortino, Omega and Kalmar and some other
ratios, the results of their research showed abilities of
Sharp ratio on performance evaluation in companies is
more effective than other ratios as well as Sortino ratio.
The paper suggested that only calculating this ratio in
assessing performance of investment companies is
sufficient. Neverthless in all cases the condition of

7430 Afr. J. Bus. Manage.
asymmetric distribution of data for using postmodernratio
is mentioned.
Also addressing this point (Aragon and Ferson, 2006),
they mentioned the inability of ratio based on post
modern portfolio theory in providing real performance of
investment companies. They suggested using modern
ratios in this regard (Mau, 2009). Also in a study entitled,
"Back to the Basics: A Process Approach for Managing
Portfolio Risk" proposed to use a framework that
contained both quantitative and qualitative aspects of risk
on return. This framework includes seven different
strategies that are used under different market
conditions.
Finally, one of the most recent researches on the
structure of optimal portfolio management by (Ben et al.,
2010) has been applying the theory of the rank
dependent utility framework. They illustrated how these
products can be in accordance to investor's attitude
towards risk, whereas, for the standard expected utility
case.
Performance evaluation measures
In order to better understand the relationship between
these measures and portfolio performance, we reviewed
and pondered the previous researches on these matters.
Associated with firm size: (Lu, 2007) In his master's
thesis he wrote, although, much research has been done
in connection with the impact of firm size on performance,
and and believing that increasing in the size of the
company lead to higher company turnover. Therefore, the
cost will be dividedinto more units, and has a positive
effect on performance of the company. Even so, positive
and clear evidence in this case has not been found. The
main reason in this matter is the positive perspective
about increasing size of a company and its effect on
performance, and its relation with the economic sphere
and reducing transaction costs in large volume.
In connection with the turnover as firm size: (Lo and
Wang, 2000). They xpressed that turnover is defined by
the total number of traded shares. In other words, it is the
total volume of money that is used in the stock exchange
trading on an investment portfolio. The same advantages
for high firm size are also conceivable for the high
turnover.
According with liquidity portfolio performance: (Donor
Advised Funds, 2010). In their Liquidity Portfolio leaflet
they mentioned that the Liquidity Portfolio is designed to
maintain account balances for active grant making and is
comprised primarily of deposits with leading community
development and environmental banks; as well as, bonds
that offer supporting economic development projects,
affordable housing, and environmental initiatives. The
portfolio maximizes diversification among deposit
institutions to secure the highest level of federal
insurance for its cash deposits. Also, regarding liquidity
(Liu, 2006) he said that liquidity of assets is the ability to
quickly deal with the high volume of securities with the
lowest cost and lowest negative effect on stock prices.
Effect of portfolio diversification on portfolio performance:
(Sullivan and Sheffrin, 2003). In connection with
the effect of portfolio diversification on portfolio
performance they have said, diversification means
reducing financialrisk by investment in a variety of assets.
If the asset values do not move up and down in perfect
synchrony, a diversified portfoliowill have less risk than
the weighted mean risk of its constituent assets, and
often less risk than the least risky of its constituents.
The following part is about, more recent research
mentioned in connection with these indicators:
Associated with the impact of turnover of investment
portfolio on the performance of investment companies,
recently (Rao, 2010) in a research about selected 37
companies from 307 available listed companies in
Bombay Stock Exchange. The findings of the study were
of mixed nature and lacks evidence that is statistically
significant to suggest that increase in portfolio turnover
ratio would result in enhanced performance of the fund
which implies that high portfolio turnover ratios does not
necessarily improve the fund performance consistently
over a long time period. There is no conclusive evidence
to suggest that there is significant relationship between
portfolio turnover ratio and measures of fund
performance used for this study, absolute fund return and
fund performance relative to Benchmark index.
The effect of risk reduction through diversification of the
investment portfolio (Hyung et al., 2005) in an article
reviewed the effect of risk reduction through diversification
of the investment portfolio. In this case (Damodaran,
2009) his research alsoexpressed that diversification lead
to company risk reduction and has many economic
benefits for the companies. Through this way, we can
achieve the lowest level of risk for each element in the
investment portfolio. However, unlike the twopervious
mentioned studies, in a study conducted in Shanghai
Stock Exchange (Hu, 2010) expressed over the desirable
diversification in the investment portfolio lead to
disturbing levels of risk, and it will be gaining the results
inconsistent with the principle of diversity.
Recently, many studies about the impact of firm size on
portfolio performance have been done and significant
results have been expressed. For example,
(Hishamuddin, 2006) in a study conducted in the
Malaysian Stock Exchange expressed that large companies
have higher return and lower risk in comparison
with small companies that have fewer volume of
investment. He concludes there is a negative relationship

etween size and unsystematic risk in which the larger
the firm size, the unsystematic risk is lower. In a similar
paper (Hernandez-Perez et al., 2006) studied distribution
of company size in firms in developing countries and
developed countries. The results showed the size of
companies in developing countries is different from
developed countries with significant basis.
This point will provide suitable information about
economic conditions in both developing and developed
countries. In another study (Maffini and Clandia, 2009)
examined the effect of company in innovative
performance in Brazil Stock Exchange. They concluded
according to the size of the companies, there are some
significant differences in aspects related to the access to
technology and the types of external sources of
technological information used by the firms (Kalin and
Zagst, 2004) explored in an issue about the effect of
liquidity of portfolio in German Stock Exchange on
portfolio performance. The case study shows how the
results can be applied to practical trading problems. And
also (Gonzalez and Rubio, 2007) reviewed the portfolio
selection and examined the liquidity of portfolio and its
effects on portfolio performance.
They used sharp ratio in this regard and their research
results showed that companies with positive signs about
the ability of liquidity on their portfolio have better
performance than those companies with neutral
respondents about liquidity on those portfolios. In a
recent study, (Kanasro et al., 2009) examined the
position of stock market liquidity at Karachi Stock
Exchange (KSE) during the period from 1985 to 2006.
They found less liquidity causes fewer synchroni-city in
prices attracting fewer investors and results is a smaller
size of market.
MATERIALS AND METHODS
The materials and methodsused in this research are as scientificas
possible. In addition, the correlation of its main goal is to identify the
relation between dependent and independent research variables.
Our research did notignored companies which had inactive
portfolios for several months during the period of study. Therefore,
this study consists of all the investment companies listed in Tehran
Stock Exchange during 2006 to 2010.
The relevant data is gathered from Tehran Stock Exchange
companies and analyzing stock software’s as Dena Sahm and Pars
Portfolio. Other needed information is obtained from financial
statements, relevant auditing statements and other creditable
sources.
Research objectives
The aims of the investments are to increasing the assets value.
Therefore, the investors have to invest some of their assets in bout
high and low risk stocks. Portfolio assessment is important for
Tehrani et al. 7431
investors. If the results are not satisfactory to investors, their
portfolio performance should be adaptable to change. Thus,
portfolio performance evaluation is crucial. Whether a person may
evaluate his/her portfolio or have it done by a brokerage company
in one of the following three ways:
1. The company perspective: It is instrumental for the investment
company to show good results in their performance to attract
investors from their competitors.
2. The investors perspective: Investor’s bottom line is the maximum
return on investment. Therefore, investors consider any firm that
whichachieves the highest return on investment.
3. The stock market and economic perspective: Public participation
increases or decreases based on economic situation. Entering the
market for every investor is based on his/her experience.
Importance of research
The 2009 financial crisisalarmed us to be more careful in formation
of a portfolio. Also, in the same token the managers, shareholders,
other interested individuals, and investment institutions are
considering the importance of portfolio management more than
ever. Therefore, the present study in this regard reviews the
following aspects:
1. The organization of a portfolio is an important consideration
bythe above interested individuals and companies. Nevertheless,it
is essential for them to be informed with the components of
investment portfolio.
2. How to organize the portfolio of the company, impacts the
performance, and will be effective. Portfolio is relevant with
systematic risk of companyand noteworthy for shareholder, financial
managers, creditors, as well as competitors of the investment
companies.
The hypotheses
When investors want to make a portfolio, they had to pay attention
to several components. For this reason, we identified important
parts of the portfolio based on previous research that had
significant influence on performance of the investment companies
listed in Tehran stock exchange. The main goal of this research is
finding the best structure of portfolio for the companies which has
the lowest risk while having the highest performance. Hypotheses
called in finance, optimum portfolio were defined as follows:
H1: There are a significant differences between the results of
performance evaluated by Sharp, Treynor and Sortino ratios.
H2: There is a direct correlation between return on investment and
size, liquidity, diversification, and the turnover of the portfolio.
The ratios and measures
Performance ratios
This research is done according to (Bacon, 2008) definition of
Sharp, Treynor and Sortino ratios as they are shown in (Table 1a).

7432 Afr. J. Bus. Manage.
Table 1. The Sharp, Treynor and Sortino Ratios (Bacon, 2008).
Ratio Formula Explanation
Sharp
Treynor
Sortino
rp
− rf
SR =
σ
p
rp
− rf
TR =
β
SOR =
p
( r − r )
p
σ
p
f
r = Portfolio Return
p
r = Risk Free Ratio
p
σ = SD of Portfolio
p
r = Portfolio Return
p
r = Risk Free Ratio
p
β = Systematic Risk of Portfolio
p
r = Portfolio Return
p
r = Risk Free Ratio
p
σ = Downside Risk of Portfolio
p
The risk Free ratio is defined as the geometric mean of the ratio that central bank of The Islamic Republic of Iran is
published during study period of this survey.
Table 1b. Result of Kolmogorov-Smirnov and Shapiro-Wilk tests about distributions of data.
Kolmogorov-Smirnov Shapiro-Wilk Result
Research Variables T Stat D.F Std. Dev. T Stat D.F Std. Dev. The distribution is not normal.
Sharp 0.461 64 0.000 0.184 64 0.000 The distribution is not normal
Treynor 0.431 64 0.000 0.291 64 0.000 The distribution is not normal.
Sortino 0.309 64 0.000 0.352 64 0.000 The distribution is not normal
Turnover of portfolio 0.440 64 0.000 0.224 64 0.000 The distribution is not normal.
Size of portfolio 0.269 64 0.000 0.538 64 0.000 The distribution is not normal
Diversification of portfolio 0.258 64 0.000 0.728 64 0.000 The distribution is not normal.
Liquidity of portfolio 0.351 64 0.000 0.386 64 0.000 The distribution is not normal
Performance measures
We used Turnover, Size and Diversification of portfolio as
measures and we gathered required data from financial statements,
audition statements and relevant statements published by Tehran
Stock Exchange. Another measure that we used in this paper was
Liquidity of portfolio that we calculate it according to (Amihud, 2002)
as formula I:
ILLIO
i
t
=
1
Days
i
t
Days
∑
d = 1
R
V
i
td
i
td
Formula I: Liquildity of Portfolio (Amihud, 2002).
The variables
In this research variables according to ratios and measures and
their affecton performance of investment companies are considered
as:
Independent variables
Are two types: ratios and measures. Ratios are as follow: SD
Return, Systematic Risk (β) and Downside Risk of portfolio.
Measures are as follow: turnover, liquidity, Size and diversification
of the portfolios.
Dependent variables
Are two types: Ratios, and measures. Ratios are as follow:
performance evaluated by Sharp,Treynor and Sortino. Measures
are as follow: real performance of investment companies. More
information will be mentioned in the next section III under hypo
testing part.

The research schema
Figure 1 indicates our research scheme.
Data analyzing and statistical tests
Figure 1. The research scheme.
In the present study data analysis is considered both quantitative
and qualitative. Furthermore, statistical analysis of data has been
expanded to the research population.
For this purpose, at the beginning, we summarized and classified
collected data by using descriptive statistics. Moreover, we
calculated relevant central parameters, including mean and median,
and dispersion parameters, including variance and standard
deviation. Then, we examined relationships between variables by
inferential statistic tests, such as Comparison Test Rating and
Anova. Process of data analyzing took place by staffing software
packages "SPSS" and "Eviews".
Analyzing the nature of variables and testing hypotheses
The aim of this study is to test and compare performance of
investment companies between both dependent and independent
variables. In this research data is gathered in a population study
consist of 12 members from investment companies listed in Tehran
Stock Exchange. During the study period, these 12 companies had
active portfolio management. According to hypotheses the suitable
tests for examining hypotheses are, test of comparing two pair
Tehrani et al. 7433
variables and Anova.
The research data were obtained from our resources which was
extracted on an annual basis for the period six years. Combined
Anova analysis test was required and were lead us to the best
result. The result of Kolmogorov-Smirnov and Shapiro-Wilk (Table
1b) tests showed the distribution of data was not normal, and Table
2 is the test results. Since, the variable distribution is not normal,
and sample size was large, and data wereremote, As a result,
according to the conditions and status of research data, we used
two groups rank comparing test, and several groups rank
comparing test.
Hypotheses testing
Hypothesis 1
There are a significant differences between the results of
performance evaluated by Sharp, Treynor and Sorting ratios.
The distribution of data was not normal. So, we couldnot use
parametric test to compare multi dependent mean. In an other word
range of changing in observed data was so wide, and they had
been remote.
To examine the hypotheses we had to use nonparametric test.
So, we used the Fridman and Wilcaxon tests for comparing the
relationship among Sharp, Trynor and Sortino ratios in investment
companies.
In the first step, the Fridman test was used and in second step
the pair compares test was used. We consider two hypotheses for

7434 Afr. J. Bus. Manage.
step one as follow:
Table 2. Result of Freidman rank test for comparing mean of ranking on performance ratio in investment companies.
Mean of ranking in compaired ratios
Result of Freidman rank test
Ratio Mean ranking Number State square Fischer D.F Confidence Level
Sharp 1.85
Treynor 2.22
67 5.224 2 0.073
Sortino 1.93
H0: The mean of ranking ofSharp,Treynor and Sortino ratios in
investment companies are not diffrent.
H1: The mean of ranking of Sharp, Treynor and Sortino ratios in
investment companies are different.
⎧H
0 : mean rank
⎨
⎩H1:
mean rank
sSH
sSH
− mean rank
− mean rank
TR
TR
mean
mean
rank
rank
SO
SO
= 0
≠ 0
The results indicate that existence of difference between the three
ranking mean in independent variables are not rejected at 95%
confidence level. The reason was state square Fischer was (5.224)
with two degree of freedom,and it was smaller than critical value
(5.99). In the other word calculated level of error (0.073) was larger
than (0.05).
Based on results obtained from Fridman rank test, from the
largest to the smallest mean of rating for ratios dedicated as follow:
1. Treynor
2. Sortino
3. Sharp
To conclude we can say according to the result of test investment
companies listed in Tehran Stock Exchange had better calculated
performance with Trynor ratio than the other ratios. The result of
test is shown in Table 2.
The Freidman rank test is a general test, and it does not analyze
available missing data.In careful and presice study we also used
Wilcoxen test, to examine the relationship between three mentioned
ratios. We consider three Subsidiary hypotheses about hypotheses
one, as follows:
H1a: There is a significant difference between results of
performance evaluated by Sharp and Treynor ratios in investment
companies.
⎧H
0 : mean ranksh
− mean rankt
= 0
⎨
⎩H1:
mean ranksh
− mean rankt
≠ 0
The result of test indicated that evaluated performance in
investment companies listed in Tehran Stock Exchange by Treynor
ratio is significant better than evaluated performance by Sharp ratio
in the investment company listed in Tehran Stock Exchange. The
result of Wilcoxen test is shown in Table 3.
H1b: There is a significant difference between results of
performance evaluated by Sharp and Sortino ratios in investment
companies.
⎧H
0 : mean rank
⎨
⎩H1:
mean rank
SH
SH
− mean rank
− mean rank
SO
SO
= 0
≠ 0
The result of test indicated that there is no significant difference
between evaluated performances by Sharp and Sortino ratios in
investment companies listed in Tehran Stock Exchange. The result
of Wilcoxen test is shown in Table 4.
H1c: There is a significant difference between results of
performance evaluated by Treynor and Sortino ratios in investment
companies.
⎧H
0 : mean rank
⎨
⎩H1:
mean rank
TR
TR
− mean rank
− mean rank
SO
SO
= 0
≠ 0
The result of test indicated that there is no significant difference
between evaluated performances by Treynor and Sortino ratios in
investment companies listed in Tehran Stock Exchange. The result
of Wilcoxen test is shown in Table 5.
Hypothesis 2
There is a direct correlation between return on investment and size,
liquidity, diversification, turnover of the portfolio.
H0: There is no significant relation between four independent
variable and return of portfolio in investment companies.
H1: There is a significant relation between four independent variable
and return of portfolio in investment companies.
⎧H
0 : β TO , βSI
, β
⎨
⎩H1:
β TO , βSI
, β
VO,
VO,
β
β
LI
LI
= 0
≠ 0
The hypothesis is tested by Combined Anova. Based on results of
Combined Anova, among four coefficients independent variables,
slope variation of the beta coefficients on turnover variable has
significant and positive relation with return of portfolio in investment
companies. The reason was calculated T Test was positive and
larger than 2.58. Therefore, zero hypotheses are rejected at the
confidence level of 95 and 99%, and another hypothesis is
acceptable.
The coefficient of three other variable, including: size,
diversification and liquidity of portfolio according to calculated T

Table 3. Result of Freidman rank test for comparing mean of ranking on performance ratio in investment companies.
Tehrani et al. 7435
Pair variable Status Number Average rating Total ranking Result of test
Negative ratings 26(a) 33.02 858.50 Z stat -2.247
Positive ratings 44(b) 36.97 1626.50 Error level 0.025
Sharp - Treynor
Equality 0(c) a Treynor ˂ Sharp
Sum 70
b Treynor ˂ Sharp
c Treynor = Sharp
Table 4. Result comparing mean of ranking by Sharp and Treynor ratios.
Pair variable Status Number Average rating Total ranking Result of test
Negative ratings 32(a) 27.20 870.50 Z stat -1.677
Positive ratings 35(b) 40.21 1407.50 Error level 0.093
Sharp - Sortino
Equality 0(c) a Sortino ˂ Sharp
Sum 67
b Sortino ˂ Sharp
c Sortino = Sharp
Table 5. Result comparing mean of ranking by Sharp and Sortino ratios.
Pair variable Status Number Average rating Total ranking Result of test
Negative ratings 40(a) 32.67 1307.00 Z stat -1.049
Positive ratings 27(b) 35.96 971.00 Error level 0.294
Treynor - Sortino
Equality 0(c) a Sortino < Treynor
Sum 67
b Sortino > Treynor
c Sortino = Treynor
Test level don't have significant relation with return of portfolio in
investment companies.
In changeing turnover of portfolio for the companies are listed in
the Tehran Stock Exchange has direct and significant relationship
with return on investment, and do not have any relation with three
other measures (Liqutity, diversification, and size).
In more careful study, we tested effect of four independent
variablesseparatly with dependent variable. The results of this test
emphasized the previous test results.
The results of multiple Anova test are shown in model 1 and
Table 6.
MODEL 1:
RE=
C(1) + C(2) * TO+
C(3) * SI+
C(4) * VO+
C(5) * LI+
[CX=
F]
RE=
21.45+
0.0058*
TO-0.179*
SI-0.0389*
VO+
0.400*
LI+
[CX=
F]
Τ=
5.900
P=
0.
000
2
R = 0.269
3.306
0.
0017
D.W=
2.330
-0.619
0.
538
-0.688
0.
494
0.595
0.
553
Model 1: The results of multiple Anova test
RESEARCH FINDINGS
There is a significant relation among Sharp, Treynor
and Sortino ratios in investment companies
We used Spearman correlation coefficient to examine
relations among Sharp, Treynor and Sortino ratios in
investment companies. The result of test indicates that
three mentioned ratios have positive and significant
relation together in investment companies. The result of
test is shown in Table 7. Therefore, we can claim that
increasing or decreasing in each of the ratios let to
increase or decrease in other ratios in investment
companies.

7436 Afr. J. Bus. Manage.
Table 6. Result comparing mean of ranking by Treynorand Sortino ratios.
Independent Variable: Return of Portfolio
Method: panel weight Total courses: 6 period Total level: 12 companies Views of unbalanced: 67 View
Variable Coefficient Standard error T State Confidence level
Fixed coefficient 21.45269 3.635810 5.900388 0.0000
TO 0.005813 0.001758 3.306076 0.0017
SI -0.179708 0.289990 -0.619704 0.5382
DI -0.038923 0.056528 -0.688561 0.4942
LI 0.400021 0.671204 0.595975 0.5538
Detection factor 0.269131 Mean dependent variable 11.82923
Improved detection coefficient 0.054170 SD dependent variable 97.02115
SD Waste 95.05254 Durbin- Watson State 2.330620
Table 7. Results of multiple Anova analysis between the four independent variables and the Return of portfolio.
Variable & Ratio Sharp Treynor Sortino
Sharp Spearman correlation coefficient 1.000 0.269 0.668
Significant Level 0.000 0.024 0.000
Number 70 70 67
Treynor Spearman correlation coefficient 0.269 1.000 0.332
Significant Level 0.024 0.000 0.006
Number 70 70 67
Sortino Spearman correlation coefficient 0.668 0.332 1.000
Significant Level 0.000 0.006 0.000
Number 67 67 69
Among independent research variables, liquidity
variable has significant relation with portfolio return
in investment companies
We used Spearman correlation coefficient to examine
relations among research independent variables
including Turnover, Size, Diversification and Liquidity of
portfolio with Return on investment in brokerage firms.
The result of the test indicates that among independent
variable only Liquidity of portfolio has positive and
significant relation with Return on investment in
brokerage companies. The result of test is shown in
Table 8.
Among independent research variables, turnover and
size of portfolio variables have significant relation
with Sharp ratio in investment companies
We used Spearman correlation coefficient to examine
relations among research independent variables
including Turnover, Size, Diversification and Liquidity of
portfolio with calculated Sharp ratio in investment
companies. The result of test indicates that among
independent variables Turnover of portfolio has positive
and significant relation with Treynor ratio, and Size of
portfolio has negative and significant relation with Sharp
ratio in investment companies. The result of test is shown
in Table 9.
Among independent research variables,
diversification of portfolio variable has significant
relation with Treynor ratio in investment companies
We used Spearman correlation coefficient to examine
relations among research independent variables
including Turnover, Size, Diversification and Liquidity of
portfolio with calculated Treynor ratio in investment
companies. The result of test indicates that among

Table 8. The result of Spearman correlation coefficient test among performance Ratios.
Tehrani et al. 7437
Variable and Ratio Turnover Size Diversification Liquidity
Spearman correlation coefficient 0.194 -0.064 -0.066 -0.449
Return of Portfolio Significant Level 0.102 0.597 0.579 0.000
Number 72 71 72 67
Table 9. The result of Spearman correlation coefficient test among Return of Portfolio and Independent variables.
Variable and Ratio Turnover Size Diversification Liquidity
Spearman correlation coefficient 0.270 -0.250 -0.020 -0.006
Sharp Significant Level 0.024 0.037 0.870 0.959
Number 70 70 70 67
Table 10. The result of Spearman correlation coefficient test among Sharp ratio and Independent Variables
Variable and ratio Turnover Size Diversification Liquidity
Spearman correlation coefficient 0.074 -0.048 -0.285 0.148
Treynor Significant Level 0.0542 0.690 0.017 0.232
Number 70 70 70 67
Table 11. The result of Spearman correlation coefficient test among Treynor ratio and Independent Variables
Variable and Ratio Turnover Size Diversification Liquidity
Spearman correlation coefficient 0.195 -0.164 -0.047 0.214
Sortino Significant Level 0.108 0.180 0.703 0.090
Number 69 68 69 64
independent variable only Diversification of portfolio has
negative and significant relation with Treynor ratio in
investment companies. The result of test is shown in
Table 10.
There is not any significant relation between
independent variables and Sortino ratio in
investment companies
We used Spearman correlation coefficient to examine
relations among research independent variables,
including Turnover, Size, Diversification and Liquidity of
portfolio with calculated Sortino ratio in investment
companies. The result of test indicates that, there is not
any significant relation among independent variables and
Sortino ratios in investment companies. The result of test
is shown in Table 11.
Summing up the results
The results of the first research hypothesis test showed
that a Treynor ratio presents better performance for
investment companies(Iranian companies) compared
with other ratios. As we expressed in the theoretical
framework section,Thisratio present the ability to manage
the risk in the market for the companies. As a result, the
investment firms control the market risk (beta factor).
Also, this ratio is more precise than others, and thus
Iranian investment firms have been able to have better
performance depending on the incoming risk. Among the
three performance evaluation ratios, Sortino ratio have
also acquired the middle position. Investment companies

7438 Afr. J. Bus. Manage.
that considered this ratio havemoderately managed to
avoid the related downside risk of their portfolio development.
Actually, they still have to pay more attention to
this important factor. Iranian investment firms considered
Sharp ratio still have not been managed to control the
existing risk in their internal structure appropriately.
In regard with the second hypothesis, results show that
the portfolio turnover has had the greatest impact on the
companies' return on investment. Therefore, investment
companies that have had the greatest turnover, are
known for having investment priorityaccording to the
result of the statistic tests for the investor and since the
diversity and liquidity measeares have not had many
relationships with the companies return on investment.
We can concluded that these companies have not yet
achieved the optimal structure of the portfolio, and they
should perform more active in this regard. Furthermore,
there is not any correlation between the firm size and the
companies’ return on investment. Inefficient application of
investing funds in the portfolio,either by the investment
companies and by inappropriate allocation of the assets
may cause higher or lower retun on investment. We may
found an investments company with a small sizewhich
has acquired much better efficiency than a large
company.
Results interpretation based on the previous
research
In the present study, it has been indicated that the
Treynor ratio is a suitable ratio for evaluating
performance of the investment companies while the
research of (Pedersen and Ted, 2003) and (Goetzmann
et al., 2006) recommended using the Sharp ratio for
evaluating the performance of companies of this caliber
also the Sortino ratio acquired the second place in
evaluation of the investment companies' performance,
while this result, with the little difference, is parallel with
the result of (Chaudhry et al., 2008) research. In fact, a
significant point that be able to obtained from the first
hypothesis test, and superiority of the investment
companies' performance by Treynor ratio is that given
that systemic risk in the reviewing investment companies
is better than other controller ratio as they were
anticipated, these companies have reacted upon the
changes of the market economic conditions, that this fact,
according to the research of (Ben et al., 2010) recommends
using a more optimal structure of the portfolio to
these companies in addition to controlling systemic risk,
they may educe the causes of risk enhancement within
these companies.
Moreover, according to the results of the second
hypothesis and the other findings of the research, since
corporate functions have no relation with the size and
diversifying and liquidity of portfolio, it canbe stated
based on the research of (Maffini and Clandia, 2009) that
an above the marketperformance and innovative function
should not be expected from investment companies.
Nevertheless, due to the lack of firm size in the
companies performance, the results of the this research
is inconsistent with the results of (Hishamuddin, 2006)
research which stated that thelarge companies acquire
better performance and it is possible smaller companies
in Iran have better performance. The result fromour
second hypothesis of the study shows that the portfolio
turnover has a significant affecton the performance of
portfolio. This results is inconsistent with results of (Rao,
2010) research that does not regard this relationship as
significant. On the other hand, the results of the other
findings in our research indicated that the Treynor ratio
has a reverse relationship with portfolio diversity, and the
more diversified portfolio, the better investment
companies maycontrol the systematic risk in the market
that this result is parallel with (Mau, 2009) research which
proposed using an approach with an appropriate
framework for risk control. Regarding to the firm size
impact on the Sharp ratio,In summary, we state that the
bigger Iranian investment companies are, the bigger is
standard deviation from their efficiency. As a result, we
found out that investments companies with smaller
investment portfolio, have presented a better
performance.
LIMITATIONS OF RESEARCH
Basis for any research is data that researchers collected
and analyzed them in his research. Obviously, if much
more transparent and complete information has been
available, the results of the investigation will be more
creditable. In this research, we had some limitation of
research as follow:
1. We didnot consider changes in macroeconomic
conditions, political and social changes over the years of
studied.
2. Due to limited statistical community of investment
companies listed in Tehran Stock Exchange, distributions
of results to other economic units should be done with
caution.
3. We did not consider banks and other credit institutes in
Tehran Stock Exchange and omit which did stablished
less than one year.
SUGGESTIONS
As we mentioned in our first hypostasis, there are a

significant differences between the results of
performance evaluated by Sharp, Treynor and Sortino
ratios. After we examine the three above ratios in our
research, we found out that Treynor ratio will shows
better result in an Iranian investment companies. Not to
mention, it suggests investor to use verity of stock in their
portfolio which allow them to have systematic control than
other ratios.
In our second hyposthasis, we stated there is a direct
correlation between return on investment and size,
liquidity, diversification and the turnover in portfolio.
Result from our research is pointing out that the return on
investment just had direct correlation with the turnover.
We suggest in managing portfolio considering the
importance of turnover.
SUGGESTIONS FOR THE FUTURE RESEARCHES
According to the previous researches and our founding
we are pointing out the following propositions and
suggestions:
1. The assessment and comparison of ratios in
organizing a portfolio.
2. The assessment verity of industrial companies in terms
of their performance.
3. Examine and recognize precise competency of
companies’ performance with verity of models to organize
a portfolio.
ACKNOWLEDGEMENT
We would like to submit our sincere and heart feeling
thanks to assistant professor Dr. Mohsen Nazary for all
the helps and guidance that we received in writing our
research.
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Journal of Business Management Vol. 5(17), pp. 7440-7448, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.220
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
To the promotion of work life quality using the
paradigm of managerial coaching: The role of
managerial coaching on the quality of work life
Seyed Ali Akbar Ahmadi 2 , Najmeh Jalalian 1 , Yashar Salamzadeh* 2 , Mohammadreza daraei 2
and Azam Tadayon 2
1 Higher Education Center, Department of Management, Mehriz Payam Noor University, Mehriz, Iran.
2 Higher Education Center, Department of Management, Payam Noor University, Tehran, Iran.
Accepted 17 June 2011
In the past, the examination of quality of work life (QWL) and its effect on the organizational
performance has been considered so much and many investigations have been done. In new paradigms
in which the development of human resources and organizational goals are considered instead of using
them for achieving the organizational goals, the QWL has been defined through new indices, which
according to Hayrol et al. (2010) are as follows: interpersonal, the organization's policies and
managerial style, organizational support, personal and family life, security and satisfaction in the
organization, work environment, well-being and personal health. As it was previously mentioned, one of
the indices of QWL is the managerial style in the organization. In this paper, considering the objective
of developing human resources, the effect of managerial coaching style which is used today for
learning and development through open communications, team procedures, valuing people over task,
the acceptance of ambiguity and development of facilities on the QWL in the Government Offices of
Yazd city have been analyzed which is done through modeling of structural equations by Lisrel 8.5
software. It becomes obvious that managerial coaching has a significant role on the QWL and it
indicates 36 percent variance of the QWL with 95 percent accuracy rate. Also all the observed variables
in the model could indicate latent variables except for well-being and individual health and personal life
(managerial coaching variable p

leadership.
The process of managerial coaching in knowledgebased,
universal and complex organizations of today can
actually elevate the organization to an excellent level of
performance. According to Brocato (2003), nowadays the
organizations are passing through the continuity,
conformity and the command to change, coordination and
managerial coaching and use managerial coaching in
balancing their new work life in order to facilitate the
development of staffs (De Macro, 2007). In this article,
the effect of this new managerial style on the quality of
work (QWL) life has been investigated.
MANAGERIAL COACHING
The history of managerial coaching dates back to
Socrates, Socrates believed that when the people have
some responsibilities or they are the owner of the
achieved status, they would have a better learning.
Generally, the term "coach" has been common in sport,
but it also is used today in trade. In sports, as most of the
common organizational models, people and team work
are much significant, it can be said that the team work of
people is more important in the organizations, as people
in the organizations cannot succeed individually but
through synergies (Edvards, 2003).
Based on the definition of Parsloo and Wray (2000),
managerial coaching is a process which leads to learning
and development and the improvement of the performance.
Lynos and Goldsmith (2005) consider the use of
managerial coaching style as a way for promoting the
performance and skills of leadership which is known as a
strategy for developing management. Bianco-Mathis et
al. (2002) argue that the powerful leaders are those who
have inserted the managerial coaching in their actions
and beliefs. Managerial coaching is moving toward
achieving high performance in organizations through
increasing the effectiveness of organizational communications,
success of team building, self-knowledge,
improving the ability to create, moving toward chang and
generally, empowering of staffs and creating open communications
(Natal and Diamant, 2005). Achievement to
high performance needs committed and powerful staffs
which put emphasize on achievement to quality in
performance and satisfying the organizational objectives.
Based on the studies, managerial coaching is influencing
all dimensions of the organization as a method for
changing human beings, for example Wright (2007)
realized in 2007 that managerial coaching leads to a
reduction in stress in work place. Clegg et al. (2005)
presented a paper on managerial coaching in trade in
2005, other examples include: communication and
leadership skills in the paper by Wilson (2004), development
of occupational career (Scandora, 1992), team
making and the development of the group (Cunha and
Louro, 2000), improvement of group's skills and
Ahmadi et al. 7441
performance (Rich,1998), managerial coaching and the
improvement of per-formance in occupational interviews
(Maurer et al., 1998).
Generally, it can be said that managerial coaching
consists of five dimensions of open communication, team
work, acceptance of ambiguity, the priority of the
individual to task and the development of facilities, which
the first four dimensions have been introduced by
McLean et al. (2005) and Park (2007).
Open communication
One of today’s main changes which occur in
organizations is the shift from formal and hierarchical
communications to partnership and network communications
which requires sharing information and team
consultancy, and this does not occur except by open
communication (Muetzelfeldt, 2005).
One of the main characteristics of the effectiveness of
coaching is open communications. In fact, these open
communications help the managers and staffs to have a
better understanding of each other and plan a better
foundation for communication.
Evered and Selman (1989) in their study emphasize on
the effectiveness of coaching. In order to make open
communication there should be some cooperation,
sincerity and collaboration of staffs.
Team approach
This dimension of coaching means making collaboration
with each other. When working with team approach, at
the time of decision-making and obtaining results, team
working is preferred. After some investigations Kritner
and Kiniki (2006) concluded that the successful teams
give credence to the objectives of the individuals and
team. In coaching, the manager tries to evaluate the staff
and give feedback to them instead of commanding and
he does this with continuous participation in order to help
the staffs to achieve the objectives of the organization
and their personal occupational desires (Brecher, 2004).
Fournies (2000) considers coaching as a preventive
factor for failure in team works.
Valuing people over task
A good managerial coaching manager distinguishes the
personal needs from tasks and knows that how much
attention he/she should pay to each. This factor has more
relationship with the job satisfaction of the staffs. In the
study of Landdon (1996), most respondents believed that
their job satisfaction has much relation with receiving
respect from their organizations. In this dimension of
coaching, the managers should listen carefully to their
staff and support their efforts.

7442 Afr. J. Bus. Manage.
Acceptance of ambiguity
In order to achieving high performance through coaching
in organizations, the flexibility in the communications and
acceptance of opinions and new innovations are considered
as most important factors (Peterson and Hicks,
1996). Managers should look for multiple solutions and
communicate with their staff and accept their views if it
has a useable view in it.
Development of facilities
One of the skills of a leader is to provide proper conditions
and environment for training staffs and improving
them. The leader should give feedback to his staff in a
way that he gets the control of them and improves them.
In fact, the coaching manager should strategically
accompany his staff when facilitating their affairs
(DeMacro, 2007).
The quality of work life
For an organization to succeed, its staff should not be
ignored as a driver motor. This motor should be serviced
through the best reliable methods. Staff that their needs
are not meet, are unsatisfied and they work less than
their true and actual power (Azril, 2010). Robbins considered
QWL as the organization's responsiveness to the
needs of staff through developing some mechanisms
which let them to be involved in those decisions which
influence their life.
The concept of the QWL was mentioned for the first
time by Davis in 1973. In the literature of management,
from past to now, so many key factors have been introduced
as influencing on QWL, as an example, Lau and
May (1998) considered the work condition, job satisfaction,
behavioral aspect of staff, growth and development
as main factors.
As it was mentioned with the development of the
organizations and in paradigmatic pass, the indices of
QWL increased too. Arzil et al. (2010) define these
indices as follow:
1. Payments: the most significant factor which is
mentioned in the literature of QWL is payment which
includes the wages, increase of wages, benefits, and
subsidiaries, retire rights and medical benefits. Wan
(2007) and Matzler and Renzl (2007) in their investigation
has demonstrated that the most significant aspect of job
satisfaction is payment.
2. Interpersonal relationships: other aspect which is
important after payment is interpersonal relationships
which are nowadays mentioned as one of the main
factors in organizational performance. This criterion
includes respecting others, collaboration with others and
sharing some information with affirmation of the organization
which will have some benefits for managers and
staffs.
3. Work environment: another determining factor in
deciding on the performance is work environment which
includes argonomy, harmonic and safe environment.
4. Job safety and satisfaction: The security and safety
aspect such as retirement programs and the community
of staffs can increase the motivation, utilization, organizational
commitment, physical and mental health of staff.
Job satisfaction factors such as JDI indices (the nature of
job, supervisor, cohort, promotion and payments) are
placed within QWL.
5. Organization's policies and management: According to
the investigations done by Keiningham et.al, (2006), the
existence of fair policies and proper management styles
are among the most important aspects in the QWL and
performance of staff. For example the participation of
staff in decision-making process, the facilitation of the
relationships between the manager and staff and the
working teams are effective for their performance (Eaton
and Gordon, 1992).
6. Organizational support: this index is one of the main
tools in strong and powerful performance of staff. It
should be noted that if staff work individually without any
support from manager, their performance will be
decreased. This is surprisingly obvious in the studies of
Ussahawanitichakit (2008) and Hutchinson and Garstika
(2006).
7. Personal and family life of staffs: Mazerolle et al.
(2008), Mulvaney (2006) and Ezra and Deckman (1996)
found that the balanced personal and family life of people
leads to high performance among staff and conversely,
their unbalanced life leads to instable morale and a
negative performance.
8. Personal health and well-being: Piqueras (2006)
recognized a significant relationship between this factor
and QWL; also he considers some factors such as
personal health, stress, personal problems, body fitness
and personal desires as some of important factors. In a
study which has been done by Azril (2010) to investigate
the relationship between performance and QWL it was
demonstrated that there is some relationships between
performance and well-being.
Managerial coaching and the quality of work life
Bartlett (2007) believes that coaching is a far-reaching
performance in development of human resources. Also in
a study which has been done in 2005 by Chartered
Institute for Personnel and Development (2005) in the
U.K. stated that 88 percent of organizations use coaching
method for developing their staff. It can be said that
coaching affects many aspects and indices of quality of
work life.
It can be said that coaching can be effective on the

indices of quality of life work. One of the main skills of
coaching is the creation of interpersonal relationships.
Denfeld Wood (2008) believes that in coaching we are
following three objectives: 1. Improvement of life: to
balance professional and personal roles as carter, 2.
Leadership: improvement of team and interpersonal skills
and 3. Self-knowledge: to be aware of deficiencies and
opportunities that we can have in order to grow. Haiz
(2008) also introduces coaching as a necessary tool for
creating mutual interpersonal relationships. In fact
coaching is a practice which empowers interpersonal
relationships (Denver, 2005).
In the list of coaching model of Noer (2005), one of the
behavioral indices of managers is his support of his staff
by creating interpersonal relationships for facilitating the
trust, open relation, respect and perception which
consists of behavioral elements attending, inquiring,
reflecting and affirming.
One of the main streams in coaching is teaching
personal development. Williams et al. (2002) believes
that the coaching manager encourages staff to obtain a
better status in respect of health and well-being. Williams
et al. (2002) believes that the coach should be in a better
level of goodness rather than his subordinates. One of
the main factors which are in a mutual relation with work
environment is the quality of management. In the studies
done by Meret Labriola (National institute of occupational
Health Copenhagen, Denmark) low level of support and
quality of management, low authority in decision-making
and supervision have been mentioned as the causes of
staffs' absenteeism due to sickness.
Coaching manager seeks to obtain and promote the
policies and programs such as creating equal opportunities
for staffs, personal development, team work,
making changes, communication skills and contradiction
management and so on, in an organization. Generally it
can be said that coaching manager is going to find those
policies which are followed by highest level of performance,
obtaining a new level of personal improvement,
increase of learning, more successful occupational path
and totally, the increase of life satisfaction (TenHoor,
2002).
In the past studies, the role of managers in job
satisfaction has been investigated widely in such a way
that is has been considered as an important indices of
their managing technique in measuring the staff's job
satisfaction.
In the field of coaching management method and its
effect on job satisfaction, many studies have been done
including Wrench and McCroskey (2006) which in their
study on coaching scales they found that there is some
relationship between organizational coaching and the
satisfaction and motivation of staffs. Elligner et al. (2003)
has studied the coaching behavior of supervisors and job
satisfaction of staffs.
The most prominent aspect of coaching is its psychoanalysis
approach which seeks to discover the personal
Ahmadi et al. 7443
values, motivations and even family matters (Lawler and
Candidate, 2009).
Bowels and Picano assert that in a work environment in
which there is managerial coaching style, there is a
higher level of job satisfaction. One of the objectives of
coaching management is the promotion of occupational
security and safety.
It can be said that the success or failure of manager's
actions, work environment and coaching, can be effective
on occupational security and communications and totally,
the meaning of coaching includes different matters of
work life (Cavanagh and Grant, 2006).
Hypotheses of research
In order to measure the coaching behavior of
management and quality of work life, based on the above
review of literature, it is assumed that:
H1: There is a significant relationship between open
communication and coaching.
H2: There is a significant relationship between team
approach and coaching.
H3: There is a significant relationship between ambiguity
and coaching.
H4: There is a significant relationship between the
individual's priority rather than the task and coaching.
H5: There is a significant relationship between facilities
development and coaching,
H6: There is a significant relationship between payment
and QWL.
H7: There is a significant relationship between work
environment and QWL.
H8: There is a significant relationship between security
and job satisfaction and QEL.
H8: There is a significant relationship between the
organization's policies and managerial style and QWL.
H9: There is a significant relationship between
organizational support and QWL.
H10: There is a significant relationship between personal
mutual relationships and QWL.
H11: There is a significant relationship between personal
and family life and QWL.
H12: There is a significant relationship between
goodness, personal health and QWL.
And the final hypothesis which examines the relationship
between latent variables after confirming their
relationship with observed variables is:
H13: There is a significant relationship between
managerial coaching and QWL.
The conceptual model of the research
In this study, coaching is considered as an independent
variable and QWL as dependent variable. The variables

7444 Afr. J. Bus. Manage.
Open communication
Team approach
Acceptance of
ambiguity
Priority of individual
over task
Development of
facilities
Figure 1. Conceptual model of research.
Coaching
of open communication, team approach, the acceptance
of ambiguity, the priority of the individual to task and
development of facilities are observed variables for latent
variable of coaching. On the other hand, variables of
personal relation in the organization, policies of organization
and managerial styles, organizational support,
personal and family life of staff, security and satisfaction
in organization, work environment, payment, well-being
and personal health are observed variable for quality of
work life. In this research the relation of managerial
coaching style and QWL has been examined (Figure 1).
MATERIALS AND METHODS
Methodology
The present study is a field study with descriptive data collection
and in respect of the relation between variables, it is a causal study.
Tools for data collection
In this study two questionnaires have been used for data collection.
1. A 41-questions questionnaire which examines the degree of
coaching (the measurement of managerial coaching which has
been designed by McLean et al. (2005) and its reliability and validity
has been proved in previous studies and it has been taken from Lai
(2008). The response range of questions has been from 1 to 6
(from total disagreement to total agreement).
2. The questionnaire used for evaluation of quality of life in which,
according to Azril's indices, the criteria used in International
Standard Organization (ISO) are used, has been designed by
researcher. In this questionnaire Likert's range has been used. The
results of computation of cronbach’s α values in pre-test for each
Quality of
Work life
variable are shown in Table.1
Research samples
Payment
Interpersonal relations
Organizational
policies and
management style
Work Enviroment
Organizational support
Security and job
satisfaction
Personal and family life
Personal health and wellbeing
This study is on executive organizations of Yazd provience in Iran
which is presented according to statistics of Yazd organization
which has been conducted in 1388 by the Office for Human
Resources and Administration Revolutions of Deputy of
Management Development and Human Resources. The population
consists of 150 individuals who has been selected based on their
reputations which was distributed randomly between 10
organizations, and finally 110 questionnaires have been collected.
Demographics
Before data analysis, it is better to have a clear picture of the
respondents. Based on the data from Table 2, the frequency and
the distribution percentage of gender, age, education and work
background variables can be seen. Also the average age of
respondents is 32 years old and their work experience is 9 years.
RESULT
In order to analyze data and test the research hypothesis,
the structural equation's model has been used. In
Figure2, all the coefficients of measurement model and
the route of structural model can be seen. Standardized
values in the final structural model indicate the intensity
of the relation between coaching and its indices and QWL
and its indices in measurement model and structural rela-
tion of coaching with QWL. Other values of measuring
model (λ) and structural model are included in Table 3.

Figure 2. The values of standardized model for final structural model.
Table 1. The values of cronbach’s α pre-test for each variable.
Ahmadi et al. 7445
Indices The number of question Cronbach’s α
Valuing people over task 6 0.75
Team approach 8 0.83
Coaching
Development of facilities 10 0.66
Acceptance of ambiguity 8 0.71
Open communication 9 0.74
Total 41 0.89
Security and job satisfaction 11 0.8
Interpersonal relation 4 0.78
QWL
Organizational support
Organizational policies and management style
6
7
0.74
0.70
Work environment 5 0.83
Well-being and personal health 4 0.70
Family and personal life 0.72
Total 33 0.86
Based on the presented data, it can be said that with
95% degree of confidence the indices of payment, interpersonal
relation, organizational policies and managerial
style, organizational support, security and job satisfaction
have significant relation with QWL. In which the security
and job satisfaction with λ= 0.85 and lowest variance
error (0.083) has the highest role in the QWL and
payment with λ= 0.27 and variance error of 0.94 has the
lowest role on QWL. In final model, indices of personal
and family life and well-being and personal health have

7446 Afr. J. Bus. Manage.
Table 2. The characteristics of respondents (n=110).
Variable Frequency Percentage
Gender
Female 62 56.4
Male 48 43.6
Age
Under 40 years 89 80.9
Above 40 years 21 19.1
Education
Diploma 15 13.6
Associate of Arts 16 14.5
BA 70 63.6
MA 8 7.3
Occupational experience
Between 1-5 48 43.6
Between 6-15 43 39.1
Between 16-25 14 12.7
>25 2 1.8
Table 3. The values for QWL indices in structural model.
Indices of QWL based
on priority
Is: job security and
Satisfaction
Ipc: interpersonal
Relation
Orsu: organizational
Support
Organizational policies
And management styles
Standard estimated
value (λ)
t-value
Estimated
standard error
p- value
The value of
coefficient of R 2
0.85 2.43 0.22 P

Table 4. The values of coaching indices in structure.
Indices of coaching based
On priority
Priority of individual over
task
Standard estimated
Value (λ)
t-value
Estimated
Standard error
P value
Ahmadi et al. 7447
The value of
Coefficient of R 2
0.97 13.29 0.047 P

7448 Afr. J. Bus. Manage.
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African Journal of Business Management Vol. 5(17), pp. 7449-7460, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.257
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
The effects of Iranian consumers’ buying tendencies on
utilitarian and hedonic shopping value
Neda Irani* and Kambiz Heidarzadeh Hanzaee
Department of Business Management, Islamic Azad University, Science and Research Branch, Tehran, Iran.
Accepted 1 June, 2011
This study investigates the effects of Iranian consumers’ buying tendencies including variety-seeking,
compulsive and impulsive buying tendencies and price sensitivity on utilitarian and hedonic value as
influencing factors on shopping experience for Manto and Shirt shoppers in the Iranian market. The
main constructs were identified from the literature and then the relationships between them were
tested. A questionnaire was developed and successfully administered to a national sample of 1466
women and men in four big cities of Iran through face to face interviews. Results were analyzed by
structural equation modeling (SEM) and parameters were estimated using maximum likelihood method
and ten hypotheses were tested. Based on this study, both variety-seeking and compulsive buying
tendencies were critical factors of shopping values for Manto and Shirt shoppers. On the contrary,
there was a negative relationship between price sensitivity and hedonic value. However, there were no
positive relationships between impulsive buying tendency and shopping values and there was also no
positive relationship between price sensitivity and utilitarian value. Moreover, the result of this study
revealed that utilitarian and hedonic value positively influenced the shopping satisfaction.
Key words: Variety-seeking buying, compulsive buying, impulsive buying, price sensitivity, utilitarian and
hedonic value, shopping satisfaction.
INTRODUCTION
Marketers and retailers often seek to learn why people go
shopping. Researchers have recently shown that the
shopping experience provides consumers with a
combination of utilitarian and hedonic shopping value
(Holbrook and Hirschman, 1982; Babin et al., 1994, 2005;
Babin and Darden, 1995; Jones et al., 2006; Cottet et al.,
2006; Seo and Lee, 2008; Carpenter, 2008; Lee et al.,
2009). Utilitarian value is task-oriented and cognitive in
nature, whereas hedonic value is tied to the emotional
aspects of the shopping experience (Holbrook and
Hirschman, 1982; Babin et al., 1994). In general,
consumers perceive utilitarian value by acquiring the
product that necessitated the shopping trip while
simultaneously perceiving hedonic value associated with
the enjoyment of the shopping experience itself
*Corresponding author. E-mail: neda_irani@yahoo.com. Tel:
+9821 44869667. Fax: +9821 44869664.
(Carpenter, 2008). Since the establishment of the
Personal Shopping Value scale approximately a decade
ago (Babin et al., 1994), research has focused almost
exclusively on antecedents to both hedonic and utilitarian
shopping value (Babin et al., 1994, 2005; Babin and
Darden, 1995; Griffin et al., 2000; Babin and Attaway,
2000; Babin and Babin, 2001; Seo and Lee, 2008;
Scarpi, 2005; Jones et al., 2006; Carpenter, 2008).
Interestingly, previous studies have examined the role of
shopping values in determining post-shopping responses
such as satisfaction (Babin et al., 1994, 2005; Jones et
al., 2006; Cottet et al., 2006), loyalty (Jones et al., 2006;
Carpenter, 2008), word of mouth and share of purchases
(Jones et al., 2006; Carpenter, 2008), customer share
(Babin and Attaway, 2000), and re-patronage intentions
(Seo and Lee, 2008; Scarpi, 2005; Jones et al., 2006).
Clothing has been classified as products with high
hedonic value (Crowley et al., 1992; Rossiter et al., 1991)
due to its symbolic, experiential, and pleasing properties
(Holbrook and Hirschman, 1982). In the measurement of

7450 Afr. J. Bus. Manage.
shopping experience, the hedonic side of shopping must
be considered as well as utilitarian side in order to reflect
the complete shopping experience (Hirschman and
Holbrook, 1982). Because the different levels of hedonic
shopping value result in different consumption behaviors
(Babin et al., 1994) and this tendency is probably
augmented in shopping for hedonic products, the
investigation how the hedonic shopping value influences
consumers’ behavioral consequences is necessary on
apparel marketing.
To date, few researchers have examined the influence
of consumers’ buying tendencies and the mediating role
of utilitarian and hedonic shopping values in shopping
satisfaction (Change, 2002; Lee et al., 2009) even though
such relationships would seem to be particularly
important given the tremendous amount of resources and
expenses that marketers and domestic and foreign
investors are devoting to create satisfied and loyal
customers. This led the authors to investigate proposition
for this study which are: how Iranian consumers’ buying
tendencies including variety-seeking, compulsive and
impulsive buying tendencies and price sensitivity effect
on utilitarian and hedonic value as influencing factors on
shopping satisfaction for Manto and Shirt shoppers in the
Iranian market. Iran has undergone significant change for
the last thirty years after Iran’s Islamic revolution. Due to
these changes, consumption patterns, investment and
other components of domestic demand are all strongly
growing. This has created: (1) more disposable income;
(2) the emergence of younger consumers; (3)
accelerated urbanization; and (4) quality improvement.
Enhanced domestic spending power is the basis for the
changes in the growth of the economy. Iranian
consumers’ tastes have become fashionable and stylish
in short years and expectations of improved quality and
diversity of choice and style have increased. This change
in consumption pattern is very visible in Iran’s cloth
industry. Since Iran is such a young and attractive
potential clothing market, there is no empirical study of
shopping behavior and shopping value of Iranian
consumers; this led the authors to investigate the
consumer shopping value phenomenon and contribute to
the developing stream of literature and it is necessary to
study more diverse dimensions of shopping value
perceived by Iranian consumers.
THEORETICAL BACKGROUND
Shopping values: Utilitarian and hedonic values
Value is one of the most powerful forces in the
marketplace to understand consumer behavior (Zeithaml,
1988; Dodds et al., 1991; Holbrook, 1996). Value
originates from the confrontation between what the
customer receives (e.g. quality, benefits, worth, utilities)
and what he or she gives up to acquire the benefits (for
example, price, sacrifices) (Zeithaml, 1988) and thus is
defined as a consumer’s overall judgment of benefits and
sacrifices (Overby and Lee, 2006). Value plays an
important role in predicting customers’ choice and future
repurchase intentions (Zeithaml, 1988; Dodds et al.,
1991; Holbrook, 1996). Thus, value judgment creates
consumer preference and this consumer preference
increases behavioral intention to participate in various
shopping processes (Cronin et al., 2000; Overby and
Lee, 2006).
Utilitarian value
Hirschman (1984) asserted that all shopping experiences
involve the stimulation of thoughts and/or senses and that
they accordingly may be viewed as a process that
provides the individual with cognitive (utilitarian) and
affective (hedonic) benefits. More specifically, tangible
attributes of goods and services provide input to cognitive
process and is closely related to assessments of
utilitarian value. Thus, a consumer receives utilitarian
shopping value when he or she obtains the needed
product, and this value increases as the consumer
obtains the product more effortlessly (Babin et al., 1994).
Early studies on shopping value mostly focus on the
utilitarian aspect of shopping (Bloch and Bruce, 1984).
Utilitarian consumer behavior is explained through taskrelated
and rational behavior (Batra and Ahtola, 1990;
Kempf, 1999). Perceived utilitarian shopping value is
determined by how much of the consumption need that
prompts the shopping experience, is met (Seo and Lee,
2008). This means that the consumer purchases goods in
a deliberant and efficient manner (Hirschman and
Holbrook, 1982; Engel et al., 1993). Therefore, utilitarian
purchasing behavior is more logical, rational, related to
transactions (Sherry, 1990; Batra and Ahtola, 1990), and
associated with more information gathering compared to
hedonic purchasing behavior (Bloch and Richins, 1983).
Although this utilitarian approach to consumer shopping
values is helpful for analyzing consumer purchases, it
offers no framework for measuring product selection and
analyzing consumption behavior based on emotional
needs (Hirschman and Holbrook, 1982).
Hedonic value
Compared to utilitarian value, hedonic shopping value is
more subjective and individualistic. Its value is perceived
through fun and pleasure as opposed to goal
achievement (Hirschman and Holbrook, 1982). Also,
hedonic shopping value reflects the pleasure and
emotional worth of shopping (Bellenger et al., 1976).
Recently, as the needs of consumers have become more
diverse, many studies have begun to focus on hedonic
shopping value. In the past, however, there was a

Table 1. Contrast between hedonic and utilitarian shopping value (Lehtonen, 1994).
Hedonic shopping value Utilitarian shopping value
An end itself A means to an end
Does not necessarily include purchases Always includes purchases
Impulsive Planned
Efficiency not central As efficient as possible
For pleasure Out of necessity
Outside of daily routines Part of daily routine
No clear beginning or end Clear beginning and end
Emphasis of the experience Emphasis of rationality
considerable lack of studies examining hedonic shopping
value compared to utilitarian shopping value (Sherry,
1990). Previous studies have identified and included fun,
pleasure, recreation, freedom, fantasy, increased
arousal, heightened involvement, new information,
escape from reality, and others as hedonic shopping
value (Darden and Reynolds, 1971; Tauber, 1972;
Hirschman and Holbrook, 1982; Babin et al., 1994).
Therefore, hedonic shopping value refers to the level of
perception where shopping is considered emotionally
useful through various positive feelings and worthwhile.
Thus, hedonic shopping value can be understood as the
emotional benefits the consumer perceives through the
shopping experience other than the achievement of the
original purchase intent (MacInnis and Price, 1987).
Abstract characteristics of goods and services can
contribute to affective elements in shopping and are
closely related to hedonic value (Cottet et al., 2006). In a
similar context, Babin et al. (1994) defined hedonic
shopping value as perceived entertainment and
emotional worth provided through shopping activities. As
Bloch and Bruce (1984) stated, consumers obtain
hedonic value as well as task-related or product
acquisition value during the shopping experience.
Contrasts between utilitarian and hedonic shopping
values
Traditional shopping experience measurements have not
reflected the total value of the shopping experience as
they have failed to recognize and measure many
intangible and emotional costs and benefits (Bloch and
Richins, 1983; Hirschman, 1984; Holbrook et al., 1984).
Defining shopping value as functional and objective
product acquisition is too narrow to reflect the complete
shopping experience (Hirschman and Holbrook, 1982).
Although hedonic experiences in shopping are often
considered as more important than more the product
acquisition, the festive or epicurean side of shopping has
been researched less often (Bloch and Bruce, 1984;
Sherry, 1990). Therefore, to measure the complete
shopping experience, the hedonic side of shopping must
Neda and Kambiz 7451
be considered as well as the functional, utilitarian side
(Babin et al., 1994).
With or without purchasing, shopping can provide
hedonic value. Some consumers enjoy a product’s
benefit even without purchasing it (MacInnis and Price,
1987; Markin et al., 1976). Perceived enjoyment itself is
an important hedonic benefit through a shopping
experience (Bloch et al., 1986). Hedonic value induces
increased arousal, heightened involvement, perceived
freedom, fantasy fulfillment, and escapism (Bloch and
Richins, 1983; Hirschman, 1983).
On the contrary, utilitarian value is relevant to
heuristics, goal fulfillment, and less risk propensity (Batra
and Ahtola, 1990; Engel et al., 1993). Babin et al. (1994)
insisted that utilitarian shoppers find value only if the
shopping chore is completed successfully and, even
better, in a fastidious manner. Lehtonen (1994) compared
two types of shopping value (Table 1), hedonic and
utilitarian value. According to him, the hedonic shopping
activity itself is an end so it does not necessarily include
purchases. It is often accompanied by impulse buying. As
this kind of shopping is for pleasure, shopping efficiency
is not important, so there is no clear beginning and end
point of shopping. It also emphasizes an experiential
aspect of shopping. On the contrary, utilitarian value
usually plays a role as a means to an end of achievement
of more optimal values; shopping efficiency is
emphasized, so shopping is planned and performed out
of necessity with rationality in utilitarian shopping.
Although in most shopping situations, consumers seek
both hedonic and utilitarian values, shopping can be
regarded as shopping with a goal or shopping as a goal
according to consumer attitude toward shopping (Chang,
2002).
Consumers’ buying tendencies
Several researchers eluded consumers’ buying
tendencies such as compulsive behavior, variety-seeking
tendency, impulsive buying tendency and price sensitivity
as possible significant factors of shopping behavior.
This study considers variety-seeking buying tendency

7452 Afr. J. Bus. Manage.
Variety-seeking
Buy Tendency
Compulsive
Buy Tendency
Impulsive
Buy Tendency
Price Sensitivity
Figure 1. Conceptual model.
(Bawa, 1990; Steenkamp and Baumgartner, 1995;
Menon and Kahn, 1995; Kahn, 1995; Van Tripj et al.,
1996), compulsive buying tendency (Hirschman, 1992;
Faber and O’Guinn, 1992; O’Guinn and Faber, 1989;
Rook, 1987) and impulsive buying tendency (Rook, 1987;
Bayley and Nancarrow, 1998; Dittmar et al., 1996; Rook
and Fisher, 1995; Beatty and Ferrell, 1998; Hausman,
2000) and price sensitivity (Han et al., 2001; Jin and Kim,
2003; Goldsmith et al., 2005) as consumers’ buying
tendencies.
To date, few researchers have examined the influence
of consumers’ buying tendencies and the mediating role
of utilitarian and hedonic shopping values in shopping
experience satisfaction. Chang (2002) examined the
mediating role of hedonic shopping value in shopping
experience satisfaction by investigating the relationships
between its assumed antecedents such as involvement,
variety-seeking tendency, and physical environment of
stores and shopping experience satisfaction. Lee et al.
(2009) examined the relationship between consumer
characteristics (for example, compulsive buying behavior,
variety-seeking tendency, and price sensitivity) and
shopping value (such as utilitarian and hedonic) in online
auctions. However, none of these studies have as their
central focus, the complex interrelationship between
shopping value, consumers’ buying tendencies and
shopping experience satisfaction. Overall, this literature
describes information on consumers’ buying tendency
differences in shopping behavior; however, these
differences have not been linked to shopping values of
the clothing market.
MODEL AND HYPOTHESES DEVELOPMENT
This study is based on the model (Figure 1) linking
consumers’ buying tendencies and shopping values to
Utilitarian
Value
Hedonic
Value
Shopping
Satisfaction
shopping satisfaction. Further, all the variables in the
model are discussed for their relationships, followed by
hypotheses development.
The role of variety-seeking buying tendency on
shopping values
Kahn (1995) defined variety-seeking as “the tendency of
individuals to seek diversity in their choices of services or
goods”. Variety-seeking tendency is rooted in need for a
change in an attempt to resolve the boredom associated
with a brand and a product (Van Tripj et al., 1996). Bawa
(1990) argued that there are two mutually exclusive types
of consumers’ variety-seeking: one is a variety-seeking
consumer assumed to derive no utility from making
habitual (repeat) purchases, and the other, an inertial
consumer is similarly assumed to have no utility for
variety. As Rogers (1979) argued, “… a tendency to
avoid variety may coexist with the tendency to seek
variety”. Consumers might fluctuate between inertia
behavior (brand loyal) and variety-seeking (brand
switching) behavior. This reflects the effort of consumers
to have Optimum Stimulation Level (OSL) (Steenkamp
and Baumgartner, 1995). Consumers try to increase
stimulation in such situations by seeking something
different or new, relative to their previous choice
(McAlister and Pessemier, 1982; Menon and Kahn, 1995;
Van Tripj et al., 1996).
Variety-seeking has been found to be related to
hedonic shopping. According to Holbrook and Hirschman
(1982), variety-seeking was related to non-purposeful
behavior (such as, exploratory purchase behavior), and it
should be understood by the view of hedonic
consumption because it cannot be accounted for by the
traditional perspective of utility driven consumption. This
construct has generated considerable research attention

in consumers’ shopping behavior. Variety-seeking
tendency has been identified as an important shopping
motivation and an influential factor in shopping channel
patronage (Michaelidou et al., 2005). It has also been
associated with feeling-based decision making and
hedonic shopping motivations (Sharma et al., 2006).
Feelings of excitement and gratification can be generated
by finding a variety of items (Kahn and Isen, 1993) and
by encountering rare, novel, and innovative items
(Roehm Jr. and Roehm, 2005). Chang (2002) studied the
relationship between the variety-seeking buying tendency
and hedonic shopping value in apparel. He found that
there is a positive relationship between variety-seeking
tendency and hedonic shopping value. That is,
consumers who sought variety and stimulation from
shopping were more likely to have hedonic shopping
value rather than utilitarian value. Similarly, Lee et al.
(2009) found that there is a positive relationship between
variety-seeking tendency and utilitarian and hedonic
values in online auctions. The positive relationship
between variety-seeking tendency and utilitarian value
suggests that variety seekers evaluate online auction as
providing high utilitarian value. Therefore, greater product
diversity helps buyers to reduce time costs and increase
shopping efficiency. At the same time, variety-seekers
evaluated online auctions as providing high hedonic
value. This means that variety-seeking tendency is an
important consumer characteristic influencing hedonic
shopping value. It was verified that variety provides
pleasant stimulation and novelty that increases
excitement and enjoyment in shopping (Steenkamp and
Baumgartner, 1995; Roehm Jr. and Roehm, 2005; Lee et
al., 2009). In sum, variety-seeking, likely influences both
utilitarian and hedonic value. Based on this:
H1: A variety-seeking buying tendency will directly
influence utilitarian shopping value.
H2: A variety-seeking buying tendency will directly
influence hedonic shopping value.
The role of compulsive buying tendency on shopping
values
Compulsive buying behavior is defined as ‘‘chronic,
repetitive purchasing that becomes a primary response to
negative events or feeling’’ (O’Guinn and Faber, 1989).
Compulsive buying therefore, is perceived to be in the
realm of abnormal consumer behavior that is
inappropriate, typically excessive and destructive to the
individual lives. Compulsive consumers participate in
many shopping activities despite having little or no
physical need for a product. Indeed these types of
shopping enhance their emotional state. Compulsive
shoppers may view product acquisition as unimportant
compared to the emotional lift shopping provides
(O'Guinn and Faber, 1989). Also, this behavior can be
Neda and Kambiz 7453
perceived as emotional and affective because
compulsive buyers are frequently motivated to buy things
in order to release themselves from an internally unstable
status, and to alleviate their discomfort and feelings of
self-loathing (Rook, 1987; Hirschman, 1992). Babin et al.
(1994) found that the pattern of correlations between
consumer compulsivity and personal shopping value is
consistent with this position. While compulsiveness is
related significantly to hedonic value, it is unrelated to
utilitarian value, which better reflects functional product
acquisition. This finding indicates that consumers may
use shopping as a form of therapy in managing their
emotions. In the case of compulsive consumption,
however, this therapy can quickly turn into a destructive
behavior (Hirschman, 1992). Lee et al. (2009) found that
there is a positive relationship between compulsive
buying behavior and hedonic shopping value in online
auctions. This relationship implies that compulsive buyers
are likely to engage in online auctions because of the
hedonic aspect of online auctions (such as thrill of
bidding, excitement of winning, stimulation of beating
competitors, and enjoyment in finding rare or unusual
items). Therefore, we should expect the following
relationships:
H3: A compulsive buying tendency will directly influence
utilitarian shopping value.
H4: A compulsive buying tendency will directly influence
hedonic shopping value.
The role of impulsive buying tendency on shopping
values
Impulse buying behavior is a sudden, compelling,
hedonically complex buying activity in which the rapidity
of an impulse decision process precludes thoughtful and
deliberate consideration of alternative information and
choices (Bayley and Nancarrow, 1998). Several
researchers have reported that consumers do not view
impulse purchasing as wrong; rather, consumers
retrospectively convey a favorable evaluation of their
behavior (Dittmar et al., 1996; Hausman, 2000; Rook,
1987). Other researchers have treated impulse buying as
an individual difference variable with the expectation that
it is likely to influence decision making across situations
(Beatty and Ferrell, 1998; Rook and Fisher, 1995).
According to Ko (1993), impulse buying behavior is a
reasonable unplanned behavior when it is related to
objective evaluation and emotional preferences in
shopping. Ko (1993) found apparel impulse buying was
distinguished from reasonable unplanned buying that was
based on emotional preference or objective evaluation
rather than rational evaluation.
The lack of research focused on the experiential
aspects of consumption underscore the need to
understand how fashion-oriented impulse buying relates

7454 Afr. J. Bus. Manage.
to hedonic consumption tendency or the emotional factor
in retail environments. Previous studies on impulse
buying focused on defining differences between impulse
and non-impulse buying behavior (Cobb and Hoyer,
1986; Piron, 1991). Many researchers have provided
theoretical frameworks for examining impulse buying
related to psychological variables (for example
personality, self-regulation), hedonic experiences (e.g.
shopping enjoyment, emotional state and mood), and
situational variables (e.g. available time, money) in a
shopping context (Beatty and Ferrell, 1998; Burroughs,
1996; Rook and Fisher, 1995). Generally, researchers
found that impulse buying satisfied hedonic or emotional
needs for fun, social interaction, and gratification
(Hausman, 2000; Piron, 1991). Rook (1987) notes that
impulse purchases, a subset of unplanned purchases,
lead more to hedonic responses than do other purchases
and are less likely to fulfill a utilitarian need. Babin et al.
(1994) found that there is a positive relationship between
unplanned purchases and hedonic value and unplanned
purchases and utilitarian value are not related significantly.
Therefore, given this reasoning, we should expect
the following relationships:
H5: An impulsive buying tendency will directly influence
utilitarian shopping value.
H6: An impulsive buying tendency will directly influence
hedonic shopping value.
The role of price sensitivity on shopping values
Price sensitivity is the extent to which consumers
perceive and react to price levels and price changes
(Goldsmith et al., 2005) and works as a barometer of how
much a consumer will pay in the market. Thus, price has
a significant influence on consumers’ purchase behavior
and consequently on sales and profits of firms (Han et al.,
2001).
Price-sensitive consumers were traditionally viewed as
rational and logical problem solvers emphasizing
utilitarian shopping value (Tauber, 1972; Schindler,
1989). However, researchers have begun to view them
as those who seek hedonic value from bargain hunting.
For instance, Jin and Kim (2003) found that hedonic and
recreational shoppers exhibited high price sensitivity by
hunting bargains and using coupons. Other researchers
(Babin et al., 1994; Arnold and Reynolds, 2003) also
noted a positive relationship between bargain perception
and hedonic shopping value. Babin et al. (1994) expected
that the consumers’ bargain perceptions to influence
shopping value. They discussed that price discounts
create transaction utility or smart shopper feelings, which
may increase hedonic value. In addition, price discounts
could create utilitarian value by facilitating an efficient end
to the product-acquisition task. Consistent with this
reasoning, they found that consumer bargain perceptions
relate significantly to both hedonic value and utilitarian
value.
They suggested that if substantiated by future studies of
price discounts and shopping value, these findings may
indicate that the subjective emotional component of price
promotions is at least as important as the more tangible
component. However, Lee et al. (2009) found that there
is a negative correlation between price sensitivity and
hedonic shopping value. In addition, there was no
relationship between price sensitivity and utilitarian value.
This result indicates that consumers who participate in
online auctions are not price sensitive. Many shoppers
use online auctions to find rare and unusual items, or a
quality items with a good deal, rather than to find just lowpriced
or inexpensive items. Also, auction participants
have a feeling of attachment to auction items when
bidding duration gets long. Hence, it can be posited that
price sensitive consumers obtain higher levels of
utilitarian and hedonic value. Thus:
H7: Price sensitivity will directly influence utilitarian
shopping value.
H8: Price sensitivity will directly influence hedonic
shopping value.
The role of shopping values in shopping experience
satisfaction
The generally accepted and most widely applied method
for conceptualizing consumer satisfaction is Oliver’s
Expectancy-Disconfirmation model (1980). The model
contends that attitudes about a purchase experience,
product or service lead form expectations in the mind of
the consumer. After the consumer purchases and/or uses
the product or service, they evaluate the purchase
experience and the performance of the product or service
relative to their initial expectations. The outcome of this
evaluation is an attitude; a decision to be satisfied or
dissatisfied. If the evaluation and subsequent attitude
confirms the consumer’s expectations of the purchase
experience, product or service, a state of satisfaction
occurs. This state of satisfaction leads to a positive
attitude toward the purchase experience, product and/or
service, and can positively influence future purchase
intentions. However, if the evaluation and subsequent
attitude disconfirms the consumer’s expectations, a state
of dissatisfaction occurs; thus, future purchase intentions
could be negatively affected. Also, for a specific
transaction, by analyzing Holbrook’s typology, Oliver
(1993) concluded that consumption value may enhance
satisfaction.
Babin et al. (1994), by testing the discriminating validity
of the scale they suggested, showed the impact of the
hedonic and utilitarian values on satisfaction. Other
researchers stressed the impact of shopping values on
satisfaction (Babin et al., 1995; Jones et al., 2006; Cottet

et al., 2006; Carpenter, 2008). For instance, Cottet et al.
(2006) found that there is a positive relationship between
shopping values and satisfaction. In this study, in a food
products context, the hedonic value plays a key role in
the satisfaction process. It explains satisfaction better
than a utilitarian value does. Similarly, Carpenter (2008)
examined the relationships between consumer shopping
value, satisfaction and loyalty in retailing. In this research
utilitarian and hedonic shopping values are found to
influence key outcome variables including satisfaction,
loyalty, word of mouth communication and share of
purchases in the highly competitive discount retail sector.
Therefore, the following hypotheses are offered:
H9: Utilitarian shopping value will directly influence
shopping satisfaction.
H10: Hedonic shopping value will directly influence
shopping satisfaction.
METHODS
This study tested a conceptual model (Figure 1) depicting the
relationships among consumers’ buying tendencies (varietyseeking,
compulsive and impulsive buying tendencies and price
sensitivity), shopping values (utilitarian and hedonic value) and
shopping satisfaction in Iran’s clothing industry. The model
describes that consumers’ buying tendencies influence utilitarian
and hedonic value, which in turn influence shopping satisfaction.
Data collection and sampling
To attain the aims of this study, based on the product (Manto for
female shoppers and Shirt for male shoppers), two different version
of one questionnaire was developed and completed by 1540
respondents. The sample for the study was drawn from female and
men shoppers in four major cities in Iran; Tehran, Mashhad, Isfahan
and Shiraz. Tehran is the capital of Iran located in the center, which
has been greatly influenced by different lifestyles; Mashhad is the
largest city located in the eastern region, which is largest religious
city in Iran with traditional lifestyle; Isfahan and Shiraz in the center
of Iran, representing the more historical part of the country. Data
were collected from shopping malls located in these four major
cities in Iran. The target population for this study consisted of
female shoppers who purchased a Manto and male shoppers who
purchased a Shirt in their recent shopping trip. Manto is a national
dress for Iranian women. Since the Islamic revolution, a formal form
of acceptable dress for Iranian women has emerged; a long dress
with full-length opaque stockings or pants, and a headscarf
covering the hair. The long dress has gradually evolved into a
shoulder-to-ankle smock called a Manto after the French word
Manteau (Overcoat). In Iran today, Manto is the norm for everyday
public wearing for women. Following these trends, some of the
clothing companies in Iran offer various veiling and Manto models
and styles to Iranian women who dress up according to Islamic
principles.
To obtain a sample of Manto and Shirt shoppers, 35 shopping
malls in these cities have been selected by cluster random
sampling; 20 shopping malls in Tehran and 5 shopping malls in
each of three other cities. Sample size was determined using the
Krejcie and Morgan (1970) table and considering the population
size of each city. The aim was to collect data from 450 females, and
470 males in Tehran, 142 females and 144 males in Mashhad, 93
Neda and Kambiz 7455
females and 96 males in Isfahan and 71 females and 74 males in
Shiraz. The data collection resulted in 1466 usable questionnaires
from 1540 respondents.
A Marketing research firm with expertise in research methods
was contracted to carry out data collection during September 2010
by face-to-face interviews. Trained interviewers administered the
survey during a 3-week period. First, interviewers assured that
female and male shoppers purchased a Manto or a Shirt in their
recent shopping trip; then they completed the questionnaires.
The average age of respondents was 33 years. A total of 63% of
the respondents were employed and 37% were unemployed. With
regard to education level, 32% had graduated from college or a
higher level institution, 21% had completed junior college, 41% had
completed high school, and 6% had less than a high school
education.
Measures
The measures consisted of consumer buying tendencies (varietyseeking
buying tendency, compulsive buying tendency, impulsive
buying tendency and price sensitivity), shopping values (hedonic
and utilitarian value), and post-shopping responses (shopping
satisfaction). Variety-seeking buying tendency (alpha= 0.94), from
previous studies (Steenkamp and Baumgartner, 1995; Baumgartner
and Steenkamp, 1996; Chang, 2002; Lee et al., 2009), compulsive
buying tendency (alpha= 0.95), from Faber and O’Guinn (1992) and
Lee et al. (2009), impulsive buying tendency (alpha=0.95) from
Rook and Fisher (1995), and price sensitivity (alpha=0.94) from
Goldsmith et al. (2005). Utilitarian value (alpha=0.84) and hedonic
value (alpha=0.90) as shopping value scales in this study were
adapted from Babin et al. (1994). The scale items for shopping
satisfaction (alpha= 0.86) were adopted from Ganesan (1994),
Maxham and Netemeyer (2002), Jones et al. (2006), Chang (2002)
and Carpenter (2008). Each item was rated on a 5-point scale
anchored by “strongly disagree” (1) and “strongly agree” (5). Table
2 shows the final measurement items organized by construct.
RESULT
The proposed model consisted of four exogenous
variables (variety-seeking, compulsive and impulsive
buying tendencies, price sensitivity) and three endogenous
variables (utilitarian value, hedonic value and
shopping satisfaction). Structural Equation Modeling
(SEM) with Lisrel 8.80 was used to analyze the data and
parameters were estimated using maximum likelihood
method. Following Confirmatory Factor Analyses (CFA)
and the structural models were tested.
Structural model and hypotheses testing
A structural model was constructed to examine the
hypothesized relationships among constructs. Goodnessof-fit
statistics, indicating the overall acceptability of the
structural model analyzed, were acceptable: Χ 2 (1309) =
7800.75, ρ

7456 Afr. J. Bus. Manage.
Table 2. Variables and their measures (confirmatory factor analysis).
Constructs Items Estimates t- value
Variety-seeking I like to continue doing the same old things rather than trying new and different 1.00 --tendency(α=0.94)
things. (-)
I like to experience novelty and change in my daily routine. 1.32 30.59***
I like a job that offers change, variety, and travel, even if it involves some danger. 1.23 27.92***
I am continually seeking new ideas and experiences. 1.29 29.35***
I like continually changing activities. 1.21 28.58***
When things get boring, I like to find some new and unfamiliar experience. 1.22 28.91***
I prefer a routine way of life to an unpredictable one full of change.(-) 1.14 26.78***
I am very cautious in trying new or different styles of Manto or Shirt. (-) 1.06 25.50***
I enjoy taking changes in buying new styles of Manto or Shirt just to get some variety
in my purchases.
1.07 25.95***
I rarely buy new Manto or Shirt styles about which I am uncertain. (-) 1.10 25.49***
When old Manto or Shirt gets boring, I like to find some new styles and products. 1.15 26.81***
Compulsive buying
tendency(α=0.95)
Impulsive buying
tendency(α=0.95)
Price
sensitivity(α=0.94)
Utilitarian
value(α=0.84)
Hedonic
value(α=0.90)
If I have any money left at the end of the pay period, I just have to spend it. 1.00 ---
Bought myself something in order to make myself feel better. 0.76 42.84***
Felt anxious or nervous on days I didn’t go shopping. 0.92 55.47***
Made only the minimum payment on my credit cards. 0.77 40.32***
Bought Manto or Shirt even though I couldn’t afford them. 0.98 58.98***
Wrote check when I know I didn’t have enough money in the bank to cover it. 1.17 67.83***
Felt others would be horrified if they knew my spending habits. 0.89 54.06***
I often buy a Manto or Shirt spontaneously. 1.00 ---
"Just do it" describes the way I buy a Manto or Shirt. 0.88 48.49***
I often buy a Manto or Shirt without thinking. 0.94 63.18***
"I see a Manto or Shirt, I buy A Manto" describes me. 0.90 45.58***
"Buy now, think about the Manto or Shirt later" describes me. 1.02 56.15***
Sometimes I feel like buying a Manto or Shirt on the spur-of-the-moment. 0.90 48.69***
I buy a Manto or Shirt according to how I feel at the moment. 0.74 41.03***
I carefully plan most of my purchases. (-) 0.73 40.39***
Sometimes I am a bit reckless about what I buy. 0.78 42.55***
I don’t mind spending a lot of money to buy a new Manto or Shirt. 1.00 ---
I don’t mind paying more to try out a new Manto or Shirt. 0.97 59.80***
I am less willing to buy a new Manto or Shirt if I think that it will be high in price 0.83 45.50***
I know that a new Manto or Shirt is likely to be more expensive than high in price. 0.96 51.78***
A really great new Manto or Shirt is worth paying a lot of money for. 0.88 45.71***
In general, the price or cost of buying a new Manto or Shirt is important to me. 0.77 40.03***
I accomplished just what I wanted to on this shopping trip. 1.00 ---
I couldn't buy what I really needed. 0.95 29.57***
While shopping, I found just the item(s) I was looking for. 0.87 29.05***
I was disappointed because I had to go to another store(s) to complete my shopping. 1.01 28.47***
This shopping trip was truly a joy. 1.00 ---
I continued to shop, not because I had to, but because I wanted to. 0.80 30.65***
Compared to other things I could have done, the time spent shopping was truly
enjoyable.
0.82 34.28***
I enjoyed being immersed in exciting new products. 0.88 33.74***
I enjoyed this shopping trip for its own sake, not just for the items I may have
purchased.
0.82 33.00***
I had a good time because I was able to act on the spur-of-the-moment. 0.52 20.15***

Table 2. contd
Shopping
satisfaction(α=0.86)
Neda and Kambiz 7457
During the trip, I felt the excitement of the hunt. 0.84 32.43***
While shopping, I was able to forget my problems. 0.67 27.13***
While shopping, I felt a sense of adventure. 0.71 29.03***
This shopping trip was not a very nice time out. (-) 0.62 22.17***
I am happy with the outcome of that shopping trip. 1.00 ---
I am satisfied with this store. 0.76 25.27***
Overall, I am not satisfied with this store. (-) 0.72 22.65***
I am please with the outcome of that shopping trip. 0.84 29.63***
I am contented with the outcome of that shopping trip. 0.85 30.09***
Overall, I am satisfied with the outcome of that shopping trip. 0.75 25.43***
(-) Denotes that scale item are reverse coded; *** Significant at p

7458 Afr. J. Bus. Manage.
0.20
0.15
0.89
0.93
VSBT
CBT
IBT
PS
Figure 2. The results of SEM.
0.06
0.11
0.38
0.02
0.03
0.04
-0.06
0.21
hedonic value. This means that variety-seeking tendency
is an important consumer buying tendency influencing
hedonic shopping value. It was verified that variety
provides pleasant, stimulation and novelty that increases
excitement and enjoyment in shopping (Steenkamp and
Baumgartner, 1995; Roehm Jr. and Roehm, 2005;
Chang, 2002; Lee et al., 2009).
Similarly, there is a positive relationship between
compulsive buying tendency and utilitarian value which
does not support the finding of Babin et al. (1994). This
relationship expresses that compulsive shoppers
evaluate Manto or Shirt shopping as providing high
utilitarian value. In the other words, the utilitarian value is
important for compulsive shoppers in the Iranian market.
The positive relationship between compulsive buying
tendency and hedonic value in Manto or Shirt shopping
shows that compulsive buyers are likely to engage in
Manto or Shirt shopping because of the hedonic aspect
of Manto or Shirt shopping (such as releasing
themselves, making them feel better, enjoyment in
spending money) which supports the finding of Babin et
al. (1994) and Lee et al. (2009).
According to the previous studies, there might be a
positive relationship between impulsive buying tendency
and utilitarian and hedonic value (Rook, 1987; Prion,
1991; Babin et al., 1994). However, this study found that
there is no significant relationship between impulsive
buying tendency and shopping values. In other words,
Manto or Shirt shoppers were more likely to plan for this
shopping trip to get the most value for their money.
The negative relationship between price sensitivity and
USHV
HSHV
0.41
0.24
0.40
0.45
hedonic value implies that Manto or Shirt shoppers are
not price sensitive. This result supports the finding of Lee
et al. (2009). However, there was no relationship
between price sensitivity and utilitarian value. Although,
Manto or Shirt shoppers may be sensitive to an initial
price at the early stage of Manto or Shirt shopping, an
excited and competitive shopping trip may increase a
willingness to pay more for a desirable, fashionable or
new Manto or Shirt and decrease price sensitivity for a
final price.
Both utilitarian and hedonic value equally influenced
shopping satisfaction which supports the findings of
Babin et al. (1994), Chang (2002), Eroglu et al. (2005),
Jones et al. (2006) and Carpenter (2008). This reveals
that shopping satisfaction for Manto or Shirt shoppers is a
response to different levels of utilitarian and hedonic
value in a shopping trip. In other words, increasing
consumers’ shopping satisfaction could be manipulated
by enhancing consumers’ utilitarian and hedonic
shopping value. Although consumers’ buying tendencies
are difficult to control due to its intrinsic, the influence of
consumers’ buying tendencies on shopping experience
satisfaction may be moderated through manipulating
utilitarian and hedonic shopping value.
These results have broader theoretical implications with
respect to our understanding of the role of utilitarian and
hedonic shopping value in explaining shopping
satisfaction. The present study provides not only
observed associations among variables related to
clothing shopping but also the structural dimensionality
including mediating variables of utilitarian and hedonic
SS
0.25

value in the construct of clothing shopping satisfaction.
This study offers new insights into the nature of
consumers’ utilitarian and hedonic value and
development of the more exciting shopping environment
which makes consumers get more involved in their
clothing shopping and enjoy more their shopping, and in
turn, feel more satisfied with their shopping.
As confirmed in the structural modeling, for apparel
(Manto and Shirt) marketing in the Iranian market, efforts
should be made in indentifying what the causal variables
of utilitarian and hedonic values are. Based on the results
of the present study, shopping satisfaction can be
increased through manipulating consumers’ utilitarian
and hedonic value. For Manto and Shirt shoppers,
because consumer buying tendencies such as varietyseeking
and compulsive buying tendencies and price
sensitivity were found to affect their utilitarian and
hedonic value, meeting their intrinsic needs and wants
can be important managerial strategy.
Providing variety of new products, provision of better
assortment of products, friendly sales personnel, and
exciting shopping environments, providing shopping
information regularly, and offering a high level of service
might make shopping activities more recreational,
enjoyable, and functional.
In addition, information on consumers’ buying
tendencies, shopping values, and the relationships
between them will be useful for domestic and foreign
marketers targeting Iranian markets. For Iran’s clothing
industry, an understanding of Iranian shoppers’ behavior,
with particular reference to their buying tendencies and
shopping values, is crucial. Profiling consumers by
identifying their consumer buying tendencies and
shopping values provide more meaningful ways to
identify and understand various consumer segments and
to target each segment with more focused marketing
strategies.
LIMITATIONS AND FUTURE RESEARCH
This study has limitations. First we used the scale set by
Babin et al. (1994) to measure value, because it seemed
to be best adapted to our study. However, for Iranian
apparel, we would consider other values based on
Iranian culture, values and principles for women and
men; therefore, it would be interesting in the future to
take other dimensions of value into account and therefore
use another scale based on Iranian values. Secondly, the
sample size was determined based on Krejcie and
Morgan (1970) table which limit the sample size of
research. Future research should attempt to improve on
the results of this study, and more representative
samples are needed that include broader geographic
locations and cross-national comparisons in Iran. Another
limitation was using only one product category (apparel)
and two main products (Manto and Shirt). Therefore, this
study could be extended to different product categories
Neda and Kambiz 7459
(such as cosmetics, home furnishings, accessories) and
other areas of retailing such as grocery shopping and
holiday shopping. Finally, considering the findings of
previous research that product involvement can influence
shopping behavior (Laurent and Kapferer, 1985; Kim,
2005; Martin, 1998; Park et al., 2006; Bloch and Richins,
1983; Zaichkowsky, 1985; Bloch et al., 1989; 1986;
Jones and Reynolds, 2006; Smith and Carsky, 1996),
future research can incorporate this variable when
examining shopping values in apparel shopping
satisfaction.
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African Journal of Business Management Vol. 5(17), pp. 7461-7473, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.302
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
The perceived service quality, satisfaction and
behavioural intent towards cellphone network service
providers: A generational perspective
D. J. Petzer* and C. F. De Meyer
Department of Marketing Management, University of Johannesburg, P. O. Box 524, Aucklandpark 2006, South Africa.
Accepted 15 June, 2011
The importance of providing customers with quality services in order to satisfy them and encourage
future purchases is well documented in literature. Yet, the cellphone network provider industry of South
Africa seems to be riddled with service quality problems. This study aims to determine different
generations’ perceived service quality of services and satisfaction levels with services provided by
cellphone network service providers, as well as their behavioural intentions towards these providers.
The study furthermore examines the correlations between these three constructs and uncovers
significant differences between different generations. Data was collected from 2339 respondents by
means of a self-administered questionnaire. Young Generation Y consumers perceive the service
quality levels and service satisfaction levels of these providers as significantly lower than other
generations. This is also true for their behavioural intent. Significant correlations also exist between the
generations’ perceived level of service quality they experience, their perceived level of satisfaction with,
and their behavioural intent towards providers. This implies that providers should strongly focus their
efforts on satisfying the needs, and improving the service satisfaction of young Generation Y
consumers in order to retain them in the future. Providers should also vary marketing strategies based
upon the differences uncovered between the generations.
Key words: Cellphone network service provider, baby boomer, Generation X, Generation Y, service quality,
service satisfaction, behavioural intent
INTRODUCTION
The South African cellular industry is the fourth fastest
growing cellular market in the world with every third call
made being from a cellphone (Mbendi, 2010). The four
main cellular service network providers in South Africa
(Vodacom, MTN, Cell C and Virgin Mobile) are embroiled
in a highly competitive market, which has been made
even more competitive with the introduction of a fifth
provider; 8ta. Over 80% of South Africa’s population
owns a cellphone, with the prepaid packages being
preferred over contract packages (SouthAfrica.info,
2008).
The competitiveness of this market requires from
*Corresponding author. E-mail: dpetzer@uj.ac.za.
cellphone network service providers to develop and
maintain a competitive advantage through the provision
of quality services (Boshoff and du Plessis, 2009).
Mbendi (2010) adds that the importance of providing
quality services and encouraging future repurchase intentions
cannot be underestimated, yet cellphone network
service providers in South Africa have been known to
provide poor levels of service. Cellphone network service
providers thus need to understand that providing
customers with quality services and satisfying their needs
are essential components of their marketing strategy in
order to ensure that customers will repurchase from the
service provider in future (Saeed et al., 2009). These
providers can also benefit from positive word-of-mouth
and repeat purchases if customers are satisfied with the
services they provide (Ryu et al., 2007). Koenderman

7462 Afr. J. Bus. Manage.
(2009) adds furthermore that the new generation of
service offerings from cellphone network service
providers (such as cellphone banking, internet access
and mobile marketing) necessitates an in-depth
understanding into customer expectations and trends.
Hoyer and MacInnis (2010) explain that various internal
and external factors influence consumers’ expectations
and their decision-making processes. The cultural
environment in which consumers find themselves
specifically has an influence on how and why they make
decisions, including repurchases decisions. Elements
such as age, gender, social class and reference groups
affect consumers’ values and lifestyles which influence
consumption patterns. According to Munnukka (2007),
demographic variables such as gender, age, culture and
usage patterns are often used to segment customers, but
research in these variables from a services perspective
has been limited. Munnukka (2007) continues that
research has found that demographic variables
(especially age, race and gender) influence consumers’
attitudes towards technology and impacts their future
intentions and actions. It therefore, stands to reason that
consumers belonging to different generations (different
age groups) have different needs and expectations from
their cellphone network service providers. Age is also a
critical variable impacting customer satisfaction levels
and repurchase intentions (Anderson et al., 2008; Kumar
and Lim, 2008). Marketers need to develop various
marketing strategies to target different generations or age
groups (Hoyer and MacInnis, 2010). From previous
studies conducted it can be noted that age does influence
consumer purchasing patterns and their behavioural
intent towards a service provider where consumers from
various generational groups exhibit different consumption
patterns (Jordaan and Ehlers, 2009; Kumar and Lim,
2008; Munnukka, 2007; Jorgensen, 2003), yet few
studies have been conducted from a South African
cellphone network service provider perspective.
The purpose of this article is to investigate and
compare the perceptions of different generations of consumers
(baby boomers, Generation X, adult Generation
Y and young Generation Y consumers), regarding
perceived service quality levels, service satisfaction with
their cellphone network service provider as well as their
behavioural intent towards their cellphone network
service provider.
LITERATURE REVIEW
The literature background starts with a discussion of
generational theory with a focus on the various
generations to which consumers typically belong. This
section also provides an overview of the unique
characteristics typically associated with these generations
and provides some insight into their cellphone
usage habits. As this article focuses on three constructs
namely, perceived service quality, customer satisfaction
and behavioural intent, each of these, and the relationships
between them are also discussed in more detail.
The hypotheses formulated for this study also flow from
the literature background.
Generational theory
As pointed out in the introduction, Munnukka (2007) and
Jorgensen (2003) specify that age has a large impact on
the use of technology (such as cellphones) and that each
age group have distinct differences which will cause
differences their future purchasing behaviour. Hoyer and
MacInnis (2010) continue that it is beneficial for
marketers to segment consumers according to their age
as people from the same generation tend to show similar
consumption patterns due to their shared life experiences
and needs. For this reason, it is necessary to determine
the characteristics of each age group.
According to Hoyer and MacInnis (2010) and Schiffman
et al. (2008) four main generations can be identified by
marketers, namely seniors (consumers over the age of
65), baby boomers (born between 1946 and 1964),
Generation X (1965 -1976) and Generation Y (1977 -
1994) consumers. For the purposes of this study, only
baby boomers, Generation X and Generation Y
consumers will be included and compared as these three
age groups (generational cohorts) are the main users of
cellphone services (Kumar and Lim, 2008; Schiffman et
al., 2008). Each generational cohort is furthermore
discussed. According to Grewal and Levy (2010) and
Hawkins and Mothersbaugh (2010), baby boomers are
self-centred, individualist, with leisure time being of great
importance. They are brand loyal and purchase for
indulgence (Schiffman et al., 2008). Baby boomers are
also an important target market for cellphone network
service providers as they are experienced users of
technology and have been part of technological
advancements through their lifetime (for example
microwaves and the Internet). Baby boomers mainly use
cellphones for make voice calls and do not regularly use
cellphones for data downloads or SMSs compared with
the other generations (Kumar and Lim, 2008).
Hoyer and MacInnis (2010) state that Generation X
consumers take time to research purchases and require
marketers to customise offerings to their personal tastes.
This cohort purchase electronic gadgets such as the
newest cellphones and other technologically related products.
They exhibit high levels of spending power as they
tend to get married later in life. Generation Xers require
convenience but are cynical consumers and are unlikely
to believe the advertising claims made by businesses
(Grewal and Levy, 2010; Schiffman et al., 2008).
Generation Y consumers are technologically savvy and
use the latest technology to communicate and shop.
These consumers are characterised by their

independence, assertiveness, innovativeness and
curiosity (Hawkins and Mothersbaugh, 2010; Hoyer and
MacInnis, 2010). Jordaan and Ehlers (2009) explain that
Generation Y use cellphones as a medium of individual
expression through personalised ringtones and
screensavers and demand up-to-date technology.
Due to the wide age range of the Generation Y cohort
as well as their diversity in cultural and social activities,
marketers often separate this group into Generation Y
adults, Generation Y teens and tweens where each group
should have their own marketing strategy (Kotler and
Armstrong, 2010; Jorgensen, 2003). Kumar and Lim
(2008) suggest that cellphone service providers should
develop different marketing strategies for Generation Y
adults (aged 15 – 23) and younger Generation Y
consumers (aged 15 – 24) as they differ in their cellphone
usage. The younger Generation Y consumers ‘outnumber
all other users in terms of minutes used, number of calls
placed, messages sent/received and wireless data
transmitted/received’ (Kumar and Lim, 2008).
Extant literature propagates that significant differences
do exist between the generations with regards to how
they perceive the world around them, their consumer
behaviour in general and more specifically in terms of
their cell phone usage habits (Jordaan and Ehlers, 2009;
Kumar and Lim, 2008; Munnukka, 2007; Hamilton, 2003;
Jorgensen, 2003). As Munnukka (2007) and Jorgensen
(2003) explain, the variations within each generation
pertaining to their consumer behaviour and in particular
their expectations, service perceptions, customer
satisfaction and behaviour intent requires that service
providers need to understand each cohort and determine
their differences to make managerial decisions. Based on
the discussion above, the following hypotheses can be
formulated:
H1: The generations perceive the level of service quality
cellphone network service providers provide significantly
different.
H2: The generations perceive the level of service
satisfaction they experience from cellphone network
service providers significantly different.
H3: The generations exhibit significantly different
behavioural intentions towards cellphone network service
providers.
Service quality
As suggested by literature, providing customers with
quality services presents the best opportunity for
businesses to obtain a sustainable competitive
advantage (Boshoff and du Plessis, 2009). Wang and Lo
(2002) add that due to customers’ needs changing and
evolving, service quality needs greater attention. Dagger
et al. (2007) explain that the perceptions customers’ have
of the service quality refers to the impression that they
Petzer and Meyer 7463
have about the overall service provided by the service
provider. Dean (2004) continues to describe service
quality as the way in which customer’s asses the service
encounter in terms of whether the perceived performance
of the service provider has met or exceeded the
customers’ service expectations. Customer expectations
and perceptions have been found to be the main
antecedents of service quality (Lee et al., 2001). Service
providers need to understand that customers develop
their expectations through their previous dealings with the
service provider or through their dealings with other
service providers which implies that service providers
need to continually monitor their service levels and
ensure that they meet customer expectations (Kumar and
Lim, 2008).
Zeithaml et al. (2009) explain that consumers evaluate
service quality according to five main dimensions
(reliability, responsiveness, assurance, empathy and
tangibles). In most cases consumers evaluate these five
dimensions and formulate their expectations and
perceptions of the overall service quality provided by the
service provider, by combining the five dimensions. As
consumers have different needs and expectations
pertaining to service quality service providers need to
identify that different market segments need different
marketing strategies as customers will differ in terms of
their service expectations (Anderson et al., 2008).
Service providers need to ensure that the meet
customers’ expectations through the provision of quality
services as this will impact on customers’ satisfaction
levels pertaining to the services (service satisfaction)
received as well as their future repurchase intentions
(Zeithaml et al., 2009).
Service satisfaction
Although many researchers use the terms “service
quality” and “customer satisfaction” interchangeably,
these concepts are different, yet connected (Zeithaml et
al., 2009). Palmer (2008) as well as Vlachos and
Vrechopoulos (2008) state that divergent results have
been presented in studies conducted on service quality
and service satisfaction. Some studies note that service
quality is an antecedent of service satisfaction (Cronin
and Taylor, 1992), while others found the reverse relationship
(Bitner, 1990). Taking this into account, however,
there seems to be a definite relationship between service
quality and service satisfaction that should not be
underestimated (Palmer, 2008). Wang and Lo (2002)
mention that satisfaction needs to be an important goal
for service providers as this can influence their
profitability and sustainability.
For purposes of this study, service satisfaction is
defined as the customers’ evaluation of the service
provided by the cellphone network service provider in
terms of how it has met or exceeded the customers’

7464 Afr. J. Bus. Manage.
Figure 1. The relationships between service quality, service satisfaction and behavioural intent.
Source: Adapted from Dagger et al. (2007). *The arrows in this figure represent the relationships between constructs.
expectations (Zeithaml et al., 2009). It is important to note
that customers will evaluate each service quality
dimension provided as well as the overall satisfaction
they experience due to their interaction with the service
provider over a period of time (Bodet, 2008; Saeed et al.,
2009; González et al., 2007). Only if customers are
satisfied with the services offered by the service provider,
will they be less receptive to competitors’ offerings
(Torres-Moraga et al., 2008) and will they consider
repurchasing from the service provider and will they be
willing to form a long-term relationship with the service
provider (Kumar and Lim, 2008).
Behavioural intent
Service satisfaction has furthermore a major impact on
the behavioural intent of consumers as only satisfied
consumers will be committed to the business in the longterm
and will spread positive word-of-mouth to others (Lu
and Seock, 2007; Ryu et al., 2007). Wang and Lo (2002)
add that service satisfaction drives favourable
behavioural intentions and that behavioural intent is often
seen as a predictor of future purchases (Torres-Moraga
et al., 2008; Saeed et al., 2009; González et al., 2007).
Schiffman et al. (2008) explain that behavioural intent
determines the ‘likelihood that consumers will act in a
certain way in the future”. Saha and Theingi (2009)
elaborate on this definition by defining behavioural intent
as the probability of customers performing a certain
behavioural act such as spreading positive word-ofmouth
about the service providers to others; repurchase
intentions and loyalty towards the service provider.
Service providers rely on customer repurchasing their
service offerings in order to remain competitive over a
long-term period of time (Torres-Moraga et al., 2008).
The foregoing discussion provides insight into the
relationships between customers’ perception of service
quality, the service satisfaction they experience and their
ultimate behavioural intent. The following figure based
upon the work of Dagger et al. (2007) provides a graphic
illustration of the relationships (correlation or association)
between the three constructs (Figure 1).
Based on the differences in perception and consumer
behaviour uncovered between the different generations,
the universality of the relationship between the three
constructs in terms of the different generations are
investigated. Based on this statement and the discussion
above the following hypotheses were formulated:
H4: There is a correlation between the different
generations’ perceived level of service quality and the
perceived level of service satisfaction they experience
from cellphone network service providers.
H5: There is a correlation between the different
generations’ perceived level of service satisfaction they
experience from cellphone network service providers and
their behavioural intent towards cellphone network
service providers.
H6: There is a correlation between the different
generations’ perceived level of service quality they
experience from cellphone network service providers and
their behavioural intent towards cellphone network
service providers.
PROBLEM STATEMENT, OBJECTIVES AND
RESEARCH HYPOTHESES
South Africa has one of the largest growing cellular
markets in the world and is characterised by intense
competition between the cellphone network service
providers Vodacom, MTN, Cell C and Virgin Mobile
(Mbendi, 2010). The cellphone network service providers
in South Africa are therefore competing fiercely for
market share in a fairly saturated market (Mbendi, 2010).
In order to remain profitable in this competitive market,
cellphone network service providers need to ensure that
they provide customers with good quality services that
will meet and exceed customer expectations in order to
create customer satisfaction (Koenderman, 2009).
Service satisfaction also impacts on consumer
behavioural intent, whether the consumer generates
positive or negative word-of-mouth and whether the
consumer uses additional services offered by the service
provider or not. In order to increase market share,
cellphone service providers need to convince customers
of other cellphone network service providers to switch
service providers. They also need to convince new
customers entering the market to select their network

over those of competitors in order to grow (Lu and Seock,
2007; Ryu et al., 2007). Yet in the cellphone industry of
South Africa, customers are riddled with service levels
such as dropped calls, incorrect billing and lack of
network coverage (Deng et al., 2010).
Kumar and Lim (2008) state that age group plays an
important role when conducting research on the adoption
of technology (including cellphones) as differences exist
in the different generations’ cellphone usage due to
different inherent needs. Anderson et al. (2008) add that
customer characteristics such as age will affect
customers’ level of satisfaction (where older consumers
tend to be more satisfied than younger consumers) and
repurchase intentions. Based on this notion, marketers
need to differentiate their marketing strategies when they
target consumers from different generations in order to
attract and retain them over the long-term.
Although Kumar and Lim (2008) conducted a study on
the difference between Generation Y and baby boomers
in cellphone service perceptions, these authors did not
examine the relationship that exists between customer
satisfaction and future repurchase intentions and did not
include the Generation X cohort in their research.
Furthermore González et al. (2007) and Wang and Lo
(2002) add that service quality, customer satisfaction and
behavioural intent are important factors for service
providers, yet few studies have been conducted on these
studies in the telecommunications industry. From a
South African perspective, although 60% of all South
Africans above the age of 16 own a cellphone (Jordaan
and Ehlers, 2009), research into the effects of service
quality on satisfaction and behavioural intentions in the
cellphone industry of South Africa is lacking.
It is thus important for cellphone network service providers
to (1) be conversant in how different generations
perceive the quality of the services they provide, (2) be
familiar with the level of service satisfaction the different
generations experience, (3) have insight into the
generations’ behaviour intentions toward the cellphone
network service providers in the future and (4) determine
the strength of the relationship or correlation between
service quality, service satisfaction and behavioural intent
in relation to the cellphone network service provider
industry (Dagger and Sweeney, 2007; Dagger et al.,
2007). Doing this may assist cellphone network service
providers in crafting marketing strategies to acquire
prospective customers and to retain existing customers
by taking generational differences and similarities into
account.
To achieve the purpose of this article as presented in
the introduction of this article, the following objectives
were formulated:
Investigate the service quality perceptions of the
generations toward the services offered by cellphone
network service providers.
Determine the level of service satisfaction the
generations experience from cellphone network service
Petzer and Meyer 7465
providers.
Uncover the behavioural intent of the generations
towards cellphone network service providers.
Determine whether correlations exist between the
generations’ perceived levels of service quality, the
service satisfaction they experience from cellphone
network service providers, and their behavioural intent
towards cellphone network service providers.
MATERIALS AND METHODS
The target population for this study included all individuals in the
Gauteng province of South Africa who owned a cellphone and who
were 64 years of age or younger at the time of the study (thus
excluding the senior generation). A total of 2339 useable
responses were gathered.
A non-probability convenience sampling technique was used to
collect select the sampling units or respondents. A sampling frame
of the target population does not exist. This fact excluded the use of
a probability sampling technique and necessitated the use of
convenience sampling to select the sampling units or respondents
from the target population.
Trained fieldworkers were used to select respondents, distribute
questionnaires for completion and to collect completed questionnaires
from respondents. The self-administered questionnaire
respondents had to complete consists of a number of sections. The
first section includes a preamble explaining the objectives of the
study, instructions for completion of the questionnaire as well as the
rights of the prospective respondent. This section also includes a
screening question field workers used to select suitable
respondents.
The second part of the questionnaire focuses on the
demographic information of respondents, most notably their age
group, so as to determine the generation the respondents belong
to. This section furthermore includes questions focusing on gender
and home language. This section also enquires about the cellphone
network service provider patronage of respondents.
The third section includes three adapted Likert scales that
measure the three constructs of the study (service quality, service
satisfaction and behavioural intent). In order to measure each of
these constructs three measurement sets were included, each
containing a number of scale items. Respondents had to indicate
their level of agreement with each of the scale items on an
unlabelled five-point scale where 1 represents ‘strongly disagree’
and 5 represents ‘strongly agree’.
The statistical package for social sciences (SPSS) was used to
capture, clean, edit and analyse the data obtained from the
questionnaires. Pair wise deletion was employed to deal with
missing values. The data analysis involved the examination of the
frequency distribution of the results for each of the scale items
included in the three measure sets to measure the three constructs
of the study were also assessed in order to determine whether all
scale items fall within the acceptable limits of normality.
The data analysis also involved the calculation of Cronbach’s
alpha coefficient in order to determine the reliability of each of the
three measurement sets used in the study. The descriptive statistics
for the demographic and patronage variables (frequencies) were
also calculated. The article also reports the descriptive statistics
(mean and standard deviation) for each of the scale items included
in the three measurement sets included in the questionnaire as well
as the measurement sets overall. With regards to the hypotheses
formulated for the study, the researchers relied on a 95%
confidence interval and a subsequent 5% level of significance. A p-
value of 0.05 or less is thus indicative that a hypothesis formulated

7466 Afr. J. Bus. Manage.
Table 1. Reliability of the measurement sets.
Measurement set Cronbach’s alpha value
Service quality (4 items) 0.886
Service satisfaction (4 items) 0.875
Behaviour intention (6 items) 0.907
for the study may be supported. Parametric tests were furthermore
used to test the hypothesis. Such tests are suitable since the
sample size is large (n = 2339) and the distribution of data obtained
for all scale items used to measure each construct fall within the
acceptable limits of normality (section 5.1 provides a discussion of
the related findings).
One-way analysis of variances (ANOVAs) were first of all used to
determine whether there are significant differences between
generations in terms of (1) their service quality perceptions
regarding the services they receive from cellphone network service
providers, (2) the level of service satisfaction they experience from
cellphone network service providers and (3) their behavioural intent
towards cellphone network service providers. In order to determine
the generations between which significant differences exist,
Scheffe’s post hoc test for multiple comparisons was used when
equal variances could be assumed between the means of the
different generations. Similarly, Dunnett’s T3 post hoc test for
multiple comparisons was used when equal variances between the
means of the different generations could not be assumed.
Pearson’s product moment correlations were performed to
determine the correlations between the three different constructs
stated in the hypotheses formulated for the study. Eiselen et al.
(2007) indicates that a correlation coefficient of less than 0.1
indicates that virtually no correlation exists between the two
variables, a correlation coefficient between 0.1 and 0.3 indicates a
small correlation, a correlation coefficient between 0.3 and 0.5
indicates a medium correlation and a correlation coefficient of
greater than 0.5 indicates a strong correlation.
RESULTS AND DISCUSSIONS
This section reports on the empirical results of the study.
It communicated the findings in terms of the distribution
of the results for each scale item included in the three
measurements sets, the reliability as well as the construct
validity of the three measurement sets. This section
furthermore presents the findings made with regards to
the respondents’ demographics, service provider
patronage and also the findings in terms of each of the
constructs measured. The results section ends of with a
presentation of the findings made in relation to the
hypotheses formulated for the study.
Distribution of results
Before the individual scale items included in each of the
measurement sets can be subjected to hypotheses
testing using parametric tests, it is important to determine
and report on the normality of the distribution of the
results obtained for each scale item included. West et al.
(1995) are of the opinion that the distribution of the
results collected for a scale item can be considered as
normal if it exhibits a skewness of the distribution of less
than an absolute value of 2.00 and a kurtosis of the
distribution of less than 7.00. The results for all scale
items used to measure the three measurement
instruments fall within these parameters and can be thus
considered (taking other assumptions underlying correlation
analysis into account) suitable for parametric tests.
Reliability
Before an overall average value for a construct may be
calculated, it is necessary to determine reliability or the
extent to which individual scale items included in the
measurement set correlates with one another (Pallant,
2010). It is thus necessary to calculate the Cronbach’s
alpha value. The closer the value is to 1 the more reliable
the measurement set may be considered. Pallant (2010)
states further that a cut-off point of 0.7 is the lower limit
for reliability. Table 1 presents the Cronbach’s alpha
value for each measurement set. It is evident from Table
1 that all the measurement sets may be considered
reliable.
Construct validity
The three measurement sets used to measure service
quality; service satisfaction and behavioural intention
were taken from the work of Dagger et al. (2007). These
scale items included in these measurement sets proved
reliable since it showed significant paths to relationship
the constructs and are associated with low residuals.
Demographic profile and cellphone network service
provider patronage
The majority of respondents are female (52.7%) and the
balance of the 47.3% of respondents are male. English is
spoken by most respondents (39.4%) followed by those
who speak Nguni languages (21.5%) and Sotho
languages (20.2%). The majority of respondents are adult
Generation Y consumers (50.2%) followed by Generation
X (20.6%), Baby boomers (15.1%) and young Generation
Y consumers (14.2%). The majority of respondents use

Table 2. Demographic profile and cellphone network service provider patronage of respondents.
Petzer and Meyer 7467
Variable Categories
Number of respondents
(count)
Percentage
Gender
Male
Female
1106
1231
47.3
52.7
Home language Afrikaans 260 11.2
English 918 39.4
Nguni (Zulu, Xhosa, Swati and Ndebele) 501 21.5
Sotho (Sepedi, Sesotho and Tswana) 470 20.2
Venda/Tsonga 140 6.0
Other language 41 1.8
Age 24 years and younger (young Generation Y) 331 14.2
25 to 33 years (adult Generation Y) 1174 50.2
34 to 45 years (Generation X) 481 20.6
46 to 64 years (Baby boomers) 353 15.1
Cell phone network service
provider currently used
Vodacom 1205 51.6
MTN 750 32.1
Cell C 300 12.8
Virgin Mobile 80 3.4
Type of customer Contract customer 1145 49.0
Prepaid customer 1178 50.4
Length of time with current
cell phone network service
provider
Vodacom (51.6%) as cellphone network service provider
are prepaid customers (50.4%) and have been with their
current cellphone network service provider for at least
five years but less than 10 years. The respondents’
demographic profile and their cellphone network service
provider patronage are provided in Table 2.
Service quality
Respondents were required to indicate their level of
agreement with four statements measuring service
quality perceptions where 1 represents ‘strongly agree’
and 5 ‘strongly disagree’. Table 3 provides a comparison
of the service quality perceptions of the different
generations and the overall service quality rating.
Respondents indicated the highest level of agreement
overall with the scale items. ‘The overall quality of service
provided by the cellphone network service provider is
Less than 6 months 93 4.0
6 months or longer but less than 1 year 135 5.8
1 year or longer but less than 3 years 396 17.00
3 years or longer but less than 5 years 520 22.3
5 years or longer but less than 10 years 839 36.0
Longer than 10 years 348 14.9
excellent’ (mean = 3.30) and ‘The service provided by the
cellphone network service provider is of a high standard’
(mean = 3.30). The scale item ‘I believe the cellphone
network service provider offers service that is superior in
every way’ (mean = 3.04), is the scale item respondent’s
agreed with the least.
Service satisfaction
Respondents were also required to indicate their level of
agreement with six statements measuring behavioural
intent on a scale where 1 represents ‘strongly agree’ and
5 ‘strongly disagree’. Table 4 provides a comparison of
the level of service satisfaction the different generations
experience as well as the overall service satisfaction
rating. Respondents indicated the highest level of agreement
overall with the scale items ‘I feel good about using
this cell phone network service provider’ (mean = 3.56)

7468 Afr. J. Bus. Manage.
Table 3. Service quality perceptions of different generations toward the services offered by cellphone network service providers.
Scale items
The overall quality of
service provided by the cell
phone network service
provider is excellent
The quality of the service
provided by the cell phone
network service provider is
impressive
The service provided by
the cell phone network
service provider is of a
high standard
I believe the cell phone
network service provider
offers service that is
superior in every way
Young
Generation Y
Standard
deviation
Mean
Adult
Generation Y
Standard
deviation
Mean
Generation X
Standard
deviation
Mean
Baby
boomers
Standard
deviation
Mean
Standard
deviation
Overall
Mean
ANOVA
(p-value)
0.843 3.04 0.942 3.33 0.954 3.39 0.936 3.35 0.936 3.30 0.000*
0.854 2.97 0.947 3.29 0.979 3.29 0.970 3.26 0.951 3.24 0.000*
0.969 2.96 0.991 3.37 1.017 3.35 0.937 3.31 0.994 3.30 0.000*
0.933 2.76 1.029 3.08 1.063 3.12 1.015 3.09 1.027 3.04 0.000*
Overall 0.768 2.93 0.836 3.26 0.874 3.28 0.844 3.24 0.844 3.21 0.000*
*Significant differences between at least two of the generations
and ‘My feelings toward the cellphone network service
provider are very positive’ (mean = 3.38). The scale item
‘I feel satisfied that the results from using this cellphone
network service provider is the best that can be achieved’
(mean = 3.03), is the scale item respondents agreed with
the least.
Behavioural intent
Respondents were furthermore required to indicate their
level of agreement with six statements measuring
behavioural intent on a scale where 1 represents
‘strongly agree’ and 5 represents ‘strongly disagree’.
Table 5 provides a comparison of the behavioural intent
of the different generations and their overall behavioural
intent. Respondents indicated the highest level of agreement
overall with the scale items ‘I intend to continue
using this cellphone network service provider’ (mean =
3.65) and ‘I intent to follow the advice given to me by the
cellphone network service provider’ (mean = 3.53). The
scale item ‘If I had to choose a cellphone network service
provider all over again, I would choose this cellphone
network service provider’ (mean = 3.46), is the scale item
respondents agreed with the least.
Hypothesis testing
Hypothesis 1
With regards to hypothesis 1 that the generations
perceive the level of service quality of cellphone network
service providers provide significantly different, the
following findings were make (Table 1 provides the
means and corresponding p-values):
There is a significant difference between young
Generation Y consumers and consumers in the other
generations (adult Generation Y, Generation X and baby
boomers) with regards to their perceptions regarding the
level of service quality cellphone network service
providers provider for all the individual scale items and for
the measurement set overall (see means and
corresponding p-values in Table 3).
It can therefore, be said that overall, young Generation
Y consumers perceive the level of service quality that
cellphone network service providers provide significantly
lower than the other generations. H1 can therefore, be

Table 4. Service satisfaction levels of different generations experience from the cellphone network service providers.
Scale items
My feelings toward the cell
phone network service
provider are very positive
I feel good about using this
cell phone network service
provider
I feel satisfied that the results
from using this cell phone
network service provider is
the best that can be achieved
The extent to which using
this cell phone network
service provider has
produced the best possible
outcome is satisfying
Young
Generation Y
Standard
deviation
Mean
Adult
Generation Y
Standard
deviation
Mean
Generation X
Standard
deviation
Mean
Baby
boomers
Standard
deviation
Mean
Petzer and Meyer 7469
Standard
deviation
Overall
Mean
ANOVA
(p-value)
1.079 3.13 1.053 3.42 1.035 3.49 1.034 3.35 1.055 3.38 0.000*
1.048 3.33 1.058 3.62 1.054 3.63 1.014 3.48 1.053 3.56 0.000*
1.035 2.73 1.096 3.07 1.105 3.13 1.030 3.00 1.087 3.03 0.000*
0968 2.87 0.970 3.15 1.004 3.21 0.939 3.15 0.977 3.12 0.000*
Overall 0.890 3.01 0.883 3.32 0.900 3.36 0.870 3.24 0.891 3.27 0.000*
*Significant differences between at least two of the generations
partially supported.
Hypothesis 2
With regards to hypothesis 2 that the generations
perceive the level of service satisfaction they experience
from cellphone network service providers significantly
different, the following findings were made:
There is a significant difference between young
Generation Y consumers and consumers in the other
generations (adult Generation Y, Generation X and Baby
Boomers) with regards to their perception of the level of
service satisfaction they experience from cellphone
network service providers for all the individual scale items
except for the scale item ‘I feel good about using this
cellphone network service provider’ where young
Generation Y consumers and baby boomers exhibit
significantly lower levels of agreement with the statement
that the other generations (see means and corresponding
p-values in Table 4).
In terms of the overall measurement set, young
Generation Y consumers perceive the level of service
quality significantly lower than the other generations. It
can therefore, be said that overall, young Generation Y
consumers perceive the level of service satisfaction with
cellphone network service providers significantly lower
than the other generations. H2 can therefore, be partially
supported.
Hypothesis 3
With regards to hypothesis 3 that the generations exhibit
significantly different behavioural intent towards services
provided by cellphone network service providers, the
following findings were made:
There is a significant difference between young
Generation Y consumers and consumers in the other
generations (adult Generation Y, Generation X and baby
boomers) with regards to their behavioural intent towards
services provided by cellphone network service providers
for the first three scale items (see means and
corresponding p-values in Table 5).
For the scale item ‘I will make use of any other services
and products I need form this cellphone network service
provider’, young Generation Y consumers’ level of
agreement with the scale item is only significantly lower

7470 Afr. J. Bus. Manage.
Table 5. Behavioural intent of different generations towards cellphone network service providers.
Scale items
If I had to choose a cell
phone network service
provider all over again, I
would choose this cell
phone network service
provider
I would highly
recommend the cell
phone network service
provider to other people
I intend to continue using
this cell phone network
service provider.
I will make use of any
other services and
products I need from this
cell phone network
service provider
I intend to follow the
advice given to me by the
cell phone network
service provider
I am glad to use this cell
phone network service
provider rather than going
somewhere else
Young
Generation Y
Standard
deviation
Mean
Adult
Generation Y
Standard
deviation
Mean
Generation X
Standard
deviation
Mean
Baby
boomers
Standard
deviation
Mean
Standard
deviation
Overall
Mean
ANOVA
(p-value)
1.373 3.25 1.276 3.50 1.278 3.51 1.152 3.44 1.275 3.46 0.013*
1.206 3.16 1.182 3.45 1.188 3.49 1.106 3.34 1.180 3.50 0.000*
1.210 3.39 1.173 3.71 1.155 3.68 1.064 3.64 1.163 3.65 0.000*
1.082 3.35 1.115 3.55 1.125 3.55 1.059 3.39 1.107 3.50 0.005*
1.073 3.31 1.064 3.61 1.081 3.59 1.052 3.41 1.073 3.53 0.000*
1.154 3.35 1.189 3.48 1.206 3.53 1.138 3.46 1.180 3.47 0.201
Overall 0.973 3.30 0.963 3.55 0.980 3.56 0.900 3.45 0.963 3.50 0.000*
* Significant differences between at least two of the generations.
than that of adult Generation Y consumers.
For the scale item ‘I intend to follow the advice given to
me by the cellphone network service providers”, young
Generation Y consumers’ level of agreement with the
scale item is significantly lower than that of the other
generations, while adult Generation Y consumers’ level of
agreement is significantly lower than the other
generations.
It can therefore, be said that overall, young Generation
Y consumers’ behavioural intent is significantly lower
than other generations. H3 can therefore, be partially
supported.
Hypothesis 4
With regards to hypothesis 4 that there is a correlation
between the different generations’ perceived level of
service quality and the perceived level of service
satisfaction they experience from cellphone network
service providers, the following findings were made:
There is a strong significant correlation (Pearson
correlation coefficient = 0.769; p-value = 0.001) between
young Generation Y’s perceived level of service quality
and the perceived level of service satisfaction they
experience from cellphone network service providers.

There is a strong significant correlation (Pearson
correlation coefficient = 0.804; p-value = 0.001) between
adult Generation Y’s perceived level of service quality
and the perceived level of service satisfaction they
experience from cellphone network service providers.
There is a strong significant relationship (Pearson
correlation coefficient = 0.779; p-value = 0.001) between
Generation X’s perceived level of service quality and the
perceived level of service satisfaction they experience
from cellphone network service providers.
There is a strong significant correlation (Pearson
correlation coefficient = 0.817; p-value = 0.001) between
baby boomers’ perceived level of service quality and the
perceived level of service satisfaction they experience
from cellphone network service providers.
There is a strong significant relationship (Pearson
correlation coefficient = 0.799; p-value = 0.001) overall
between the different generations perceived level of
service quality and the perceived level of service satisfaction
they experience from cellphone network service
providers.
It can therefore, be concluded that strong significant
correlations (relationships) exist between the generations’
perceived level of service quality and the perceived level
of service satisfaction they experience from cellphone
service network providers (p values ≤ 0.05 and Pearson
correlation coefficients > 0.5, respectively). H4 can
therefore, be supported.
Hypothesis 5
With regards to hypothesis 5 that there is a correlation
between the different generations’ perceived level of
service satisfaction they experience from cellphone
network service providers and their behavioural intent
towards cellphone network service providers, the
following findings were made:
There is a strong significant correlation (Pearson
correlation coefficient = 0.737; p-value = 0.001) between
young Generation Y’s perceived level of service satisfaction
they experience from cellphone network service
providers and their behavioural intent towards cellphone
network service providers.
There is a strong significant correlation (Pearson correlation
coefficient = 0.809; p-value = 0.001) between adult
Generation Y’s perceived level of service satisfaction
they experience from cellphone network service providers
and their behavioural intent towards cellphone network
service providers.
There is a strong significant correlation (Pearson
correlation coefficient = 0.794; p-value = 0.001) between
Generation X’s perceived level of service satisfaction
they experience from cellphone network service providers
and their behavioural intent towards cellphone network
service providers.
There is a strong significant correlation (Pearson
Petzer and Meyer 7471
correlation coefficient = 0.805; p-value = 0.001) between
baby boomers perceived level of service satisfaction they
experience from cellphone network service providers and
their behavioural intent towards cellphone network
service providers.
There is a strong significant correlation (Pearson correlation
coefficient = 0.797; p-value = 0.001) between the
different generations’ perceived level of service
satisfaction they experience from cellphone network
service providers and their behavioural intent towards
cellphone network service providers.
It can therefore, be concluded that strong significant
correlations (relationships) exist between the different
generations’ perceived level of service satisfaction they
experience from cellphone network service providers and
their behavioural intent towards cellphone network service
providers (p-values ≤ 0.05 and Pearson correlation
coefficients > 0.5, respectively). H5 can therefore, be
supported.
Hypothesis 6
With regards to hypothesis 6 that there is a correlation
between the different generations’ perceived level of
service quality they experience from cellphone network
service providers and their behavioural intent towards
cellphone network service providers, the following
findings were made:
There is a strong significant correlation (Pearson
correlation coefficient = 0.630; p-value = 0.001) between
young Generation Y’s perceived level of service quality
they experience from cellphone network service providers
and their behavioural intent towards cellphone network
service providers.
There is a strong significant correlation (Pearson
correlation coefficient = 0.692; p-value = 0.001) between
adult Generation Y’s perceived level of service quality
they experience from cellphone network service providers
and their behavioural intent towards cellphone network
service providers.
There is a strong significant correlation (Pearson
correlation coefficient = 0.709; p-value = 0.001) between
Generation X’s perceived level of service quality they
experience from cellphone network service providers and
their behavioural intent towards cellphone network
service providers.
There is a strong significant correlation (Pearson
correlation coefficient = 0.711; p-value = 0.001) between
baby boomers perceived level of service quality they
experience from cellphone network service providers and
their behavioural intent towards cellphone network
service providers.
There is a strong significant correlation (Pearson correlation
coefficient = 0.692; p-value = 0.001) between the
different generations’ perceived level of service quality
they experience from cellphone network service providers

7472 Afr. J. Bus. Manage.
and their behavioural intent towards cellphone network
service providers.
It can therefore, be concluded that strong significant
correlations (relationships) exist between the different
generations’ perceived level of service quality they
experience from cellphone network service providers and
their behavioural intent towards cellphone network service
providers (p-values ≤ 0.05 and Pearson correlation
coefficients > 0.5, respectively). H6 can therefore be
supported.
Managerial implications and recommendations
An important finding of this study is the fact that young
Generation Y consumers perceive the service quality
levels and service satisfaction levels offered by cellphone
network service providers significantly lower as the other
generations. Associated with this, is a low level of
behavioural intent towards cellphone network service
providers by this generation, making customer defection
a real threat. More worrying is the fact that young
Generation Y consumers represent a critical market for
cellphone network service providers, since they are
growing into adulthood; they are entering the job market
and subsequently their incomes increase, thus enabling
them to spend more on cellphone and related expenditures.
Based on these findings, the cellphone network
service providers need to uncover the reasons why this
generation perceive service quality and service
satisfaction to be low. As a result, cellphone network
service providers should determine what they need to do
to improve the perceptions of service quality and service
satisfaction among young Generation Y consumers. To
address the differences between generations uncovered
in service quality, service satisfaction and behavioural
intent, cellphone network service providers should
furthermore develop customised marketing strategies to
target the different generations. Clear relationships also
exist between service quality, service satisfaction and
behavioural intent, as advocated in previous research,
has been confirmed in this research. Cellphone network
service providers should therefore, ensure that quality
services are consistently provided to customers. Once
customers are satisfied with the levels of service they
receive from cellphone network service providers, they
will be more inclined to continue purchasing from the
cellphone network service provider in the future.
LIMITATIONS AND FUTURE RESEARCH
This research was limited in that it was only conducted in
one province of South Africa (namely Gauteng) and that
the research excluded the senior generation. The
research also did not take into consideration the effect of
service failures on satisfaction and behaviour intent as
the way in which the cellphone network service provider
deals with service failures could influence customers’
satisfaction levels and their future behavioural intent to
repurchase from the cellphone network service provider.
Another limitation of the study involves the fact that a
non-probability convenience sampling was used to select
respondents from the target population. This sampling
method limits the ability to generalise the results to the
total population.
It is recommended that the research be conducted in
other provinces and includes other demographic
variables (for example gender) and other influences such
as personality, culture and usage patterns. Future
research could include the effect of service failures on
customer satisfaction levels and behavioural intent.
Conclusion
This study provides insight into the views of various
generations on their perceptions of the service quality
provided by their cellphone network service provider.
Furthermore, the research provides an understanding
into the satisfaction levels and future behavioural
intentions of various generations towards their cellphone
network service provider which has been lacking from a
South African perspective. The results indicate that
significant correlations exist between the different generations’
perceived level of service quality and perceived
level of satisfaction as well as their perceived level of
satisfaction and behavioural intent. This research therefore
indicates the importance to South African cellphone
network service failures to provide customers with
services that meet and exceed expectations. Furthermore,
the results can offer insights into how cellphone
network service providers in South Africa should target or
market their services to customers of various generations
and the importance of developing different marketing
strategies for the different generations.
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African Journal of Business Management Vol. 5(17), pp. 7474-7480, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.320
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Value at risk: Evidence from Pakistan Stock Exchange
Faisal Nawaz* and Muhammad Afzal
Department of Management Sciences, COMSATS Institute of Information Technology, Attock -Pakistan
Department of Management Sciences COMSATS Institute of Information Technology Park Road Chak Shahzad,
Islamabad -Pakistan
Accepted 16 May, 2011
The impetus of this work comes from the October 2008 crisis, termed Tsunami of the Financial Markets,
which stems from a small problem in US real estate market. It has been observed that this type of
events occurs once in a century. To the Green Span, ex-chief of the US Fed, the financial models that
have been trusted in the past rendered absurd in the wake of this snowball effect. The study tries to find
how the margin calculated on VaR influence the Trade Volume of Pakistani bourse. Pro method was
considered to be accurate one than other two models at λ = 0.85, for five hundred days at 99%
confidence interval. The study shows that in the case of Slab System, the initial margin charged by the
clients fell between 5 and 25%. It has been observed that the cap of margins under VaR system was
about 5%. The VaR based margin system has proved to be better than slab system on the empirical as
well theoretical grounds.
Key words: Value at risk, financial risk management, financial risk modeling, financial econometric modeling,
financial time series, Pakistan.
INTRODUCTION
During the past two decades, the world has witnessed
tremendous capital inflow as well as outflow from one
country to another that has been reflected in the stock
market activities. Compared to developing countries, we
see a lot of trade in the developed countries stock
market. However, developing countries also have stock
markets which play vital role in macroeconomics stability.
Pakistan is an important developing country. Its economy
did well during the first half of 2000 that was reflected in
the stock market index. Pakistan stock market did well
after 9/11 when stock market of many developed
countries had a sluggish performance.
The motivation for focusing on equity market is due to
increase in volatility which subsequently brings changes
in risk management frame work for the stock exchanges
in Pakistan. The impacted risk is perceived in Pakistan at
present. Risk management frame work of the stock
exchange of Pakistan, has undergone a paradigm shift to
calculate the margins. Members of clearing house paid
these margins (Government of Pakistan (GOP), 2006).
*Corresponding author. E-mail: profafzal@gmail.com. Tel: +92-
51-9243004, +92-333-9982533.
Since Pakistan is an emerging economy, it has its own
unique problems. Brokers and investors are not adequately
aware of risk measures and their impact on the
capital market. Pakistan like other emerging economies
faces the problem of lack of research culture and
resistance to accept change. It has been observed that
market volume is concentrated to a handful of Brokers
that can influence the trading activities to a large extent.
Due to absence of adequate margin financing system,
Carry Over Trade (COT) called Badlais, adds to their
market manipulative power. Also, Security Exchange
Commission of Pakistan (SECP) (2005) report revealed
that broker in emerging economies enjoyed market
manipulative power. This study is an intellectual inquiry
to find the impact of value at risk (VaR) based margins on
the trade volume of stock market from Pakistan.
VaR is a method of assessing risk that uses standard
statistical techniques used routinely in other technical
fields. In other words, VaR summarizes the worst losses
over a target horizon that will not be exceeded with a
given level of confidence (Jorion, 2007).
Margins can be considered as down payment
assuming an investor takes long position in scrip ‘X’ for
1,000 shares each at the rate of Rs. 10. With respect to
the prevailing T+3 systems, he has to pay Rs. 1,000 now

as a margin rate of 10% and rest to settle his account
within three working days. Margins basically safeguard
brokers from excessive losses. It believed that the
application of VaR for Initial Margins in Pakistani Stock
Exchanges would build the trust of local and foreign
investor. This would ultimately increase the trade volume
of the Pakistani Stock Market.
To reform of the stock market situation, SECP (2005)
made many recommendations. The most important are;
(a) the pre-trade margin financing is carried out by a bank
(since bank is a regulated financial institution). In this
way, the interest rate on margin financing will be capped
(b) the initial margin on scrips should be levied using VaR
techniques. In this manner, appropriate margins will be
charged. As a result, on the average, lesser margins will
be charged. In this way, an average income investor can
also participate in the stock market. Moreover, stock split
is a good measure in this respect for scrip’s having
unaffordable price per share. Phasing out Badla and
introduction of VaR techniques would slash the brokers’
manipulative power. In such situations, the investor’s trust
in Pakistan capital market will be enhanced and will lead
to more capital flows towards the capital market which
enhances the efficiency of Pakistan market. Now, the
initial margin on T+3 system was determined on the sole
discretion of the brokers, only keeping in view the current
price, demand and supply of the scrip traded, which
normally ranges from 10 to 25%. This measure does not
take into account the underlying scrip’s historical price
volatility and relative liquidity. As a result, initial margins
on some scrip (under prevalent margin system) are more
than proposed VaR based margins and vice versa. If the
VaR is used for determining the margin requirement in
the place of initial margin, then there will be a cancellation
effect as in the least square estimation that net
effect of upward and downward variations about a mean
of the random variable is almost insignificant.
LITERATURE REVIEW
VaR is basically involved in estimating quantile of the
underlying distribution of returns. The basic inspiration of
the VaR methodologies came in after the work of
Mandelbrot (1963) and Fama (1965) on the financial
data. The work can be summed up as follows:
1. Financial return distributions undergone at hick tail
phenomenon.
2. Equity returns are skewed. These are negative
skewed.
3. Volatility clustering phenomenon has been observed in
the financial markets.
Further, it has been noticed that volatilities are quasistable.
There are some famous model such as Risk
Metrics (1996) and GARCH Bollerslev (1986). Engle
1982) and Bollerslev (1986) introduced the family of
Nawaz and Afzal 7475
(ARCH models).
VaR has its origin in portfolio theory and capital
requirements (Holton, 2002). Early VaR techniques were
developed along with these two parallel lines. Authors like
Hardy (1923) discussed the fruits of diversification. Later
on, Hicks (1935) also discussed the same in detail. It is
observed that first ever quantitative example of VaR was
published by Leavens (1945). Simple return metric’s
variance was used by Markowitz (1952) for measuring
VaR. Shortfall risk metric was used by Roy (1952). Sharpe
(1963) described VaR measure in his PhD dissertation.
This measure later on helped motivate Sharpe (1964) to
his famous asset pricing model.
Work of Mossin (1966), Lintner (1965), Sharpe (1964),
Treynor (1961) and Tobin (1958) was on the theoretical
issues of VaR, since then, the computation power was not
sufficient to implement it on the trading floors. Wilson
(1993) published a sophisticated VaR measure. Wilson’s
work is widely to be reckoned as the first study that
encompasses heteroskedasticity and thick tail phenomenon
in the VaR calculation. Wilson (1993) and Garbade’s
(1987) work was considered to be one of the pioneering
detailed work that was put on practice for financial
markets. Under the leadership of Till Guldimann in the late
1980’s, JP Morgan Bank developed VaR system for firms.
That popular system is known as Risk Metrics.
In April 1993 when joint venture of the International
Organization of Securities Commissioners (IOSCO), and
Basle failed, the Basle committee proposed some amendments
to the 1988 accord. This document also discussed
minimum capital requirements regarding banks’ market
risk. It was in strict coherence to Europe’s Capital
Adequacy Directive (CAD). The Committee tabled the
revised proposal in April 1995. The main changes, which
covered the organization-wide commodities exposures,
increased the market risk capital requirements. This proposal
was embraced in 1996. In 1998, it was implemented.
The SECP proactively undertook market reform
initiatives and implemented sustainable risk management
measures. SECP explored the implementation of a new
risk management structure based on international best
practices to improve the prevalent risk management
framework at the exchanges. A new risk management
structure (RMS) was introduced in December 2006. The
new RMS includes among others, a new netting regime;
a margining system based on value at risk (VaR) and
capital adequacy. The VaR is a state of the art risk
management system practiced internationally, that takes
into account risk associated with each share based on
historical data (GOP, 2006). The panel of brokers association
argues that new system would increase trading
margin requirement and subsequently the trade volume
would substantially be decreased.
The premise of the argument basically is that VaR
slashes trade volume. This paper tests the same by
determining the average margin using VaR on the basis
of back testing results. Then, the margins will be compared
with the actual average initial margin levied in the

7476 Afr. J. Bus. Manage.
same period. If the aforesaid difference is not substantial
(

(7)
Table 1. Descriptive statistics of KSE-100 index returns.
Nawaz and Afzal 7477
Mean Median Maximum Minimum Std. Dev Skewness Kurtosis Jarque-Bera Prob.
0.134 0.25 5.8 -6.06 1.512 -0.541 4.733 214.42 00000
Where: LRind = the likelihood ratio statistic for the null hypothesis of
serial independence against an alternative that the process follows
a first order Markov process; T00 = number of exceed (prior no
exceed); T10 = number of exceed (prior exceed); T11 = number
exceed (prior exceed); T01 = number of exceed (prior no exceed);
; ;
The volatility clustering is captured with the test for conditional
coverage (LRcc). This test is formulated by uniting the
aforementioned two tests (LRuc, LRind) and the relevant test
statistics is:
Data
We collected data from the SECP and KSE. The KSE-100 index,
trading volume, trading value, rate (return in percentage), their
proportional change, opening and closing values and the
associated change per day were collected from SECP and the KSE.
The trading data of Karachi Stock Exchange are used for the period
2003 to 2007.
EMPIRICAL RESULTS
The study data consist of KSE-100 daily equity index
from January 2003 to December 2007. The daily return
series comprise 1231 observation. The daily returns are
computed as the logarithm of ratio of the price today to
price yesterday. Table 1 provides summary of statistics.
KSE-100 series has high mean value of 0.13% per
trading day. The standard deviation is 1.5% per trading
day, reflecting a high risk market. We use kurtosis to
measure whether data are peaked or flat relative to
normal distribution, and its value is 4.73 which indicates
that data are leptokurtic, that is, it is characterized by
simultaneous occurrence of distinct peak near the mean
and exhibition of fat tails. Skewness is used to measure
the asymmetry in the data distribution and it is -0.54
which indicates that returns are negatively skewed.
These statistics imply that returns are not normally
.
(8)
distributed. To confirm this result, Jarque-Bera (JB) test is
applied. Its value is 214 which imply that it is significant at
1%.
To examine the persistence in volatility, we examine the
squared returns. The autocorrelation coefficients of
squared returns are presented in Figure 1 of Appendix B.
The significant autocorrelation coefficients reflect the
presence of volatility clustering in the returns. These
findings are in agreement with stylized facts observed in
the financial time series. Figure 2 of Appendix B
represents the KSE-100 index return series.
The result from the VaR models at 95 and 99%
confidence intervals are obtained under different criterion.
The table of results shows that the widely accepted
models were Risk Metrics at λ = 0.85 with 99%
confidence interval and Historical Simulation for 500 days
with 99% confidence interval. The Pro method produced
best results at λ = 0.85, 500 days at 99% confidence
interval (the results are given in Tables 1 and 2 in
Appendix A). The result of Pro is better than the other two
VaR models. Its failure rate is 0.41%, which is less than
any other model. Also the result of coverage test confirms
the same. It is also worth noting that the average initial
margin under slab system 17.5% is far greater than the
average margin 4.58% calculated by VaR system.
It is conceivable, that more sophisticated statistical
models which can estimate volatility contagion across
several financial markets could provide better protection
against the market risk. The development of multivariate
models of volatility estimation that can account for
contagion is a topic for further research. In addition to
this, applying extreme value theory may provide a better
comprehension of the market behavior.
Conclusion
We conclude that the Pakistan Stock Exchange VaR
system is more effective than the Slab system. The initial
margin charged by the clients under the current Slab
System was ranging from 5 to 25%. We found that the
margin under VaR base System were maximum to the
5%. Hence, it is proved that the VaR based margins are
less than the current Slab Margins. In this manner, the
argument that the market depth will decrease by the
introduction of VaR margins is nullified. And the
hypothesis that the VaR base margins negatively impact
the trade volume of the Pakistani Stock Exchanges is
rejected in favor of the hypothesis that VaR based Margin
System has a favorable rather than a impact on the trade

7478 Afr. J. Bus. Manage.
volume of Pakistani stock exchanges.The average
margin using VaR model is less than the margin collected
under current slab system. Therefore, there are some
basic differences between VaR and slab system for
margins. First, in former system, margins rate on the
scrip will increase as volatility increase. While in later
system, margins rate is irrespective of volatility and
depends upon the size of outstanding position of a
broker. Another point that goes in the favor of VaR system
is that VaR is applied nowadays in almost most of the
international exchanges. In case of slab system, it is
almost an archaic one and is subjective too.
There is a dire need to revamp the archaic margin
system with international best practices which is
transparent and more objective. These issues of risk
management are becoming acute. If these issues are not
resolved in timely manner, it may cause the next crisis in
the bourse.
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APPENDIX A
Table 1. Failure rate test result.
Nawaz and Afzal 7479
Method
95%
Avg. margin (%) Failure rate (%)
99%
Avg. margin (%) Failure rate (%)
RM 0.90 2.27 6.50 3.22 2.52
RM 0.94 2.32 6.17 3.28 2.44
RM 0.97 2.37 6.17 3.35 2.19
RM 0.88 2.26 6.50 3.19 2.44
RM 0.85 2.24 6.58 3.16 2.70
HS-250 days
2.84
5.77
4.05
1.46
HS-500 days 2.84 5.61 4.30 1.06
Pro 0.85,250
3.10
3.41
4.36
0.49
Pro 0.90,500 3.08 3.33 4.56 0.49
Pro 0.94,500 3.05 3.66 4.52 0.57
Pro 0.97,500 3.00 4.14 4.46 0.65
Pro 0.88,500 3.09 3.25 4.57 0.49
Pro 0.85,500 3.10 3.17 4.58 0.41
Table 2. Coverage test results.
Method
LR uc
95%
LR ind LR cc LR uc
99%
LR ind LR cc
RM 0.90 5.34090721 -2.74710309 2.59380412 20.16977545 -5.93632 14.23346
RM 0.94 3.3335777 -0.23595397 3.09762373 18.32515875 -5.8335 12.49166
RM 0.97 3.3335777 1.692685946 5.02626365 13.21073397 -5.45962 7.751115
RM 0.88 5.34090721 -2.74710309 2.59380412 18.32515875 -5.8335 12.49166
RM 0.85 5.91038292 -4.01341879 1.89696413 14.84325702 -2.6674 12.17586
HS-250 days 1.45843281 25.83685728 27.2952901 2.325161193 7.175866 9.501027
HS-500 days 0.91497942 31.89846718 32.8134466 0.038363588 4.677471 4.715835
Pro 0.85,250 7.32187663 -0.82865219 6.49322444 4.028785336 -5.34796 -1.31917
Pro 0.90,500 8.14423681 -0.49729417 7.64694264 4.028785336 -5.34796 -1.31917
Pro 0.94,500 5.14625503 4.180930405 9.32718544 2.740077795 -5.66156 -2.92148
Pro 0.97,500 2.01641973 7.816874247 9.83329398 1.739698365 -5.92366 -4.18396
Pro 0.88,500 9.01706298 -0.15030638 8.86675661 4.028785336 -5.34796 -1.31917
Pro 0.85,500 9.94157363 -2.67653102 7.26504261 5.654019479 -4.96324 0.690778

7480 Afr.J.Bus. Manage.
Appendix B
Figure 1. Autocorrelation squared returns.
AC, PAC stands for Autocorrelation and Partial Autocorrelation respectively. The figure
shows that the results are all significant.
Figure 2. Graph of log of KSE-100 index return.

African Journal of Business Management Vol. 5(17), pp. 7481-7487, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.328
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Entrepreneurial motivation as a determinant of South
American firm consolidation
Agustin Álvarez-Herranz 1 * and Pilar Valencia-De Lara 2
1 Faculty of Economic and Business Sciences, Department of Econometric, University of Castilla-La Mancha,
Plza. de la Universidad, 1. 02071-Albacete, Spain.
2 Faculty of Social Sciences, Department of Business Administration, University of Castilla-La Mancha, Avda. de los
Alfares, 44. 16071-Cuenca, Spain.
Accepted 28 April, 2011
The aim of this study is to analyze the determinants of entrepreneurial consolidation in South America.
To analyze the entrepreunirship phenomenon in South America and the determinants of start-up
consolidation, this study uses logistic regressions and analyses of variance with a sample of 10,018
interviewees, gathered during 2002 to 2006, under the framework of the global entrepreneurship
monitor (GEM) project. Men, young people, and those with little fear of failure attempt start-ups more
often. Men, older entreprenuers, those starting a business to exploit opportunities, and those who
consider entrepreneurship a good career alternative also exhibit a higher probability of consolidating.
Finally, South American entreprenuers tend to invest in their ventures slightly more than the average
entrepreneurs in all GEM countries, though, financing is not a significant factor for explaining
consolidation.
Key words: Entrepreneur, entrepreneurial consolidation, individual motivations, opportinities, risk, GEM project
(global entrepreneurship monitor project).
INTRODUCTION
Vast literature, outlines individual motivations for starting
companies (Dana, 2000; Craig and Lindsay, 2001;
O’Connor and Ho, 2001; Gelderen et al., 2001; Lee and
Tsang, 2001; Boecker and Karichalit, 2002; Frederking,
2004; Baughn et al., 2006; Wagner, 2007; Hessels et al.,
2008; Alam and Taher, 2009; Alam et al., 2010; Álvarez
and Valencia, 2008; Álvarez et al., 2010). In particular,
research suggests that the motivations driving the startup
process relate closely to the psychological
characteristics of the individual founder, the sociodemographic
characteristic of the surrounding society, and
cultural settings and beliefs (Arenius and Minniti, 2005;
Uhlaner and Thurik, 2007; Hessels et al., 2008; Stovall,
2009). Yet, few studies approach this issue from a broad
perspective that integrates both individual and
*Corresponding author. E-mail: Agustin.Alvarez@uclm.es
environmental factors together. Moreover, research on
start-up consolidation is even more limited, although,
Harada (2003) studies the process for a sample of
Japanes companies. To our knowledge, no studies of this
type investigate South American countries.
Therefore, in this article, we conduct a twofold analysis:
We determine who starts up businesses, and then we
study who maintains those start-up firms for at least 3.5
years, which we take as our measure of consolidation.
Our approach thus covers a wide spectrum of independent
variables, at both individual and societal levels.
THEORETICAL DETERMINANTS OF
ENTREPRENEURSHIP AND CONSOLIDATION
Prior literature distinguishes two key motivations for
entrepreneurship: individual drivers and societal drivers.
The former pertain to personal principles and beliefs that

7482 Afr. J. Bus. Manage.
lead people to create and manage their own businesses.
The latter instead, encompass community codes, morals,
rules, and norms that encourage the creation of business
(Bosma et al., 2004; Sternberg and Wennekers, 2005;
Davidsson, 2006; Frank et al., 2007; Furkukawa et al.,
2007; Uhlaner and Thirik, 2007; Instituto de Empresa,
2007, 2008, 2009). Using a different classification, the
global entrepreneurship monitor (GEM) consortium,
distinguishes opportunity and necessity drivers, such that
entrepreneurs create businesses because they identify a
business opportunity to exploit, or because they need to
satisfy certain needs or make a living. However, GEM
reports, persistently indicate positive relationships
between the per capita income of a given country and the
relevance of opportunity. That is, low per capita income
countries tend to contain a significantly higher proportion
of businesses that start out of need. The opportunity
driver clearly depends on the environment, such that it
must offer an entrepreneur a chance to start a new
business.
Yet, opportunity also relates closely to the individual
entrepreneur’s characteristics. For example, some
authors indicate that to discover opportunities, entrepreneurs
must possess strong perceptive skills and common
sense, as well as accumulated relevant experience that
enables them to detect opportunities where other people
cannot (Kirzner, 1995; Venkataraman, 1997; Bell, 2001;
Ardichvili et al., 2003; De Carolis and Saparito, 2006;
Alsaaty, 2007; Wiklund et al., 2009). Craig and Lindsay
(2001) also note that personal characteristics such as
intuition determine who recognizes opportunities in the
market.
Furthermore, personal risk perceptions influence
entrepreneurship likelihood. Prior literature signals that
entrepreneurs are more willing to assume risks that are
nonentrepreneurs (Low and MacMillan, 1988; Timmons,
1989; Palich and Bagby, 1995; Sitkin and Weingart,
1995; Busenitz and Lau, 1996; Stewart and Roth, 2004;
Miner and Raju, 2004; Briggs, 2009; D'Amboise and
Muldowney, 1988), thus describe entrepreneurs as risk
takers who attempt to achieve fast growth and aboveaverage
profits. However, other authors (Palich and
Bagby, 1995) posit that entrepreneurs are not actually
more prone to risk but rather, they see the business
reality with “rose-colored glasees” and perceive present
and future conditions uniquely. For samples of
entrepreneurs and nonentrepreneurs, risk propensity
levels are similar for both groups, though entrepreneurs
tend to associate business situations with more positive
cognitive structures.
Overall, entrepreneurs must not only risk capital when
they start up a business, but also their reputations
(Schumpeter, 1963), and this concern may be more or
less tightly linked to their success, depending on the
country environment. We therefore investigate the role
that this factor plays for both entrepreneurship and
consolidation. We recognize that the degree to which the
entrepreneurship represents a well-recognized and
respected activity in society, can determine its extent.
Entrepreneurship recognition reflects cultural and social
values, inherited and developed over time (Dana, 2000;
Davidsson and Honing, 2003; Nikolaus and Christian,
2004; Instituto de Empresa, 2007, 2008, 2009; Bosma et
al., 2009; Alam and Taher, 2009; Alam et al., 2009; Sadi
and Al-Ghazali, 2010; Herranz et al., 2010). As Shapero
(1982) shows, a person’s motivation to start a venture
increases when the social legitimacy of such an action
increases; similarly, a negative perception of
entrepreneurship likely hinders firm creation. According to
economic theory, institutions dictate the incentive
structure of a society, such that political and economic
institutions underlie and determine economic
performance (North, 1993; Erogul and McCrohan, 2008;
Alam et al., 2010). In this sense, entrepreneurship and its
values might represent an institution, and when society
has a greater appreciation for this institution, it should
lead to higher incentives and levels of entrepreneurial
activity.
With regards to start-up consolidation, existing
literature is much more limited as are the data available
to perform analyses. Harada (2003) studies consolidation
determinants for a sample of Japanes companies and
reveals, using a probit model, that both the degree of the
entrepreneur’s previous relevant experience and the
initial firm size relate positively to the probability that the
firm lasts for at least 3.5 years. Harada also finds that
younger people and men are more likely to persist; these
variables reflect the individual level. In another somewhat
related study, Roure and Mandique (1986) identify
determinants of high-technology venture success, which
are, the pre-venture experience of the founders in the
sector, the length of time the founders knew one another
before the start-up, the completeness of teams in the
firm, and management devotion to product development.
To our knowledge, no studies attempt to explain both
entrepreneurship and consolidation from both individual
and societal aspects, especially in the context of South
American countries.
DATA DESCRIPTION AND METHODOLOGY
We use logistic regressions of data gathered from 10,018
respondents in telephone interviews, conducted during 2002 to
2006, under the auspices of the GEM project in Argentina. We also
use analyses of variance (ANOVA) to determine relevant relationships
and thereby explicate entrepreneurship phenomena. In our
logit model, we relate the dependant variable Yi to the independent
X1, …, Xp using the following equation:
Yi = (1 / ( 1 + e -Z )) + εi, (1)
where Yi is a dichotomous variable (0 or 1). From Xi1, …, Xip (i = 1,
…, n), which represents a sample of n observations for the
independent variables that reflect the two possible values of Y, we
obtain a linear combination of independent variables. With this

Table 1. Results of the multivariant logit regression for the variable tea.
Álvarez-Herranz and Lara 7483
Variable
Logistic regression tea
Coef. Std. Err.
z P>|z| [95% Conf. Interval]
Male 0.53 0.10 5.63 0.00 0.35 0.72
Age -0.23 0.03 -7.65 0.00 -0.29 -0.17
Fearfail -0.84 0.12 -7.20 0.00 -1.07 -0.61
_cons -1.12 0.12 -9.74 0.00 -1.35 -0.90
Number of obs = 3759
LR χ 2 (3) = 159.58 Prob > χ 2 = 0.0000
combination, we compute the probabilities that an individual
belongs to either group. For example, the probability that an
individual belongs to group p is given by:
p = e Z / ( 1 + e Z ), (2)
or equivalently,
p = 1 / ( 1 + e -Z ). (3)
For the linear combination,
Z = β0 + β1X1 + … + βpXp, (4)
where β0, β1, …, βp represent unknown parameters to be estimated.
In turn, the probability of the i-th individual belonging to group p is
given by:
pi = 1 / ( 1 + e -(β0 + β1X1 + … + βpXp) ). (5)
Because we are interested in analyzing both indidual and societal
factors that determine entrepreneurship and consolidation, our
variables span both individual and societal aspects and are mostly
categorical, as listed here:
i. Tea: A binary variable equal to 1 if the individual has commited
resources to starting up a business or already has a business
running, and 0 otherwise.
ii. Teaopp: A binary variable equal to 1 if the start-up originated
due to recognition of an opportunity, and 0 otherwise.
iii. Teanec: A binary variable equal to 1 if the start-up originated out
of necessity, and 0 otherwise.
iv. Estbbuso: A binary variable equal to 1 if the business is
consolidated (i.e., business owner paid wages for more than 42
months), and 0 otherwise.
v. Male: A binary variable equal to 1 for men and 0 for women.
vi. Age: Six intervals: 1 = 18 to 24 years of age, 2 = 25 to 34, 3 =
35 to 44, 4 = 45 to 54, 5 = 55 to 64, and 6 = 65 to 98 years of age.
vii. Fearfail: A binary variable equal to 1 if the individual senses a
fear of failing when considering starting up a business, and 0
otherwise.
viii. Nbgoodc: A binary variable equal to 1 if the individual
considers entrepreneurship a good career alternative, and 0
otherwise.
ix. Nbstatus: A binary variable equal to 1 if the individual believes
that entrepreneurship provides status, and 0 otherwise.
x. Nbmedia: A binary variable equal to 1 if the individual believes
that the media pays attention to entrepreneurship activity, and 0
otherwise. It is a proxy for societal appreciation of entrepreneurship.
xi. Sumontot: Total investment required to start up a business.
xii. Sumonown: Amount of investment provided by the
entrepreneur him- or herself.
xiii. Owninv_totinv: Ratio between sumonown and sumontot.
We require a further note on owninv_totinv. To analyze the impact
of financing on consolidation phenomena, we construct this variable
to reflect the amount of the total required that has been personally
financed by the entrepreneur. It thus provides a proxy for
commitment to the venture, and this commitment should influence
success or failure. We construct it in two steps: exclude any missing
values of sumontot and sumonown; divide sumonown into
sumontot.
RESULTS
Drivers of business start up
To determine what drives a person to start up a business,
we distinguish two groups, according to whether the
respondents have started up a business or not. Among
those who actually started a business, we exclude those
who have initiated consolidation. That is, we use two
variables to select this subsample:
Group 3: did start a business (tea = 1), did not
consolidate (estbbuso = 0).
Group 4: did not start a business (tea = 0), did not
consolidate (estbbuso = 0).
Because those who have not started a business do not
answer questions regarding their motivations, we cannot
use the necessity or opportunity identification variables to
compare these groups. Instead, our contrast focuses on;
male, age, fearfail, nbgoodc, nbstatus, and nbmedia.
Furthermore, most of the independant variables are
qualitative, so we apply logistic regressions to determine
our model. After running multivariate logit regressions on
tea, we identify three relevant variables that explain this
event, as shown in Table 1: male, age, and fearfail.
The coefficient signs indicate that men are more prone
to starting up a business, and younger people tend to be
more active in entrepreneurship. Finally, those who start
up new businesses tend to feel less fear of failing. The
result of the χ 2 test also rejects the null hypothesis that

7484 Afr. J. Bus. Manage.
Figure 1. Entrepreneurship as a function of gender.
Figure 2. Entrepreneurship as a function of age.
the model cannot explain entrepreneurship phenomena.
We used one-way ANOVA to graph the effects of
gender, age, and fear of failure on entrepreneurship,
according to the proportion of people in these groups that
start businesses. Figure 1 reveals that roughly 9% of
women and 17% of men start new ventures. Figure 2
further reveals that the highest entrepreneurship activity
corresponds to people between the ages of 25 and 34
years. Finally, with Figure 3, we show that on average,
18% of people who express no fear of failure launch

Figure 3. Entrepreneurship as a function of fear of failure.
businesses, but only 9% of those who express such fears
do so.
Factors determining consolidation
We also investigate relevant features that characterize
those entrepreneurs who reach a consolidation stage;
therefore, we created subsamples of entrepreneurs,
according to whether they have consolidated or not:
Group 5: did start a business (tea = 1), did consolidate
(estbbuso = 1).
Group 6: did start a business (tea = 1), did not
consolidate (estbbuso = 0). 1
Our strategy is to contrast both groups, though
consolidating a business is often just a matter of time,
because we define consolidation as having run a
business for at least 3.5 years. Therefore, some
entrepreneurs in Group 6, will likely consolidate their
ventures, with enough time, and the contrast between the
groups is partially diluted, which makes it more difficult to
find important differences.
We run logit regressions with the response variable;
estbbuso and the independent variables; male, age,
fearfail, nbgoodc, nbstatus, nbmedia, and owninv_totinv,
as we detail in Table 2. Gender, age, a belief that
entrepreneurship is a good career option, and opportunity
1 Group 6 thus is equal to Group 3.
Álvarez-Herranz and Lara 7485
are the most relevant factors for consolidation. Men and
older entrepreneurs enjoy higher chances of success and
consolidation, as do those who consider entrepreneurship
a good carrer alternative and those who start a
business because they see an opportunity.
In the process of creating the model, we recognized
consistently negative values of the coefficient for
owninv_totinv. Although it appears only marginally
significant, according to its p-value in the different
intermediate models, its sign implies that greater debt
taken on by the entrepreneur increases the chances of
success in the venture. It appears that people’s behavior
is conditioned by the methods they use to finance their
businesses, and when an entrepreneur owes more to
third parties, the chances of consolidation in the venture
increase.
Finally, we computed standard descriptive statistics to
compare financing in Argentina with values observed
across the GEM universe. In GEM countries overall,
entreprenuers finance an average of 62% of the total
investment in the start-up; however, in Argentina, they
finance 68.4%, or slightly more than average, with a
standard deviation of 32%.
DISCUSSION
We analyze entrepreneurship in Argentina, including its
determinants and the determinants of start-up success.
Our study, which includes responses from 10,018 people
who participated in the GEM project during 2002 to 2006,

7486 Afr. J. Bus. Manage.
Table 2. Results of the multivariant logit regression for the variable ESTBBUSO.
Variable
Logistic regression estbbuso
Coef. Std. Err. z
P>|z| [95% Conf. Interval]
Male 0.78 0.44 1.78 0.08 -0.08 1.65
Age 0.46 0.14 3.37 0.00 0.19 0.73
Nbgoodc 1.32 0.55 2.42 0.02 0.25 2.39
Teaopp 1.42 0.55 2.58 0.01 0.34 2.50
_cons -6.82 0.93 -7.35 0.00 -8.64 -5.00
Number of obs = 549
LR χ 2 (4) = 31.12 Prob > χ 2 = 0.0000
relies on both logistic regressions and ANOVAs. In turn,
we find that people who fear failure less are more prone
to starting up a business, consistent with most prior
literature. Furthermore, men and young people make up
the bulk of entrepreneurs.
Regarding consolidation as a measure of success, the
results are robust and indicate that men are also more
prone to consolidate, as are older entrepreneurs. This
finding seems consistent with existing research that
indicates experience makes a difference in success rates
- if we assume that experience and age generally
correlate.
Moreover, people who start up their business because
they saw an opportunity enjoy higher consolidation
probabilities, as do those who start up a venture and
consider entrepreneurship a good career option.
Finally, we find that Argentinean entreprenuers tend to
invest in their ventures slightly more than do average
entrepreneurs in other GEM countries; however, the
financing factor is not significant as an explanation for
consolidation.
Moreover, the main contributions to the field of
entrepreneurship research are:
1) The study sample: since most studies of
entrepreneurship work with very small samples, our study
sample is 10.018 entrepreneurs.
2) The study phase: we think this is another contribution
since this paper aims to analyze the phase of
consolidation, unlike most studies of entrepreneurship, by
analyzing together the new business and consolidated.
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African Journal of Business Management Vol. 5(17), pp. 7488-7498, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.402
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
An empirical study on the causes of business failure in
Iranian context
Zahra Arasti
Faculty of Entrepreneurship, University of Tehran, Tehran, Iran. Email: arasti@ut.ac.ir. Tel: +98-2161119227.
Accepted 3 August, 2011
Business discontinuation is an important feature of dynamic economies, and entries and exits of
businesses are closely connected. A majority of entrepreneurship literature have focused on
successful ventures, therefore, little is known about why ventures fail. Previous studies showed
significant inter-country differences in SME failure rates, while most researches on business failure
have been conducted in developed countries, and there is limited knowledge on the causes of business
failure in other countries with different economical, political, social, and cultural conditions. As
entrepreneurship is a newly developed phenomenon in Iran, considering the economical, social, and
cultural conditions of the country, analysis of the entrepreneurship process, and the causes of failure
and success, would provide critical information for individual entrepreneurs, venture financiers, and
government policy-makers. The purpose of the present study is to identify the main causes of business
failure based on an empirical study in Iran. This empirical study on the sample of failed businessowners/managers
pointed out that the main causes of business failure are due to lack of good
management, no support from banks and financial institutions, inadequate economic sphere, and
insufficient governmental policies. In addition, this study indicates differences in some causes of
business failure influenced by gender and business sector.
Key words: Entrepreneurship, business, causes of business failure, Iran.
INTRODUCTION
New firms create new jobs, open up opportunities for
upward social mobility, foster economic flexibility, and
contribute to competition and economic efficiency (Liao et
al., 2009). Although the failure of an individual SME will
never attract the media’s attention; the consequences of
the failure of smaller companies are certainly a serious
matter for directly involved stakeholders (FEE, 2004).
Business discontinuation is an important feature of
dynamic economies, and entries and exits of businesses
are closely linked (Bosma et al., 2009). It is impossible to
talk wisely about a theory of entrepreneurship without first
acknowledging the pivotal role of entrepreneurial failure.
Most entrepreneurship literature focuses on successful
ventures. As a result, little is known about why ventures
fail. Even less is known about how they fail. Our understanding
of entrepreneurship will never be completed
until we have a clear understanding of what causes discontinuation.
Developing a deeper understanding of new
venture failures should provide critical information for
several key stakeholders in a new venture - individual
entrepreneurs, venture financiers, and government
policymakers (Liao et al., 2009).
There is a limited but growing body of knowledge on
the topic of failure, on which researchers can base their
investigations, especially in the small business domain.
The research articles are, however, scattered across
business, management, financial, psychology, entrepreneurial
and many other journals, and no proof could be
found that these investigations have ever been
comprehensively reviewed. There is no specific body of
science to which failure exclusively belongs (Pretorius,
2009).
The health of a firm in a highly competitive business
environment is dependent upon its capability of achieving
profit and financial solvency.
When a firm loses competence to maintain profit and
financial solvency, it becomes unhealthy, or deteriorates
to the point where it is in danger of suffering business
failure. Business failure is not only common with new
start-ups, but also with listed companies, and can easily

happen to firms of any and all sizes (Wu, 2010).
The annual report of Global Entrepreneurship Monitor
(Bosma et al., 2009) shows that there is significant intercountry
differences in SME failure rates. Discontinuance
rates are relatively high in factor-driven economies (in
Uganda for example, the reported rate is as much as
24%) and relatively low in innovation-driven economies.
Failure rates are somewhat higher in efficiency-driven
countries as a proportion of discontinuation, reflecting the
increasing importance of scale and efficiency in business
in these countries. Failure rates, both in absolute terms
and in proportion to all discontinuations, are lowest in
innovation-driven economies, because entrepreneurs
have better skills and environments are more favorable.
In Iran, the business discontinuation rate (6%) is almost
higher than average of efficiency-driven economies
(4.9%). Denmark and Italy in innovation-driven economies
have the lowest business discontinuation rate
(1.1%) (Bosma et al., 2009).
On the other hand, most of the researches in business
failure have been conducted in developed countries, and
there is limited knowledge on the causes of business
failure in other countries with economical, political, social,
and cultural differences. In order to know more about the
business environment of Iran, we address the annual
report of World Bank in 2011.Doing Business 2011 is an
annual report investigating the regulations that enhance
business activity and those that constrain it. Doing
Business presents quantitative indicators on business
regulations and the protection of property rights that can
be compared across 183 economies over time. Regulations
affecting 11 areas of the life of a business are
covered: starting a business, dealing with construction
permits, registering property, obtaining credit, protecting
investors, paying taxes, trading across borders, enforcing
contracts, closing a business, getting electricity and
employing workers. Iran with 72.9 million population and
GNI per capita (US$ 4.530), is 129 from 183 countries in
the ranking on the ease of doing business.
The ranking of starting a business in Iran is 42 while in
obtaining credit is 89. We must mention that the Islamic
Republic of Iran eased business start-up in 2011 by
installing a web portal allowing entrepreneurs to search
for and reserve a unique company name, the establishment
of a new private credit bureau improved access to
credit information. The Islamic Republic of Iran made
enforcing contracts easier and faster by introducing
electronic filing of some documents, text message
notification and an electronic case management system
(World Bank, 2011).
These data show that the business environment in Iran
is not encouraging for entrepreneurs and makes a lot of
barriers to them. Therefore, a study on business failure
and the factors that cause failure in Iranian context could
help policy makers to identify the most important challenges
of business that lead to business discontinuance.
This paper aims to discuss the causes of business
Arasti 7489
failure in a different context of a developing country.
LITERATURE REVIEW
It has been widely recognized that business growth and
survival depend both on external and internal factors.
While most of the challenges which a business will face
may be foreseeable, some will be completely unpredictable.
However, if a business is to succeed, management
must be mindful to all matters which are likely to have a
material impact on its viability, and must then demonstrate
skills both in exploiting opportunities and mitigating
threats (FEE, 2004). There is a vast literature review on
business failure, mostly on the prediction of failure by
using financial models, but in this paper, we focus on the
causes of business failure.
Definition
The Oxford English Dictionary defines the term “failure”
as “to become deficient, to be inadequate”. In general,
many different terminologies are related to business
failure, such as firm closures, entrepreneurial exit,
dissolution, discontinuance, insolvency, organizational
mortality and bankruptcy. Normally, entrepreneurial
failure is referred to as the cease of an operation for
financial reasons. Since we examined nascent entrepreneurs
during the firm’s gestation process, one type of
entrepreneurial failure is the discontinuance of venturing
efforts by entrepreneurs (Liao et al., 2009), but business
failure can be defined as wanting or needing to sell or
liquidate, to avoid losses or to pay off creditors, or the
general inability to make a profitable go of the business
(Gaskill et al., 1993).
Pretorius, at the end of his review of business failure
definition, proposed a universal definition for the failure
phenomenon - a venture fails when it involuntarily
becomes unable to attract new debt or equity funding to
reverse decline; consequently, it cannot continue to
operate under the current ownership and management.
Failure is the endpoint at discontinuance (bankruptcy)
and when it is reached, operations cease and judicial
proceedings take effect (Pretorius, 2009).
There are problems relating to the use of various terms
involved in research in business failure. In particular,
definitions of business “disappearance”, “closure”, “exit”,
and “failure” are confused and often overlapping. “Disappearance”
of a business may occur because the
business failed, or because the business was acquired by
or merged into another company, or because the owners
voluntarily closed it (Cardozo and Borchert, 2004).
“Closure” can be categorized as the inability of a
business to survive and thus represents a discontinuation
of a business. “Exit” refers to several different meanings;
it can refer to the exit of a business from trading in a

7490 Afr. J. Bus. Manage.
specific market or from producing a particular product. It
also refers to the end of the owner’s participation in the
business, as in the search for “exit routes” by entrepreneurs
wishing to sell or exit from a business (Stokes and
Blackburn, 2002). “Failure” is generally regarded as the
discontinuance of the business due to the lack of
adequate financial resources (Everet and Watson, 1998),
cessation of operations with loss to creditors (Cardozo
and Borchert, 2004), cessation of operations, and exit
from business population because it is no longer a viable
concern (Bickerdyke et al., 2000).
Causes of business failure
The causes of business failure are many and varied, and
may stem both from the external environment as well as
from factors internal to the business. Internal causes of
business failure may in many cases be capable of being
foreseen in advance, while on the other hand some
external causes are not so predictable. In most cases, a
complex mixture of causes contribute to business failure;
it is very rare for one single factor to be involved (FEE,
2004).
Earliest empirical studies on business failure examined
the role of various owners and firm characteristics to
explain business failures. The numerous characteristics
shared by failed firms, are directly related to personal
decision-based characteristics of the owner (lack of
insight, inflexibility, emphasis on technical skills, etc.),
managerial deficiencies (lack of management skills and
appropriate managerial training, etc.) and financial shortcomings
(no accounting background, cash flow analysis,
financial records, etc.). Many aspects of poor management
are reported to be connected to several related
issues, such as poor financial circumstances, inadequate
accounting records, limited access to necessary
information, and lack of good managerial advice (Gaskill
et al., 1993). Some studies focused more on the managerial
causes of failure and listed some 25 causes and
categorized them simply as poor management, and
concluded that poor management combined with the
personality traits of the owner-manager, and external
factors cause business failure (Berryman, 1983). A
business failure may happen as a result of poor management
skills, insufficient marketing, and lack of ability to
compete with other similar businesses. It can also be the
result of a domino effect caused by business failures of
suppliers or customers (Wu, 2010).
In the annual report of GEM, financial problems were
cited as the reason for quitting the business by no more
than 55% of all respondents; it was cited more often by
respondents in the factor- and efficiency-driven economies
(just over 50%) than innovation-driven countries
(just over 40%) (Bosman et al., 2009).
The effect of the environment depends upon the time
period, geographic area, and market sector in which the
firm operates (Burns, 2001). Government and
government-related policies is also an important factor
affecting business failures, and is discussed in some
studies. The scholars found that failure rates increased
due to the heavy burden of taxation and regulation, while
the growth in money supply (higher growth decreased the
failure rate) and the volume of bank lending (higher
volume of bank lending reduced the rate of business
failures) are significant factors (Gaskill et al., 1993;
Burns, 2001; Oparanma et al., 2010). They discussed the
negative internal and external environmental factors
including pressure from competitors or new entrants,
poor improvement in modern technology and poor sales,
the outbreak of pests, and farm diseases etc (Oparanma
et al. 2010).
A conceptual failure model was presented by Ooghe
and Waeyaert in 2004 expounding the causes of failure
and mutual relations between the general and immediate
environment of the company as external causes, and the
company’s management and policy as internal causes of
failure (Ooghe and De Prijcker, 2008). In this model, the
causes of failure can be grouped into five interactive
aspects. These include general environment (economics,
technology, foreign countries, politics, and social factors),
immediate environment (customers, suppliers, competitors,
banks and credit institutions, stockholders, and
misadventure), management/entrepreneur characteristics
(motivation, qualities, skills, and personal characteristics),
corporate policy (strategy and investments, commercial,
operational, personnel, finance and administration, corporate
governance), and company characteristics (size,
maturity, industry, and flexibility) (Ooghe and Waeyaert,
2004). Liao (2004) also mentioned the effects of four
groups of factors-individual characteristics of the founder,
resources, structural characteristics and strategies of the
firm, and environmental conditions in which a firm
operates on business failure.
The European Federation of Accountants has identified
the following internal and external causes of business
failure. Accordingly, internal causes include poor
management, deficit in accounting, poor cash flow
management, inappropriate sources of finance, dependency
on customers or suppliers, impending bad debt,
fraud/collusion and external causes of business failure
are economy, catastrophic unpredictable events,
governmental measures and international developments,
environmental protection and other regulatory requirements,
and the bankruptcy of main customer or supplier
(FEE, 2004).
Inter-country difference
Some inter-country studies show that there are significant
inter-country differences in SME failure rates and causes
of business failure. In their inter-country study of business
failure in Malaysia and Australia, Ahmad and Seet (2009)
found that some reasons for business failure were given
more emphasis in one country than the other. Australian

participants attributed their failure to reasons such as the
inability to manage a large number of employees, the
inability to manage the fast growing firm, and the inability
to administer a large firm. This may perhaps provide an
insight into why the participants preferred to stay small in
business. Malaysian participants, by contrast, highlighted
softer issues such as the lack of personal contacts and
the failure to maintain close personal relationships with
customers, providing evidence of the importance of
maintaining good personal relationships with others.
According to the annual report of GEM, evidence show
that business discontinuance rates are relatively high in
factor-driven economies (in Angola, for example, the
reported rate is as much as 23%) and relatively low in
innovation-driven economies. Among high-income
countries, Norway, United States of America, Republic of
Korea, Iceland and Ireland have the highest rates of
business discontinuation. The business not being
profitable on its own was the most reported financial problem.
Problems with raising finances were considerably
lower in innovation-driven countries where the “Entrepreneurial
Framework Condition” and “Entrepreneurial
Finance” are generally more developed. “The opportunity
to sell” and in particular “retirement” were mentioned
more often in innovation-driven countries as the most
important reason to discontinue the business. Personal
reasons caused around 20 to 25% of all discontinuations.
Such reasons could include sickness, family, death of a
business partner, divorce, the need to finance an event
such as a wedding, through sale of business assets
rather than the business itself, or simply boredom.
They were more prevalent in factor- and efficiencydriven
countries (Bosma et al., 2009).
Research questions
As indicated in the literature, several factors cause
business failure; some of them are internal and could be
controlled by the entrepreneur, while others are external
and rather unpredictable. There are factors on which
more emphasis has been given in prior studies. Prior
studies focused only on some internal or external factors
without a general view. This is an investigation on
different internal and external causes of business failure
in a developing country with different socio-cultural,
economical, and political context. The following are the
research questions:
1. What are the characteristics of failed business
owners/managers and their businesses?
2. What are the personality characteristics of failed
business owners/managers?
3. What are the main causes of business failure in Iranian
context?
4. How does gender of a business owner/manager
influence the causes of business failure?
Arasti 7491
5. How does the business sector influence the causes of
business failure?
METHODOLOGY
Some researchers have expressed difficulty in studying failed ventures
(Liao, 2004; Bruno et al., 1987). They argue that it is difficult
to locate ventures that failed because of poor performance, and
homogenous samples are hard to find. Entrepreneurs are reticent
about failure and they are more likely to attribute failure to external
causes than to internal ones. As it is extremely difficult to obtain
feedback from entrepreneurs who have experienced business
failure, this approach is hardly utilized by researchers. In this
research, we used this approach to obtain the point of view of failed
business-owners/managers concerning causes of business failure.
This survey is implemented based on a face-to-face questionnaire.
In the first part, the failed business-owners/managers were
questioned about their background, experience, education, and
family. Then a personal characteristic test examined six entrepreneurial
characteristics including tolerance of ambiguity, need for
achievement, risk taking, creativity, locus of control, and independence.
The questionnaire on the personal characteristics was
obtained from the Entrepreneurship Development Institute of India
and had been used many times in Iranian context (Ahmadpour and
Moghimi, 2006). The participants finally reported on their causes of
business failure. The questionnaire on causes of business failure
was obtained from a previous study on the causes of business failure
in Iranian context (Gholami, 2008) in which both authors were
involved. This questionnaire was developed based on a literature
review and interview with 13 Iranian entrepreneurs whose
businesses had failed. The validity of the questionnaire was
significantly revised by 7 experts in entrepreneurship. Reliability or
internal consistency of the items within the structure of this study
was assessed by indication of Cronbach’s alpha. Each item in the
questionnaire was accompanied by a Likert-type scale, allowing
perceived indication of the extent to which the item contributed to
the business failure. The Likert-type scale ranged from 1 (to very
little extent) to 5 (to great extent). Responses to this measure were
based on perceptions of ex-business owners/managers.
Sample
Sample group is the business owner/manager who has
experienced business failure and stops his/her business activities
voluntary or involuntary. One of the greatest barriers to study about
business failure is to identify ex-owners/managers who failed in
their business. In this study, we developed our own sampling frame
that sought to be as representative as possible of the range of
business failure and exit types, rather than relying on one source,
such as official receivers’ data that reflects only a limited number of
types of closure. This was derived with the help of entrepreneurship
masters students in our faculty who are dispersed all over the
country. We did not put the limitation in the business sector, failure
phase and geographical location of business, to study more cases
of failed businesses. In total, a database of 150 ex-owners/
managers was created. The questionnaire was sent to a random
sample of 80 ex-owners/managers. 51 complete and valid questionnaires
were obtained and analyzed using SPSS software.
Variables
The research variables are classified in three categories:
i. Characteristics of failed business-owner/ manager (age in start

7492 Afr. J. Bus. Manage.
up, age in failure’s time, gender, level of education, marital status,
previous experience in the sector, previous entrepreneurial
experience, and personal characteristics, tolerance of ambiguity,
need for achievement, risk taking, creativity, internal locus of control
and independence);
ii. Characteristics of failed businesses (business sector, business
age, business life cycle);
iii. Causes of business failures (lack of financial support from banks
and financial institutions, inaccurate evaluation of project, unclear
determination of business sector, inconsideration of market issues,
problems in product or service supply, lack of related experience,
expertise and good work relationships, management deficiency,
cheating and fraud, substituted products or services, government
policies, inconsideration of legal issues, inadequate financial
circumstances, problems of partnership and teamwork, lack of
interest and dissatisfaction in work or at the work place, and
negative influences by the family).
Validity and reliability
Content validity of the questionnaire on the causes of business
failure was estimated by submitting the questionnaire to several
experts in entrepreneurship, all of whom approved the content of
the questionnaire. To test the reliability, the internal consistency of
the questionnaire was assessed by Cronbach's alpha coefficient
that was 0.81 for the questionnaire on the causes of business
failure, and alpha equal to or greater than 0.70 was considered
satisfactory.
RESULTS
Results of this research contain four sub-sections: first, a
description of sample, then, the results of Friedman’s test
on causes of business failure, and finally, the role of gender
and business sectors on the causes of business
failure were further presented.
Sample description
Most of the failed business owners/managers were aged
between 25 and 45 years old (Mean = 32.9, SD = 6.43).
84.3% of them were men. They were well educated and
most of them were married. 64.4% had experience in the
related sector and 35.3% were experienced in business.
The number of businesses in the manufacturing and
services sector were equal (47%), while 6% were in the
agriculture sector. 76.1% of businesses failed within three
years and 55.1% failed in the phase of establishment
(Table 1).
Personal characteristics of failed business
owners/managers
The results of the chi-square test on personal characteristics
of failed business owners/managers show
significant difference in the level of some personal
characteristics. This difference is significant for "tolerance
of ambiguity", "need for achievement", "creativity", and
"internal locus of control". These results point out that
failed business owners/managers have low level of
tolerance of ambiguity, while they have high level of
creativity and internal locus of control and moderate level
of need for achievement (Table 2).
Main causes of business failure
Given the fact that our data regarding the causes of
business failure is in the Likert scale, we used non-parametric
Friedman analysis of variances to identify the main
causes of business failure. The results show significant
variable differences in mean rank (2, N = 51) = 105.180,
p

Table 1. Descriptive statistics of Iranian failed business owners/managers (n = 51).
Variable
Characteristics of failed business-owner manager
Percentage
Age in failure time
Under 25 years old
Between 25 and 45 years old
9.8
84.3
More than 45 years old 5.9
Gender
Level of education
male 84.3
female 15.7
Diploma and under diploma 27.5
B.Sc. 51
M.Sc. 17.6
Ph.D. 3.9
Marital status Married 81.6
Previous experience in related sector 64.4
Previous entrepreneurial experience 35.3
Characteristics of failed business
Business sector
Business age
Business life cycle
Table 2. Personal characteristics of failed business owners/managers.
Manufacturing 47
Service 47
Agriculture 6
Under 3 years 76.1
Between 3 and 5 years 10.9
More than 5 years 13
Establishment 55.1
Growth 44.9
Personal characteristics High Moderate Low Chi-square Sig
Tolerance of ambiguity 15 8 27 11.08 0.004
Need for achievement 15 26 9 8.92 0.012
Risk taking 16 18 16 0.16 0.923
Creativity 28 7 15 13.48 0.001
Internal locus of control 40 5 5 49 0
Independence 15 13 22 2.68 0.262
failure in Iranian context. Findings show that most failed
business owners/managers are in the middle age and
failed in the phase of establishment. Most of their
businesses do not survive more than three years. The
results on their personal characteristics show the significant
difference in the level of some personal
characteristics.
The results of this research indicate that four main
causes of business failure in Iranian context are
Arasti 7493
management deficiency, lack of financial support from
banks and financial institutions, inadequate economic
sphere and insufficient government policies. These
results show the effect of external factors on the success
and failure of businesses in Iranian context. In other
words, the entrepreneurship environment in Iran is not
encouraging. The World Bank report on doing business
confirms this result. Despite of efforts that the Islamic
Republic of Iran makes to ease business start-up, Iran is

7494 Afr. J. Bus. Manage.
Table 3. Main causes of business failure.
Causes of business failure Mean Mean rank
management deficiency 3.33 10.59
lack of financial support from banks and financial institutions 3.29 10.09
inadequate economic sphere 3.24 10.09
insufficient government policies 3.00 9.48
inconsideration of market issues 2.92 9.18
problems in product or service supply 2.65 8.45
lack of interest and dissatisfaction in work or at the work place 2.63 8.21
inaccurate evaluation of project 2.47 7.72
lack of related experience, expertise and good work relationships 2.43 7.43
problems of partnership and team work 2.39 7.19
unclear determination of business sector 2.27 7.16
substituted product/service 2.18 6.53
negative influences by the family 2.00 6.42
inconsideration of legal issues 1.92 5.91
cheating and fraud 1.84 5.57
Table 4. Difference in the causes of business failure by gender.
Causes of business failure Gender Mean Mean difference t Sig
Lack of financial support from banks and
financial institutions
M
F
3.09
4.37
1.41108
0.91613
-2.464 0.017
Inaccurate evaluation of project
Unclear determination of business sector
Inconsideration of market issues
Problems in product or service supply
Lack of related experience, expertise and
good work relationships
Management deficiency
Cheating and fraud
Substituted product or service
Insufficient government policies
M 2.44 1.25930
F 2.62 1.40789
M 2.25 1.31100
F 2.37 1.18773
M 2.93 1.40400
F 2.87 1.55265
M 2.74 1.43250
F 2.12 1.12599
M 2.56 1.41929
F 1.75 1.38873
M 3.39 1.29357
F 3.00 1.41421
M 1.93 1.36966
F 1.37 1.06066
M 2.30 1.48861
F 1.50 0.92582
M 3.05 1.46309
F 1.37 1.28174
-0.371 0.712
-0.239 0.812
0.101 0.920
1.155 0.254
1.483 0.144
0.783 0.437
1.084 0.284
1.465 0.149
0.535 0.595

Table 4 Contd.
Inconsideration of legal issues
Inadequate economic sphere
Problems of partnership and team work
Lack of interest and dissatisfaction in work
or work place
Negative influences by the family
129 from 183 countries in the ranking on the ease of
doing business. The ranking of starting a business in Iran
is 42 while in getting credit is 89 (World Bank, 2011).
Other studies on the causes of business failure mention
some internal and external factors that cause business
failure. The results of this study confirm some prior
researchers, concerning management deficiency
(Berryman, 1983; Gaskill et al., 1993; FEE, 2004; Ooghe
and De Prijcker, 2008; Pretorius, 2009; Wu, 2010), lack
of financial resources (Gaskill et al., 1993; Everet and
Watson, 1998; Ooghe and De Prijcker, 2008; Bosma et
al., 2009; Liao et al., 2009; Wu, 2010), inadequate
economic sphere (Berryman, 1983; Burns, 2001; Liao,
2004; Ooghe and De Prijcker, 2008), and government
policies (FEE, 2004; Oparanma et al., 2010), while the
current study indicates other causes of business failure
that marginally developed in prior studies like
inconsideration of market issues, problems in product or
service supply, lack of interest and dissatisfaction in work
or at the work place, inaccurate evaluation of a project,
lack of related experience, expertise and good work
relationships, problems of partnership and team work,
unclear determination of the business sector, substituted
products or services, negative influences by the family,
inconsideration of legal issues, and cheating or fraud.
Concerning the gender of business owners/managers,
findings of this study point out the difference on the
causes of business failure by gender, though "lack of
financial support from banks and financial institutions"
influence women more than men, while men are more
susceptible to "problems in partnerships and team work".
The studies on women's entrepreneurship show that
access to financial resources is the most important
challenge of women entrepreneurs, so it is no surprise
when this factor influences more women than men. About
the problem of partnership, results could be discussed in
relation to gender difference in business management,
though insufficient study requires more research in this
M 2.00 1.19523
F 1.50 1.06904
M 3.25 1.51332
F 3.12 1.64208
M 2.60 1.59074
F 1.25 .46291
M 2.60 1.31184
F 2.75 1.48805
M 2.07 1.20308
F 1.62 1.40789
1.102 0.276
0.222 0.825
4.629 0.000
-0.282 0.779
0.936 0.354
Arasti 7495
arena.
This research also points out that the causes of
business failure differ by business sector so much that
"inaccurate evaluation of the project" is more severe for
businesses in agriculture in comparison to manufacturing.
On the other hand, "lack of interest and dissatisfaction in
work or at the work place" is more important for
manufacturing businesses in comparison to businesses
in the service sector.
CONCLUSION
Most entrepreneurship studies have been conducted in
western countries and focused on successful ventures.
As indicated in several studies, a deep understanding of
new venture failures in a different context would provide
critical information for individual entrepreneurs, venture
financiers, and government policymakers. This first study
on the causes of business failure in Iranian context
focused on the influence of several internal as well as
external factors by using a hard approach to obtain
feedback from entrepreneurs who have experienced
business failure.
Contrary to the belief that failed entrepreneurs will
attribute their failure to external factors, the respondents
in this research ranked their management deficiency as
the main cause of business failure and it may be due to
their high internal locus of control. While the external
factors such as lack of financial support, inadequate
economic sphere and insufficient government policies
were also mentioned as the main causes of business
failure. These results could help policymakers to identify
the problematic areas of entrepreneurship and indicate
need for a support system in financial management,
competition and growth strategies, and most importantly
entrepreneurial skills training programs.
This study is one of the limited studies of business

7496 Afr. J. Bus. Manage.
Table 5. Difference in the causes of business failure by business sector.
Causes of business failure Business sector Mean Mean difference F Sig
Lack of financial support from banks and
financial institutions
Manufacturing
Service
Agriculture
3.75
2.96
2.33
1.19
1.57
0.58
2.786 0.072
Inaccurate evaluation of project
Unclear determination of business sector
Inconsideration of market issues
Problems in product or service supply
Lack of related experience, expertise and
good work relationships
Management deficiency
Cheating and fraud
Substituted product or service
Insufficient government policies
Inconsideration of legal issues
Inadequate economic sphere
Problems of partnership and team work
Manufacturing 2.29 1.23
Services 2.42 1.21
Agriculture 4.33 0.58
Manufacturing 2.38 1.31
Services 2.17 1.27
Agriculture 2.33 1.53
Manufacturing 3.13 1.62
Services 2.79 1.18
Agriculture 2.33 1.53
Manufacturing 2.63 1.50
Services 2.75 1.36
Agriculture 2.00 1.00
Manufacturing 2.83 1.61
Services 2.08 1.14
Agriculture 2.00 1.73
Manufacturing 3.46 1.25
Services 3.21 1.38
Agriculture 3.33 1.53
Manufacturing 2.00 1.47
Services 1.75 1.26
Agriculture 1.33 0.58
Manufacturing 2.46 1.61
Services 2.00 1.29
Agriculture 1.33 0.58
Manufacturing 2.79 1.64
Services 3.17 1.13
Agriculture 3.33 2.08
Manufacturing 1.79 1.06
Services 2.08 1.32
Agriculture 1.67 1.15
Manufacturing 2.88 1.62
Services 3.54 1.28
Agriculture 3.67 2.31
Manufacturing 2.25 1.51
Services 2.42 1.56
Agriculture 3.33 2.08
3.886 0.027
0.156 0.856
0.601 0.552
0.380 0.686
1.852 0.168
0.213 0.809
0.435 0.650
1.165 0.321
0.490 0.616
0.430 0.653
1.302 0.281
0.648 0.528

Table 5 Contd.
Manufacturing 2.17 1.24
Lack of interest and dissatisfaction in work
Services 3.13 1.26
or at the work place
Agriculture 2.33 1.53
Negative influences by the family
Manufacturing 3.75 1.19
Services 2.96 1.57
Agriculture 2.33 0.58
Table 6. Influence of business sector on the causes of business failure.
Arasti 7497
3.538 0.037
1.872 0.165
Causes of business failure Business sector Business sector Mean difference
Manufacturing
Service
Agriculture
-0.13
-2.04*
Inaccurate evaluation of project
Lack of interest and dissatisfaction in work
or at the work place
Services
Agriculture
Manufacturing
Services
Agriculture
failure in different context of a developing country and
could be an introduction to future studies. In this study,
we used an unlimited sample to study more cases of
failed businesses. Future studies on a large and homogenous
sample can lead to a better result.
We examined the entrepreneurial characteristics of
failed business-owners/managers and found a low or
moderate level in most of these characteristics. Other
studies could investigate on the impact of failed business
owner/ manager's characteristics in business failure.
This study indicated the influence of gender on the
causes of business failure. More investigation on a
sample of unsuccessful women business owners/
managers is needed to better understand the phenolmenon
of business failure in this particular population.
The difference in the causes of business failure by
business sector asks for more investigation on each
business sector. In addition, future researches could
study the causes of business failure in different phases of
establishment or growth.
Future research can study the influence of push and
Manufacturing 0.13
Agriculture -1.92
Manufacturing 2.04*
Service 1.92
Service -.958*
Agriculture -0.17
Manufacturing 0.958*
Agriculture 0.79
Manufacturing 0.17
Service -0.79
pull factors that motivate people to start a business to
know whether those different motivations at start-up
influence business failure. The inter-country study on
business failure and post-failure process is also an
interesting area of research.
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African Journal of Business Management Vol. 5(17), pp. 7499-7506, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.424
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Using greedy clustering method to solve capacitated
location-routing problem
Ali Nadizadeh 1* , Rashed Sahraeian 2 , Ali Sabzevari Zadeh 2 and Seyed Mahdi Homayouni 3
1 Industrial Engineering Department, Faculty of Engineering, Yazd University, Yazd, Iran.
2 Industrial Engineering Department, Faculty of Engineering, Shahed University, Tehran, Iran.
3 Mechanical and Manufacturing Engineering Department, Faculty of Engineering, University Putra Malaysia, Selangor,
Malaysia.
Accepted 15 April, 2011
This paper introduces a new heuristic method to solve the location-routing problem (LRP). Facility
location problem (FLP) and vehicle routing problem (VRP) are considered simultaneously in the LRP.
The problem selects the location of depot(s) to be established among a set of potential sites. On the
other hand, the allocation of customers to depot(s), and the distribution routes between the customers
and depot(s) are decided, too. In this paper, capacitated LRP (CLRP) is considered, in which the
vehicles and the depots have a predefined capacity to serve the customers. A greedy clustering
method (GCM-LRP) in four phases is proposed. The method clusters the customers using a greedy
search algorithm, selects the most appropriate location of depot(s), allocates the clusters to the
depot(s), and finally sets routes between the depot(s) and customers using ant colony system (ACS).
The numerical experiments on a set of benchmark instances show the efficiency of the proposed
method.
Key words: Capacitated location-routing problem, greedy clustering method, greedy search algorithm, ant
colony system.
INTRODUCTION
Ever increasing demand of customers for less waiting
time to receive their desired products, and competitive
prices between the producers, make logistics the main
problem in supply chain management. The efficient,
reliable, and flexible decisions on location of depots and
the distribution routings are of vital importance for
managers, in recent years. Many researches indicated
that if the routes are ignored while locating the depots,
the costs of distribution systems, might be immoderate
(Prins et al., 2006). Moreover, Barreto et al. (2007)
mentioned that considering FLP and VRP separately,
may lead to a suboptimal solution for capacitated LRP
(CLRP). The location-routing problem (LRP) is a set of
problem within location theory (Nagy and Salhi, 2007).
*Corresponding author. E-mail: alinadizadeh1@gmail.com.
Tel:+98 (913) 2551763. Fax: +98 (611) 2133513.
The LRP is defined as a facility location problem (FLP)
that solves the vehicle routing problem (VRP),
simultaneously.
LRP is applicable for a wide variety of fields such as
food and drink distribution, newspapers delivery, waste
collection, bill delivery, military applications, parcel
delivery and various consumer goods distribution
(Zarandi et al., 2011). In capacitated LRP (CLRP), the
problem is constrained with the vehicles and the depot(s)
capacities to supply the customers. Furthermore, the
customers must only be supplied by a single vehicle; in
other words, the vehicle meets every customer in a
cluster, once. The objective is to minimize the routing and
location costs (Bouhafs et al., 2006; Barreto et al., 2007).
In CLRP, a homogenous fleet of vehicles transports the
products with specific capacity from depots to the
customers and return there as soon as finishing the entire
tour. It is assumed that the location and demand of
customers are known in advance due to previous

7500 Afr. J. Bus. Manage.
patterns and data. Moreover, the capacity and the type of
products for each potential site are predefined. The
unitary cost of distribution system and the capacity of the
vehicles are considered in solving the problem too. The
objectives are to determine the location of depots, and a
set of customers to be served by each depot as well as
the distribution routes.
This paper proposes a greedy clustering method
(GCM-LRP) to solve the CLRP. Since a greedy search
algorithm was used for clustering the customers, the
proposed method is called “greedy clustering method”. In
first step, the customers are clustered using a greedy
search algorithm. Then, among a set of potential depots,
the most appropriate one(s) are selected to be
established. The third step allocates the clusters to
depots, and finally, ant colony system (ACS) is applied to
set up the best routes between the depot(s) and the
assigned customers.
LITERATURE REVIEW AND PROBLEM DEFINITION
A given set of customers with known demand are
considered to be served in the LRP. On the other hand,
the LRP considers a set of potential sites for the depots.
The objectives are to determine the location of depot(s),
and efficient allocation of customers to the depots and
appointing routs to supply the customers, while
minimizing the costs associated with establishing the
depot(s) and product distribution to the customers. In the
CLRP, demand of each customer should be supplied by
a single vehicle, while total load of each route must not
exceed the capacity of the vehicle. The routes starts and
ends at the same depot, and total load of allocated
customers must be less than or equal to the capacity of
the depot (Prins et al., 2006). Each potential site for
depots needs a fixed cost to be established, and the
distribution costs include the set up cost (F) of the route
and unitary cost linearly related to the transportation
distance between the depot and customers.
The CLRP in this paper includes both kinds of
constraints, which is formulated by Prins et al. (2006). It
is assumed that m potential sites are available for the
depots and there are n customers to be served. A
weighted and directed graph G = (V, A, C) shows the set
of nodes for depots and customers (V), the arc set
associated with each edge (i,j) (A), and the related cost to
each arc (Ca). A capacity (Wi) and opening cost (Oi) are
related to each potential site (i є I). The customers (j є J)
have a demand (dj), and K vehicles with capacity of Q are
available to serve the customers. Let S denote a subset
of nodes, then δ + (S) (δ - (S)) is the set of arcs leaving
(entering) S, and L(S) is the set of arcs with both
extremities in S. If S contains only one node x, then δ + (x)
is a simplified form for δ + ({x}). The number of vehicles or
the number of routes is the decision variable of the
problem. The following binary decision variables are
defined for the model, yi = 1 if depot i is established, fij = 1
if customer j is assigned to depot i, and xak = 1 if arc a is
used in the route performed by the vehicle k є K, and
zero otherwise. Therefore, the problem can be formulated
as the following zero-one programming model.
Minimize
Subject to
∑ ∑
x
ak
k∈Ka∈ −
j
δ ( )
∑ ∑
j∈J a∈
−
j
∑
j∈J
δ ( )
z = ∑ O . y + ∑ ∑ C . x + ∑ ∑ F . x (1)
=
j
i∈I
i
i
a ak
a∈Ak ∈K
k∈ K a∈δ
+ ( I )
1 ∀ j ∈ J
(2)
d . x ≤ Q
k ∈ K
ak
ak
∀ (3)
d . f ≤ W . y
∀ i ∈ I
(4)
j
∑ x
ij
δ ( i)
a∈δ
( )
i
− ∑ x
ak
ak
a∈
+
−
i
∑
a∈
+
x
ak
δ ( I )
∑ x
ak
a∈L
( S )
∑ x
≤
≤ S
i
= 0
∀ k ∈K
, ∀i
∈V
(5)
1 ∀ k ∈ K
(6)
−1
+ ∑ x
ak
ak
a∈δ
+ ( i ) ∩δ
− ( J ) a∈δ
− ( j )
x ak
y i
f ij
∀ S ⊆ J,
∀k
∈ K (7)
≤ f
ij
+ 1
{ , 1}
∀a
∈ A ∀k
∈ K
∀ i∈ I,
∀j
∈ J,
∀k
∈K
(8)
∈ 0 ,
(9)
{ , } ∀i
∈ I
∈ 0 1
(10)
{ 1, } ∀i∈
I ∀j
∈V
∈ 0 ,
(11)
The objective function (1) is the sum of depot(s)
opening costs and the routing costs, including the travel
costs and the fixed costs to set up a route. Each
customer should be served within one route only and the
customers should have only one predecessor, which is
stated by constraint (2). Constraints (3) and (4) imply that
total load assigned to a route or a depot must be less
than its capacity. The continuity of the routes and
return to the original depot are guaranteed through
constraints (5) and (6). Constraint (7) is to eliminate
subtours. Constraint (8) specifies that a customer can be
assigned to a depot only if a route linking them is opened.
Finally, constraints (9), (10), and (11) specify the binary
variables used in the formulation.

The CLRP is an NP-hard problem, so some
approximating heuristic algorithms had been developed
to solve it (Marinakis and Marinaki, 2008a, 2008b;
Barreto et al., 2007). In this kind of problems, the solution
times increase exponentially as with an increase in the
size of the problem, while an exact algorithm is applied to
solve them. Nagy and Salhi (2007) categorized the
heuristics algorithm presented in literature in four main
groups which are, sequential, clustering, iterative, and
hierarchical methods. In sequential methods, the
summation of depot-to-customer distances is minimized
in the first step. Then, the VRP is solved based on the
location of depots. The clustering-based methods, first
set up clusters for the customers, then, either solve the
VRP for each potential site, or solve the traveling
salesman problem (TSP) to find the best location of
depots. In iterative heuristics, VRP and FLP subproblems
are solved iteratively, feeding information from one phase
to the other. In hierarchical method, location of depots is
the main problem and routing is a subordinate problem.
Albareda-Sambola et al. (2005) developed a two-phase
tabu search algorithm for the LRP with one single route
per capacitated open depot. The two phases consist of
an improvement that optimizes the routes and a
permutation that modifies the set of open depots.
Bouhafs et al. (2006) described two-phase procedure to
solve the CLRP. First, a simulated annealing algorithm
finds a good configuration of distribution centers, and
then the ant colony system (ACS) seeks for a good
routing related to the configuration. The two-phase is run
repeatedly until the total costs justify the algorithm
termination. The results showed the efficiency of their
method. Prins et al. (2006) for CLRP, proposed a greedy
randomized adaptive search algorithm combining with a
learning process to set up the depots and a path relinking
(PR) adaptive search method to solve the routing
problem. Moreover, Prins et al. (2007) presented a
cooperative heuristic to solve the CLRP. Their heuristic
was based on the principle of alternating between a
locating phase and a routing phase, exchanging
information on the most promising edges. Barreto et al.
(2007) proposed a cluster analysis based on sequential
heuristics. Moreover, four grouping techniques and six
proximity measures were applied to obtain several
versions of the heuristic. As a result, they provided
guideline to choose a suitable clustering technique in
future application.
Marinakis and Marinaki (2008a) proposed a genetic
algorithm for the LRP in a large wood distribution
company in Greece. The problem was solved in two
levels, in which the optimal location of the depots and the
optimal routing of the vehicles are decided in strategic
and operational levels, respectively. The results of the
benchmark test cases showed that for six problems, a
new best solution was found. Moreover, Marinakis and
Marinaki (2008b) proposed a particle swarm optimization
(PSO) algorithm for LRP, in which PSO and multiple
Nadizadeh et al. 7501
phase neighborhood search, the expanding
neighborhood search, and PR are combined to solve the
problem. The comparative results showed that their
proposed method obtained the same or better results
than the best known solutions (BKS). Lopes et al. (2008)
developed a decision tool and user interface to solve the
CLRP. The user interface can help managers who do not
have any background on modeling and optimization
methods, to make more scientific decision, in a way that
is easily understandable. They used a sequential
“distribution-first location-second” heuristic method to
solve the problem in background of the software.
Schwardt and Fischer (2009) addressed the singledepot
LRP and proposed a neural network approach
based on a self-organizing map to solve the considered
problem. They compared the efficiency of their proposed
algorithm with some well-known heuristics and reported
that the self-organizing map approach is almost as
efficient as some of them. Zarandi et al. (2011) presented
a multi-depot capacitated LRP (MDCLRP) in which travel
time between two nodes was a fuzzy variable. A
simulation-embedded Simulated Annealing (SA)
procedure was proposed in order to solve the problem.
They tested the proposed method using a standard test
problem of MDCLRP and the results showed that the
proposed method is robust and could be used in real
world problems.
DETAILS OF THE HEURISTIC METHOD
A greedy clustering method, GCM-LRP, is presented to solve the
CLRP. In general, GCM-LRP consists of four phases, which is
illustrated in Figure 1. In first phase, the customers are clustered
using a greedy search algorithm (Figure 1a). The nearest customer
to last added customer to the cluster is selected to be included in
the cluster. This is the same as to form a tour in TSP, in which the
nearest city to the current city (in a “greedy” search algorithm) is
selected as next destination. So, the proposed heuristic method is
called “greedy clustering method”. Each cluster should include as
much customers as its total demand, being less than the capacity of
vehicle (Cap). In second phase, the gravity centre of each cluster is
calculated, which is used to select depot(s) to be established
(Figure 1b). The minimum number of required depots is selected to
cover total demand of customers and minimizing total cost of
establishing depot(s). The clusters are allocated to the opened
depot(s) in third phase, considering the distance between the
gravity center of clusters and depot(s) and the capacity of depots
(Figure 1c). Finally, in fourth phase, ACS forms an admissible tour
between each cluster and depot (Figure 1d). The problem is
initialized by defining a plane comprising the set of customers,
depots, and their coordinate points which are, CUST and DEP,
respectively. The heuristic method is repeated for a predefined
number of iterations. When the algorithm obtained a better solution,
it is replaced to the last best known solution.
In the proposed algorithm, clustering and iterative methods are
hybridized efficiently. The customers are clustered into some
clusters in advance, and then, the best location of depots is
founded by the constituted clusters. It is important to mention, VRP
and FLP which are two sub problems of CLRP are solved iteratively
so that at each iteration, a better solution for overall problem
replace the last one. Moreover, since in the first phase of GCM-

7502 Afr. J. Bus. Manage.
a)
c)
Customer Not-open depot Opened depot Gravity of center Assignment Route of vehicle
Figure 1. Illustrative example for the proposed heuristic method.
LRP, the first customer at each cluster is selected randomly, the
constituted clusters at each iteration of proposed algorithm are
different together. Thus, the proposed algorithm can search some
feasible solutions among all the solution space. This can ensure
that GCM-LRP avoid confining suboptimal solutions. Details of
heuristic method are described further.
Clustering the customers
The first phase of the GCM-LRP is to cluster the customers. The
customers are grouped considering their intra distance and the
capacity of the vehicles. A greedy search algorithm is used to select
a set of customers. In the first step, a customer is selected
randomly from the set of non-clustered customers belonging to
CUST, to form a cluster. The algorithm searches for the nearest
customer to the last selected customer of the current cluster. The
nearest customer is not included in the cluster if either of the
following criteria is met:
i. The number of assigned customers to a cluster reached the
maximum number of allowed customer per cluster (N);
ii. Total demand of customers is more than the Cap.
When the number of customer in each cluster reaches a given
number, there is no opportunity for any of the customers to enter
b)
d)
the cluster, even adding its demand to total demand of cluster,
which is less than the Cap. This is to balance the number of
customers in various clusters, which influences choosing the depots
in next phase, and the final solution. The maximum number of
members for a cluster is determined using a trial and error method.
Once a new customer is selected to be included in a cluster, total
demand of current members of the cluster adding to its new
member is compared with the capacity of the vehicle. If total
demand is less than the capacity of the vehicle, the customer is
included in current cluster. On the other hand, if total demand of
customers exceeds the Cap, last selected customer is withdrawn
from the cluster, and its demand is deducted from total demand of
the cluster. This customer is removed from the current search
space of the algorithm. The greedy search algorithm searches for a
new customer close to the last added member of the cluster among
the ungrouped customers. This is to use the maximum capacity of a
vehicle. The algorithm forms a new cluster if there are either no
more customers to be included in current cluster maintaining the
Cap constraint, or the maximum number of customer per cluster is
reached. When there are no more customers without a cluster, the
algorithm stops. Figure 2 illustrates the greedy search algorithm.
Choosing the depots
The second phase of the GCM-LRP searches potential sites to

No
START
Form a new cluster.
Select a customer from
CUST, randomly.
Calculate total demand
of the cluster (Dem).
Is the number of
customers in
this cluster ≤ N?
Yes
Is Dem ≤ Cap?
No
Remove the selected
customer from the
current search space.
Deduct demand of the
customer from Dem.
Is there any
customer in current
search space?
No
Is there any
unclustered
customer?
No
END
Yes
Yes
Yes
Figure 2. The proposed greedy search algorithm.
establish depot(s). In the first step of the phase, the gravity centre
of the clusters is calculated according to Equation (12), in which
Search the current space
for the nearest customer
to last added member of
cluster.
Add the new customer to
the to cluster, the cluster, and remove and
it remove from the it search from space the
search and CUST space and CUST.
Nadizadeh et al. 7503
(X(I),Y(I)) is the coordinates of gravity center of I th cluster, (xi,yi) is the
coordinates of i th customer of I th cluster, and nI is the number of

7504 Afr. J. Bus. Manage.
customers in I th cluster. The gravity centre of the cluster is used as
a representative to allocate it to the proper depot:
∑ ∑ ∈
( ( ) ( ) ) ⎟ ⎛
⎞
i∈I xi
i I yi
X =
⎜
I , Y I ,
(12)
⎝ nI
nI
⎠
Choosing the potential site(s) for depot(s) is the same as single
facility location problem (SFLP). In this step, the sum of distances
between the gravity centre of the clusters and potential sites is
calculated. The potential sites are sorted ascendingly according to
their Euclidean distance with gravity centre of clusters, which is
calculated by Equation (13).
In this equation, (x * ,y * ) is the coordinates of desired potential site
among all the candidates. Moreover, wj is the total Euclidean
distance between j th potential site and the gravity centre of clusters,
(xj,yj) is the coordinates of j th site, (ai,bi) is the coordinates of gravity
center of i th cluster, m is the number of clusters, and n is the
number of potential sites:
2
[ ]
∗ ∗ ( ) = ( − ) + ( − )
m
2
x , y : Min w x a y b
j
∑
i=
1
j
i
j
i
1
2
∀j
= 1,...,
n
(13)
In sorted list of potential sites, the first site is selected to be
established. If total demand of customers in all clusters is satisfied
through the capacity of the first depot, the second phase will be
finished. Otherwise, the next potential site (according to the sorted
list of sites), is selected to supply the clusters. This procedure is
repeated until the demand of all the clusters is covered. Therefore,
the GCM-LRP always establishes minimum number of depots.
Allocating clusters to depot(s)
The vehicles start their journey from a depot, move to all the
customers of a cluster, and return to the depot once finishing the
service to the customers. In the third phase of the GCM-LRP, the
clusters are allocated to the opened depot(s). Each depot is able to
serve some clusters according to its capacity, and each cluster is
supplied from exactly one depot. To allocate the clusters, the
Euclidian distance of gravity centre of the clusters to the first depot
is calculated. Based on the distance, the clusters are sorted
ascendingly. The first cluster is allocated to the depot if its demand
is less than or equal to the capacity of the depot. If there is
unallocated capacity for the first depot, the next cluster is allocated
to the depot if the total allocated demand to the depot is less than
its capacity. Otherwise, other sorted clusters are considered to be
allocated to the depot. The allocation process is finished once there
are no more clusters to be allocated to the depot maintaining the
constraint of the depot capacity. This procedure is repeated for the
remainder of the established depots and clusters.
Routing
In the fourth and last phase of the GCM-LRP, the routing problem
for the vehicles from the depot to the customers in each cluster is
solved. Each cluster is served by exactly one vehicle, and some
vehicles are supplied from a depot based on its capacity. The
routing problem of CLRP is the same as TSP, which is solved by
using ant colony system. ACS is referred to ants’ treatment to find
food. The ants spread a material called pheromone and put it on
their way so that other ants can pass the same route. The
pheromone of shorter route increases and therefore, more ants
move from that way. Artificial ants construct a solution by selecting
a customer to visit sequentially, until all the customers in a route
have been visited. Ants select the next city to visit using a
combination of heuristic and pheromone information. A local
updating rule is applied to modify the pheromone on the selected
arc, during the construction of a route. Once all ants have
constructed their tours, the amount of pheromone of the best
selected route and the global best solution, are updated according
to the global updating rule. Dorigo et al. (1996) mentioned that the
proper parameters' values in their proposed heuristic ACS algorithm
are α = 1, β = 5 and ρ = 0.65. Hence, these values are selected in
routing phase (phase 4) of the proposed heuristic algorithm. More
details on ACS can be found in Dorigo et al. (1996) and Bouhafs et
al. (2010).
COMPUTATIONAL RESULTS
To validate the efficiency of the presented GCM-LRP, a
series of computational experiments are carried out. The
efficiency of the proposed algorithm is evaluated by using
19 standard benchmark instances of CLRP presented by
Barreto (2003). The proposed heuristic algorithm is
programmed in MATLAB ® 7.0.4 on a computer, holding
Intel ® Core Duo CPU T2450 2.00 GHz. The
comparative results are summarized in Table 1. First
column indicate the author of the instance, the number of
customers, and the number of potential depot sites.
Second column shows the vehicle capacity in the
instances, and the third column reports the best known
solutions (BKS) that either are given in the literature or
obtained in this study. The solutions obtained by SA-ACS
(Bouhafs et al., 2006), GRASP (Prins et al., 2006),
LRGTS (Prins et al., 2007), the clustering based heuristic
(CH) (Barreto et al., 2007) and HybPSO-LRP (Marinakis
and Marinaki, 2008b) are shown in columns 4 to 8.
Column 9 shows the solutions obtained by the proposed
GCM-LRP.
In the tenth column, the minimum number of required
depots is given for each instance. The GCM-LRP
establishes the minimum number of depots, which can be
calculated through Num of Dep = [D/R] + 1, where R is
the capacity of depot and D is the total demands of
customers. [D/R] is the biggest integer number which is
less than D/R. The Minimum number of required vehicles
is illustrated in the last column, that can be calculated
through Num of Veh = [D/r] + 1 in which r is the capacity
of the vehicle. D, R and r can be obtained by data in
Barreto et al. (2007).
Computational results show that the GCM-LRP has
obtained 9 best solutions out of the 19 instances; while 2
of them are new best solutions. Further comparison of
the performance of three algorithms that could solve all
standard instances is shown in Table 2. It can be seen
that the proposed heuristic method is competitive with
two other algorithms in terms of solution quality by
providing the lowest average gap. For each algorithm, the
gap of the heuristic to the BKS is defined as: %100 ×
(solution obtained by algorithm - BKS) / BKS. In GCM-

Table 1. Computational results of GCM-LRP on standard instances.
Nadizadeh et al. 7505
CLRP instance –
customer × depot
Vehicle
capacity
BKS SA-ACS GRASP LRGTS CH HybPSO-LRP GCM-LRP
No. of
depots
No. of
vehicles
Christ69–50×5 160 582.7 – 599.1 586.4 582.7 582.7 582.7 1 5
Christ69–75×10 140 861.6 – 861.6 863.5 886.3 886.3 886.3 1 10
Christ69–100×10 200 842.9 – 861.6 842.9 889.4 889.4 842.9 1 8
Gaskell67–21×5 6000 424.9 430.4 424.9 424.9 435.9 432.9 427.7 2 4
Gaskell67–22×5 4500 585.1 586.7 585.1 587.4 591.5 588.5 591.5 1 3
Gaskell67–29×5 4500 512.1 512.1 515.1 512.1 512.1 512.1 512.1 1 3
Gaskell67–32×5 8000 567.2 569.3 571.9 587.4 571.7 570.8 567.2 1 4
Gaskell67–32×5 11,000 504.3 506.1 504.3 504.8 511.4 511.1 504.3 1 3
Gaskell67–36×5 250 460.4 470.4 460.4 476.5 470.7 470.7 469.2 1 4
Perl83–12×2 140 204 204 – – 204 204 205.3 1 2
Perl83–55×15 120 1118.4 1118.4 – – 1136.2 1135.9 1127.1 3 10
Perl83—85×7 160 1647.9 1651.3 – – 1656.9 1656.9 1647.9 3 11
Perl83—318×4 25,000 580680.2 – – – 580680.2 580680.2 580791.5 1 8
Perl83—318×4 8000 747619 – – – 747619 747619 747619 1 24
Dasnki95–88×8 9,000,000 356.9 – 356.9 368.7 384.9 384.9 384.9 2 5
Dasnki95–150×10 8,000,000 44386.3 – 44625.2 44386.3 46642.7 46642.7 46642.7 3 10
Min92–27×5 2500 3062 3062 3062 3065.2 3062 3062 3062 1 4
Min92–134×8 850 5965.1 6208.8 5965.1 – 6238 6230 6229 3 10
Or76–117×14 150 12474.2 – – – 12474.2 12474.2 12474.2 3 5
BKS: solutions obtained either by the algorithms in their published version or during their parameter analysis phase.
GCM-LRP: the best solution obtained by the proposed algorithm. –: the problem is not solved in the corresponding study.
Bold numbers indicate that best known solution values are attained by the corresponding approach.
Table 2. Further computational results on standard instances.
CLRP instance –
customer × depot
BKS
CH
Solution Gap (%)
HybPSO-LRP
Solution Gap (%)
GCM-LRP
Solution Gap (%)
Christ69–50×5 582.7 582.7 0.00 582.7 0.00 582.7 0.00
Christ69–75×10 861.6 886.3 2.87 886.3 2.87 886.3 2.87
Christ69–100×10 842.9 889.4 5.52 889.4 5.52 842.9 0.00
Gaskell67–21×5 424.9 435.9 2.59 432.9 1.88 427.7 0.66
Gaskell67–22×5 585.1 591.5 1.09 588.5 0.58 591.5 1.09
Gaskell67–29×5 512.1 512.1 0.00 512.1 0.00 512.1 0.00
Gaskell67–32×5 567.2 571.7 0.79 570.8 0.63 567.2 0.00
Gaskell67–32×5 504.3 511.4 1.41 511.1 1.35 504.3 0.00
Gaskell67–36×5 460.4 470.7 2.24 470.7 2.24 469.2 1.91
Perl83–12×2 204 204 0.00 204 0.00 205.3 0.64
Perl83–55×15 1118.4 1136.2 1.59 1135.9 1.56 1127.1 0.78
Perl83—85×7 1647.9 1656.9 0.55 1656.9 0.55 1647.9 0.00
Perl83—318×4 580680.2 580680.2 0.00 580680.2 0.00 580791.5 0.02
Perl83—318×4 747619 747619 0.00 747619 0.00 747619 0.00
Dasnki95–88×8 356.9 384.9 7.85 384.9 7.85 384.9 7.85
Dasnki95–150×10 44386.3 46642.7 5.08 46642.7 5.08 46642.7 5.08
Min92–27×5 3062 3062 0.00 3062 0.00 3062 0.00
Min92–134×8 5965.1 6238 4.57 6230 4.44 6229 4.42
Or76–117×14 12474.2 12474.2 0.00 12474.2 0.00 12474.2 0.00
Avg. 1.90 1.82 1.33
Gap: relative percentage gap calculated as %100 × (solution values obtained by individual algorithm – BKS)/BKS.

7506 Afr. J. Bus. Manage.
LRP, the average gap is 1.33% that can indicate the
efficiently of the proposed GCM-LRP heuristic.
CONCLUSION AND FUTURE RESEARCH
A new heuristic method for the capacitated locationrouting
problem is presented in this paper. In CLRP, the
vehicles and depots have a predefined capacity to supply
the customers. The aims of the problem are to select
locations for establishing the depots among a set of
potential sites, to allocate the customers to the depots
according to their demand and find the best route for the
vehicles between the customers and the depot. The
objective function of the proposed method is to minimize
the opening costs of depot(s), and the tour cost of the
vehicles. The GCM-LRP is presented in four phases; in
the first phase, the customers are clustered based on a
greedy search algorithm. In the second phase, the best
location of depots based on the distance of the potential
sites and the gravity centre of clusters is determined. The
proposed heuristic method uses minimum number of
depots to solve the CLRP. The clusters are allocated to
opened depots according to the capacity of the depot and
the distance between the depot and the clusters in third
phase, and the best routes between the depot and
allocated clusters are decided in the fourth phase.
Computational results and comparisons of the GCM-
LRP algorithm with various promising LRP heuristics
shows that, the efficiency of the proposed algorithm is
satisfactory so that proposed algorithm obtains 9 best
solutions out of 19 instances, while 2 of them indicate
new best solutions. Moreover, the qualities of the
obtained solutions demonstrate that, the proposed GCM-
LRP has the lowest average gap in comparison with
three other algorithms that can solve all standard
instances.
The LRP has attracted more researches in recent
years. However, many parameters still needs more
researches, for example, it is highly recommended to
include stochastic demand of customers in the
formulation of the problem. Delivery time constraints for
each customer, and/or adding the variable costs of
establishing depots are interested for future researches,
too.
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Albareda-Sambola M, Dı´az JA, Ferna´ndez E (2005). A compact model
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Oper. Res., 32(3): 407-428.
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Barreto SS, Ferreira C, Paixao J (2007). Using clustering analysis in a
capacitated location-routing problem. Eur. J. Oper. Res., 179(3): 968-
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Bouhafs L, Hajjam A, Koukam A (2006). A combination of simulated
annealing and ant colony system for the capacitated location-routing
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Bouhafs L, Hajjam A, Koukam A (2010). A hybrid heuristic approach to
solve the capacitated vehicle routing problem. J. Artif. Intel. Theo.
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Dorigo M, Maniezzo V, Colorni A (1996). The Ant System: Optimization
by a colony of cooperating agents. IEEE Trans. Syst. Man.
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Lopes RB, Barreto S, Ferreira C, Santos BS (2008). A decision-support
tool for a capacitated location-routing problem. Decis. Supply Syst.,
46(1): 366-375.
Marinakis Y, Marinaki M (2008a). A bilevel genetic algorithm for a real
life location routing problem. Int. J. Log. Res. Appl., 11(1): 49-65.
Marinakis Y, Marinaki M (2008b). A particle swarm optimization
algorithm with path relinking for the location routing problem. J. Math.
Model. Algor., 7: 59-78
Nagy G, Salhi S (2007). Location-routing: Issues, models and methods.
Eur. J. Oper. Res., 177: 649-672.
Prins C, Prodhon C, Calvo RW (2006). Solving the capacitated locationrouting
problem by a GRASP complemented by a learning process
and a path relinking. 4OR. 4(3): 221-238.
Prins C, Prodhon C, Ruiz A, Soriano P, Wolfler Calvo R (2007). Solving
the capacitated location-routing problem by a cooperative lagrangean
relaxation granular tabu search heuristic. Transport. Sci., 41(4): 470-
483.
Schwardt M, Fischer K (2009). Combined location-routing problems-a
neural network approach. Ann. Oper. Res., 167(1): 253-269.
Zarandi MHF, Hemmati A, Davari S (2011). The multi-depot capacitated
location-routing problem with fuzzy travel times. Exp. Sys. Appl.,
doi:10.1016/j.eswa.2011.02.006.

African Journal of Business Management Vol. 5(17), pp. 7507-7510, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.428
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
The relationship between cultural intelligence and
group effectiveness in Mobarakeh steel company
A. Khani*, A. Etebarian and M. Abzari
Department of Public Management, Islamic Azad University, Khorasgan Branch, Isfahan, Iran.
Accepted 25, May 2011
Today's environment creates a growing way for organizations to perform their functions through teams
and groups. Organizations want to hire individuals who can perform better in groups and frequently
adjust with people from various cultures and handle intercultural communications. People need to
know other cultures and interact with people from other cultures. Consequently, they need cultural
intelligence. The purpose of this study is to investigate the relationship between cultural intelligence
and its facets with group effectiveness in Mobarakeh Steel Company. Forty Seven teams participated in
this study. According to the results, cultural intelligence and its facets (metacognition, cognition,
motivation and behavior) have significant and straight relationship with group effectiveness. Also,
motivation and behavior facets can predict group effectiveness.
Key words: Group, group effectiveness, cultural differences, cultural intelligence.
INTRODUCTION
Unawareness about properties and orientations of own
culture, sense of fear and peril in interacting with people
from other cultures, inability to understand and explain
behavior of people from different culture, misapprehendsion
effect of culture on behavior and inability to adjust
with other’s work and life increase tension and stress.
Consequently, these factors cause incorrect performance
and lost opportunities (Thomas and Inkson, 2004).
It is derived from the Latin word "cultura", the word
'culture' means to cultivate (Harper, 2001). Values,
customs, artifacts, behaviors and beliefs are derive from
culture. Therefore, people’s cultural perceptions are
different. These differences cause various and
heterogeneous behaviors (Tousi, 1993).
Getting people to work together, to listen to every
member, to consider all view points and to exercise
courtesy and respect for each other has always been a
challenge. In today's society, when cultural diversity is
common in workplaces, good communication has
become an even greater challenge (Lankard, 1994).
Staffs from varied cultures reflect different learning styles
*Corresponding author. E-mail: khani.azam@gmail.com. Tel:
+989132276164.
and bring different preferred working styles to their jobs.
Sometimes, managers consider such differences wrong
or problematic but, recognizing, valuing and supporting
these and other differences can maximize the productivity
of everyone in the workplace (Bibikova and Kotelnikov,
2006).
The ability to adapt successfully to the new specific
cultural values is determined by the person's culture
intelligence (CI). Work groups should develop cultural
intelligence to perform effectively (Thomas and Inkson,
2004).
Some aspects of culture are easy to see, like art, music
and behavior. However, the significant and most
challenging parts of other cultures are hidden. These
might include our beliefs, values, expectations, attitudes,
and assumptions. Our cultural programming in these
areas shapes everything we do. Most importantly they
help us to decide what is ‘normal’ in our eyes. It is the
perceived deviation by other cultures from our version of
normality that causes the problems (Bibikova and
Kotelnikov, 2006).
In the most systematic treatment of cultural intelligence
to date, Earley and Ang (2003) defined cultural
intelligence as “a person’s capability to adapt effectively
to new cultural contexts”. This definition is consistent with
Schmidt and Hunter’s definition (2000) of general

7508 Afr. J. Bus. Manage.
intelligence as ‘the ability to grasp and reason correctly
with concepts and solve problems (Earley and Ang,
2003). Ang et al. (2004) defined cultural intelligence as
“an individual’s capability to deal effectively in situations
characterized by cultural diversity” (Imai, 2007).
Cultural intelligence is set to be in motion when
individuals are able to analyze the new culture and
accept that other individuals from a different culture may
perceive a situation differently. However, adjustment is
likely to happen only when the employee understands the
reasons behind each value or rule within the new culture
and is conscious of the meaning of the novel behavior
(Earley et al., 2006).
Early and Mosakowski (2004) developed a multidimensional
construct (CQ) to measure cultural intelligence
based on the emotional and social quotient of employees.
This scale is comprised of four facets: Strategy or
metacognition CQ that is an individual acquires and
understand cultural knowledge through processes and
manners he/she employs. Motivation CQ is the
individual's interest with new and different cultures.
He/she is directed by his/her energy to interact with
people from the other cultural environment. Behavior CQ
is the individual's ability to control his/her verbal and
nonverbal behavior when adapting to different cultures.
The person's behavior should be flexible enough in order
to respond appropriately to the different cultural situations
(Van Dyne and Ang, 2005). Knowledge or cognition CQ
is the person's awareness and understanding of his/her
culture and that of others (Thomas and Inkson, 2004).
According to Thomas (2006), the importance of learning
about your own culture and that of others leads to the
ability to understand and decode your personal behavior
and other's behavior (Lane et al., 2000).
Cultural intelligence will help individuals manage
effectively cultural differences, in particular, Lower the
cultural barriers and predict what ‘people’ are thinking
and how they will react to other’s behavior patterns and
harness the power of cultural diversity.
In today's organization, cultural intelligence is a
necessary tool for every manager who deals with diverse
teams of employees, customers, partners, competitors,
government, and other business players (Bibikova and
Kotelnikov, 2006).
When individuals work in a group, they should know
that every member has different culture. This is important
for managers to know how people from different cultural
background can work together. Experts believe that
member’s of group need an important ability to perform
effectively in group that is called cultural intelligence.
Groups in organizations became a focal point of
interest in the 1940s (Cantu, 2007). A “work group” is
made up of individuals who see themselves and who are
seen by others as a social entity, who are interdependent
because of the tasks they perform as members of a
group, who are embedded in one or more larger social
systems (for example community and organization) and
who perform tasks that affect others (such as customers
or coworkers) (Alderfer, 1977; Hackman, 1987).
According to group definition, group members must deal
with people from different cultures and they should have
knowledge about cultural differences. Thus, they need
cultural intelligence.
A core element in evaluating and measuring groups is
effectiveness. The 1998 Advanced Learner’s Oxford
dictionary defines effectiveness as: “Having the desired
effect; producing the intended result, making a strong and
pleasing impression” (Scott and Pollok, 2006). An
effective group has certain characteristics, clear and
shared goals, participation, respected feelings,
consensus decision making, share leadership, trust,
recognizing group problems and creativity (Schein,
1988).
MATERIALS AND METHODS
The aim of this research was to investigate the relationship
between the different facets of cultural intelligence and group
effectiveness.
For this investigation, a three part questionnaire was designed.
The first part consisted of the revised four factor model of CQ
developed by Ang et al. (2007). This instrument included 24
statements designed to measure the four facets of cultural
intelligence that is strategic or Metacognition, motivation, behavior
and knowledge or cognition CQ. This part was measured using a 5
point Likert scale type from 1=SD to 5=SA. The second part
included 8 questions intended to measure group effectiveness
adapted from Schein (1988). This part was measured using a 10
point scale type from 1=bad to 10=good. The third part, collected
demographic data and asked about gender, age, education and
work experience.
The survey took place between the months of September 2009
and April 2010. Participants were employees working in
Multicultural teams in Mobarakeh Steel Company. Out of 307
distributed questionnaires among 47 teams, 242 questionnaires
from 44 teams were received. The sample consisted of 2.5%
females and 97.5% males, 23.1% less than 30 years old, 24.4%, 31
to 40 years old, 48.3%, 41 to 50 years old and 4.1% more than 51
years old, respectively. 51.2, 14.5, 27.7 and 6.6% have diploma,
junior degree, bachelor and post graduated. 36.8, 13.6 and 49.6%
have respectively less than 10 years, 10 to 20 years and more than
21 years of experience. We then coded the generated data and
used the computerized software SPSS 14.0 for analysis. The
reliability for the CQ questionnaire and group effectiveness
questionnaire were satisfactory with Cronbach's Alpha of = 0.92
and 0.86.
RESULTS
Correlation analysis was used to test if a relationship
existed between the independent variables: CQ and its
facets with the dependent variable: Group effectiveness.
The Pearson correlation coefficients among the variables
showed a significant relation between cultural intelligence
and group effectiveness (P

Table 1. Correlation of facets of CQ and group effectiveness.
Facets of CQ Pearson coefficient Sig (2-tailed) R 2
Metacognitive CQ 0.375 0.012* 0.14
Cognitive CQ 0.404 0.007** 0.16
Motivational CQ 0.502 0.001** 0.25
Behavioral CQ 0.483 0.001** 0.23
**Correlation is significant at the 0.01 level. *Correlation is significant at the 0.05 level.
Table 2. Stepwise multiple correlation.
Model R R Square
Adjusted R
square
Std. error of the
estimate
Khani et al. 7509
F Sig.
1 0.502 a 0.252 0.234 7.2522 14.113 0.001 a
2 0.577 b 0.333 0.301 6.9268 10.254 0.000 b
a Predictors: (constant), motivation, b Predictors: (constant), motivation, behavior.
Table 3. Stepwise multiple linear regression.
1
2
Model
Unstandardized coefficients
B Std. Error
Standardized coefficients
Beta
t Sig.
Constant 14.029 10.303 1.362 0.181
Motivation 2.248 0.598 0.502 3.757 0.001
Constant 11.341 9.914 1.144 0.259
Motivation 1.595 0.641 0.356 2.486 0.017
Behavior 0.972 0.433 0.321 2.245 0.030
r=0.375 for metacognitive, r=0.404 for cognitive, r=0.502
for motivational and r=0.483 for behavioral CQ). The
coefficient of determination [R.sup.2] was 0.14 for
Metacognitive, 0.16 for cognitive, 0.25 for motivational
and 0.23 for behavioral (shown in Table 1). This means
that 14, 16, 25 and 23% of the variation in the independent
variables are explained by the variations in the
dependent variable. Stepwise multiple linear regression
was used to provide a linear model for predicting group
effectiveness. The Unstandardized coefficient B of
motivational and behavioral CQ indicated that these
facets can predict group effectiveness (shown in Tables 2
and 3). According to Tables 2 and 3, linear relationship
between cultural intelligence facets and group
effectiveness is:
Group effectiveness= 1.59 Motivation + 0.972 Behavior
(1)
DISCUSSION
This research set out to investigate the relationship
between the different facets of cultural intelligence and
group effectiveness. Our findings demonstrated that (1)
cultural intelligence and its facets were positively related
to group effectiveness; (2) two facets of CQ can be
considered as predictors of group effectiveness that is,
motivational and behavioral CQs.
Our results indicated that cultural intelligence was
positively related to group effectiveness (Hadizadeh and
Hoseini, 2008; Imai, 2007). Individuals high in CQ are
better equipped with the metacognitive, cognitive, motivational
and behavioral skills necessary in overcoming
cultural barriers such as clashing schemas and
metaphors. Also, they will be able to solve problems
(Imai, 2007). With CQ, individuals can be aware of their
beliefs and values, reduce conflicts derived from
differences and participate to goal setting. Therefore, CQ
is a means of growing group and conquering group
problems.
Our results indicated that metacognitive CQ was
positively related to group effectiveness (Ang et al.,
2007). Consequently, Individuals can understand cultural
differences and help to improve group performance.
Those with high metacognitive CQ are consciously aware
of other’s cultural preferences before and during
interactions. They also question cultural assumptions and
adjust their mental models during and after interactions
(Triandis, 2006).
Cognitive CQ was also positively related to group

7510 Afr. J. Bus. Manage.
effectiveness (Hadizadeh and Hoseini, 2008). This facet
refers to skills of general thoughts and uses for identifying
actions in new settings. In addition, it includes individual
beliefs and values, methods and procedures that others
use for doing their functions. Many people are not able to
understand other cultures, but one who is powerful in
cognitive CQ, finds shared concepts earlier. Learning
other’s cultural concepts help to understand and
recognize other’s behavior.
Motivational CQ was also positively related to group
effectiveness (Hadizadeh and Hoseini, 2008). The
motivational CQ refers to one’s self motivation and
commitment to adapt and adjust to a different culture. So,
individuals have capability to direct attention and energy
toward learning about and functioning in situations
characterized by cultural differences. Kanfer and
Heggestad (1997) argued that such motivational
capacities provide agentic control of affect, cognition and
behavior that facilitate goal accomplishment.
Behavioral CQ was also positively related to group
effectiveness (Ang et al., 2007; Hadizadeh and Hoseini,
2008). So individuals with high behavioral CQ display
suitable verbal and nonverbal behaviors when interacting
with individuals from the unfamiliar culture (Van Dyne and
Ang, 2005). They have a flexible repertoire of behavioral
responses that enhances their task performance in
culturally diverse settings.
Also, our findings demonstrated that among four facet
of CQ, motivational and behavioral CQ can respectively
predict group effectiveness with 1.59 and 0.972
coefficients. Thus, in effective groups, knowledge and
mental process should have used for interacting and
communicating with others and their members have
sufficient motivation to communicate. Also, group
members’ behavior is adapted with situations. Having
interest to know other cultures and ability to control
behavior and be flexible when dealing with different
cultures is basis of group effectiveness.
Conclusion
Our findings indicated that cultural intelligence and its
facets have significant and straight relationship with
group effectiveness. Motivational and behavioral CQ can
predict group effectiveness. Having the necessary
attitude towards exerting effort is the basis for developing
the necessary skills and behaviors to effectively interact
with people with different social backgrounds. This study
indicated that metacognitive and cognitive CQ can’t
predict group effectiveness.
Our findings are limited to studied organization’s teams
and cannot be generalized to other teams in other
organizations. However, this study did not take into
account demographic characters of groups. It is
recommended that further studies including such
variables be undertaken.
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Development and cross-validation of a four-factor measure. Paper
presented at the 19th annual meeting of the Society for Industrial
and Organizational Psychology, Chicago, IL.
Ang S, Van Dyne L, Koh Ch, Ng KY, Templer KJ, Tay Ch and
Chandrasekar NA (2007). Cultural intelligence: Its measurement
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and task performance. Manage. Organ. Rev., 3: 335-371.
Bibikova A, Kotelnikov V (2006). Cultural Intelligence (CQ):
knowledge, arts and skills. www.1000ventures.com/the key to
leveraging the power of diversity.htm. (accessed on 20 September
2009).
Cantu C (2007). Evaluating team effectiveness: examination of the
team assessment tool. Dissertation Prepared for the Degree of
PhD. University of North Texas.
http://digital.library.unt.edu/permalink.pdf.
Earley PC, Ang S (2003). Cultural intelligence: Individual interactions
across cultures. Palo Alto, Calif: Stanford University Press.
Earley CP, Ang S, Tan JS (2006). CQ: Developing Cultural
Intelligence at Work. Stanford: Stanford University Press.
Earley CP, Mosakowski E (2004). Cultural intelligence. Harvard
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CQ on intercultural negotiation effectiveness. MR Thesis.
University of Maryland.
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African Journal of Business Management Vol. 5(17), pp. 7511-7515, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.439
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Factors of cross-buying intention - bancassurance
evidence
Chiang Ku Fan 1 , Li-Tze Lee 2 *, Yu-Chieh Tang 3 and Yu Hsuang Lee 4
1 Department of Risk Management and Insurance, Shih Chien University, China.
2 Department of Accounting and Information, Overseas Chinese University, Taiwan, China.
3 Graduate Institute of Management Sciences, Tamkang University, Taiwan, China.
4 Graduate Institution of Business Administration, Shih Chien University, Taipei, Taiwan.
Accepted 15 April, 2011
The question of why bank customers decide to cross-buy and to enhance their relationship with a bank
has received scant attention in the literature, and has not been appropriately investigated in prior
studies. The first purpose of this study is to address this research gap by developing and assessing an
objective research model to weigh the factors that affect intention of cross-buying insurance in banks.
The second purpose of this study is to identify the resulting degree of satisfaction of these factors. The
gaps between the factors of cross-buying intention and the resulting satisfaction are recognized by
using the “Importance Performance Analysis.” On the basis of the findings, bancassurance strategy
makers can identify and allocate the marketing or operational resources for an organization
accordingly.
Key words: Cross-buying, bancassurance, intention, conjoint analysis, importance performance analysis.
INTRODUCTION
The banking industry in Taiwan has experienced
tremendous change and an increased growth in earnings
from selling insurance products. Banking networks
represent the major distribution channel for life insurance
products. Most banks are looking for the same things -
better ways to retain customers and to increase income.
Similarly, most insurers are looking for the same things -
more efficient distribution channels to sell policies and to
expand premium incomes.
To manage their relationship development efforts
better, it is important for practitioners to understand the
motivations that lead the customer to reduce their market
choices and to engage in a relationship with a financial
firm (Sheth and Parvatiyar, 1995).
Cross-selling is the practice of promoting additional
services or products to a firm’s existing customers, which
are in addition to the ones that the customers already
have (Butera, 2000). Selling additional products or
services to existing customers may reduce the cost of
*Corresponding author. E-mail: leelitze@ocu.edu.tw.
customer acquisition and yield price advantages over
competitors (Nbogo, 2004). In spite of cross-selling being
associated with increased lifetime duration and value
(Reinartz and Thomas, 2001), prior studies have implied
that it is not easy to motivate customers to cross-buy
services or products from the same provider. Unfortunately,
the question of why customers decide to crossbuy
and to enhance their relationships with a bank has
received scant attention in the literature and has not been
appropriately investigated in prior studies (Ngobo, 2004).
Furthermore, no satisfaction evaluations of these factors
that affect cross-buying intention have been conducted.
There is, therefore, a significant research gap which has
emerged in understanding the factors that motivate
cross-buying intention (Soureli et al., 2008). Obviously,
additional evidence and conceptualizations are
necessary in this area.
The first purpose of this study is to address this
research gap by developing and assessing an objective
research model to weigh those factors that affect
intention of cross-buying insurance in banks that have
been suggested in previous studies. The second purpose
is to identify the degree of satisfaction of these factors

7512 Afr. J. Bus. Manage.
Table 1. The factors impact cross-buying intention for bancassurance.
Factors impact cross-buying intention References
Image Ngobo, 2004; Soureli et al., 2008
Service convenience Dimitriadis, 2010; Berry et al., 2002; Ngobo, 2004; Liu and Wu, 2007
Interpersonal relationships Reinartz, 2003; Jeng, 2008
Trust Anderson and Weitz, 1989; Doney and Cannon, 1997; Liu and Wu, 2007, 2008;
Soureli et al., 2008
Payment equity Bolton, 1998; Verhoef, 2001
Experience Anand and Cunnane, 2010; Verhoef, 2001; Ngobo, 2004
Pricing Verhoef, 2001; Jeng, 2008
Product variety Jeng, 2008; Kumar et al., 2008
that affect intention of cross-buying insurance in banks.
LITERATURE REVIEW
Verhoef et al. (2001) were the first to introduce the term
“cross-buying” and defined it as the purchase of a
number of different services from the same provider. In
other words, cross-buying is the behavior expressed in
buying various products from the same provider (Soureli
et al., 2008; Verhoef et al., 2001). In fact, cross-selling
and its benefits can only be achieved if consumers are
willing to cross-buy (Polonsky et al., 2000). Therefore,
cross-buying is complementary to cross-selling, which
pertains to the supplier’s efforts to increase the number of
products or services that a customer uses within a firm
(Aurier and N' Goala, 2010; Kamakura et al., 2003).
A number of factors that may impact bank customers’
cross-buying intentions have been proposed in previous
research studies. The findings of these prior studies are
reported in Table 1.
A summary of the literature review with regard to
factors that affect cross-buying intention is listed thus:
1. The tendency of most prior studies has been to
examine variables such as image, service convenience,
interpersonal relationships, trust, payment equity,
experience, pricing, and product variety.
2. It is difficult to determine the relative importance of the
weight or ranking of each cross-buying intention, because
they were not defined in previous studies.
3. Prior studies have neither focused on evaluating the
strategies of stimulating the customer’s cross-buying
intentions, nor suggested how bancassurance decisionmakers
should allocate marketing resources.
METHODOLOGY
The estimation model in this study consists of three phrases. In the
first phrase, the factors of cross-buying intention for bancassurance
are identified using the modified Delphi method. In the second
phrase, the factors' weights of cross-buying intention are also used
as the evaluation criteria and are calculated effectively by
employing the “Conjoint Analysis.” In the third phrase, the gaps
between the factors' weights of cross-buying intention and the
customers’ satisfaction are recognized by using the “Importance
Performance Analysis.” The main theoretical approaches adopted
herein are described, as shown in Figure 1.
RESULTS
To identify the factors that affect intention of cross-buying
insurance in banks, this study applied a purposive sampling
technique and selected 23 financial advisers who
were employed by different model banks and have many
years of experience working with bancassurance. The
interviews were conducted either through e-mail or faceto-face.
Respondents were asked to justify their answers
to interview questions and to rate their level of agreement
toward the factors of cross-buying intentions, ranging
from strongly agree (SA) (5) to strongly disagree (SD) (1).
The interview protocol was developed on the basis of
the literature review. On the basis of the result of a
Wilcoxon Signed-Rank test, no significant attitude
difference toward each factor of cross-buying intention
was found between round 2 and round 3. This means that
the 8 items proposed by this study can be identified as
factors that affect intention of cross-buying insurance in
banks according to the Delphi study procedures. All
factors that affect cross-buying intention were ranked SA
by most of the Delphi panelists in the 3 rd round of the
interviews.
The CA questionnaire was developed on the basis of
some of the literature, planned with an orthogonal design,
and distributed to 300 customers. Two hundred and sixtynine
questionnaires were completed in the survey.
According to the CA report, the most important factor
was image (relative importance = 36.172%), the second
most important factor was service convenience (relative
importance = 11.099%) and the third most important
factor was interpersonal relationships (relative
importance = 10.514 %).
The purpose of the attitude survey was to collect data
with regard to the performance of each factor that affect
intention of cross-buying insurance in the bank. The

Figure 1. Theoretical approach adopted in this study.
Table 2. Gap analysis of factors' importance and their performance.
Item Factor affecting crossbuying
intention
Linear transformation of relative
importance of cross-buying intentions (A)
Mean of
performance (B)
Fan et al. 7513
Gap analysis (B-
A)
1 Image 3.90 3.92 0.02
2 Service convenience 3.71 3.83 0.12
3 Interpersonal relationships 3.71 3.81 0.10
4 Trust 3.70 3.97 0.27
5 Payment equity 3.64 3.53 -0.12
6 Experience 3.61 3.58 -0.03
7 Pricing 3.19 3.31 0.12
8 Product variety 3.23 3.64 0.41
Overall 3.59 3.70 0.11
respondents were asked to answer a question regarding
the level of performance for each factor affecting intention
of cross-buying insurance in the bank. Through a
judgment-sampling technique, the questionnaires were
distributed to the customers who had purchased
insurance products in banks. This study successfully
surveyed 131 bank customers. As stated earlier in
methodology, the range of the rating level in the
performance survey was from one to five. However, the
range of relative importance estimated through CA was
from zero to one. To conduct comparisons, this study
transfers the relative importance of factor affecting crossbuying
intention to a scale of 1 to 5.
Table 2 reports the means of the relative importance of
factors affecting cross-buying intention; their performance
ratings were 3.59 and 3.70, respectively. Table 2 also
shows the gap between the relative importance of factors
affecting cross-buying intention and their performances. If
the gap shows as negative, it means the factor of crossbuying
intention’s performance is less than its relative
importance. On the other hand, if the gap shows as
positive, it means that the factor of cross-buying intention's
performance is more than its relative importance.
In the grid, there were 8 factors that affect intention of
cross-buying insurance in the bank that fell into four
quadrants (Figure 2). According to the grid, a total of two
factors of cross-buying intention fell into the area of
“concentration” (quadrant (I)). These included payment
equity (3.53, 3.64) and experience (3.58, 3.61). That is,
payment equity was more important than experience in

7514 Afr. J. Bus. Manage.
Figure 2. Importance-performance grid of factors affecting intention of CROSS-buying insurance in a bank.
Figure 3. Resources allocation for bancassurance.
quadrant (I). Furthermore, of the four factors of crossbuying
intentions located in quadrant (II), image (3.92,
3.90), service convenience (3.83, 3.71), interpersonal
relationships (3.81, 3.71), and trust (3.97, 3.70) were
included. The management scheme action is “keep up
the good work.” In addition, two factors of cross-buying
intention were plotted in the area of “low priority”
(quadrant III). These were product variety (3.64, 3.23),
and pricing (3.31 3.19). However, no factor of crossbuying
intention fell within the area of “possible overkill”
(quadrant IV).
CONCLUSION AND RECOMMENDATIONS
(I) Concentration
(III) Low priority
Resources
The above-mentioned analysis supports the argument
that, although it is necessary to identify areas of
importance, and low performance, neither of these
factors, by themselves, is sufficient. Just because a factor
(II) Keep up the good work
Maintain
Resources
(IV) Possible overkill
of cross-buying intention is important does not mean that
resources should be focused and expended on that factor
of cross-buying intention; the performance may be
adequate, in which case the benefits of expending
resources will be limited.
In the context of this study, factors affect cross-buying
intention, such as payment equity and experience that fell
into quadrant (I), and are perceived as more important
but performed poorly in bancassurance. The managerial
implication is that management has to put greater efforts
into improving performance with respect to these factors.
Factors of cross-buying intention, such as image,
service convenience, interpersonal relationships, and
trust, that were located in quadrant (II), are rated as
important with a high level of performance, and management
has to maintain the performance with respect to
these factors to sustain the resultant competitive
advantages (Figure 3).
Factors of cross-buying intention that are located in

quadrant (III), including product variety and pricing, are
rated as having a low level of importance, and
performance. Thus, it is not necessary that management
put too much effort into improving their performance with
respect to these factors (Figure 3).
To improve the performance of bancassurance,
administrators should move some of those efforts that
were originally invested in the factors of product variety
and pricing into payment equity and experience. On the
other hand, administrators should not expand the
resources devoted to the factors that affect cross-buying
intention of image, service convenience, interpersonal
relationships, and trust (Figure 3).
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African Journal of Business Management Vol. 5(17), pp. 7516-7525, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.468
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Ownership structure and dividend policy: Evidence
from Iran
Sasan Mehrani, Mohammad Moradi and Hoda Eskandar*
Faculty of Management, University of Tehran, Pol-e-Nasr, P. O. Box 14155-6311, Tehran, Iran.
Accepted 28 April, 2011
Ownership structure is an influential factor on firm policies. One of these policies is dividend policy.
Therefore, a significant relationship between ownership structure and dividend policy is expected. This
paper examined the relationship between dividend policy and ownership structure in Tehran Stock
Exchange from 2000 to 2007. In this study, four regression models were used. Institutional ownership
was negatively associated with dividend payout. It indicated that the presence of institutional investors
results in less usage from dividend as a signal for good corporate performance. Moreover, positive
relationship was founded between dividend payout and concentrated institutional ownership. However,
there was not a significant relationship between managerial ownership and dividend payout.
Key words: Ownership structure, institutional ownership, concentrated institutional ownership, managerial
ownership, dividend policy.
INTRODUCTION
Dividend policy is one of the important components of
firm policies and has been viewed as an interesting issue
in the literature. Dividend payout decisions affect on the
firms valuation. Moreover, cash dividend has a special
position among the shareholders. However, the main
problem is the reasons for adopting a policy of divided
payout. Dividend policies depend on several factors. One
of these factors is corporate governance.
Corporate governance has recently received
considerable attention due to the financial scandals. The
reason for the attention is the interest conflicts among
shareholders in the corporate structure (Gillan and
Starks, 2003). Differences exist between the shareholder
types and the demand for dividend (Truong and Heaney,
2007). Among shareholder types, institutional shareholders
and managerial shareholders have a greater
influence on firm policies. The relationship between a
firm’s dividend policy and its ownership structure is
recognized in the established literature (Short et al.,
2002). Dividend policies vary across countries (Laporta et
al., 2000). Prior studies suggested significant differences
*Corresponding author. E-mail: heskandar@ut.ac.ir. Tel:
+989123846856.
in dividend policy between developed countries and
developing countries (Abdelsalam et al., 2008). Most
studies (Gillan and Starks, 1998; Claessens et al., 2000)
argued that corporate governance practices including
ownership structure are affected by environmental
characteristics. Therefore, the relationship between
ownership structure and divided policies is expected to
be different in various environments and countries.
This study examined the relationship between ownership
structure and dividend policy in Iran. The present
study proved to be different because a few studies
discussed the relationship between ownership structure
and dividend policy in developing countries. This study is
a case study of Iran which is a developing nation with
characteristics, different from those of developed
countries and many emerging economies and developing
nations like Malaysia and China (Mashayekhi and
Mashayekh, 2008). These environmental characteristics
will be discussed further.
Using an Iran panel data set, this paper examined the
possible relationship between dividend policy and
ownership structure. In particular, the role of institutional
ownership and managerial ownership in relation to
dividend policy was analyzed within the context of the
dividend models of Lintner (1956), Waud (1966) and
Fama and Babiak (1968). The evidence from four models

consistently showed negative (positive) and statistically
significant associations between institutional ownership
(concentrated institutional ownership) and dividend, and
thus suggested a link between institutional ownership and
dividend policy. However, there was not a significant link
between managerial ownership and dividend policy.
BACKGROUND AND MOTIVATION
The corporate environmental characteristics affect
corporate governance practices. Therefore, corporate
governance changes simultaneously with the environmental
changes. Corporate governance changes have
been common in countries with relatively high level of
institutional ownership and managerial ownership. These
investors play a key role in prompting change in many
corporate governance systems (Gillan and Starks, 2003).
Gillan and Starks (1998) argued that corporate
governance changes, including ownership structure, are
responses to environmental characteristics changes.
Claessens et al. (2000) show that corporate governance
and investors and creditors protections are stronger in
developed markets, as opposed to emerging markets like
Iran.
According to afore mentioned grounds, the studying of
ownership structure in Iran, a country with unique
environmental characteristics, is an interesting issue.
These characteristics include religion, culture, capital
market and ownership structure (Arabsalehi and
Velashani, 2009). Iran’s environmental characteristics are
described further.
Religion
Iran is an Islamic country located in the Middle East, a
politically troubled and unstable region of the world.
Therefore, business risk is high in this region. Searching
through ABI-Information data base, we were unable to
find a related study for adjacent countries such as Saudi
Arabia, Kuwait, Jordan, Syria, and of course, Iran. Islamic
revolution in 1979 intermingled politics and religion in
Iran. The revolution changed people’s vision of cultural
and social values. Consequently, social and business
activities were based on religious laws and regulations
(Mashayekhi and Bazaz, 2008). For example, Iranian
companies have few long-term liabilities because of the
forbiddance of bonds (Mashayekhi and Mashayekh,
2008). Therefore, firms generally finance by issuing of
common stock.
Capital market
Tehran Stock Exchange (TSE) was inaugurated in April
1968. Initially, only government bonds and certain statebacked
certificates traded on the market. During the
Mehrani et al. 7517
1970s, the need for capital increased the demand for
stocks. The transfer of shares of public companies to the
private sector led to the expansion of stock market
activity. The changes of the economy after the Islamic
Revolution in 1979 expanded public-sector control over
the economy and reduced the need for private capital
(Mashayekhi and Mashayekh, 2008). At the same time,
business activities based on fundamental religious laws
and regulations (Mashayekhi and Bazaz, 2008). Therefore,
the interest-bearing bonds were abolished because
Islamic law and regulations forbid interest. Thus, the TSE
experienced a period of standstill. This period ended in
1989 with the privatization of public companies and the
promotion of private-sector economic activity based in the
first five-year development plan of the country
(Mashayekhi and Mashayekh, 2008).
In recent years, the Iranian government has moved
towards privatization of governmental companies for the
fulfillment of Article 44 of Iranian constitution; therefore, it
began to sell their stocks on the stock exchange (Yegane
et al., 2008). Since then, the TSE has expanded
continuously.
Investors’ rights protection
Iran has an emerging and somewhat inefficient capital
market (Mashayekhi and Mashayekh, 2008). Emerging
markets often have less protection for shareholders and
creditors (Shaleifar and Vishny, 1998) and are less
efficient than developed markets (Walczak, 1999).
Therefore, the type and level of conflicts of interest are
different from those in developed markets. For example,
in emerging markets, the risk of expropriation of minority
shareholders by large shareholders is higher than in
developed markets (Claessens et al., 2000). Leuz et al.
(2003) state that in emerging countries like Iran, in which
investors protection rights are not well established or
legally enforced, and in which securities markets are not
huge with concentrated ownership, and in addition,
Iranian Trade Law being very old, allows firms to ignore
many requirements in Iranian Code of Corporate
Governance. According to this law, it is difficult for
minority shareholders to impose their rights against
management or controlling shareholders. Corporate
governance in Iran appears to optimize the interests of a
broader group of stakeholders rather than just
maximizing the interests of shareholders. In countries like
Iran, the main objective of the corporation does not
appear to be creating wealth for the shareholders (Allen,
2005).
Ownership structure
Several surveys have been conducted on ownership
structure In Iran. These surveys find that all the listed
companies are owned and controlled by few major

7518 Afr. J. Bus. Manage.
shareholders (Moradi, 2007). These shareholders are
often governmental and are divided into two major
groups: governmental and institutional investors that are
generally owned by the government. Now, institutional
investors own more than half of the publicly held stock on
the TSE (Mashayekhi and Mashayekh, 2008). Therefore,
governmental members occupy important seats in board
of directors (Mashayekhi and Bazaz, 2008).
According to Claessens et al. (2000), ‘…the direct
participation by government officials in the control of a
large part of the corporate sector opens up the possibility
of widespread conflicts between public and private
interests…’. For example, public sector shareholders may
apply the company’s resources to the provision of
cheaper goods and services or may not prefer dividend
distribution, which may impair private sector shareholder
interests. Another characteristic of ownership structure in
Iran is relating to managerial ownership. In most of the
Iranian companies, managers do not own their
companies stocks or may own little percentage of their
companies stocks (Moradi, 2007).
LITERATURE REVIEW AND HYPOTHESIS
DEVELOPMENT
Ownership structure is an influential factor on company
policies. Decisions regarding to dividend are one of the
fundamental components of corporate policies (Kouki and
Guizani, 2009). Therefore, a significant relationship
between ownership structure and dividend policy is
expected.
Institutional ownership and dividend policy
Institutional investors are large investors such as
insurance firms, banks, pension funds, financial
institutions, investment firms, and other nominee firms
associated with the mentioned categories of institutions
(Koh, 2003). The presence of institutional investors may
lead firms to change their behavior. They have the
influence on investee corporations and can affect their
policies because of their substantial shareholdings. One
of these policies is dividend policy. Significant
relationship between institutional ownership and dividend
policy is expected. There are different theories about this
relation. Two of these theories are more prevalent,
agency theory and signaling theory.
Agency theory
Agency theory refers to interest conflicts between the
manager (agent) and owner (employment). The first time,
Jensen and Mackling (1976) discussed the principles of
agency theory. Dividend policies are depending on the
alignment of ownership and control incentives. Agency
problems that arise from diversion of these incentives will
therefore affect payout dividend policy. The role played
by the institutional framework and related ownership
structures is thus important when dividend policies are to
be investigated (Wiberg, 2008).
The payment of dividends may act to help in reducing
agency costs because: (1) management is forced for
creating enough cash to pay dividends, (2) management
is forced for funding projects refers to their capital market
and naturally provide more information in the market and
(3) free cash flow decreases and does not waste (Laporta
et al., 2000).
Jensen’s (1986) suggested that extra cash is better to
pay as dividend in order to reduce managerial
discretionary funds and agency costs. Eckbo and Verma
(1994) showed that institutional investors prefer free cash
flow to be distributed in the form of dividends. The
agency perspective, therefore, hypothesizes a positive
relation between institutional ownership and dividend, as
institutions demand dividends in order to reduce the
agency costs of free cash flow (Short et al., 2002). An
increasing number of studies argue that institutional
investors help to resolve agency problems by monitoring
management. As a result, institutional ownership may
have a positive effect on agency costs, and consequently
on dividend policy (Han et al., 1999).
Truong and Heaney (2007) examined this relationship
among companies in 37 countries and showed that a
positive relationship exists between institutional ownership
and dividend payments. Wiberg (2008) reviewed the
relationship between research institutions ownership and
dividend policy among 189 Swedish companies. Results
showed that institutional ownership and dividend
payments are positively related.
Short et al. (2002) used the four models to examine this
relationship. Evidence showed a significant positive
relationship between these two variables in all four
models.
Signaling theory
This theory suggests that there is information asymmetry
between managers and stockholders. Managers have
internal information while stockholders do not. Managers
would take costly but credible measures to transfer this
information. One of these measures is dividend.
Therefore, dividend policy is a signal to transfer the
information relating to future profitability (Miller and Rock,
1985; Pettit, 1972).
Zeckhauser and Pound (1990) suggested that
dividends and institutional shareholders may be viewed
as alternative signaling devices. The presence of
institutional shareholders may mitigate the use of
dividend as a signal of good performance, as these
shareholders themselves can act as a (more) credible

signal. This hypothesis predicts a negative relation
between dividend and institutional shareholders.
Jensen et al. (1992) found the evidence of a negative
relationship between institutional ownership and dividend
payments. Jain (2007) showed that individual investors
prefer dividend-paying firms whereas institutional
investors typically prefer non-paying firms. Also, Barclay
et al. (2006) showed that institutional investors prefer
retains cash in the company to dividend distribution.
Kouki and Guizani (2009) analyzed this relation among
Tunisian companies. They used five linear regression
models. They concluded institutional ownership is
negatively associated with dividend. As a result, we
hypothesize that:
H1: There is a significant relationship between the
institutional ownership and dividend payout.
Concentrated institutional ownership and dividend
policy
In a related issue, prior researches examined the role of
concentrated institutional ownership (for example, block
holders). According to Shleifer and Vishny (1986), concentrated
institutional ownership creates the incentives to
monitor management, which overcomes the free-rider
problem. Several studies (Claessens and Djankov, 1999)
showed that concentrated institutional ownership contributes
to financial discipline and therefore fewer resources
consumed in low return projects and more cash flows can
be distributed as dividends. Also, Mitton (2005) showed
that firms with higher concentrated institutional ownership
pay higher dividends. Kouki and Guizani (2009) also
realized that with more ownership concentration in the
hands of institutions, dividend distribution would be
greater.
In contrast, Gugler and Yutoglu (2003) showed that
firms with high ownership concentration tend to pay lower
dividends. Also, Maury and Pajuste (2002) found a
significant negative relationship between concentrated
institutional ownership and dividend payments among
Finland companies. As a result, we hypothesize that:
H2: There is a significant relationship between
concentrated institutional ownership and dividend payout.
Managerial ownership and dividend policy
An important body of literature exists on how ownership
structure influences dividend policies. Especially the link
between managerial ownership and dividend policies has
been well documented (Wiberg, 2008). Jensen’s (1986)
free cash flow theory suggests that managers are
reluctant to pay out dividends, preferring instead to retain
resources under their control.
Mehrani et al. 7519
The evidence shows that dividend decreases as the
increasing of the voting power of owner-managers, and
is almost zero when owner-managers have absolute
control, while it is always positive when firms controlled
by institutional shareholders (Eckbo and Verma, 1994).
Short et al. (2002) found a negative association between
dividend payout and managerial ownership. Chen et al.
(2005) found a negative relationship between managerial
ownership and dividend policy in Hong Kong. Jensen et
al. (1992) showed that managerial ownership is associated
with significantly lower dividend payout among US
firms. Farinha (2003) documented a similar negative
relationship in UK. As a result, we hypothesize that:
H3: There is a significant relationship between
managerial ownership and dividend payout.
Control variables
Given that ownership structure is not the sole affecting
factor on dividend policy, several control variables
introduced to isolate other contracting incentives that
have been found to influence dividend policy. These
control variables are size, leverage (LEV), market-tobook
value (MTBV) and free cash flow (FCF).
Size
This is defined as natural logarithm of total assets. Fama
and French (2001) and Grullon and Michaely (2002)
documented that firms with more assets have higher
dividend payout. However, Gugler and Yurtuglu (2003)
and Farinha (2003) showed that dividend payouts are
negatively associated with firm size.
Leverage (LEV)
This is defined as long-term debts to total assets.
According to Jensen and Meckling (1976), and Stulz
(1988), leverage has an important role in monitoring
managers and reducing agency costs. Moreover, some
debt contracts limit dividend payout. Therefore, we
expect a negative relationship between payout and
leverage. Fama and French (2001) and Grullon and
Michaely (2002) found companies with less leverage
have more incentive to pay dividends.
Market-to-book value (MTBV)
Batacharya’s (1979) found that dividend policy negatively
affected by MTBV of the firm. Also, Batacharya (1979)
used the market-to-book ratio as a proxy for future
investment opportunities and find firms with lower MTBV

7520 Afr. J. Bus. Manage.
have a more incentive to pay dividends. In contrast, Gul
(1999) reported MTBV has little influence on dividend
payouts in Japan.
Free cash flow
This is defined as free cash flow per unit of asset.
Crutchley and Hansen (1989) define FCF as the funds
available to managers before discretionary capital
investment decisions. FCF is calculated as a subtraction
of company's capital expenditures from its cash flow from
operations.
Kouki and Guizani (2009) show a strong effect of the
free cash flow on dividend policy. The more available
cash, the higher the dividend per share.
METHODOLOGY
Models
Similar to Short et al. (2002), in this study, four models were used to
test the hypothesized link between ownership structure and
dividend policy: Lintner Models (1956) (the full adjustment model
and the partial adjustment model), the Waud model (1966) and
Fama and Babiak model (2001) (earnings trend model). Further
discussion explains these models.
The full adjustment model (FAM)
If income changes are considered permanent and a firm has a
desired payout ratio r, then the relationship between changes in
earnings (E) and changes in dividends (D), for firm i at time t, will be
given by:
Dti – D (t-1)i = α + r (Eti – E(t-1)i)
Firms with institutional ownership and managerial ownership may
have a different r. therefore, the model becomes:
Dti – D (t-1) i = α + r (Eti – E (t-1) i) + rI (Eti – E (t-1) i) × INST+ rC (Eti – E (t-1)
i) ×CONC + rM(Eti – E (t-1) i) × M
Also, we include control variables. Therefore, this model will be as
follows:
Dti – D (t-1) i = α + r (Eti – E (t-1) i) + rI (Eti – E (t-1) i) × INST+ rC (Eti – E
(t-1) i) ×CONC + rM (Eti – E (t-1) i) × M + rSSIZE+ rLLEV+ rMMTBV +
rOFCF +ε (1)
Where; D: the total amount of ordinary dividends related to the
accounting year; E: net profit derived from normal trading activities
after depreciation and other operating provisions; INST: the
percentage of equity held by institutions at the beginning of the
accounting year; CONC: the sum of square of institutions ownership
percentage at the beginning of the accounting year; M: total
percentage of equity owned by directors at the beginning of the
accounting year; SIZE: natural logarithm of total assets; LEV: longterm
debts to total assets; MTBV: market to book value of
stockholders equity; FCF: capital expenditures minus operating
cash flow; ε: error term.
The partial adjustment model (PAM)
This model assumes that for any year, t, the target level of dividend,
D * , for firm i at time t is relating to profits, Eti, by a desired payout
ratio, r:
Dti * =r Eti
Firms with institutional ownership and managerial ownership may
have a different r, therefore, the model becomes:
Dti * =r Eti + rI Eti× INST+ rC Eti× CONC+ rM Eti×M
In any given year, the firm adjusts only partially to the target
dividend level. Thus:
Dti – D (t-1) i = α + c (Dti * - D (t-1) i)
where α = a constant representing the resistance of management to
reduce dividends, and c equals the ‘speed of adjustment coefficient’
which represents the extent to which the management wishes to
‘play-safe’ by not adjusting to the new target immediately.
Substitution yields the following reduced form:
Dti – D (t-1) i =α + cr Eti + crI Eti×INST+ crCEti× CONC + crM Eti×M -c D
(t-1) i
Also, we include control variables. Therefore, this model will be as
follows:
Dti – D (t-1) i = α + c r Eti+ c rI Eti× INST + crCEti× CONC+ crM Eti×M –
c D (t-1) i + rSSIZE+ rLLEV+ rMMTBV + rOFCF +ε (2)
Variables are defined as in the full adjustment model.
The Waud model (WM)
The Waud model includes elements of both partial and full
adjustment model. This model assumes that the target dividends,
D * , for firm i at time t, are proportional to the long-term expected
earnings, E * :
Dti * =r Eti *
Also, it is assumed that the actual dividend change follows a partial
adjustment mechanism:
Dti – D (t-1) i = α + c (Dti * - D (t-1) i)
The formation of expectations follows an adaptive expectation
model:
Eti * –E (t-1) i * = α + d (Eti–E (t-1) i * )
Assuming a possible difference in payout ratio for firms with
institutional and managerial ownership, the reduced form becomes:
Dti – D (t-1) i = αd + cdr Eti+ cdrI Eti× INST+ cdrC Eti× CONC+ cdrM Eti×
M + (1– d – c) D (t-1) i – (1– d) (1– c) D (t-2) i
Also, we include control variables. Therefore, this model will be as
follows:
Dti – D (t-1) i = αd + cdrEti+ cdrIEti× INST+ cdrC Eti× CONC+ cdrM Eti×
M+ (1– d – c) D (t-1) i – (1– d) (1– c) D (t-2) i + rSSIZE+ rLLEV+
rMMTBV + rOFCF +ε (3)

Variables are defined as in the full adjustment model.
Earnings trend model (ETM)
The earnings trend model is represented by Fama and Babiak
(2001). It is a modified partial adjustment model. It assumes that:
Eti = (1+j) E (t-1) i
j is an earnings trend factor. Assuming a possible difference in the
earnings trend factor for firms with institutional and managerial
ownership, the model becomes:
Eti= E (t-1) i + j E (t-1) i+ jI E (t-1) i× INST + jC E (t-1) i× CONC+ jM E (t-1) i× M
Target dividends is given by:
Dti * =r Eti *
It is assumed that there is full adjustment of dividends to the
expected change, that is:
j E (t-1) i+ jI E (t-1) i× INST + jC E (t-1) i× CONC+ jM E (t-1) i× M
and partial adjustment to the reminder. The resulting reduced form
is:
Dti – D (t-1) i = α +c[r (Eti– j E (t-1) i – jI E (t-1) i× INST – jC E (t-1) i× CONC–
jME (t-1) i× M) – D (t-1) i] +rj E (t-1) i+ rjI E (t-1) i× INST + rjC E (t-1) i×
CONC+ rjM E (t-1) i× M
Arranging, the reduced form becomes:
Dti – D (t-1) i = α + rc Eti +rj(1-c) E (t-1) i+ rjI (1-c) E (t-1) i× INST+ rjC (1-c)
E (t-1) i× CONC+ rjM (1-c) E (t-1) i× M– c D (t-1) i
Also, we include control variables. Therefore, this model will be as
follows:
Dti –D (t-1) i =α + rc Eti+rj(1-c) E (t-1) i+ rjI (1-c) E (t-1) i× INST+rjC (1-c) E
(t-1) i× CONC + rjM (1-c) E (t-1) i× M– c D (t-1) i + rSSIZE+ rLLEV+
rMMTBV + rOFCF +ε (4)
Variables are defined as in the full adjustment model.
In four models, the coefficients rI, rC and rM denote the respective
impacts of institutional ownership, concentrated institutional
ownership and managerial ownership on dividend payout.
Sample selection
The sample for this study is comprised of all firms listed in TSE
excluding financial firms. We collected ownership structure and
financial and accounting data directly from annual reports and TSE
reports on CDs and web.
In this study, sample period is from 2000 to 2007. We selected
firms, which their fiscal years end is the end of calendar year, and
excluded the firms with insufficient data.
To mitigate the effect of outliers for all variables, we deleted
observations that had values three standard deviations from their
respective means. Finally, our sample consists of 427 firms-years
observations.
RESULTS
Descriptive statistics
Mehrani et al. 7521
We represent the results of four regression models. Table
1 describes sample firms’ characteristics in our sample.
The table shows that institutional ownership averagely
includes 45% of ownership structure in the sample
companies and this ownership is relatively concentrated.
Moreover, managerial ownership includes very little
percentage from ownership structure in the Iranian
companies.
The mean long-term debt is approximately 8% of total
assets. This means that Iranian companies have few
long-term liabilities. It may be interpreted Iran is Islamic
country and companies have few long-term liabilities
because of forbiddance of bonds. Market value is
averagely 4.53 fold of book value of stockholders equity.
The mean size is approximately 25. Finally, free cash
flow is averagely 18% of assets.
Empirical results
Table 2 shows the results of model (1). The table shows
that the level of institutional investment is negatively
associated with distributed dividend (coeff. = -9.03, pvalue
= 0.000). Concentrated institutional ownership
variable is positively associated with distributed dividend
(coeff. = 13.52, p-value = 0.000). However, managerial
ownership is not significantly associated with distributed
dividend (coeff. = -4.35, p-value = 0.840).
The table also shows a direct relationship between
earnings and dividend payout while the control variables
(Size, LEV, MTBV and FCF) do not have a significant
relationship with the dividend payout. Table 3 shows the
results of model (2). Institutional ownership is negatively
associated with distributed dividend (coeff. = -2.51, pvalue
= 0.000). A significant positive relationship exists
between dividend payments and concentrated
institutional ownership (coeff. = 3.89, p-value = 0.056).
Managerial ownership is not significantly associated with
distributed dividend (coeff. = -1.48, p-value = 0.763).
The table also shows that a positive relationship exists
between earnings and dividend payments. There is
significantly positive association between size and
dividend payments. However, LEV, MTBV and FCF are
not significantly relating to dividend payments. Table 4
shows the results of model (3).
Concentrated institutional ownership is positively
associated with the dependent variable (coeff. = 3.57, pvalue
= 0.000). While the table shows institutional
ownership is negatively associated with distributed
dividend (coeff. = -2.17, p-value = 0.000), managerial
ownership is not significantly associated with distributed
dividend (coeff. = -1.64, p-value = 0.715). Firm earnings,
size are positively associated with distributed dividend.
Other control variables are not significantly associated

7522 Afr. J. Bus. Manage.
Table 1. Descriptive statistics.
Variable MIN MAX MEAN SD
Dti – D (t-1) i -5289126.30 -2907157.00 1004.45 374646.05
INST 0.00 0.99 0.45 0.31
CONC 0.00 0.88 0.17 0.19
M 0.00 0.52 0.02 0.5
Eti – E(t-1)i -443360.00 2889601.00 35911.22 216458.29
(Eti – E(t-1)i) × INST -147296.00 682812.70 10336.07 57025.01
(Eti – E(t-1)i) × CONC -111420.00 99169.84 2246.94 14092.08
(Eti – E(t-1)i) × M -6647.68 7254.45 52.82 759.54
Eti -95468.00 6814114.00 184101.51 683834.65
Eti× INST -72555.70 1875926.00 64898.05 172636.66
Eti× CONC -28583.10 278896.60 18915.01 36570.18
Eti× M -32.40 14618.40 684.11 1729.14
E(t-1)i -95468.00 5338834.00 148190.29 512544.36
E(t-1)i × INST -76269.40 1475120.00 54561.97 138250.38
E(t-1)i × CONC -28647.40 217755.70 16667.57 32465.96
E(t-1)i × M -32.54 19391.32 631.29 1730.64
D (t-1) i 0.00 5353892.00 142239.62 511718.60
D (t-2) i 0.00 5353892.00 124057.46 461895.25
Size 19.94 31.59 25.23 2.19
LEV 0.00 0.41 0.08 0.07
MTBV 0.31 38.73 4.53 5.47
FCF -0.96 24.66 0.18 1.21
Table 2. The results of model (1).
Model (1) Coefficient t- statistic P-value
constant -170827.11 -0.88 0.382
(Eti – E(t-1)i) 2.41 8.21 0.000***
(Eti – E(t-1)i) × INST -9.03 -6.38 0.000***
(Eti – E(t-1)i) × CONC 13.52 5.49 0.000***
(Eti – E(t-1)i) × M -4.35 -0.20 0.840
Size 5545.16 0.71 0.477
LEV -10119.02 -0.04 0.966
MTBV 1553.63 0.50 0.618
FCF 2308.56 0.17 0.865
Adjusted R square 21.40%
F 15.50
***, **, * denote significance at 0.001, 0.05, and 0.10 levels, respectively, based on t-tests (two-tail).
with distributed dividend.
Table 5 shows the results of model (4). Concentrated
institutional ownership is positively correlated with
dividend (coeff. = 5.20, p-value = 0.000) while institutional
ownership is negatively associated with distributed
dividend (coeff. = -3.22, p-value = 0.000) and managerial
ownership is not significantly associated with distributed
dividend (coeff. = 1.55, p-value = 0.731). Firm size is
positively associated with distributed dividend but other
control variables are not significantly associated with
distributed dividend.
CONCLUSIONS AND SUGGESTIONS
This paper contributes to the ongoing debate about the
role of ownership structure, as one of corporate
governance mechanisms, in firm policies. It examined the

Table 3. The results of model (2).
Model (2) Coefficient t- statistic P-Value
constant -403792.22 -3.93 0.000
Eti 1.12 22.73 0.000***
Eti × INST -2.51 -11.10 0.000***
Eti × CONC 3.89 8.25 0.056*
Eti × M -1.48 -0.30 0.763
D (t-1) i -0.88 -36.49 0.000***
Size 0.95 4.04 0.000***
LEV -111010.98 -0.90 0.368
MTBV 2625.75 1.58 0.114
FCF 5429.12 0.77 0.441
Adjusted R square 79.00%
F 177.73
***, **, * denote significance at 0.001, 0.05, and 0.10 levels, respectively, based on t-tests (two-tail).
Table 4. The results of model (3).
Model (3) Coefficient t- statistic P-value
constant -346331.97 -3.67 0.021
Eti 1.15 25.44 0.000***
Eti × INST -2.17 -10.33 0.000***
Eti × CONC 3.57 8.24 0.000***
Eti × M -1.64 -0.36 0.715
D (t-1) i -0.95 -39.21 0.000***
D (t-2) i -0.22 -8.97 0.023**
Size 14552.05 3.86 0.000***
LEV -86667.71 -0.77 0.443
MTBV 1709.84 1.12 0.262
FCF 3414.04 0.53 0.597
Adjusted R Square 82.40%
F 198.757
***, **, * denote significance at 0.001, 0.05, and 0.10 levels, respectively, based on t-tests (two-tail).
relationship between ownership structure and dividend
policy in Iran, a country with unique environmental
characteristics.
In this study, four regression models were used. The
results demonstrated evidence on a negative association
between institutional ownership and dividend payout. It
showed that the presence of institutional investors results
in less usage from dividend as signal for good firm
performance. This result is in line with Jain (2007), and
Barclay et al. (2006). Also, in all four models, positive
relationship was founded between dividend payout and
concentrated institutional ownership. In other word, firms
are forced to distribute more dividends for decreasing the
agency costs when big institutional investors exist in
ownership structure. This result was in line with Kouki
and Guizani (2009).
Based on findings, managerial ownership was not
Mehrani et al. 7523
significantly associated with dividend payout. It is
because managers-owners have a little percentage of
ownership in the Iranian firms and they can’t affect on
dividend payout. Moreover, in most of the models, a
positive relationship was found between size and
dividend payments. It showed that larger firms distribute
more dividends. It indicates that managers of big firms
are politically more sensitive and they prefer to decrease
political costs by distributing dividend.
Findings from this study are useful to regulators for
future directions in TSE. Moreover, the results may be
helpful to investors for predicting firms’ dividend payouts
and consequently, valuation of their stocks. Future research
might consider the relationship between dividend
policy and other corporate governance mechanisms,
such as characteristics board of directors, auditors,
internal control and so on, which might influence dividend

7524 Afr. J. Bus. Manage.
payout decisions.
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Table 5. The results of model (4).
Model (4) Coefficient t- statistic P-Value
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Eti 0.97 1.55 0.122
E(t-1) i 0.10 1.34 0.047**
E(t-1) i × INST -3.22 -13.15 0.000***
E(t-1) i × CONC 5.20 10.53 0.000***
E(t-1) i × M 1.55 0.34 0.731
D (t-1) i -0.88 -32.70 0.000***
Size 13244.80 3.46 0.001***
LEV -112619.85 -0.99 0.323
MTBV 1109.80 0.74 0.459
FCF 7982.69 1.23 0.220
Adjusted R Square 82.10%
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African Journal of Business Management Vol. 5(17), pp. 7526-7532, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.581
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Exploring the efficiency of international tourism
development in an emerging market
Meng-Chun Kao 1 , Che-Yang Lin 1 *, Mei-Chi Lai 2 and Hao-Chen Huang 3
1 Department of Finance, Yuanpei University, No.306, Yuanpei Street, Hsinchu 30015, Taiwan, R.O.C.
2 Institute of Health Policy and Management, National Taiwan University, 6F., No.17, Syujhou Road, Taipei, 100,
Taiwan, R.O.C.
3 Graduate Institute of Finance, Economics, and Business Decision, National Kaohsiung University of Applied Sciences,
No. 415, Chien Kung Road, Kaohsiung, 807, Taiwan, R.O.C.
Accepted 23 June, 2011
This work combines several analytical techniques, including data envelopment analysis (DEA) models
and the canonical analysis model, in order to shed new light on the relative efficiency of international
tourism development. This study analyzes the international tourism development in the 31 regions of
China. For the analysis, we take the following inputs into consideration: the number of international
travel agencies, employees of international travel agencies. As regards the outputs, we choose the
number of international tourists, sales for international travel agencies, and foreign exchange earnings
from travel. In the first stage, we use the canonical analysis model to investigate the correlations of
related variables. In the second stage, we adopt DEA models, including Charnes, Cooper, and Rhodes
(CCR), Banker, Charnes, and Cooper (BCC) and slacks-based measure (SBM), to analyze the relative
efficiency of international tourism development. Finally, we provide some management suggestions for
the development of international tourism industry in emerging China.
Key words: International tourism industry, canonical analysis, data envelopment analysis (DEA), slacks-based
measure (SBM).
INTRODUCTION
Tourism is one of the fastest growing industries in many
emerging countries such as China, Korea, and India. The
Chinese government views the tourism industry as an
engine for economic growth and has taken various
measures to support it (Huang et al., 2007). Statistics and
information from the Ministry of Tourism show that China
has designated 99 cities as famous historical and cultural
cities of national caliber, and has placed 750 cultural
relics under key protection. There are also 119 national
scenic and tourist resorts across the land. Nineteen
Chinese scenes and sights have appeared on a
UNESCO (United Nations Educational, Scientific and
Cultural Organization) list of natural and cultural heritage
sites. China’s venerated history and splendid culture have
resulted in a land that is pockmarked with cultural relics
*Corresponding author. E-mail: lincy@mail.ypu.edu.tw.
and treasures. Not only that the Chinese tourism industry
is rich in resources, but it also has come a long way in
terms of transportation, service, accommodation, catering
and shopping facilities, and recreation. Due to the
Chinese government’s recently launched projects to support
its tourism development, tourist facilities and service
qualities are being constantly improved. Furthermore,
international events such as the 2008 Beijing Olympic
Games, the 2010 World Exposition, and the 2010 Asian
Games are all closely related to the development of
Chinese tourism industry. Therefore, the tourism industry
and the number of international travel agencies have
grown rapidly in China. By employing the data envelopment
analysis (DEA) as the analytical tool, this work
attempts to answer the following questions that which
region performs better in terms of productivity of international
tourism industry development and whether the host
cities or regions of international sporting events perform
better in terms of the relative efficiency of international

tourism industry development.
In this work, we measure the relative efficiency of international
tourism industry development in emerging China.
The purposes of this work are to measure the productive
efficiency of international travel agencies in an emerging
country.
The methodology used to perform efficiency analysis
of the international travel agencies is data envelopment
analysis (DEA). DEA is a linear programming-based technique
that converts multiple input and output measures
into a single comprehensive measure of productivity
efficiency (Charnes et al., 1978; Epstein and Henderson,
1989; Boussofiane et al., 1991; Mota et al., 1999;
Medina-Borja and Triantis, 2007). Moreover, DEA is nonparametric,
and therefore it does not require a prior
assumption about the form of the production function to
eliminate the possibility of the misspecification. Unlike
other frontier approaches that define input-output relationships
by estimating a true production frontier, DEA
uses actual input-output data to construct a best practice
frontier.
DEA has been widely applied to examine the
performance and the efficiency of the tourism industry. A
number of studies have considered the measurement of
the hotel efficiency (Parkan, 1996; Hwang and Chang,
2003; Barros and Alves, 2004; Chiang et al., 2004;
Barros, 2005; Wang et al., 2006; Yang and Lu, 2006;
Haugland et al., 2007; Shang et al., 2008; and Hsieh et
al., 2010). Some of the studies utilized the DEA procedure
to evaluate managerial efficiency of hotels in Taiwan
(Hwang and Chang 2003; Wang et al. 2006). Chiang et al.
(2004) compared hotel performance under different
structures of international tourist hotels in Taiwan. Barros
(2005) estimated the efficiency of 43 Enatur hotels in
Portugal by DEA. Shang et al. (2008) measured the
ecommerce and hotel performance by applying DEA.
Hsieh et al. (2010) also used DEA to measure the operational
efficiency and effectiveness of international hotels
in Taiwan.
According to the prior studies, the inputs are summarized
including the number of employees, the number of
guest rooms, food and beverage capacity and total cost
as well as the outputs including the number of guests and
various revenues such as room revenue, food and beverage
revenue and other revenue. Moreover, Koksal and
Aksu, (2007) considered three inputs, the number of staff,
annual expenses and service capacity and one output
variable, the number of customers to explore the
efficiency of travel agencies in the Turkey. There are few
studies to measure the efficiency of travel agencies that
can be attributed to the lack of data. Furthermore, no
studies on the relative efficiency of international tourism
industry or international travel agencies in China have
been done. In this work, we discuss the relative efficiency
of inputs and outputs for international travel agencies to
explore the performance of regional international tourism
industry in China.
METHODOLOGY AND DATA
Data envelopment analysis
Kao et al. 7527
Farrell (1957) introduced a framework for efficiency evaluation and
measurement, which was subsequently studied by Charnes et al.
(1978), Banker et al. (1984) and others. Charnes et al. (1978)
extended Farrell’s model to multiple inputs and outputs. They
utilized mathematical programming to develop an efficient frontier
and to estimate the efficiency score. The CCR model, named after
Charnes, Cooper, and Rhodes (1978), was limited to the following
three restrictions: (1) constant returns to scales (CRS), (2) strong
disposability of inputs and outputs, and (3) convexity of the set of
feasible input-output combinations. For any special DMUs, the CCR
model with constant return to scale can be formulated as follows to
obtain a score of technical efficiency:
Maximize
0 = ∑u
r
s.t. ∑ vi xij0
= 1,
∑
r
ur vi i
u
r
y
rj
w r yrj0
−∑
i
v x
i
ij
≤ 0, j = 1,...,
n,
≥ ε , r = 1,...,
s,
(1)
≥ ε , i = 1,...,
m
where m is the number of inputs, and s is the number of
outputs.
The BCC model, named after Banker, Charnes, and Cooper
(1984), was developed by relaxing the CCR model or the constant
returns to scale assumption on the envelopment surface. The
∑ j
constraint λ = 1 is added to the aforemrntioned mathematical
formulation of the CCR model. We can achieve discrimination
between departures due to pure technical inefficiency or to scale
inefficiency.
Tone (2001) has proposed a slacks-based measure (SBM), which
is non-radial and deals with input/ output slacks directly. The SBM
returns an efficiency measure between 0 and 1, and gives unity if
and only if the DMU concerned is on the frontiers of the production
possibility set without input/output slacks. In order to estimate the
efficiency of a DMU ( x 0 , y0
), we formulate the following fractional
− +
program in λ , s ,and s :
Min
s.t.
1
m
−
1−
∑ si
/ xi0
m i=
1
ρ ,
= s 1
1+
s
x = Xλ
+ s
0
∑
y = Yλ
+ s
0
r=
1
−
,
−
,
s
+
r
/ y
− +
λ ≥ 0 , s ≥ 0 , ≥ 0
r0
s . (2)
In this model, we assume that X ≥ 0 . If x i0
=0, then we delete
the term si / si
0
−
in the objective function. If y ro ≤ 0 , then we
replace it with a very small positive number so that the term
s r / yr
0
+
plays the role of a penalty.
One of the DEA models, the bilateral comparison model,

7528 Afr. J. Bus. Manage.
Table 1. Canonical structure matrix.
Input canonical variable Human resources (W1) Equipment resources (W2)
Number of International travel agencies (X1) -0.6055* -0.7958*
Employees of international travel agencies (X2) -0.9903* -0.1388
Output canonical variable Service revenue (V1) Reception services (V2)
Number of International Tourists (Y1) -0.8457* -0.5273*
Sales for international travel agencies (Y2) -0.9039* -0.2457
Foreign exchange earnings from travel (Y3) -0.9090* -0.2004
”*” Canonical loadings>0.5.
measured and compared efficiency between the host cities or
regions of international sporting events (Group I) and other regions
(Group II). The bilateral comparison model tested the null
hypothesis that the efficiency of DMUs in the two studied groups
belongs to the same statistical distribution obtained using
nonparametric rank-sum statistics. The data format is the same as
the CAT model, where the only level numbers assigned are I or II.
This idea is formulated as follows for each DMU:
Min θ
s.t.
∑ ∈
j
II
∑ ∈
j
j
II
j
X λ ≤ θX
Y λ ≥ θY
j
j
,
k
λ ≥ 0 ( ∀j∈
II)
j
,
k
k ∈ I ,
k ∈ I ,
where θ denotes the efficiency score of international tourism
industry
Data selection and definitions of variables
Mainland China has 31 regions 1 , including autonomous regions and
municipalities. Consequently, thirty-one regions were subjected to
empirical analysis in this study. Data from the China statistics
database were used to determine the relative efficiency of these
regions in China.
In this work, international travel agencies provided two inputs,
which produced the outputs. Constructing the models allowed us to
investigate the relative efficiency scores for international travel
agencies. According to the prior studies, the inputs and outputs are
selected as follows. The two inputs in the operational performance
model are the number of international travel agencies ( x ) and
employees of international travel agencies (
(3)
x ). Identifying the
2
output of productive activities in general and of international travel
agencies in particular presents difficulties for cost measurement
and also production performance. The three outputs used here
were the number of international tourists ( y ), sales for international
1
travel agencies (
y ), and foreign exchange earnings from travel
2
1 The DMUs contain China 31 regions including Beijing, Tianjing, Hebei,
Shanxi, Inner Mogolia, Liaoning, Jilin, Heilongjiang, Shanghai, Jiangsu,
Zhejiang, Anhui, Fujian, Jiangxi, Shandong, Henan, Hubei, Hunan, Guangdong,
Guangxi, Hainan, Chongqing, Sichuan, Guizhou, Yunnan, Shaanxi, Gansu,
Qinghai, Ningxja, Xinjiang, and Tibet.
1
( y ).These variables were defined as follows:
3
(1) Number of international travel agencies ( x 1 ): Number of total
international travel agencies.
(2) Employees of international travel agencies ( x 2 ): The total
number of employees who are full-time employees of international
travel agencies.
(3) Number of international tourists (ten thousand) ( y 1 ): Number of
tourists served by the international tourist agencies.
(4) Sales for international travel agencies (million RMB) ( y 2 ): Total
sales revenue generating from international travel agencies.
(5) Foreign exchange earnings from travel (million RMB) ( y 3 ):
Total sales revenue generating from travel.
RESULTS
Correlation analysis
First, Pearson correlation test is utilized to measure the
relationship between input and output variables. The
result shows that the correlations of outputs and inputs
are all positive and the correlation coefficients are all
above 0.8 significantly at 1%, indicating a highly relevant
level. Furthermore, we used canonical correlation analysis
(CCA) to reduce the dimension and investigate the
correlations to quantify the associations between these
two sets of variables, that is, the strength of the two sets
of variables. The canonical correlation analysis revealed
a significant correlation between the dynamics of the
inputs and outputs variables. Canonical structure matrix
generated the canonical variables, (W1 ,V1) and (W2 ,V2),
as shown in Table 1. The results of canonical correlation
analysis revealed a canonical first correlation value of
0.9332 ( 2
χ =71.774, p-value < 0.01), and a second
2
correlation value of 0.6759 ( χ =16.484, p-value < 0.01),
as shown in Table 2. Figure 1 shows that the canonical
first correlation revealed a significant correlation between
human resources and service revenue (ρ1=0.9332), and
a significant correlation between equipment resources
and reception services (p2= 0.6759).

Table 2. Canonical correlation.
2
Canonical correlation Canonical Coefficients (ρm) df χ
Kao et al. 7529
P-value
ρ1 0.9332*** 6 71.774 0.0000
ρ2 0.6759*** 2 16.484 0.0002
* Significant at the 0.01 level, ** significant at the 0.05 level, ***significant at the 0.1 level.
Figure 1. Canonical correlation.
Efficiency analysis
Table 3. Summary statistics and correlation analysis for efficiency measures (N=31).
Variable CCR BCC SBM
CCR 1
BCC 0.73** 1
SBM 0.99** 0.73** 1
Mean 0.518 0.658 0.474
S.D 0.253 0.200 0.249
Max. 1 1 1
Min. 0.100 0.381 0.091
No. of efficient DMUs 3 (9.67%) 5 (16.12%) 3 (9.67%)
* Significant at the 0.01 level, ** significant at the 0.05 level, ***significant at the 0.1 level.
In this work, the DEA analysis models included CCR,
BCC, and the SBM. DEA provides a comprehensive evaluation
of overall performance. The results for each DEA
model are summarized in Tables 3 and 4. First, an
elementary insight is obtained by considering the
dichotomous classification of DMUs as either efficient or
inefficient. The number of efficient DMUs resulting from
the use of different reference technologies is shown in the
last row of Table 3. In addition, Table 3 contains some
descriptive statistics for each of the three DEA models
and also shows the Pearson correlation coefficients for
several of these DEA models, including CCR, BCC, and
SBM. The correlation analysis results show a positive
relationship among the DEA models investigated in this
study.Table 4 presents the CCR efficiency scores under
constant returns-to-scale, BCC technical efficiency scores,

7530 Afr. J. Bus. Manage.
Table 4. Efficiency scores of DEA models for 31 DMUs.
DMU CCR BCC Scale SBM Reference set Reference frequency Group Ranking
1 1 1 1 1 1 14 I 1
2 0.818 0.956 0.855 0.716 9, 26 0 II 5
3 0.728 0.768 0.947 0.626 9, 26 0 II 7
4 0.261 0.469 0.556 0.220 1, 9, 26 0 II 26
5 0.774 0.785 0.985 0.669 9, 26 0 II 6
6 0.556 0.597 0.931 0.478 9, 26 0 II 14
7 0.397 0.490 0.810 0.343 9, 26 0 II 20
8 0.524 0.569 0.920 0.452 9, 26 0 II 16
9 1 1 1 1 9 27 I 1
10 0.726 0.749 0.969 0.721 1, 9 0 II 8
11 0.575 0.621 0.925 0.573 1, 9, 26 0 II 12
12 0.293 0.400 0.732 0.245 1, 9, 26 0 II 23
13 0.621 0.695 0.893 0.580 9 0 II 10
14 0.219 0.514 0.426 0.180 1, 9, 26 0 II 29
15 0.551 0.571 0.964 0.475 9, 26 0 II 15
16 0.418 0.546 0.765 0.368 1, 9, 26 0 II 18
17 0.493 0.645 0.764 0.379 9 0 II 17
18 0.309 0.431 0.716 0.297 1, 9, 26 0 II 22
19 0.895 1 0.895 0.764 9 0 II 4
20 0.410 0.455 0.901 0.388 1, 9, 26 0 II 19
21 0.289 0.410 0.704 0.277 1, 9 0 II 24
22 0.665 0.835 0.796 0.649 1, 9 0 II 9
23 0.337 0.422 0.798 0.303 9 0 II 21
24 0.242 0.672 0.360 0.237 1, 9, 26 0 II 28
25 0.558 0.632 0.882 0.463 9 0 II 13
26 1 1 1 1 26 20 I 1
27 0.603 0.677 0.890 0.579 9, 26 0 II 11
28 0.251 0.464 0.540 0.224 9, 26 0 II 27
29 0.100 0.661 0.151 9.13E-02 1, 9, 26 0 II 31
30 0.165 1 0.165 0.146 1, 26 0 II 30
31 0.287 0.381 0.753 0.242 1, 9, 26 0 II 25
“1”: Guangdong, “9”: Beijing, and “26”: Shanghai; “CRS”: constant returns-to-scale, “DRS”: decreasing returns-to-scale, “IRS”: increasing returnsto-scale;
“Group I”: the host cities or regions of international sporting events, “Group II”: other regions.
scale efficiency scores, and slacks-based measure
efficiency scores. The main findings can be summarized
further. The CCR efficiency score analysis results show
that three regions (Beijing, Shanghai, and Guangdong)
are relatively efficient based on the same scale efficiency
scores and SBM efficiency scores. Their efficiency scores
are all equal to 1. This result shows that resource utilization
for these regions were excellent. On the other
hand, 28 regions were found to be inefficient because
their efficiency scores were less than 1. The scale
efficiency scores as defined by the ratio CCR/BCC show
large differences between the two groups. The average
scale efficiency score was 0.7739. Of the 31 regions, 21
re-gions have low BCC efficiency scores and relatively
high scale efficiency scores, meaning that the inefficiency
of these regions as shown in the CCR model is caused
by inefficient operations rather than scale inefficiency. Of
the 31 regions, two regions have BCC efficiency scores
equal to 1 and relatively low scale efficiency scores. This
result suggests that the CCR inefficiency scores can be
mainly attributed to disadvantageous conditions.
The reference set and their frequencies for the 31
regions are also given in Table 4. The most frequent
reference province was found to be Beijing. The results
also show that Beijing, Shanghai, and Guangdong are
efficient and are in the reference set of all of the other
provinces.
Bilateral analysis
This work applies the bilateral comparison method to

Table 5. Bilateral analysis and rank-sum-test.
Group Number Average DEA-score Rank sum Z-value
Group I
Group II
3
28
1.000
0.466
3
490
-4.611*
* Significant at the 0.01 level
international tourism industry to determine the statistical
difference in technical efficiency between the host cities
or regions of international sporting events (Group I) and
other regions (Group II) in the bilateral model.
Thus, Group I comprised three regions, while Group II
comprised twenty-eight regions. The rank-sum-test
method is used to compare the DEA scores of the two
groups. The Rank-Sum-Test (Mann-Whitney) method is a
nonparametric test based on the ranking of data. Given
independent data belonging to two groups, this method
can be used to test the hypothesis that the two groups
belong to the same population. In this work, the rank sum
for the host cities or regions is 3, compared to 490 for
other regions. Z-values can be used to check the significance
of the two groups having different efficiency scores
at a given level of significance (α). Table 5 lists the result.
The result suggests that host cities or regions of international
sport have higher operational efficiency than other
regions, indicating that these host cities or regions
outperform other regions.
Conclusion
According to the statistics of World Tourism Organization,
China will replace United States and France to become
the area of most inbound tourists in 2020. International
tourism industry plays the important role in regional
economic development. In this work, we have used
nonparametric DEA methods to analyze the efficiency of
international tourism industry in 31 regions. The main
findings can be summarized as follows. First, the canonical
correlation analysis revealed a significant correlation
between the input and output variables. The CCR
efficiency score analysis results show that three regions
are relatively efficient, and the results were for scale
efficiency and SBM efficiency. Among the 31 regions,
three regions exhibit economies of scale, including
Beijing, Shanghai, and Guangdong. It infers that those
regions have relative efficiency based on these reasons
including the time of reform and opening early, high developed
economy, a completed value chain of international
tourism industry and the unique urban culture. According
to the statistics of China Tourism Administration (2007),
foreign exchange revenue from travel of those three
regions totaled U.S.$ 1,795 billion, accounts for 42.84%
of international tourism industry. Furthermore, the opportunities
of holding Olympic Games, international sport
games, and World Expositions are beneficial to develop
Kao et al. 7531
economy of tourism industry. As the hosting location of
the 2008 Olympic Games, Beijing is one of the fastest
growing regions in China. Meanwhile, Shanghai and
Guangdong would hold 2010 World Exposition and 2010
Asian Games to develop economy of tourism industry.
Therefore, these regions can effectively develop their
tourism industry. The results of bilateral analysis also
show that the host cities or regions of international
sporting events are superior to other regions in
productivity. Thirdly, the inefficient DUMs are mainly
attributed to technical inefficiency. Those inefficient host
cities and regions need to improve their efficiency through
saving costs and enhancing resource usage efficiency
with a wider holistic consideration of regional
characteristics, economic and tourism planning policies.
Throughout the study, special emphasis has been
placed on quantifying and discussing the impact of model
choice on the results. For this purpose, a framework for
model comparison is introduced and several techniques
are used to obtain the results. The results of this research
can help those involved in managing these regions
understand their relative operating performance and,
therefore, respond by appropriately regulating the levels
of the input and output variables. Further investigation
would be the examination of performance over time to
allow a dynamic view of the multidimensional
performance of tourism industry.
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African Journal of Business Management Vol.5 (17), pp. 7533-7541, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.608
ISSN 1993-8233©2011 Academic Journals
Full Length Research Paper
Is Moral Intensity Applicable to Natural Environment
Issues?
Chieh-Wen Sheng 1 and Ming-Chia Chen 2
1 Department of Commerce Technology and Management, Chihlee Institute of Technology, Taiwan.
2 Department of Hospitality Management, Ming-Dao University, Taiwan.
Accepted 30 May, 2011
Previous research about moral intensity has mostly centered on ethical issues related to people, with
relatively less exploration of ethical decisions related to the natural environment. Therefore, this study
investigated perceptions toward three aspects of business environmental ethics, including natural
ecology definition, business ecological role and business environmental protection; as well as the
relationship among three aspects of business environmental ethics and moral intensity was
investigated. The authors used the data collected from a survey of staffs, trainees, and trainers of a
consulting and training institute, which was established more than 40 years ago. After gathering 448
effective responses, we used structural equation model to test the hypotheses. Results showed that
moral intensity may be more prone to teleology and therefore can not be fully supported in this study to
apply to natural environment issues. After all, directions for further research and implications for
practice were provided.
Key words:Business environmental ethics, ethical issues, moral intensity, natural environment issues
environmental ethics.
INTRODUCTION
As the natural environment deteriorates, the concept of
environmental ethics which emphasizes treating
environment sincerely and equally has gradually gained
increasing attention (Naess, 1973; Taylor, 1986).
Concern over the natural environment has been a
persistent problem for industrial society (Strong, 1996).
Numerous studies begin to connect business
environmental operations with environmental ethics and
results mostly point toward the need for businesses to
pay attention to environmental conservation (Davidson, III
and Worrell, 2001; Gladwin, Kennelly, and Krause, 1995;
Hart, 1995; Shrivastava, 1995; Tello and Yoon, 2008).
Such results more or less form the external pressure for
companies to conduct environment-friendly practices.
However, Gadenne, Kennedy and McKeiver (2009)
stated that external pressures perhaps can require
companies to carry out higher levels of environmental
*Corresponding author. E-mail:amom@mdu.edu.tw Tel.: +886-
929024119. Fax: +886-4-7691677
measures but may not improve a firm’s environmental
awareness. If enterprises do not have higher
environmental awareness, their environmental measures
may be kind of compliant and of limited effectiveness that
they are unable to maintain a sincere approach to
ecological environmentalism (Wolff, 1996).
How to measure and improve a company’s
environmental awareness? Hsu (1998) proposed a
construct named business environmental ethics; she
thought the level that a company’s awareness and care of
the environment should be judged and improved through
multi facets, including how to define the nature, how to
recognize the role of business toward the natural
environment, and how to perceive the business policy
toward environmental issues. Since business
environmental ethics includes an aspect that is related to
a firm’s environmental policy, it is involved in an ethical
decision process. Regarding the influencing factors of an
ethical decision process, Jones (1991) proposed an
issue-contingent model. Jones thought that an ethical
decision is influenced by the issue’s moral intensity
including the magnitude of consequences, probability and

7534 Afr. J. Bus. Manage.
concentration of effect, and temporal immediacy. In
addition, it also includes social consensus as well as
proximity namely the close relationship between the
persons being influenced and the behavior policymakers.
Related to the proposition of moral intensity, Morris and
McDonald (1995) argued that moral intensity should be
unable to be directly measured but can only be indirectly
judged on the doer’s subjective perception. Meanwhile,
many researchers attempted to test the relationship
between moral intensity and ethical decisions (Haines,
Street, and Haines, 2008; Peslak, 2008; Singhapakdi,
Vitell and Franke, 1999); the results in general supported
Jones’ (1991) model; namely, moral intensity has a
certain influence on ethical decisions. However, these
researches mostly centered on people related issues; for
instance, the influence of moral intensity on consumer’s
issues etc. Little research has discussed if moral
intensity is also suitable for natural environment issues.
Therefore, this study examined the relationship between
peoples’ perceptions toward business environmental
ethics and moral intensity in order to understand if moral
intensity can be applicable to natural environment issues.
Environmental ethics
Hsu (1998) stated that business environmental ethics are
mainly derived from integrating the concepts of
environmental ethics and sustainable development.
Regarding environmental ethics Leopold (1949) argued
that humans should reconsider the scope of ethics and
expand human ethics to land ethics. Leopold also thought
that mankind and all species are symbiotic parts in the
ecological community, so humans should respect the land
and all species and biodiversity should be maintained
among the ecologies so as to help balance all species
and assist all species to adapt to various natural
evolutions and changes. Nevertheless, although the
environment will change naturally, if humans cause
drastic changes in nature, the ecology will be out of
balance, which in turn causing the environment to
worsen.
After the proposition of land ethics, Naess (1973) also
brought up the viewpoint of deep ecology, where he
emphasized that humans should think more deeply about
the relationship between humans and the environment;
humans would find the whole Earth is full of species and
each one has its own intrinsic meaning. Based on this
viewpoint, Taylor (1986) developed a series of arguments
and dialectics. He believed that nature is full of vitality, all
species are interdependent, and all species have intrinsic
meanings and are mutually equal; he also pointed out
that human history is much shorter than those of many
species and humans cannot survive alone. Since
mankind is a new resident on the Earth and needs help
from other species, humans should be more humble and
should not be conceited as being the best specie and
arrogantly meddle in nature. Taylor even brought up
some concrete environmental ethical principles, including:
1. Nonmaleficence, which means except for self-defense
or survival needs, mankind should not harm other living
species;
2. Noninterference, which denotes that all species should
get along peacefully and try to safeguard each other’s
freedom and not to interfere with each other;
3. Fidelity, which indicates that since humans should
have interpersonal fidelity, they should treat other species
with fidelity as well and behaviors like hunting, trapping,
fishing, etc. are all deceptive so as to catch other
species;
4. Restitutive justice, which intends that mankind should
redeem one’s own sins of environmental destruction in
the past in order to be able to align with common justice;
therefore, the mankind should undertake protection work
more aggressively.
Sustainable development
Sustainable development places importance on limited
resources. It is impossible for each generation to
consume and spend extravagantly, so business growth
should be restrained to reduce the resource depletion.
Gladwin, Kennelly and Krause (1995) argued that
sustainable development mainly emphasizes the balance
of economy and ecology and the interdependence of
humans and nature. In addition, Gladwin et al. also
pointed out that even though many viewpoints of
sustainable development are similar to environmental
ethics, the essence of environmental ethics is eco-centric
to claim that all beings have intrinsic values, whereas
sustainable development is broadly homocentric. That is,
when humans view nature, there is no avoidance of selfinterested
considerations. Therefore, the intrinsic values
of all species whoever argued always reflect human’s
values. Even so, Gladwin et al. still appealed that
humans should stay alert and not confine nature to only
be of instrumental value.
How to implement sustainable development in
companies? The World Business Council for Sustainable
Development brought up the concept of the eco-efficiency
in 1992; the council emphasized companies should
produce more from less and utilize the cyclic process of
plan-do-check-action (PDCA) to achieve continuous
improvements in environmental quality. In addition,
Shrivastava (1995) believed that companies can, using
life-cycle analysis, understand how much products affect
the environment during production and in turn they can
manage the products’ inputs, production, and recycling;
the practices can include: reducing waste, increasing
material re-utilization, increasing product safety, properly
handling product recycling, etc. Secondly, companies
can employ eco-sustainability to create competitive

strategies (Hart, 1995; Tello and Yoon, 2008). For
example, companies can incorporate environmental
protection concepts into their product design to create
differential advantages for products; companies also can
prevent pollution in order to lower costs and manage
products to gain leading positions; or companies can
shape the sustainability vision in order to obtain
preemptive opportunities in line with trends.
Business environmental ethics
Sustainable development and environmental ethics both
are concerned about the environment, but there are
some fundamental differences in their arguments. For
example, sustainable development emphasizes economic
aspects but has not redefined the environment, so it still
regards the environment as the object that can be
managed and consequently, it emphasizes the efficiency
of environmental management and benefits that
environmental management can bring. Oppositely,
environmental ethics expand ethical consideration to nonhuman
species and redefine species to be entities that
have the same level as mankind but have different
intrinsic values, so mankind should consider how to get
along with species harmoniously and mutually support
and truly care about the natural ecology (York, 2009).
Regarding the differences between sustainable
development and environmental ethics, Hsu (1998)
combined these two concepts with a complementary view
and developed a new construct: business environmental
ethics. Hsu laid out arguments of both concepts and
replaced “mankind” with “businesses”. If there is any
contradiction among arguments, she held focus group
meetings or expert interviews to decide which is better or
whether retouch is needed. Such a process can improve
the description of reality and consider the business logic
to avoid the construct too idealistic (Dentchev, 2009).
Lastly, Hsu divided business environmental ethics into
three aspects and gave each an operational definition: 1.
Natural ecology definition, which means the perception
toward the definition of nature, for example, considering
nature as a spiritual meaning for various lives; 2.
Business ecological role, which means the perception of
business role toward the ecological environment, for
example, whether the company should take the role of
moral responsibility for the natural environment; 3.
Business environmental protection, which means the
perception toward firms’ environmental policies, for
example, whether companies should cooperatively
protect environment.
Based on Hsu’s (1998) theoretical foundation, Sheng and
Hsu (2000) developed a questionnaire and conduct an
empirical study. Results verified these three aspects after
factor analysis and showed the higher the perception
toward business environmental ethics, the higher degree
of employees’ cooperation with firms’ environmental
Sheng and Chen 7535
measures. Moreover, since a firm’s corporate social
performance (CSP) will send signals to job applicants
about what it would be like to work for a firm (Greening
and Turban, 2000), Backhaus, Stone, and Heiner (2002)
found CSP, especially its dimensions of environment,
community relations, and diversity will have affect on
employer attractiveness for job seekers. As well Sheng
(2001) found the job seekers’ perception of business
environmental ethics will influence their needs for job
condition.
Moral intensity
Business environmental ethics includes an aspect related
to business environmental policies; showing this
construct is involved in an ethical decision process. Rest
(1986) stated that the process of ethical decisions could
be divided into four stages. The first stage is moral
recognition; that is, people need to sense moral
meanings of issues, for instance, being aware that
businesses have moral obligations toward the natural
environment. Second stage is moral judgment to
distinguish between right and wrong, for example, judging
if the company’s environmental policy or conduct is right
or wrong. Then, the third stage is moral intention,
attempting to perform right behaviors. Finally, the last
stage is the concrete moral behavior--taking the right
actions after an attempt.
Many scholars (Cottone and Claus, 2000; Gadenne,
Kennedy, and McKeiver, 2009) thought that in general the
ethical decision process is influenced by two kinds of
factors. The first kind of factor is the principle factor,
which means the moral principles of a decision maker.
These principles may come from personal experiences or
be influenced by demographics such as gender,
education, age, etc., and a decision maker will apply
these principles to make judgments even facing different
ethical dilemmas. On the other hand, the second kind of
factor has the social interactive nature, which mainly
means when a decision maker faces ethical dilemmas,
he or she will be influenced by social interactions or
situations at that time such as considering social
expectations, legal norms or economic realities, etc.
Moral intensity basically is a factor that has a social
interactive nature. When making ethical decisions, people
will be influenced by the attributes of moral issues,
namely the moral intensity, which includes: 1. Magnitude
of Consequences, meaning the harming or benefiting
level caused by decision result. 2. Concentration of
Effect, meaning the number of victims or beneficiaries
that will be influenced under a certain result and the more
people that share the influence of the result, the lower the
concentration of effect is. 3. Probability of Effect, meaning
the probability that the result will happen. 4. Temporal
Immediacy, meaning the duration time between the
decision/behavior happens and the result appears. 5.

7536 Afr. J. Bus. Manage.
Social Consensus, meaning the recognition level of the
public of the decision. 6. Proximity, meaning the physical,
psychological or societal closeness of decision makers
toward the victims or the beneficiaries (Jones, 1991).
With regard to moral intensity, lots of articles chose
specific parts, not all, of moral issue attributes to study,
for example only examining magnitude of consequences
and so on. Furthermore, many studies have found even
though moral intensity will influence the ethical decision
process in general, as the different issues or the moral
situations become fuzzy, the influence of the moral
intensity will change (Peslak, 2008). According to Jones’
(1991) original argument, to be appropriate, these
attributes should be combined and studied together. May
and Pauli (2002) also asserted all attributes should be
studied. Therefore, for business and natural environment
issues, this research will verify the relationship between
business environmental ethics and the overall moral
intensity, which covers all six attributes.
Generating hypotheses
Leopold (1949), Naess (1973), Taylor (1986), and Sheng
and Hsu (2000) all believed if people could use a more
organic or personified approach to define the
environment, a more friendly positive emotion toward the
environment will occur. Also, Michael et al. (2007)
pointed out emotion will influence one’s perception about
bearing the responsibility of ethical decisions. Aloof
people are more inclined to be self-interested; in contrast,
people who are empathetic are prone to be altruistic.
Thus, this research proposes hypothesis 1 and
hypothesis 2 is proposed on Rest’s (1986) argument that
moral recognition contributes to the formation of moral
judgment.
H1: Definitions influence ethical decisions.
H1a: Definitions influence the moral recognition of
ethical decisions; that is, the more people are inclined to
the organic or personified definition of a natural ecology,
the more they think businesses should take on the role of
bearing the moral responsibility.
H1b: Definitions influence the moral judgment of
ethical decisions, that is, the more people are inclined to
the organic or personified definition of a natural ecology,
the more they can approve of businesses’ environmental
protection actions.
H2: Moral recognition influences moral judgment; that
is, when people think businesses should bear more
ecological moral responsibility, they increasingly can
approve businesses’ environmental protection actions.
Carlson, Kacmar, and Wadsworth (2002) pointed out that
the more objective view the decision makers hold, the
less moral intensity perceived by decision makers. This
finding means when people are more prone to an organic
or personified environmental definition, people can have
more subjective emotions toward the environment, have
a connecting feeling toward natural environment issues,
and then have a more sensitive awareness toward the
moral intensity of environmental issues. Next, according
to the viewpoints of Jones (1991) and Morris and
McDonald (1995), once people are aware of the moral
intensity, ethical decisions, including moral recognition
and moral judgment, will be influenced. Accordingly, this
study proposes the following hypotheses:
H3: Definitions influence moral intensity; that is the
more organic or personified definition of natural ecology
people have, the higher the moral intensity people
perceive about the environmental issues.
H4: Moral intensity influences ethical decision.
H4a: Moral intensity influences moral recognition of
ethical decision; that is the higher the moral intensity
people perceive about environmental issues, the more
they think businesses should bear the moral
responsibility role toward the ecology.
H4b: Moral intensity influences moral judgment of
ethical decision; that is the higher the moral intensity
people perceive about environmental issues, the more
they approve a businesses’ environmental protection
actions.
METHODOLOGY
The present study chooses the trainees and employees including
consultants and staff members of a consulting and training institute
established more than 40 years ago as the research subjects. After
obtaining the institute’s approval, questionnaires were spread over
different times to all employees while stratified sampling was used
for the trainees. For total 14 types of courses, this study randomly
selected 10 percent of the trainees of each course to dispatch
questionnaires. Total of 550 questionnaires were dispatched to all
subjects. After removing questionnaires with inconsistent answers
on items, 448 questionnaires were effective, consisting of 295
trainees, 89 consultants, and 64 staff members; the effective
response rate was 81.45%.
The main reasons for choosing these subjects to conduct survey
were:
1. It was easy for the researcher or the assistants to go to the single
site (training centre) in person to dispatch the questionnaires, which
increased questionnaire returns, let respondents have enough time
to fill in the questionnaire attentively, and reduce response errors
through questionnaire explanation and small gifts;
2. The institute has a long history, good reputation, and quite a few
senior professional consultants. These people have assisted a lot of
businesses, thus we inferred that they will have some impacts on
businesses’ thinking;
3. After trainees including top level managers returned to their
companies, when training was complete, they usually had better
performance and were promoted. Therefore, these trainees had
certain influences on business decisions.
Concerning measuring instruments, the research first adopted the
questionnaire designed by Sheng and Hsu (2000) to measure the
perception of three aspects of business environmental ethics,
including natural ecology definition, business ecological role, and
business environmental protection. Then, because there was no

Table 1. Reliability and construct validity.
Variables Items
Moral
Intensity
Natural Ecology
Definition
Business
Ecological
Role
Business
Environmental
Protection
1. Businesses damage the ecological
environment severely.
2. On average, companies’ destruction to the
ecological environment will be shared among
many victims.
3. While operating, companies will possibly
destroy the ecological environment.
4. Businesses’ destruction to the ecological
environment is seen immediately
5. The public is really concerned about the
issues between business and natural
environment.
6. I will really sympathize with the victims of
ecological environment destruction.
1. Nature is not only materials gathering but
also has the spiritual meanings of various lives.
2. Companies should realize more about the
close feelings of the mankind and the earth.
3. Natural environment is the same as humans,
easily injured.
1. Companies should, with conscience, take the
moral responsibility for environment.
2. Companies’ role is complying with the nature,
not conquering the nature.
3. The moralities exist between companies and
natural environment.
1. Companies should internalize sustainable
concepts into their organizational culture.
2. Companies should cooperate to advance the
environmental protection.
3. Concepts of protecting environment should
be put in practice for any company.
relevant questionnaire for measuring moral intensity concerning
environmental issues, the researcher designed a questionnaire in
person, referred to the measuring methods of Morris and McDonald
(1995), Singhapakdi, Vitell and Franke (1999). For example, we
used “Businesses damage the ecological environment severely” to
measure the magnitude of consequences and also used other
items to measure concentration of effect, probability of effect,
temporal immediacy, social consensus, and proximity.
After collecting 448 effective questionnaires, the research used
Cronbach α to examine internal consistency of each variable.
Results are as shown in Table 1; α value of moral intensity is 0.91,
of natural ecology definition is 0.85, of business ecological role is
0.86, and of business environmental protection is 0.69. Overall,
measures are over 0.7 and reliabilities are acceptable (Cuieford,
1965; Nunnally, 1978).
We also measure the construct validity of questionnaire for
business environmental ethics and moral intensity, mainly adopting
suggestions of Kerlinger and Lee (2000). First, we assumed the
sum-up score of items for each variable was valid and then used
Correlation Coefficient
Item vs. Variable
0.7748
0.5444
0.7456
0.8101
0.7967
0.8042
0.6979
0.7667
0.6872
0.7032
0.7610
0.7595
0.2186
0.6689
0.7159
Sheng and Chen 7537
Cronbach’s
alpha
0.9077
0.8485
0.8638
0.6931
the correlation coefficient between the score of individual item and
the sum-up score to judge for the construct validity of each variable.
Results are also as shown in Table 1. Except for the first item of
business environmental protection has low coefficient, while other
coefficients are above 0.5, generally showing the construct validity
is acceptable.
RESULTS
Table 2 is the overall fit test including the test on
predictive validity of variables; this mainly investigated,
using structural equation model, the overall structure’s
causal relations among moral intensity, natural ecology
definition, business ecological role, and business
environmental protection. If the causal relations can be
accepted, then the variables have predictive validity.

7538 Afr. J. Bus. Manage.
Table 2. Overall fit test.
Reference Indicator Indicator Value Judgment Criterion
χ2 297.4274*** p-value < 0.01
χ2/d. f. 297.4274/80 =3.72 The smaller the better, best to be smaller than 0. 3.
GFI 0.9089 The bigger the better, best to be bigger than 0.9.
AGFI 0.8634 The bigger the better, best to be bigger than 0.9.
RMR 0.0549 The smaller the better, best to be smaller than 0 .05
NFI 0.9041 The bigger the better, best to be bigger than 0.9.
*** p-value < 0.001.
Natural Ecology
Definition
Moral Intensity
H1a*
H4a*
H1b
(H4b)
H2*
Business Ecological
H3 Business Environmental
Role
Protection
Figure 1. Path diagram of hypotheses test.
From Table 2, we can see χ 2 is 297.4274 (p-value <
0.001) and χ 2 /d.f. is 3.72 (close to 3), GFI is 0.9089 (>
0.9), AGFI = 0.8634 (close to 0.9), RMR = 0.0549 (close
to 0.05), and NFI = 0.9041 (> 0.9). Referring to Jöreskog
and Sörbom’s (1996) suggestion, these data show the
causal structure is basically appropriate and also show
this study’s variables have acceptable predictive validity.
Next, this study tested the latent variables and hypothesis
1 to hypothesis 4. Table 3 shows each λ reaches a level
of significance (t-value>1.96); therefore the latent
variables were verified. Table 4 is the result of
hypotheses test and Figure 1 shows the path diagram.
From Table 4 we can see that hypothesis 1-1, 2 and 4-1
are accepted (t-value> 1.96) while hypothesis 1-2, 3 and
4-2 are rejected.
Discussion and conclusion
This study’s main objective was to investigate the
relationship between business environmental ethics and
moral intensity. Figure 1 shows the results for H1 to H4.
Among them, H1a is supported, showing that the more
people are inclined to the organic or personified definition
of natural ecology, the more they approve of the opinion
that businesses should take on the role of bearing the
moral responsibility. Meanwhile, although not statistically
significant, H1b shows that people’s personified definition
of the natural ecology positively influences his or her
approval level of businesses environmental protection.
The result for H1a and H1b somehow supports the
argument of environmental ethics theorists, including
Leopold (1949), Naess (1973), and Taylor (1986); that is,
people’s friendly definition of the environment will make
people have a positive emotion toward the environment
and in turn make people approve of ethical decisions that
are favorable to the environment.
Moreover, Rest (1986) stated that people’s moral
recognition can influence moral judgment, which is
evidenced from the statistical acceptance of hypothesis 2.
Accordingly, people’s moral recognition, namely,
recognizing businesses’ ecological role, can influence
peoples’ moral judgment on business environmental
protection.
As for how to change peoples’ definition of
environment, York (2009) asserted if we adopt
environmental pragmatism, namely keep the open-ended
inquiry on the real life problems between humans and the
natural environment, it is possible to make the definition
of environment clarifier or in a more common consensus,
then we can incorporate environmental ethics into the
decision framework of actual business operations. In
practice, Sheng and Hsu (2000) and Rozzi et al. (2006)
suggested to encourage people go outdoors and
experience the beauty of nature in person, for example
making a business ecological tour, which is helpful to

Table 3. Latent variables test.
Sheng and Chen 7539
Latent variable Parameter Value t-value
λX1=0.7696 25.0674
Latent variable, Natural Ecological Definition includes three items.
*
λX2=0.8977 32.6371 *
λX3=0.7551 24.2289 *
Latent variable, Moral Intensity includes six items.
Latent variable, Business Ecological Role includes three items.
Latent variable, Business Environmental Protection includes three items.
* t-value >1.96.
Table 4. Hypotheses test.
λY1=0.8136 28.8194 *
λY2=0.8600 33.5085 *
λY3=0.5642 14.3465 *
λY4=0.8316 30.5156 *
λY5=0.8397 31.3213 *
λY6=0.8254 29.9081 *
λY7=0.5183 12.2921 *
λY8=0.4610 10.3884 *
λY9=0.7261 19.4318 *
λY10=0.5619 13.3883 *
λY11=0.5823 14.1203 *
λY12=0.5537 13.1007 *
Hypotheses Parameter Value t-value
H1a: Definitions influence the moral recognition of ethical decisions. γ2 = 0.3311 5.6198*
H1b: Definitions influence the moral judgment of ethical decisions. γ3 = 0.0830 1.2114
H2: Moral recognition influences moral judgment. β3 = 0.9480 18.8415*
H3: Definitions influence moral intensity. γ1 = 0.0880 1.6807
H4a: Moral intensity influences moral recognition of ethical decision. β1 = 0.3070 5.3168*
H4b: Moral intensity influences moral judgment of ethical decision. β2 = -0.0302 -0.4726
t-value>1.96.
keep employees good interactions with nature, leading to
the intimate and friendly definitions of nature. Based on
these arguments it may be interesting for future research
to explore what kind of “outdoor interaction” between
people and natural environment will improve peoples’
friendly definition of environment.
Lastly, the other two hypotheses are related to moral
intensity. The inference of H3, derived from Carlson,
Kacmar, and Wadsworth’s (2002) research about moral
intensity, is not significantly supported even though it is
positively related in this study. Hypothesis 4 is based on
Jones’ (1991) argument; among them, H4a is supported
but H4b is not significantly supported and even appears
to be negatively related. Accordingly, in the present study
Jones’ argument is only partially supported.
Not only in this study but also in the studies of Deborah
(2006), Piercy and Lane (2007), and Wasieleski and
Hayibor (2008), findings show that the relationship is not
stable between moral intensity and certain ethical
decision processes or some ethical decisions that are
under certain specific situations. For example, Haines,
Street, and Haines (2008) found people’s perception of
the importance of an ethical issue may affect some steps
of an ethical decision but may not influence all steps.
That is, the issue-contingent model proposed by Jones
(1991) is not supported in all studies.
Such a phenomenon may have two reasons: First,
some limitations in research resulted in deviations.
Second, the arguments of Jones (1991) may have some
implicit restrictions that were not considered in advance
in this or other research.
For the first reason, without doubt, there are many
limitations in this study. For example, there was no moral
intensity questionnaire specifically designed for natural

7540 Afr. J. Bus. Manage.
environment issues in the past, so this study had to selfdesign
the items to measure the related moral intensity.
Although the construct validity was confirmed in this
study, it still was the first time to use these items and of
course there are rooms for improvement. In addition,
Christensen and Kohls (2003) and Piercy and Lane
(2007) pointed out that ethical decision processes are
influenced by many causes, including organizational and
individual causes, which might moderate the results.
These causes were not considered in this research.
With regard to the second reason, according to Jones’
(1991) definition, we can find the six attributes of moral
intensity are basically dependent on the results of moral
issues, for example, magnitude of consequence,
concentration of effect, and probability of effect, etc. That
means moral intensity is a certain concept that is prone to
teleology, namely, using the consequence or effect of a
behavior or decision to measure its morality.
Nevertheless, beside teleology, there are many other
viewpoints such as deontology and virtue ethics to help
people judge the morality. For example, Taylor’s (1986)
fidelity principle is prone to deontology, emphasizing no
matter how the result is, deceiving ways of catching the
living things should not be allowed. In addition, Chuang
(2006) mentioned that the principle of fairness and justice
instead of maximum interest or utility of the consequence
should be used to consider allocating social resources to
various kinds of environmental issues.
Ethical decisions may be affected by teleology,
deontology or virtue ethics and everyone’s viewpoint may
not be the same and may be relative instead of absolute,
meaning humans depend on the situation to decide which
viewpoint or moral principle to adopt (Forsyth, 1980).
Therefore, just using moral intensity, which is prone to
teleology, to predict a person’s ethical judgment may not
be very thorough and appropriate. Accordingly, in this
study, arguments of Jones (1991) and Carlson, Kacmar,
and Wadsworth (2002) cannot be fully supported.
How to handle the problem that different moral
principles may affect one’s ethical decisions? Perhaps,
when conducting a research of business ethics, first
clarify what the decisions are concerned with. If a
decision is more concerned with the output not the
process, teleology may be proper. For example, in Eva,
Katja, and Erich’s (2007) research, they showed the
participants some vignettes emphasizing different results
of investment to recognize their moral perception of
investment behaviors. For this case, teleology is
appropriately used and their research results verified
Jones’ (1991) issue-contingent model. Nevertheless, if a
study focuses on the issues of basic rights, minority
groups, or natural environment protection, which are
usually concerned with justice and fairness among
unequal parties, deontology may be proper (Robbins,
2005) and Jones’ issue-contingent model that is prone to
teleology may be not applicable.
After the concerns of decisions are clarified, it should
be noticed that there are various facets or streams of
deontology and teleology. These facets or streams may
have different emphasis and different names such as
utilitarianism, egoism or enlightened egoist for teleology;
and Kant’s formalism or Rawls’ contractarianism for
deontology (Audi, 1999; Ferrell, Fraedrich, and Ferrell,
2005). Therefore, when considering the influences of
different viewpoints of teleology or deontology, the
relationship with ethical decisions and moral judgment
may become quite complicated.
For exploring a more complicated problem, Hendry
(2003) argued that grounded theory proposed by Strauss
and Corbin (1990) may be suitable. From open coding to
selective coding, grounded theory provides a framework
for straightening up the clues in a complicated situation
and finding out the possible relationship among different
concepts or constructs. Then researchers can develop
hypotheses based on the relationship and use, if
necessary, statistical methods to test hypotheses. During
such a process, researchers may identify, explore deeply
and comprehend ethical issues in a dynamic, complex, or
even dangerous business world.
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African Journal of Business Management Vol. 5(17), pp. 7542-7556, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.610
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Impact of locus of control, changes in work load and
career prospects on organizational commitment of
employees of life insurance companies during merger
and acquisition
Chiewei Hung 1 and Ker-Tah Hsu 2 *
1 Feng Chia University, Department of Risk Management and Insurance, 100 Wen-Hua Road, Seatwen 407, Taichung
City 40724, Taiwan.
2 National Taichung University of Education, Department of International Business, 140 Min-Shen Road, Taichung City
40306, Taiwan.
Accepted 21 June, 2011
This paper explores employee organizational commitment in the process of merger and acquisition. A
case study of a life insurance merge and acquisition case in which the acquiring company was a local
life insurance firm and the acquired company was a foreign-owned insurance company in Taiwan is
used. The present study explored two issues: (1) whether employees of the acquiring company and the
acquired company perceived changes in work load and career prospects differently during the process
of absorption and exhibited different levels of organizational commitment to the surviving company;
and (2) the structural relationships between organizational commitment, locus of control and the
perceived changes in work load and career prospects for employees of the two companies. We found
that work load change and career prospects change is perceived by employees of the two groups
invariantly; employees of the acquiring company have higher level of organizational commitment than
those of the acquired company; the direct influences of work load change and career prospects change
on organizational commitment are statistically significant; the direct influences of locus of control on
organizational commitment, work load change, and career prospects change are statistically significant;
the indirect influence of locus of control on organizational commitment is statistically significant; and
the moderating effect of locus of control is not statistically significant.
Key words: Organizational commitment, locus of control, work load, career prospect.
INTRODUCTION
The International Financial Reporting Standards Bulletin
IV (IFRS4) to which life insurance companies in EU are
subject, came into force in 2005. It mandates more
stringent financial norms than in other countries. Many
life insurance companies in Europe have since decided to
sell overseas assets in order to meet the dramatic
increase in reserve requirement under IFRS4. In 2004,
European life insurance companies began to withdraw
from the life insurance market in Taiwan and to sell their
*Corresponding author. E-mail: kthsu@ntcu.edu.tw. Tel: +886 4
2218 3934; fax:+886 4 2218 3356
subsidiaries and branches. Largely for this reason, the
number of foreign-owned life insurance companies in
Taiwan fell after 2007. Former subsidiary and branch
companies of European life insurance companies were
often acquired by Taiwanese life insurance companies.
The case being studied includes two companies. The
acquiring company was established in the 1990s and was
the first new life insurance company established after the
restrictions on the number of life insurance companies in
Taiwan was lifted. According to the Life Insurance
Association in Taiwan, through the end of September
2008, the market share of the acquiring company was
7.06%. After Taiwan opened its life insurance market to
foreign firms, the acquired company was the first foreign

owned insurance firm to enter the market. According to
the Life Insurance Association in Taiwan, through the end
of September 2008, the market share of the acquired
company was 6.82%. After June 1, 2009, all the life
insurance policies issued by the acquired company were
fully transferred to and borne by the acquiring company.
In other words, the acquiring company is the surviving
company.
Merger and acquisition is a key type of organizational
change. In the process of merger and acquisition, both
the employees of the acquired company and those of the
acquiring company face changes in work load, job stress,
career prospect, income, and management. The extent to
which employees are influenced by the change process
and whether employees of the acquiring company and
the acquired company are affected symmetrically
depends on the approach taken by the management of
the firms.
Organizational change may influence employee organizational
commitment via several factors. For example,
Cole et al. (2006) found that employee organizational
commitment is positively influenced by their assessments
of the appropriateness of organizational change. The
present study takes employee perceptions of work load
change and career prospects change resulting from the
merger into account. These two changes concern employees
of both the acquiring company and the acquired
company. In this paper, we hypothesize that, changes in
perceived work load and perceived career prospects are
important antecedents of employees’ organizational commitment.
Organizational commitment is generally seen as
a psychological outcome that is usually associated with
personality (Chen and Silverthrone, 2008). Organizational
change may interact with individual’s personality, and
thereby affect psychological outcomes.
In the studied case, the acquired company was
absorbed by the acquiring company. Therefore, a high
level of change was faced by the acquired company and
there was little or no change for the acquiring company
during the process of absorption after merger (Steuer and
Wood, 2008). We investigated whether, under such conditions,
employees of the acquiring company and the
acquired company perceive changes of work load and
career prospects differently during the process of absorption
and had different levels of organizational commitment
to the surviving company. We also explored the structural
relationships between organizational commitment, locus
of control and perceived changes in work load and career
prospects for employees of the two companies during the
process of absorption. Partial examination of the simple
bivariate relationships between any pair of these variables
might distort their true relationships due to omitted
variable bias. With this in mind, possible competing
models are identified further. Of interest is the specification
of the “antecedent, mediating or moderating and
consequent” relationships among these variables.
Further, two competing models are identified based on
Hung and Hsu 7543
a review of literature. At the same time, the relevant
hypotheses derived from these competing models are
proposed. Subsequently, the methodology, data collection,
scales for measuring relevant variables and their fit
indexes are then described. Statistical analyses are
conducted from which our research concludes with a
discussion of our empirical findings and their managerial
implications.
LITERATURE REVIEW AND HYPOTHESES
Organizational commitment
Organizational commitment is believed to be an important
antecedent of various psychological or behavioral outcomes,
which are indices of organizational efficiency and
effectiveness and desirable work-related outcomes. High
levels of organizational commitment have been related to
lower levels of turnover among employees, absenteeism,
tardiness and higher levels of job performance, innovative
activities and organizational citizenship (Beck and
Wilson, 2000). The study of organizational commitment is
thus of great value since results can aid management in
promotion of performance, control of turnover, and
development of desirable work-related behaviors and
attitude.
Turnover and propensity to leave have been found to
be negatively related to organizational commitment
(Chonko, 1986; Johnston et al., 1990; Bashaw and Grant,
1994; Cohen and Freund, 2005). Lambert and Hogan
(2009) surveyed correctional staff at a maximum security
private prison and found that age, job satisfaction, and
organizational commitment have direct effects on
turnover intent, whereas, gender, job satisfaction, role
conflict, role ambiguity, role overload, input into decision
making, and organizational fairness indirectly influence
employee decision to leave the organization. Turnover
incurs recruiting and training costs. Increasing employee
organizational commitment reduces these costs.
Organizational commitment is positively related to
various types of job performance. Employees with a high
level of organizational commitment are predicted to
achieve higher job performance (Bashaw and Grant,
1994; Tsai et al., 2010). Organizational commitment contributes
positively to employee innovative behaviors in an
organization, which leads to competitive advantage and
organizational success (Jafri, 2010). Employee
psychological well-being is also positively influenced by
organizational commitment. Positive well-being leads to
optimal functioning that is likely beneficial to organizations,
while negative well-being has detrimental effects on
individuals and organizations, which include reduced
performance, absenteeism and turnover (Panaccio and
Vandenberghe, 2009). Researchers have explored the
relationships between organizational commitment and
multiple consequences simultaneously. The impact of

7544 Afr. J. Bus. Manage.
organizational commitment on satisfaction with life, work
withdrawal, organizational citizenship and turnover intentions
are supported by the results of Wasti (2002).
Tsoumbris and Xenikou (2010) found that a portion of
variance in turnover intentions, intentions of changing
occupation, and organizational citizenship behavior are
explained by organizational commitment.
The earliest approach to developing a conceptual
framework of organizational commitment focused
thoroughly on the individual’s relationship with the
organization. According to Becker (1960), if they leave
the organization, employees lose the accumulation of
hidden investments they make by maintaining the
membership in a given organization. The term “side-bets”
has been used to refer to these hidden investments
(Cohen, 2007).
For Porter et al. (1974), organizational commitment refers
to the psychological attachment an individual has to
the organization. Porter et al. (1974) developed a scale
designed to measure organizational commitment, known
as the organizational commitment questionnaire (OCQ).
It consists of 15 items. A number of researchers have
used a shorter version of the OCQ. For example, Iverson
(1999) used a 9-item version and Beck and Wilson
(2000) used a 12-item version of OCQ.
For Becker (1960) and Porter et al. (1971), organizational
commitment is one-dimensional. Organizational
commitment may also be operationalized using a multidimensional
approach. The distinction between attitudinal
and behavioral commitment was established first.
Mowday et al. (1982) defined the two concepts as
follows: “Attitudinal commitment focuses on the process
by which people come to think about their relationship
with the organization. … Behavioral commitment on the
other hand, relates to the process by which individuals
become locked into a certain organization and how they
deal with this problem.” Following this distinction,
organizational commitment was conceptualized bidimensionally
in Meyer and Allen (1984).
Meyer and Allen (1991) added a third component and
proposed a three-component model of organizational
commitment. The three components reflect a desire
(affective commitment), a need (continuance commitment)
and an obligation (normative commitment) to
maintain employment in an organization. Employees with
a strong affective commitment attach themselves to,
identify themselves with, and involve themselves with the
organization. They commit to the organization because
they “want to do so”. Employees with continuance
commitment remain with an organization because of
awareness of the costs associated with leaving the organization.
In other words, they “need to do so”. Normative
commitment is viewed as a feeling of obligation to remain
with the organization. Employees with a high level of
normative commitment stay with an organization because
they “ought to do so”. In fact, organizational commitment
for Porter et al. (1974) is a synonym of affective
commitment (Meyer and Allen, 1991). For Meyer and
Allen (1991), the side-bet of Becker (1960) is one dimension
of continuance commitment.
However, the relationships between indices of
organizational efficiency and effectiveness and affective
commitment are found to be more consistent than those
between these indices and continuance or normative
commitment (Allen and Meyer, 1996). In addition, Wasti
(2005) combined three components of organizational
commitment to create distinct profiles of commitment and
explored the implications of different profiles. The results
suggest that affective commitment is the major predictor
of positive job outcomes. The cross-cultural generalizability
of the antecedents and consequences of affective
commitment is also confirmed by the results of Wasti
(2002). Therefore, affective commitment is used as proxy
for organizational commitment.
The influences of the personal characteristics of employees
on their organizational commitment are confirmed
by many previous studies. Personal characteristics may
include such traits as gender, marital status, age,
education, family income, tenure, and locus of control
(Bashaw and Grant, 1994; Joiner and Bakalis, 2006; Lin
et al., 2010).
Job-related variables are other possible antecedents of
organizational commitment. Job-related variables may
include organizational support, organizational climate,
work role, and social interaction. Job involvement could
include tenure or a second job. Their influences on
organizational commitment have abundant managerial
implications and attracted attention of many researchers.
Panaccio and Vandenberghe (2009) found that the
positive relationship between perceived organizational
support and employees’ psychological well-being is
mediated by organizational commitment. In other words,
perceived organizational support is an antecedent of
organizational commitment. Coyle-Shapiro and Morrow
(2005) examined affective commitment of long-term
contracted employees to employing and client organizations.
They found that perceived organizational support
and attractiveness of the client organization are positively
related to employees’ affective commitment to the client
organization, which is explained by employees’ commitment
to their own contracting organization. The impacts
of organizational climate and work role on organizational
commitment were examined by Gormley and Kennerly
(2010). Role ambiguity and role conflict are negatively
related to all dimensions of organizational commitment.
The consideration, intimacy and production emphasis
dimensions of organizational climate are positively
related to affective and normative commitment and have
negative impacts on continuance commitment. Heffner
and Rentsch (2001) employed a multiple constituencies
approach and hypothesized that work group interaction
would influence work group affective commitment;
department social interaction and work group affective
commitment would independently influence department

affective commitment; organizational social interaction
and department affective commitment would independently
influence organizational affective commitment.
Their results supported the hypothesized relationships
between social interaction and affective commitment.
Factors affecting employee organizational commitment
during the period of organizational change or merger and
acquisition has been relatively less discussed in the
literature. Meyer et al. (2010) conducted a longitudinal
study to examine the relationships of person-organization
fit to employees’ affective commitment and intention to
stay with an organization during the early stages of
strategic organizational change. Person-organization fit is
defined as congruence between perceived and preferred
organizational culture. The subjects of this study were
employees of a large energy company affect by deregulation
in the Canadian energy sector that was facing a
new requirement to be profit-oriented. Unlike this study,
the organizational change in their case was the layoff of
permanent employees, the hiring of contract workers,
changes in the senior management team and cultural
transformation. Organizational commitment during
periods of merger and acquisition was examined by Lin et
al. (2010), whose subjects were employees of Taiwanese
domestic banks that were acquired by foreign banks from
2007 to 2008. Their major aim was to investigate how
changes in work characteristics uplift and enforce
employee organizational commitment during periods of
merger and acquisition. However, Lin et al. (2010) did not
explore how the changes resulting from merger and
acquisition impacted organizational commitment.
Organizational change
In today’s dynamic world, no organization is immune to
organizational change. Organizational change is defined
as attempts to modify an organization’s structure, goals,
technology or work task (Carnall, 1986). Merger and
acquisition are one form of organizational change and
can be further characterized by the clash of cultures
(Evans et al., 2002; Steuer and Wood, 2008).
While any organizational change can be a very stressful
experience for individuals (Elrod and Tippett, 2002),
fundamental changes such as mergers may be more
stressful than most changes. The emotional responses to
change that an individual can experience during change
process may be equilibrium, denial, anger, bargaining,
chaos, depression, resignation, openness, readiness and
re-emergence (Perlman and Takacs, 1990). Negative
attitudes among these responses may have negative
consequences for the organization. Increased pressure
for change is associated with increased stress, low job
satisfaction, and increased intention to withdraw (Rush et
al., 1995).
The change process involves going from the known to
the unknown. This brings not only a stressful experiences
Hung and Hsu 7545
but also new possibilities for individuals. For some
individuals, mergers may mean promotion or better prospect
of his or her career. Two outcomes of merger and
acquisition, that is changes in work load and changes in
perceived career prospect, are chosen as antecedents of
organizational commitment, which represent the good
and bad side respectively. This study focuses equally on
the positive and negative aspects of mergers.
Changes in work load, which might result from layoff of
employees or more profit-oriented strategies, frequently
follow merger and acquisition. Work load used in this
study is one dimension of job overload, which in turn is
one dimension of job stress (Rahim, 1996). Vakola and
Nikolaou (2005) appear to show that highly stressed
employees demonstrate decreased organizational
commitment. The relationships between career-related
variables and organizational commitment are supported
by results of past researches (Alvi and Ahmed, 1987; Liu
and Wang, 2001; Long et al., 2002; Bambacas, 2010;
Weng et al. 2010). Employees have higher level of
organizational commitment, when they perceive high
probability of promotion and greater opportunity for
learning and personal development.
Managers generally take two approaches in implementing
the change progress. The level of change in the
organization and its impact on individuals involved in the
progress are determined by the approach used. The first
approach is absorption, which aims at a high level of
change for the acquired firm and little or no change for
the acquiring firm. The second approach is integration,
which implies change for both firms and for all of their
employees (Steuer and Wood, 2008).
For the studied case, the former is implemented. We
measure changes in perceived work load and perceived
career prospects in the process of merger and acquisition
for employees of both the acquiring firm and the
acquired. Their effects on employee organizational
commitment during merger and acquisition are then
assessed.
Locus of control
Locus of control is one aspect of personality that describes
the extent to which individuals believe they have
the ability to exercise control over their environment.
Rotter (1966) developed the internal-external locus of
control that yields a single score on a scale from highly
internal to highly external. Internals believe that events in
their life result from their behaviors. Externals believe that
they have very little control over the events in their life.
Although several researchers have proposed that locus
of control might be multidimensional, most studies of
locus of control employ Rotter’s single score scale (Chen
and Wang, 2007).
The association of personality and psychological or
behavioral outcomes is supported by many previous

7546 Afr. J. Bus. Manage.
research results. Job-related variables may be psychological
or behavioral outcomes. Chen and Silverthrone
(2008) found that locus of control is an important
antecedent of job satisfaction, stress and performance.
The results of Martin et al. (2005) confirmed that locus of
control may directly influence job satisfaction, workrelated
well-being and organizational commitment. Rahim
(1996) argued that internals perceive less stress and
strain than externals. Similarly, Chen and Silverthrone
(2008) found that internals are likely to have lower levels
of job stress and higher level of performance and satisfaction.
Job stress, job satisfaction, work-related wellbeing
and organizational commitment are psychological
outcomes, and job performance is behavioral outcomes.
The main effects of locus of control on job-related
variables are broadly supported by many other studies
(Daniel and Guppy, 1994; Judge et al., 2003).
Important for this study is the relationship of locus of
control to organizational commitment. Werbel et al.
(1996) confirmed that job fit and locus of control were the
most important antecedents of pre-entry organizational
commitment. Luthans et al. (1987) demonstrated that
locus of control is significantly associated with organizational
commitment. Individuals with a higher internal locus
of control are more likely to have a higher level of
organizational commitment.
Hyatt and Prawitt (2001) examined how auditors’ job
performance is influenced by the interaction between
individual auditors’ locus of control and the employing
firm’s audit structure. Results indicate that internals
perform at a higher level in unstructured firms than in
structured firms, while externals perform at a higher level
in structured firms than in unstructured firms. This implies
that locus of control may interact with characteristics of
the work environment and affect job-related variables. A
similar study of Lin et al. (2010) found that work characteristic
change has a greater effect on the organizational
commitment of internals than externals. In other words,
the aforementioned results imply a moderating effect of
locus of control on job-related variables. Rahim (1996)
argued that locus of control moderates the relationship
between stress and strain. This hypothesis was partially
supported by results from hierarchical regression
analyses. However, the mediating effect of locus of
control on the relationships between other variables is
another possibility. Following this approach, Chen and
Silverthrone (2008) posited that locus of control mediates
the relationship between job stress and job performance,
locus of control mediates the relationship between job
satisfaction and job performance, and locus of control
mediates the relationship between job satisfaction and
job stress. The possible moderating effect and mediating
effect of locus of control will be discussed in more detail.
Merger and acquisition may place employees of both
the acquiring firm and the acquired firm in an uncertain
environment. Employees’ locus of control will influence
their psychological reactions to organizational change.
Internals believe that their own behavior can affect what
happens to them. We therefore, expect that internals
would perceive greater improvement in or less increase
of work load after a merger than externals. We also posit
that internals would perceive a greater increase in career
prospects after a merger than externals. Internals should
also report more organizational commitment after a
merger than externals.
Models and hypotheses
When two autonomous firms are merged together,
culture clashes inevitably occur. For the employees
involved, anxieties and stress are associated with the
merger. The merger and acquisition process is not only a
series of rational decisions but also a chaotic set of
events that profoundly affect employees’ lives and future
prospects (Ashkenas and Francis, 2000; Buono, 2003).
For our case, the post-acquisition process was determined
by the logic of absorption. Employees of the
acquiring firm and the acquired firm are affected
asymmetrically. The respondents in this study are divided
into two groups, that is, employees of the acquiring firm
and the acquired firm in order to evaluate the extent to
which they were influenced by the merger process
invariantly.
The perceived changes of work load and career prospects
are two of the concomitant changes associated
with the post-acquisition process that concern employees
of both firms. Organizational commitment is a psychological
outcome of merger and acquisition. One goal of
this study is to assess group differences in the means of
work load change, career prospects change, and organizational
commitment. For this test the first hypothesis is
formulated thus:
H1: The means of work load change, career prospects
change, and organizational commitment are invariant
across employees of the acquiring firm and the acquired
firm.
Another focus of this study is the structural relationships
between the perceived changes of work load and career
prospect, organizational commitment and locus of control
in the process of merger and acquisition. Two competing
models are proposed to describe these structural
relationships. In the two models, locus of control acts as
an independent variable and a moderating variable,
respectively.
The first model is depicted in Figure 1. An organizational
change such as merger and acquisition often
leads to negative psychological outcomes such as low
job satisfaction and organizational commitment
(Schweiger and DeNisi, 1991). As discussed, the direct
influences of locus of control on organizational commitment
and other job-related variables are supported by

Figure 1. Structural relationships of Model 1.
Figure 2. Structural relationships of Model 2.
many previous research results. Therefore, it is assumed
that employees’ locus of control affects their organizational
commitment and perceived changes of work load
and career prospects directly. In addition, the possible
influences of work load change and career prospects
change on employee organizational commitment are
implied in the literature review. In the first model, it is
posited that locus of control of employees affects
employee perceptions of work load change and career
prospects and that the perceived change in work load
and career prospects in turn affects their organizational
commitment. In other words, changes in perceived work
load and career prospects act as mediating variables.
The first model is denominated Model 1 in the following
text.
The second model is specified in Figure 2 and the
structural relationship is described as follows. The
employee perceptions of changes in work load and
Hung and Hsu 7547
career prospects affect their organizational commitment.
However, these relationships are moderated by the locus
of control. This model is denominated in Model 2. As
mentioned, previous research has found that locus of
control may interact with characteristics of the work
environment and affect job-related variables. Therefore,
this study proposes that the changes in work load and
career prospects resulting from mergers may interact with
the individual employee’s locus of control, affecting
organizational commitment. More specifically, it is
hypothesized that the relationship between employee
organizational commitment and perceived changes in
work load and career prospects may be moderated by
the employee’s individual locus of control. This approach
is supported by the results of other studies. Lin et al.
(2010) observed that the effect of work characteristic
change on organizational commitment for employees with
external locus of control is greater than for those with

7548 Afr. J. Bus. Manage.
internal locus of control. Similarly, Hsu et al. (2010)
indicated that internal locus of control moderates the
relationship between service-oriented organizational
citizenship behavior, service climate and service delivery;
the relationship between service climate and serviceoriented
organizational citizenship behavior is moderated
by external locus of control.
As indicated earlier, another possibility is that locus of
control acts as a mediating variable. The possible
structural relationships may then be described as follows.
Employee perceptions of changes in work load and
career prospects affect their locus of control and organizational
commitment, and locus of control influences
organizational commitment. However, it seems impossible
that the perceived work load and career prospects
change could affect employee locus of control itself,
which is shaped early in life, certainly before the changes
in work load and career prospects. That means that
changes in the work load and career prospects perceived
by employees must not be able to affect their locus of
control in the short term or for single instances of change.
For this reason, the relationships between variables
described by this possibility are considered unreasonable
in this study and will be ignored.
In Models 1 and 2, we expect that employee perceptions
of changes in work load change and career
prospects associated with the process of merger and
acquisition have a direct influence on their organizational
commitment. This leads to the second research
hypothesis:
H2: The direct effects of work load change and career
prospects change on organizational commitment are
statistically insignificant.
In Model 1 we expect that the locus of control of employees
has a direct effect on their perceived organizational
commitment, work load change and career prospects
change. These relationships are presented in the third
hypothesis:
H3: The direct effects of locus of control on organizational
commitment, work load change, and career prospects
change are statistically insignificant.
In addition to the direct links described earlier, two
indirect relationships are possible in Model 1. They are of
both theoretical and practical interest to the current study.
Both are related to the relationship between locus of
control and organizational commitment. From a practical
standpoint, one question is whether the locus of control
has a significant indirect influence on the organizational
commitment of the employees through their perceived
work load change and career prospects change. These
indirect relationships are presented in the fourth
hypothesis:
H4: The indirect effect of locus of control on organizational
commitment is statistically insignificant.
Finally, the moderating effect of locus of control is
assessed in Model 2. This leads to the fifth hypothesis:
H5: Locus of control has no significant moderating effects
on the path from work load change to organizational
commitment and that from career prospects change to
organizational commitment.
METHODOLOGY
Structural equation modeling and tests
Structural equation modeling (SEM) is the primary method of this
study. The term structural equation modeling refers to a family of
related procedures rather than a single statistical technique (Kline,
2005). In SEM various theoretical models that hypothesize how
sets of observed indicators defining constructs (the underlying
latent variables that the indicators are presumed to measure) and
how these latent constructs are related to each other may be tested
(Schumacker and Lomax, 2004).
Whether the means of work load change, career prospects
change and organizational commitment representing the various
companies are statistically significantly different from each other is
to be tested in H1. However, these variables are latent constructs,
whose means are unobservable. The structures of these latent constructs
are derived indirectly from their indicators, which are directly
measurable in turn. More specifically, equivalency of the latent
construct means related to work load change, career prospects
change, and organizational commitment across employees of the
acquiring firm and the acquired firm are evaluated. H1 can be
reformulated as follows:
H1: The latent construct means of work load change, career
prospects change, and organizational commitment are invariant
across employees of the acquiring firm and the acquired firm.
The other hypotheses of this study focus on the structural relationships
between work load change, career prospects change,
organizational commitment, and locus of control. Again, most of
these are unobservable. For this reason, structural regression (SR)
models were used to evaluate these structural relationships. SR
models, which can be viewed as syntheses of path and measurement
models, were used in this study to test the hypotheses of the
structural and measurement relations proposed earlier. The structural
component of a SR model depicts patterns of causal effects.
The observed indicators and the constructs, that is, the underlying
latent variables that the indicators are presumed to measure, make
up measurement components of SR models (Kline, 2005).
Sample
A total of 495 survey instruments were distributed with a cover letter
indicating that completion was voluntary and responses would be
kept confidential. To ensure confidentiality, a preaddressed,
stamped envelope was mailed with each questionnaire and all
responses were returned anonymously. A pilot study based on 50
returned questionnaires revealed that participants understood the
content of the questions and no change was necessary for the
questionnaire to be used in the main study. After removing
incomplete questionnaires, 438 fully completed questionnaires were
returned for an effective return rate of 88.5%. Data were collected
from two groups of participants. Group A consisted of 184 employees
who worked in the acquiring company. Group B consisted
of 254 employees who worked in the acquired company.

Prior to analysis, variables were examined through various SPSS
18 programs for accuracy of data entry, missing values, and fit
between their distributions and the assumptions of structural
equation modeling. 19 cases were identified through Mahalanobis
distance as multivariate outliers with a p-value less than 0.001. All
of these were deleted, leaving 419 cases for analysis. The overall
sample consisted of 68% female, with the average age and organizational
tenure being 35.45 and 7.36 years, respectively. Before the
merger, 53% of respondents were administrative staff members,
with the remainder being salespeople. After the merger, 50.4%
respondents were administrative staff members. Before the merger,
25.1% of respondents were managerial level employees. After the
merger, this figure fell to 23.2%.
Measurements
The psychometric properties of work load, career prospects and
organizational commitment were evaluated by employing the
method of confirmatory factor analysis via the use of AMOS 16. The
model fit was evaluated using the model chi-square (χ 2 ), normed
chi-square (χ 2 /DF), goodness of fit index (GFI), standardized root
mean square residual (SRMR), and root mean square error of
approximation (RMSEA) (Byrne, 2010).
Bollen (1989) suggested that values for the normed chi-square of
less than 5.0 indicate reasonable fit, while GFI values higher than
0.9 may indicate good fit. Values for the SRMR of less than 0.1
generally indicate favorable model fit (Kline, 2005). RMSEA values
of less than 0.05 indicate good fit, values between 0.05 and 0.08
reasonable fit, and values higher than 0.1 suggest poor fit (Kline,
2005). The composite reliability (CR) and the average variance
extracted (AVE) for each construct were employed to evaluate the
convergent validity of each construct.
Work load change
We developed a four-item scale to capture respondents’ perceptions
of work load changes after the merger for employees of both
companies. They are (W1): after the merger, my working hours are
lower than before; (W2): after the merger, my work load is lower
than before; (W3): after the merger, my working stress is lower than
before; (W4): after the merger, my company asks for lower work
quality than before. Respondents were asked to indicate the extent
of their agreement/disagreement along a 5-point Likert scale
ranging from “strongly disagree” to “strongly agree”.
Values of selected fit indexes are as follows: χ 2 (2) = 4.310, χ 2 /DF
= 2.115, p = 0.116, GFI= 0.995, SRMR = 0.0190 and RMSEA =
0.053, with the 90% confidence interval 0.000 to 0.122. These
results are generally favorable. The composite reliability for work
load is 0.4758, which is close to the critical value suggested by Hair
et al. (2009), with average variance extracted of 0.7524, which is
higher than that suggested by Fornell and Larcker (1981). These
values are at least minimally high enough to suggest convergent
validity. Overall, the fit of the model seems acceptable.
The equivalence of means related to work load change perceived
by employees of the acquiring company and the acquired company
is then tested. Employees of the acquired company are chosen as
the reference group. The latent mean difference between the two
groups is 0.045 with a p value of 0.443. This indicates that there is
no statistical difference between the work load change perceived by
employees of the acquiring company and employees of the
acquired company.
Career prospects change
Four items were developed for this study to capture respondents’
Hung and Hsu 7549
perceptions of changes of their career prospects after merger for
employees of both life companies. They are (C1): after the merger,
my position in our company is higher than before; (C2): after the
merger, more work resources are available to me than before; (C3):
after the merger, I perceive that my contributions to our company
are considered more important than before; (C4): after the merger,
my probability of getting promoted is increased. A 5-point Likerttype
was used ranging from “strongly disagree” to “strongly agree”.
Values of selected fit indexes are as follows: χ 2 (2) = 2.419, χ 2 /DF
= 1.209, p = 0.298, GFI = 0.997, SRMR = 0.0168 and RMSEA =
0.022, with the 90% confidence interval 0.000 to 0.102. These
results are generally favorable. The composite reliability for career
prospects is 0.4053, with an average variance extracted of 0.7120.
These values are at least minimally high enough to suggest
convergent validity.
The invariance of means related to career prospects change perceived
by employees of the acquiring company and the acquired
company is then tested. Employees of the acquired company are
chosen as the reference group. The latent mean difference between
the two groups is 0.021 with a p value of 0.41. This indicates that,
there is no significant difference in career prospects change
perceived by employees of the acquiring company and employees
of the acquired company.
Organizational commitment
The scale used to measure organizational commitment for this
study was a slightly reworded version of Meyer et al. (1993) 6-item
scale. These items are named from COM1 to COM6. A five-point
Likert response format ranging from “strongly disagree” to “strongly
agree” was used for all six items.
Values of selected fit indexes are as follows: χ 2 (9) = 30.183,
χ 2 /DF = 3.354, p = 0.000, GFI = 0.975, SRMR = 0.0251 and
RMSEA = 0.075, with the 90% confidence interval 0.047 to 0.105.
The p value of model chi-square seems to be unfavorable.
According to Kline (2005), values of χ 2 /DF lower than 5.0 are
recommended as indicating reasonable fit. Therefore, these results
are generally favorable.
We then proceed to test for differences in the latent means of
organizational commitment across employees of the acquiring and
the acquired company. Employees of the acquired company are
chosen as the reference group in this step. The latent mean
difference between the two groups is 0.138 with a p value of 0.026.
This indicates that there is no statistical difference between the
organizational commitment perceived by employees of the
acquiring company and employees of the acquired company.
Locus of control
The scale used to measure locus of control is a revised version of
Rotter’s (1966) locus of control scale. It includes 11 items directly
accepted from Rotter’s (1966) locus of control scale. They are item
2, 4, 6, 11, 13, 15, 16, 18, 21, 25 and 28. Each item is constituted
by a pair of statements. One statement expresses the external
locus of control, the other the internal locus of control. Respondents
are required to choose one statement of each pair. An internal
control statement is scored as 1, whereas an external one is scored
as 0. Hence, higher scores indicate stronger internal tendencies,
and lower scores indicate stronger external tendencies.
A single score for each respondent is obtained by summing the
number of internal statements chosen from the 11 statement pairs
and is denominated as LOC sum in the following text. The total
score can range from 0 to 11.
Actual scores for the 419 respondents ranged from 0 to 11 with a
mean score of 7.29. For testing for the moderating effect of locus of
control, internals and externals were selected from all respondents.

7550 Afr. J. Bus. Manage.
LOC_sum
Figure 3. Unstandardized estimates of SR for Model 1.
Kelly (1939) reported that “twenty-seven percent should be selected
at each extreme to yield upper and lower groups which are most
indubitably different with respect to the trait in question.” This rule
was verified by Curento (1957) again.
For this reason, we split the locus of control measure into three
groups at the 27 th and the 73 rd percentiles. Thus, 117 respondents
with scores higher than 9 were classified as internals and 141
respondents with scores less than 6 are classified as externals. The
161 respondents with scores between 6 and 9 were left untested.
ANALYSIS AND RESULTS
4.32
WLC
CPC
In the preceding discussion, the latent mean differences
of work load change, career prospects change and
organizational commitment between employees of the
acquiring company and those of the acquired company
are tested. The results indicate that differences in the
latent means of work load change and career prospects
change and organizational commitment across two
groups are statistically insignificant; employees of the
acquiring company have higher level of organizational
commitment than those of the acquired company.
Next, the structural relationships proposed in Models 1
and 2 are evaluated. Since work load change, career
prospects change and organizational commitment are
latent variables, SR models were used to test the
structural relationships.
Model 1 was tested on the overall sample. Testing was
accomplished through SR via the use of AMOS 16.
Values of selected fit indexes are as follows: χ 2 (86) =
.03
.02
e1
W1
.14
1
1.00
C1
1
.48
e5
e2
.08
1
e3
.34
1
W2 W3
1.00 1.20.77
.23
1.18
.07
err1
C2
1
.26
e6
err2
1
.30
.08
1
C3
1
.39
e7
1.75
e4
W4
1.36
1.44
.39
1
C4
1
.18
e8
.20
err3
.18
1
COM
COM1
1.00
COM2
.76
1.22
COM3
1.21
1.14COM4
1.02
COM5
COM6
347.950, χ 2 /DF = 4.046, p = 0.000, GFI = 0.902, SRMR =
0.0967 and RMSEA = 0.085, with the 90% confidence
interval 0.076 to 0.095. Some results are not favorable.
The value of SRMR is higher than 0.05; the value of
RMSEA is higher than 0.08. However, the value of
RMSEA is very close to the critical value. The proposed
model seems to be at least minimally adequate. The
unstandardized estimates of SR for Model 1 are depicted
in Figure 3.
We used the method of bootstrapping to estimate the
two-tailed significance for unstandardized or standardized
total effects, total indirect effects, and direct effects. The
number of bootstrap samples is set to be 1000. The
results of the bias-corrected percentile method are
reported in Table 1.
For the path leading from work load change to organizational
commitment (WLC--->COM), the unstandardized
estimate of the direct effect is 0.197, statistically significant
at the 0.01 level. This result indicates that
employees perceiving a greater decrease in work load
tend to have a higher level of organizational commitment
to the surviving company.
For the path leading from career prospects change to
organizational commitment (CPC--->COM), the unstandardized
estimate of the direct effect is 1.358, statistically
significant at the 0.01 level. This result indicates that
employees perceiving more improved career prospects
tend to have a higher level of organizational commitment
to the surviving company.
For the path leading from locus of control to work load
1
1
1
1
1
1
.25
e9
.71
e10
.22
e11
.29
e12
.21
e13
.28
e14

Table 1. Effect decomposition for Model 1.
Effect Unstandardized S.E. P Standardized
Direct effect
LOC_sum---> WLC 0.033 0.014 0.040 0.123
LOC_sum---> CPC 0.021 0.008 0.009 0.157
LOC_sum--->COM 0.071 0.015 0.007 0.119
WLC--->COM 0.197 0.058 0.002 0.176
CPC--->COM 1.358 0.331 0.003 0.622
Total indirect effect
LOC_sum--->COM 0.035 0.012 0.007 0.119
Total effect
LOC_sum---> WLC 0.033 0.014 0.040 0.123
LOC_sum---> CPC 0.021 0.008 0.009 0.157
LOC_sum--->COM 0.107 0.014 0.002 0.358
WLC--->COM 0.197 0.058 0.002 0.176
CPC--->COM 1.358 0.331 0.003 0.622
change (LOC_sum---> WLC), the unstandardized estimate
of the direct effect is 0.033, statistically significant at
the 0.05 level. This result indicates that employees with a
greater tendency toward internal locus of control appear
to more easily to perceive decreased work load in the
process of merger and acquisition.
For the path leading from locus of control to career
prospects change (LOC_sum---> CPC), the unstandardized
estimate of the direct effect is 0.021, statistically
significant at the 0.01 level. This result indicates that
employees with greater internal locus of control tendencies
appear to more easily perceive improved career
prospects in the process of merger and acquisition.
For the path leading from locus of control to organizational
commitment (LOC_sum--->COM), there are one
direct effect and two indirect effects. The unstandardized
estimate of the direct effect is 0.071, statistically
significant at the 0.01 level. The total indirect effects of
locus of control on organizational commitment are the
sum of the effect of locus of control on organizational
commitment through work load change and through
career prospects change. The unstandardized estimate of
the total indirect effect from locus of control to organizational
commitment is 0.035, statistically significant at
the 0.01 level. The total effect is the sum of the direct and
indirect effects. The unstandardized estimate of total
effect is 0.107, statistically significant at the 0.01 level.
This result indicates that employees with greater internal
locus of control tendencies appear to have a higher level
of organizational commitment to the surviving company.
Further, the relationship between locus of control and
organizational commitment is partially mediated by work
load change and career prospects change.
The unstandardized regression weights cannot be
directly compared, while the standardized regression
Hung and Hsu 7551
weights may be. The estimated standardized regression
weight of locus of control on work load change is 0.123.
That is, a level of locus of control one full standard
deviation above the mean predicts a work load change
level 0.123 standard deviations above the mean. The
estimated standardized regression weight of locus of
control on career prospects is 0.157. These results
indicate that locus of control has a stronger influence on
career prospects change than on work load change.
As for organizational commitment, the standardized
estimate of the total effect from locus of control is 0.358,
from work load change is 0.176, and from career
prospects change is 0.622. A comparison of these
standardized total effects on organizational commitment
from three antecedents shows that the total effect of
career prospects change on organizational commitment
is greater than the effect of either of the other two and the
total effect of locus of control on organizational
commitment is greater than that of work load change on
organizational commitment.
The squared multiple correlation of career prospects
change is 0.025. This means that the predictor of career
prospects change, locus of control, explains 2.5% of its
variance. The proportion of explained variance of work
load change by locus of control is 0.015. The proportion
of explained variance of organizational commitment by
locus of control, work load change, and career prospects
is 0.536.
Next, we tested the possibility that the relationships
between organizational commitment and its two antecedents,
work load change and career prospects change,
are moderated by locus of control. In other words, we
evaluated whether the regression weights of work load
change and career prospects change on organizational
commitment are significantly invariant across internals

7552 Afr. J. Bus. Manage.
Figure 4. Unstandardized estimates of SR for externals in Model 2.
and externals. This test is based on a multigroup analysis.
How participants were classified into each group is
described in the preceding text. The initial step is to
determine a baseline model for externals and internals
separately. In the baseline model we hypothesize that
work load change and career prospects change are
interrelated and these two latent variables influence
organizational commitment directly. The model being
tested can be considered as a multigroup representation
of the baseline models. It incorporates the baseline
models for internals and externals within the same file
and is commonly termed the configural model (Byrne,
2010). For externals, values of selected fit indexes are as
follows: χ 2 (74) = 125.556, χ 2 /DF = 1.697, p = 0.000, GFI
= 0.889, SRMR = 0.0866 and RMSEA = 0.071, with the
90% confidence interval from 0.049 to 0.090. Some
results are not favorable. The value of GFI is lower than
0.900, while the value of SRMR is higher than 0.05.
However, their values are very close to the critical values.
For internals, values of selected fit indexes are as
follows: χ 2 (74) = 150.679, χ 2 /DF = 2.036, p = 0.000, GFI
= 0.853, SRMR = 0.1135 and RMSEA = 0.095, with the
90% confidence interval from 0.073 to 0.116. Some
results are not favorable. The value of SRMR exceeds
0.05 while the value of RMSEA exceeds 0.08. However,
the value of RMSEA is close to the critical values. In
summary, the baseline model seems to be at least
minimally well fitting across the two groups. The
unstandardized estimates of SR for externals and
internals are depicted in Figures 4 and 5, respectively.
The next step is to impose the equality constraints in
the configural model, that is the constrained model. Here
the influence of work load change on organizational
commitment (WLC--->COM) and the influence of career
prospects change on organizational commitment (CPC---
>COM) were set to be invariant across two groups. The
fit of the configural model without equality constraints
provides the baseline values against which the constrained
model is compared.
Invariance decisions are based on the χ 2 difference
test. The value of χ 2 difference represents the difference
between the χ 2 values for the configural model and the
constrained model. Evidence of non-invariance is found
when the χ 2 difference value is statistically significant
(Byrne, 2010). The p-value of the χ 2 difference for Model
2 is 0.832. This result indicates that the moderating effect
of locus of control is not statistically significant and
confirms the H5.
The estimates of regression weights, covariance and
correlation for externals and internals are reported in
Table 2. These results are very similar for both groups.
For the path leading from work load change to organizational
commitment (WLC--->COM), the unstandardized
estimate of the direct effect is 0.210 for externals and
0.106 for internals respectively. For externals, it is
statistically significant, and for internals, insignificant at
the 0.05 level. For the path leading from career prospects
change to organizational commitment (CPC--->COM), the

Figure 5. Unstandardized estimates of SR for internals in Model 2.
Table 2. Estimates of regression weights, covariance and correlation for externals and internals.
Hung and Hsu 7553
Unstandardized S.E. P Standardized
Regression weights of baseline model for externals
WLC--->COM 0.210 0.101 0.038 0.202
CPC--->COM 1.610 0.574 0.005 0.683
Covariance S.E. P Correlation
WLCCPC -0.037 0.017 0.032 -0.337
Unstandardized S.E. P Standardized
Regression weights of baseline model for internals
WLC--->COM 0.106 0.135 0.434 0.074
CPC--->COM 1.585 0.781 0.042 0.481
Covariance Correlation
WLCCPC -0.017 0.012 0.148 -0.219
unstandardized estimate of the direct effect is 1.610 for
externals and 1.585 for internals, and is statistically
significant for both groups at the 0.05 level. For both
groups, the estimated standardized regression weight of
work load change on organizational commitment (WLC---
>COM) is less than the estimated standardized regression
weight of career prospects change on organizational
commitment (CPC--->COM). In sum, these results are
similar with those in Model 1.
It is worth noting that the covariance and correlation
between work load change and career prospects change
(WLCCPC) are negative for both groups and statistically
significant for externals. This result indicates that
employees who perceive more work load after merger

7554 Afr. J. Bus. Manage.
are more optimistic about their career prospects.
IMPLICATIONS AND CONCLUSIONS
The process of merger and acquisition brings both stress
and possibility for employees of the acquiring and
acquired firms. It also affects the organizational commitment
of employees of both companies at the same time.
In the case studied, the acquiring firm absorbed rather
than integrated the acquired firm. Theoretically, as Steuer
and Wood (2008) suggested, changes faced by
employees of the acquiring company and the acquired
company are not symmetric. There should be little or no
change for the acquiring company, while the acquired
company may face a high level of change.
In this study, we investigated whether in the process of
merger after acquisition, employees of the acquiring
company and those of the acquired company perceive
changes in work load and career prospects invariantly
and whether employees of the acquiring company have a
different level of organizational commitment to the
surviving company than those of the acquired company.
Three relevant results are obtained. H1 is thereby partially
rejected.
Firstly, work load change is perceived by employees of
the two groups invariantly. This result is somewhat
surprising. It might be expected that employees of the
acquired company would perceive more changes of work
load. However, work load is associated with costs. For
financial industries in Taiwan, merger and acquisition for
cost reduction is often followed by layoff of employees
and increased work load for the remaining employees of
both the acquiring company and the acquired company.
Secondly, change in career prospects is also perceived
by employees of the two groups invariantly. This result
needs to be explained. The employees of the acquiring
company should be expected to have a better career
prospects than those of the acquired company. Generally
speaking, after a merger the employees of the acquired
company face a higher probability of losing their jobs than
those of the acquiring company. One explanation for this
result might be that after the process of the merger, under
cost minimization, employees of both firms may face the
same probability of job loss in a case involving life
insurance companies.
Thirdly, employees of the acquiring company have a
higher level of organizational commitment than those of
the acquired company. Since the acquiring company is
the surviving company, this result is logically consistent,
especially when the absorption approach was implemented
in the process of merger. The acquired company
was a foreign-owned company. The process of absorption
means a severe clash of cultures for the employees
originally hired by B insurance life company. That
explains why employees of the acquiring company have
higher level of organizational commitment than those of
the acquired company, even when they all perceive
change in work load change and career prospects
invariantly.
The other focus of this study is the structural relations
in the proposed models. Six results pertaining to these
models were obtained and the relevant hypotheses
evaluated. First, employees perceiving greater decreased
work load tend to have higher level of organizational
commitment to the surviving company. Second,
employees perceiving improved career prospects tend to
have a higher level of organizational commitment to the
surviving company. Thus, H2 is rejected. These two
results appear to be logical and need no further
explanation. Third, employees with greater internal locus
of control tendencies appear to more easily perceive
decreased work load in the process of merger and
acquisition. Fourth, employees with greater internal locus
of control tendencies appear to more easily perceive
improved career prospects in the process of merger and
acquisition. Fifth, employees with greater internal locus of
control tendencies appear to have higher levels of
organizational commitment to the surviving company.
These results are consistent with what we derived from
the definition of locus of control and from the previous
literature (Rotter, 1990). The impact of personality on
organizational commitment is confirmed again in this
study as in the previous literature (Luthans et al., 1987;
Werbel et al., 1996). H3 is therefore rejected. Sixth, the
relationship between locus of control and organizational
commitment is mediated partially by work load change
and career prospects change. This result demonstrates
that organizational change may interact with the
individual’s personality, affecting psychological outcomes.
H4 is thus rejected.
In Model 2, the moderating effect of locus of control is
not statistically significant. H5 is thereby confirmed. This
result points out that we can limit our focus on Model 1.
As for Model 1, all direct effects and indirect effect are
statistically significant at the 0.05 level. These evidences
reject H2, H3 and H4. In addition to that, six relevant
results are obtained.
Comparing the standardized total effects of the antecedents
on organizational commitment, we found that the
change in career prospects of employees has the more
important influence on their organizational commitment
after the merger than work load change and locus of
control. It is an additional result of this study and implies
that in order to maintain organizational commitment to the
surviving company, employees give more weight to their
career prospects than work load. However, the relationship
from career prospects to organizational commitment
appears to have eluded previous studies. It thus
represents a novel finding of this study. This result may
be enhanced by another finding. Testing Model 2 yields a
negative covariance between work load change and
career prospects change. Employees perceiving greater
work load are more optimistic about their career

prospects. In other words, less work load is not always
desirable and is associated with organizational commitment,
especially when there is possibility of layoff after
merger.
There are several limitations of this study. It is a case
study and its results are, theoretically, not easily generalized.
However, they do have some general managerial
implications for cases which are similar to ours. Further,
the cross-sectional research design normally does not
allow affirmative causal inferences. But for several variables,
whose causal relationships are already specified in
psychology or other theories, the determination of their
causal relationships is not impossible. Therefore, the
causal relationships proposed in the present study are
not groundless.
The study of organizational commitment has had a long
history and continues to be a major focus of research.
However, employees’ organizational commitment in the
process of merger and acquisition is less well studied.
Employee work load and career prospects lack treatment
in previous research. The present study covers these
gaps. For further study, we would suggest that the
approach used to implement the change progress after
merger may be important for the study of employee
organizational commitment in the process of merger and
acquisition.
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African Journal of Business Management Vol. 5(17), pp. 7557-7563, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.596
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Improving supply chain performance: The strategic
integration of lean and agile supply chain
Seyyed Ali Banihashemi
Department of Industrial Engineering, Young Researchers Club, Islamic Azad University, Zahedan Branch, Zahedan,
Iran. Email: a.banihashemi@iauzah.ac.ir. Tel: +98-9353946173.
Accepted 27 May, 2011
By emergence of new areas of business in which change is an inevitable feature, it is difficult to survive
and succeed in the manufacturing systems. In other words, business environment changes and today's
work which results from changes in customer needs leads to uncertainty in parameters. Therefore, it is
necessary for supply chain to be flexible in decision making while encountering these uncertainties.
For supply chain performance to be more improved in this paper, first, the patterns of lean and agile
supply chain will be examined, then by introducing Leagilty Supply Chain, the relationship between
product life cycle of different products (standard, innovative, hybrid) and selection of the proper type of
supply chain will be examined.
Key word: Leanness, agility, leagility, supply chain management, product life cycle.
INTRODUCTION
The turbulent market conditions in the 21st century have
heightened the need for more competitive strategies to
be developed for growth (Sánchez and Pérez, 2005).
Business, economics and the political environments are
increasingly subjected to unexpected shocks and discontinuities.
Many strategic issues that confront business
today stem from: the new rules of competition, globalization
down pressure on price and the customer taking
control. Also, as a result of the recent economic
meltdown, companies around the world are confronted by
a perfect storm: frozen credit market and long global
recession. Events are moving so rapidly that it is almost
impossible to access the implication of the meltdown for
the days ahead, let alone the years to come (Njoroge,
2009).
Enterprises are continuously paying attention to
responding to the customer demand for maintaining a
competitive advantage over their rivals. Supply Chain
Management (SCM) has gained attention as it focuses on
material, information and cash flow from vendors to customers
or vice-versa. One of the key features of present
day business pertaining to the idea which holds it is
Supply Chain (SC) that competes, not companies
(Christopher and Towill, 2001), as well as the success or
failure of supply chains, is ultimately determined in the
market place by the end customer. Getting the right
product, at the right time to the consumer is not only the
linchpin to competitive success, but also the key to
survival. Hence, customer satisfaction and market place
understanding are critical elements for consideration
when attempting to establish a new supply chain strategy
(Agarwal et al., 2006).
The popularity of supply chain management is characterized
by several deriving forces, that is, global sourcing,
and an emphasis on time and quality based competition
and their respective contributions to greater environmenttal
uncertainty. In this dynamic business environment, the
competitions are based on time and quality. Providing
defect free product to the customer on time is the
fundamental requirement to be a successful organization.
In order to meet such requirements, a closer coordination
with suppliers and distributor is essential (Tarofder et al.,
2010). The main issue is that what is the appropriate
strategy in the use of supply chain? Is agile supply chain
always better than lean supply chain? Or it depends on
certain conditions? A supply chain must have the
following conditions:
1. Consistent with the type of organization's productive
product
2. Consistent with life stages of the product over the
whole supply chain

7558 Afr. J. Bus. Manage.
3. Compatible with changing the product type
4. Continuous dynamics in turbulent and competitive
environment of supply chains
Therefore this research is looking to provide a complete
definition of the types of supply chain and ultimately I will
prove their relationship with the type of products.
SUPPLY CHAIN PERFORMANCE
A supply chain consists of all parties involved, directly or
indirectly, in fulfilling a customer request. The supply
chain not only includes the manufacturer and suppliers,
but also transporters, warehouses, retailers, and customers
themselves. Within each organization, such as
manufacturer, the supply chain includes all functions
involved in receiving and fulfilling a customer request.
These functions include, but are not limited to, new
product development, marketing, operations, distribution,
finance, and customer service. A supply chain is dynamic
and involves the constant flow of information, product,
and funds between different stages. The primary purpose
of the existence of any supply chain is to satisfy customer
needs, in the process generating profits for itself. Supply
chain activities begin with a customer order and end
when a satisfied customer has paid for his or her
purchase. The term supply chain conjures up images of
product or supply moving from suppliers to manufacturers
to distributors to retailers to customers along a chain. It is
important to visualize information, funds, and product
flows along both directions of this chain. The term supply
chain may also imply that only one player is involved at
each stage. In reality, a manufacturer may receive
material from several suppliers and then supply several
distributors.
A typical supply chain may involve a variety of stages.
These supply chain stages include:
1. Customers
2. Retailers
3. Wholesalers/Distributors
4. Manufacturers
5. Component/Raw material suppliers
Not every one of these stages is needed to be present in
a supply chain. The appropriate design of the supply
chain will depend on both the customer’s needs and the
roles of the stages involved (Chopra and Meindl, 2004).
Supply Chain is described as a chain linking each element
from customer and supplier through manufacturing
and services so that flow of material, money and
information can be effectively managed to meet the
business requirement. Most of the companies realize that
in order to evolve an efficient and effective supply chain,
SCM needs to be assessed for its performance
(Gunasekaran et al., 2001).
Lee and Billington (1995) define a supply chain as a
network of facilities that procures raw materials, transforms
them into intermediate goods and then final
products, and delivers the products to customers through
a distribution system. The management of such a
network requires mastery of optimization logistics, or the
specific quantity of goods needed at a particular time and
price. Clearly, relationships with suppliers that make up
these networks are a central component to successful
supply chain management.
The success and failure of supply chains are ultimately
determined in the marketplace by the end consumer.
Getting the right product, at the right price, at the right
time to the consumer is not only the lynchpin to
competitive success but also the key to survival. Hence,
consumer satisfaction and marketplace understanding
are crucial elements for consideration when attempting to
establish a new supply chain strategy. The initiatives for
the improvement of Supply Chain performance strive to
match supply and demand, thereby driving down costs
simultaneously with improving customer satisfaction
(Mason-Jones et al., 2000).
Supply chain management can be defined as “the design
and management of seamless, value-added process
across organizational boundaries to meet the real needs
of the end customer” (Fawcett et al., 2007). As noted by
Gansler et al. (2004), SCM is the management and control
of all materials, funds and related information in the
logistics process from the acquisition of raw materials to
the delivery of finished products to the end user. Hugo et
al. (2004) defines “SCM as the management philosophy
aimed at integrating a network of upstream linkages
(sources of supply), internal linkages inside the organization
and downstream linkages (distribution and ultimate
customer) in performing specific processes and activities
that will ultimately create and optimize value for the
customer in the form of products and services which are
specifically aimed at satisfying customer demands”.
Generally, SCM involves relationships and managing the
inflow and outflow of goods, services and information
(network) between and within producers, manufacturers
and the consumers (Samaranayake, 2005).
The objective of SCM is to maximize value in the
supply chain. The value a supply chain generates is the
differences between what the final product is worth to the
customer and the costs that supply chain will in-cure to
fulfill the customers’ request (Marcus, 2010). SCM is
about competing for value, collaborating with customers
and suppliers to create a position of strength in the
marketplace based on value derived from end consumer
(Chopra and Meindl, 2007). Within an organization,
customer value is created through collaboration and
cooperation to improve efficiency (lower cost) or market
effectiveness (added benefits) in ways that are most
valuable to key customers. Value is not inherent in products
or services, but rather is perceived or experienced
by the customer (Handfield et al., 2009). The ultimate

goal of a SCM process is to create customer and
shareholder value, thus often called a value delivery
system.
Lean supply chain (LSC)
Lean production was developed at Toyota after a Toyota
delegation visited Ford’s car factories in the US and
realized that they never could serve the small home
market with a full array of types of cars using the technologies
of mass production. So, they started to develop
techniques that allowed them to produce flexibly as batch
size 1 (Vonderembse et al., 2006).
A Lean Supply Chain (LSC) employs continuous
improvement efforts that focus on eliminating waste or
non-value steps along the chain. It is supported by efforts
to achieve internal manufacturing efficiencies and step
time reduction, which enable the economic production of
small quantities and enhance cost reduction, profitability,
and manufacturing flexibility to some degree. The short
setup times provide internal flexibility, but a LSC may lack
external responsiveness to customer demands, which
can require flexibility in product design, planning and
scheduling, and distribution in addition to manufacturing
(Both, 1996).
As the rate of market change increases, the LSC
approach has evolved into “multiple niche competition”,
which is the production of any volume, even a single unit,
combined with the ability to satisfy multiple market
segments. Organizations recognize that along with the
added variety and responsiveness squeeze, they must
remain adaptable to future changes. Customer requirements
are continuously evolving (on the one side) and
product life cycles are growing shorter (on the other side),
therefore, along with being lean, supply chains must
respond to the market. As a result, successful organizations
move from concept to cash flow in a fraction of the
time (Vonderembse et al., 2006).
Agile supply chain (ASC)
Agility is vital ability in the revolutionary turning of the
business environment into a turbulent place of competition
and struggle for success. Agility is the ability to
detect the changes in the business environment, and
responding to them by providing the appropriate
capabilities (Sharifi and Zhang, 1999).
The Agile Supply Chain (ASC) paradigm relates to the
interface between companies and markets, an external
perspective on flexibility. An ASC focuses on responding
to unpredictable market changes and capitalizing on
them through fast delivery and lead time flexibility. It deploys
new technologies, methods, tools, and techniques
to solve unexpected problems.
Banihashemi 7559
Leagile supply chain: beyond lean and agile?
The establishment of a new supply chain strategy
depends on the consideration of two foremost critical
elements, the customer satisfaction and marketplace
understanding. A manufacturing enterprise can endeavor
to develop a strategy that will meet the requirement of
both the supply chain and end customer, only when the
constraints of the marketplace are understood (Chan et
al., 2009).
Lean focuses on the elimination of basically seven
types of wastes that are overproduction, waiting time,
time incurred in transportation, inventory, motion, defective
units, and overprocessing. Agile production system
emerged as an alternative to the lean principles
(Richards, 1996). Agile strategy aims at using the market
knowledge and virtual cooperation to utilize the advantageous
opportunities in a volatile marketplace. It focuses
on the adaptation according to the changes in the market.
Both the lean and agile strategies have proven their
usefulness in their respective situations, but the present
market scenario demands a more robust strategy that
can encapsulate the salient features of both. This gave
birth to a new strategy termed as “Leagile”. The leagile
strategy combines the lean and agile principles through a
decoupling point, which separates the production line into
two parts at the point of product differentiation (Naylor et
al., 1999). Analytical process for improving supply chain
performance is depicted in Figure 1.
Leanness and Agility in a supply chain do not have to
exclude each other, however, Lean Supply Chain paradigm,
with its focus on advanced standardization as the
way to improved efficiency, can discourage innovation,
differentiation and complex learning needed to carry on
the change. Leanness is about doing more with less.
Agile Supply Chain operations are market sensitive,
network based, with process alignment and virtual
operations. Combination of these two concepts within the
scope of one firm or a single supply chain can be called
as “Leagility”. Table 1 presents the distinguishing attributes
of the associated supply chains.
STRATEGIC RELATION BETWEEN SUPPLY CHAIN
AND PRODUCT LIFE CYCLE
LSC focuses on reducing lead time, increasing efficiency,
expanding manufacturing flexibility, and cutting cost. LSC
approach attempts to build a level schedule across the
supply chain, and it uses pull production to respond to
customer demand. While striving for these goals, the LSC
focuses on incremental improvements (Kaizen). It tries to
improve the product and the associated processes, by
balancing the supply chain.
The long product life cycle of standard product provides
a stable design over many years. Being a low cost item,
globally manufactured, with highly predictable demand

7560 Afr. J. Bus. Manage.
Supply chain performance determinants
Supply chain performance dimensions
Market
sensitiveness
To analyze the supply chain
performance
Supply chain performance
weighted Index
Lead Time Cost Quality Service Level
Process
integration
Information
driver
Figure 1. Analytical process for improving supply chain performance. (Agarwal et al., 2006).
Table 1. Comparison of lean, agile, and leagile supply chain.
Flexibility
Distinguishing attributes Lean supply chain Agile supply chain Leagile supply chain
Market demand Predictable Volatile Volatile and unpredictable
Product variety Low High Medium
Product life cycle Long Short Short
Customer drivers Cost Lead-time and availability Service level
Profit margin Low High Moderate
Dominant costs Physical costs Marketability costs Both
Stock out penalties Long term contractual Immediate and volatile No place for stock out
Purchasing policy Buy goods Assign capacity Vendor managed inventory
Information enrichment Highly desirable Obligatory Essential
Forecast mechanism Algorithmic Consultative Both/either
Typical products Commodities Fashion goods Product as per customer demand
Lead time compression Essential Essential Desirable
Eliminate muda Essential Desirable Arbitrary
Rapid reconfiguration Desirable Essential Essential
Robustness Arbitrary Essential Desirable
Quality Market qualifier Market qualifier Market qualifier
Cost Market winner Market qualifier Market winner
Lead-time Market qualifier Market qualifier Market qualifier
Service level Market qualifier Market winner Market winner
Sources: Naylor et al. (1999), Mason-Jones et al. (2000), Olhager (2003), Bruce et al. (2004).

Sale
Lean Supply Chain (LSC)
Growth
Introduction
Figure 2. Standard Product Life cycle.
Sale
Maturity
Agile Supply Chain Lean Supply Chain
Growth
Introduction
Figure 3. Innovative Product Life Cycle.
patterns, profitability can be achieved by minimizing cost
and employing a level schedule over the entire supply
chain and over all the products life cycle stages (Mason-
Jones et al., 2000). This justifies the usage of a LSC for
standard products (Figure 2). In addition to providing cost
minimization, the LSC is efficient and flexible, and it
brings about incremental improvements, permitting firms
to constantly improve the quality of their products and
keep their customers satisfied.
Thus, to have the highest internal performance and
customer satisfaction, standard products should be
designed and produced by lean supply chains through all
stages of the product life cycle.
In order for innovative products to succeed, they should
be producible in any volume, as per customer requirements.
The first two stages of the product life cycle, introduction
and growth, are the testing grounds to ensure
Maturity
Decline
Time
Decline
Time
Banihashemi 7561
that organizations are achieving customization and
market adaptability. Once the product has been firmly
established, it transitions into third stages of its life cycle,
maturity. By this stage, the innovative product begins to
take on the characteristics of a standard product.
Thus, to have the highest internal performance and
customer satisfaction, innovative products should be
designed and produced by agile supply chains in the
introduction and growth stages, and lean supply chains in
the maturity and decline stages of the product life cycle
(Figure 3).
Hybrid products, which are complex, require the organization
to bring together a set of suppliers with a wide
range of capabilities (Choi and Hong, 2002). This implies
innovative and standard products as well as strategic
partnerships. While it may be true that hybrid products
that are near the end of their life cycle may use fewer

7562 Afr. J. Bus. Manage.
Sale
Leagile Supply Chain
Growth
Introduction
Figure 4. Hybrid Product Life Cycle.
innovation components than a product that is all the
beginning, there is always the opportunity to introduce
innovation into the hybrid product. As a result, hybrid
products require Leagile Supply Chain throughout their
product life cycle.
Thus, to have the highest internal performance and
customer satisfaction, hybrid products should be designed
and produced by leagile supply throughout the
product life cycle (Figure 4).
Conclusion
Lean and agile patterns in the supply chain are today the
main focus of many manufacturing companies (today)
which are seeking to improve performance. Each of the
above views, that is, Lean and agile patterns have their
own specific advantages and strengths, points and have
maximum efficiency in the specific situations. In fact by
considering different features and situations of productive
organizations and systems it is possible to take profit
from any of them or both of them. Clearly, the development
of theories and researches in this area requires an
understanding of these two models. Moreover, their
differences, barriers and constraints without having a
proper understanding of the supply chain dimensions in
the lean, agile and leagile patterns and (also) selection of
improvement in the supply chain will not have appropriate
efficiency and effectiveness. In this paper the relationship
between type of selected supply chain (lean, agile and
leagile) and life cycle of various products (standards,
innovative, hybrid) was investigated. Finally I realized that
the standard products in their entire life cycle require the
lean supply chain while standard products in the two first
stage of their life cycle (introduction and growth) require
agile supply chain and in later stages (maturity and
decline) require lean supply chain. Also hybrid or leagile
patterns are appropriate patterns for hybrid products. As
Maturity
Decline
Time
a general result it can be said that lean and agile supply
chains are highly appropriate in to enhance management
performance in turbulent market. Uncertainty in demand
and variability in product is a point of distinction between
lean and agile supply chain. For products that have short
life cycles we should consider more sensitivity in analyzing
appropriate type of chain because demands grow
faster and will have more fluctuation. Thus, organizations
may encounter greater risk for deficiencies in the early
stages of product life cycles; and these deficiencies may
create a false demand therefore potential customers may
decrease. As a result, companies may face a huge inventory
that their sale is declining. It should be noted that the
manufacturing and construction facility in this situation
may be abolished sooner than products with longer life
cycle. As a general conclusion, matching features of
supply chain and product is more important than its
improvement in the future. Because the supply chain may
not have sufficient time to improve itself and may only
benefit from interesters related to short life cycle of the
product.
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African Journal of Business Management Vol. 5(17), pp. 7564-7574, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.613
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Does proactive green logistics management improve
business performance? A case of Chinese logistics
enterprises
Yongrok Choi 1 and Ning Zhang 2 *
1 Department of International Trade, Inha University, Incheon 402-751, South Korea.
2 School of Management, Shandong Women’s University, Jinan 250300, P. R. China.
Accepted 6 May, 2011
Sustainability is a subject of growing interest in business and environmental management. Many
previous studies have emphasized the trade-off between economic activities such as manufacturing and
its effect on the environment. Moreover, previous studies have mainly focused on manufacturing
enterprises; however, no study has yet to cover the logistics sector. This study fills these gaps by
testing the causal relationship between proactive green management and the sustainable performance
of logistics enterprise in China. In addition, when compared with previous literature that discusses the
partial relationship between environmental variables and firm performance, this study synthesizes the
factors of green awareness and green strategy that may influence green logistics management in a total
systematic structural equation model (SEM). SEM has an advantage in examining the causal relationship
between green logistics practice and its business performance. The result shows that green logistics
practice has a positive impact on sustainable business performance. This impact is composed of both a
positive financial and environmental performance, while the relationship between green awareness and
business performance and the influence of green strategy on business performance is not significant.
Keywords: Green logistics management, structural equation model (SEM), business performance, Chinese
logistics enterprises.
INTRODUCTION
As the global economy integrates countries across the
world, the paradigm shift from manufacturing to assembling
has emphasized the importance of logistics. In the
era of cooperative business by assembling, businesses
have functioned with many partners. Thus, logistics has
been widely used to describe integrated practice among
the networks of transportation, storage, and handling of
products as they move from material source through the
supply chain system to the final point of sale or
consumption, which is the key determinant of business
performance (Choi, 2011). As Zhou et al. (2008) indicated,
environmental issues are increasingly important;
research on both the macro- and micro-level touch on the
environmental issues in many ways. He et al. (2009) also
suggested the importance of energy savings in the
*Corresponding author. E-mail: zn928zn@hotmail.com. Tel: +82
32 8607760. Fax: +82 32 8769328.
transportation of products.
Prior to the 1980s, the environmental initiatives for
logistics enterprises were typically temporary and passive
in response to government regulations. Recently, public
concern began to increase over environmental issues,
and new international standards were introduced,
including ISO 14001 and ISO 26000, in order to accredit
enterprises’ green practices (Lee, 2009). Customers
became more sensitive about whether suppliers had the
required environmental accreditation (Lee and Kim, 2009).
As Murphy and Poist (1995) indicated in their survey
studies, 61 percent of U.S. firms had formal or written
environmental strategies. Thus, if the enterprises plan to
extract more value by adopting green management, they
must make environmental management a strategic element
of their business performance.
Green logistics is a relatively young but rapidly evolving
subject. In fact, Aronsson and Brodin (2003) found that
only 2.2 percent of papers related to logistics addressed
environmental issues. Even if many enterprises set off

the green awareness movement by adopting corporate
social responsibility (CSR) programs into their business
plans, they would still lack the integrated practice
regarding the green logistics network. With the increasing
volume of integrated practices on green logistics, now is
the time to answer the question whether there is a tradeoff
between green logistics practice and business performance.
Will firms who pay more attention to the practice
of green logistics attract more business and achieve
greater environmental performance? This question is not
new, and similar efforts have been made to empirically
examine the relationship between green management
practices on business performance (Huang and Shih,
2010; Chang and Fong, 2010). Our paper shall extend
this approach to the field of logistics enterprises as the
network manager of all manufacturing processes.
Previous studies have suffered from some limitations
as discussed further. First, previous literature has
highlighted only a partial relationship between green
management and its performance. For instance, some
studies have analyzed a direct relationship between environmental
management and environmental performance
(Szymanski and Tiwari, 2004; Zhu and Sarkis, 2004).
Other studies have tested the causality between environmental
management and financial performance (Wanger
et al., 2002; Wanger, 2005). This paper integrates these
two factors into a more comprehensive model; we
consider the total effect between the environmental and
business variables, as well as their performance.
Environmental (green) awareness and a proactive green
strategy were integrated into the model to test the
relationship between these physical and practical issues
of green management and its sustainable performance.
Our discussion about the sustainable performance
includes information about the financial performance as
well as the environmental performance.
Secondly, while previous studies mainly focused on
manufacturing enterprises with general environmental
variables, no studies have researched the logistics sector
with special green logistics management variables. This
paper fills this gap to analyze the relationship between
green logistics management and its performance in the
logistics sectors of China which is the largest logistics
market worldwide.
Thirdly, most studies are based on the regression
analysis in their methodological approaches. Even if this
direct causality explains the role of green issues easily
and clearly, it still lacks the integrated multi-dimensional
or step-wise implication of the empirical results.
Therefore, the paper introduces the structural equation
model (SEM) to correct this methodological bias.
LITERATURE REVIEW
The more field-oriented empirical question is whether improved
environmental management could lead to better
business performance. A large body of literature has
Choi and Zhang 7565
been devoted to empirically test the link between green
management and business performance. However, a
general consensus has not been reached (Zeng et al.,
2010). Some authors argue that proactive environmental
management is simply a tool to help enterprises form
better business performance, resulting in these two input
and output variables, which create a positive relationship
(Huang and Shih, 2010; Wu et al., 2010; Zeng et al.,
2010). By placing more emphasis on environmental
management, enterprises may reduce costs and increase
revenues (Ambec and Lanoie, 2008). Other studies,
however, conclude that environmental practices and
initiatives involve higher costs and fewer benefits, and
they may even create a negative relationship between
environmental management and business performance
(Cordeiro and Sarkis, 1997; Link and Naveh, 2006;
Wanger, 2005).
As shown in Table 1, recent studies on the relationship
between green management and business performance
have made conclusions that have contradicting implications
on each other. The conclusions may come from the
different set of variables and/or the methodological bias
as shown in Table 1. Most studies have employed a
multiple regression analysis to test the relationship; one
disadvantage of the multiple regression analysis is that is
can only provide partial information. In addition, all
studies have focused on environmental management in
general, especially in manufacturing industries. None of
the studies have touched on the green logistics issues in
manufacturing or the role of logistics enterprises.
To synthesize all of these approaches, we use the
structural equation model (SEM) to analyze the causal
relationship between green logistics management and
the business performance of logistics enterprises in
China. SEM is a technique that involves multiple regression
analysis, path analysis, and confirmatory factor
analysis (Hussey and Eagan, 2007). SEM uses both
structure equations and measurement equations. The
structure equations depict the relationship among the
latent variables, which shows the qualitative relationship
between exogenous and endogenous variables in the
multiple regression analysis. The measurement equations
map the relationship between the latent variables
and observable variables using a confirmatory factor
analysis (CFA) (Chen and Li, 2010).
Hypotheses and model
Based on the comparison of previous research studies as
shown in Table 1, we shall discuss the various research
hypotheses and models.
Enterprise size hypothesis
López-Gamero et al. (2009) found that larger firms are
more likely to integrate environmental strategies into their

7566 Afr. J. Bus. Manage.
Table 1. Comparisons on the previous literature.
Authors Study object Green variables
Hart and Ahuja
(1996)
Russo and
Fouts (1997)
Cordeiro and
Sarkis (1997)
Christmann
(2000)
King and
Lenox (2002)
Wanger et al.
(2002)
Melnyk et al.
(2003)
Menguc and
Ozanne (2005)
127 U.S. firms
in SIC
Performance
variables
Emission reduction data ROA, ROE,
ROS
243 U.S. firms Environmental ratings,
compliance, waste reduction
523 U.S. firms
in SIC
88 U.S. chemical
companies
614 U.S.
manufacturing firms
37 European
firms
1222
manufacturing firms
140 Australian
manufacturing firms
Wanger (2005) European
manufacturing
sector
Link and
Naveh (2006)
77 Israel ISO
14001 certified
organizations
Toxic release inventory,
recycled on-site
Pollution prevention
technology
Total emissions, pollution
reduction, waste treatment
Environmental index
SO 2 emissions, NOx
emissions and COD
emissions
State of the environmental
management
Higher natural environment
orientation (NEO)
Method
Relationship
between findings
Regression Positive relationship
ROA Regression Positive relationship
Industry
analyst
earnings
Cost
advantage
ROA, Tobin’s
q
ROS, ROE,
ROCE
Corporate
performance
index
Market share,
sales growth,
profit
Energy,water,SO 2 ,NOx,COD ROCE, ROE,
ROS
ISO 14001 policies,
emission, use of recycled
materials
Gross profit
margin
Regression Negative
relationship
Regression Positive relationship
Regression Positive relationship
Simultaneous
equation
Wahba (2008) 156 Egyptian firms ISO 14001 certification Tobin’s q Correlation
and
regression
Wu et al.
(2010)
Huang and
Shih (2010)
Zeng et al.
(2010)
238 Taiwan IT firms Decrease of consumption
for hazardous materials and
environmental accidents
332 Taiwan
manufacturing firms
125 Chinese
manufacturing firms
Operational
cost and
training cost
Environmental knowledge Environmental
performance,
financial
performance
Cleaner production Saving,
profit,brand
Negative
relationship
Regression Positive relationship
Path analysis Partial relationship
Regression Negative
relationship
Regression No relationship
Positive relationship
Regression Positive relationship
Structural
equation
Model
Structural
equation
Model
Positive relationship
Positive relationship

usiness practices than smaller firms. The firm size may
reflect the legitimacy principle or the scale of the enterprise
that is visible to the public. A large enterprise may
be either seen as a sector leader, or it is likely to have a
greater environmental risk (Chen et al., 2006). Aragón-
Correa et al. (2008) also indicated that size is a relevant
factor to creating proactive environmental strategy, but
size is not a determining condition to developing environmental
management. Therefore, in this study, we
propose the following hypotheses:
H1a: Enterprise size has a positive effect on environmental
(green) logistics awareness.
H1b: Enterprise size has a positive influence on proactive
environmental (green) logistics strategy.
Green awareness and green strategy hypothesis
If an enterprise has green logistics awareness, then it is
easy to understand that the enterprise may also need a
proactive green logistics strategy and green logistics
practices. As some authors have indicated, green
awareness is the key element of a green strategy. López-
Gamero et al. (2010) found that if the environmental
strategies are drive from green awareness, and are not
driven from legislation, then their effect on environmental
management is significantly positive. Hart and Ahuja
(1996) demonstrated that firms with that have an early
awareness may be opting for more advanced environmental
strategies that build on low emissions. Sarkis
(2006) indicated that enterprises that develop an early
strategy in pollution-reducing processing equipment
benefit from a higher profit growth than later followers.
This implies that firms implemented green awareness into
better environmental programs and strategies will have
better environmental performance. These concepts lead
to the formulation of the following hypotheses:
H2a: There is a positive relationship between green
logistics awareness and green logistics strategy.
H2b: Green logistics awareness has a positive effect on
green logistics management.
H2c: Green logistics awareness has a positive effect on
business performance.
H3a: Proactive green logistics strategy has a positive
influence on green logistics management.
H3b: Proactive green logistics strategy has a positive
influence on business performance.
Green logistics management hypothesis
As previously discussed, extensive literature has examined
the relationship between green management and
business performance; however, these studies have
yielded no conclusive results. Some authors have
Choi and Zhang 7567
showed a positive relationship between these concepts
(Wu et al., 2010; Zeng et al., 2010). Other authors have
showed a negative relationship (Cordeiro and Sarkis,
1997; Wanger, 2005). Although the results are mixed,
research that has demonstrated a positive relationship
between “green management (not green logistics)” and
performance is found to be predominant. It is interesting
to note that all studies published after the year 2005
(Table 1) showed the positive relationship. Thus, as the
green issues become increasingly critical, green management
is a key element to help an enterprise extract more
value. In the light of these reasons, we propose the
following hypothesis:
H4: Green logistics management has a positive impact on
the business performance.
Insights into these hypotheses provide us with a basis to
make inferences on the relationship among those
variables, as shown in Figure 1.
METHODOLOGY
Sample and data collection
Our sample and data was collected via internet questionnaires; we
used the first self internet questionnaire website in China
(http://www.taidu8.com). The respondent was asked to focus on the
staff, section chief, and manager of the logistics enterprise. This
questionnaire started in May 2010, and it was completed in
September 2010. A total of 137 copies of the questionnaires were
collected and 98 copies of the questionnaires provided all of the
information required (these questionnaires came from different
areas of China). The 98 logistics enterprises represent the various
kinds of operational areas: 19.2% are in the integrated logistics
sector, 13.7% are in the transportation sector, 14.3% are in the storage
sector, 6.0% are in the packing sector, 6.6% are in the loading
and unloading sector, 7.7% are in the logistics information sector,
5.5% are in the delivery sector, and the rest are in the manufacturing
sector. The small- and medium-sized enterprises account for
79.6%, large-sized enterprise account for 20.4%.
Measurement of the latent variables
Enterprise size
The enterprise size was considered as a control variable to test our
hypotheses, which predict that the business size has a positive
effect on green logistics awareness and strategy. In this study, the
firm’s number of employees, capital sum, and gross sales of 2009
were selected to measure firm size as Choi et al. (2010) suggested.
Table 2 shows the frequency and measures of enterprise size in
this paper.
Green logistics awareness
Following the guidance of authors such as López-Gamero et al.
(2010), we used 6 items (a1 to a6) to measure green logistics
awareness in terms of self-perception of the firms’ managers including
awareness of the government’s green policies, mindfulness
of being green mind, knowledge about being green, the behavior of
staff, green standardization, and green training. Each item is

7568 Afr. J. Bus. Manage.
Figure 1. Research hypotheses and structural model.
Table 2. Enterprise size measures and frequency.
Size measure Frequency Percent Question measure
5 million below 52 53.1 1
Capital sum*
5-50 million
50 million -100 million
31
8
31.6
8.2
2
3
Over 100 million 7 7.1 4
Gross sales*
Employee
*Measured in RMB Yuan.
measured on a 7-point Likert response scale (1 = strongly disagree,
7 = strongly agree).
Green logistics strategy
Zhu et al. (2005) emphasized green logistics “strategy.” In this study,
9 items (s1 to s9) are used to measure the green logistics strategy
of firms. Some of the items included strategies on standardization,
infrastructure, emissions reduction, technological management, and
sustainability; they were measured using a 7-point Likert scale also.
Green logistics management
Green logistics management refers to detailed environmental
logistics practices on different types of logistics process. Although
many previous studies used various variables for environmental
5 million below 41 41.8 1
5 - 50million 36 36.7 2
50million – 100 million 10 10.2 3
Over 100 million 11 11.2 4
50 below 41 41.8 1
50 – 300 37 37.8 2
300 20 20.4 3
management, no studies have suggested measures for green logistics
management. In this study, 20 detailed items are selected in
relation to the different logistics processes. These items included
information sharing (m1 to m3), packing (m4 to m6), warehousing
(m7 to m9), distribution (m10 to m12), loading and unloading (m13
to m14), logistics networking (m15 to m17), and emissions reduction
(m18 to m20). We used a 7-point Likert scale to measure the
items too.
Business performance
Previous studies focused only on environmental performance
(Szymanski and Tiwari, 2004; Zhu and Sarkis, 2004) or only on
financial performance (Wanger et al., 2002; Wanger, 2005; Zeng et
al., 2010). In this paper, we integrate both items including environmental
performance (green image gain and green service level-up)
and financial performance (sales increase and energy cost

Table 3. Descriptive statistics and correlations of latent variables.
Choi and Zhang 7569
Statistics Mean Std. Dev. Awareness Strategy Management Performance Size
Awareness 4.099 1.500 1.000
Strategy 4.235 1.496 0.922 1.000
management 4.459 1.407 0.879 0.949 1.000
performance 4.273 1.534 0.828 0.882 0.913 1.000
Size 1.796 0.770 0.070 0.089 0.130 0.143 1.000
Table 4. Reliability and validity test by the Cronbach’s α and CFA.
Variables Cronbach’s α Chi-square/df (p) GFI NFI CFI RMSEA
Green awareness 0.952 1.627 (0.11) 0.962 0.982 0.993 0.080
Green strategy 0.974 1.303 (0.18) 0.956 0.983 0.996 0.056
Green management 0.984 1.628 (0.10) 0.962 0.984 0.994 0.080
Business performance 0.965 1.915 (0.15) 0.980 0.992 0.996 0.077
Recommended criteria > 0.7 < 3 (> 0.05) > 0.9 > 0.9 > 0.9 < 0.08
reduction) to represent sustainable performance.
All the details in our questionnaire items for the proxy variables
can be found in Appendix 1. Table 3 shows the descriptive statistics
and correlations of the five latent variables. Since each of the
correlations of the five variables is smaller than the corresponding
calculated Cronbach’s coefficients in Table 4, the composite index
of variables are acceptable for further analysis (López-Gamero et
al., 2009).
RESULTS
Reliability and validity
The proposed model must be statistically reliable and
valid, so it can reflect reality, and we must ensure that the
statistical results are meaningful. A positive result for the
reliability test implies that the proposed method reflects
similar results when tested again under the same conditions.
For the reliability test, we used the Cronbach’s α
coefficient, which is the most commonly used criterion to
measure reliability.
Validity refers to the extent to which items reveal true
information. A confirmatory factor analysis (CFA) is one
of the most effective tools to test the validity (Zeng et al.,
2010). SPSS 17.0 and Amos 17.0 were used to test the
reliability and validity, respectively. The results were demonstrated
in Table 4. For the reliability, the Cronbach’s
coefficients are bigger than suggested, 0.7, and for the
validity test, the CFA measures, such as Chi-square/df ,
GFI (goodness-of-fit index), NFI (normalized fit index),
CFI (comparative fit index), and RMSEA (root mean
square error of approximation) are all better than the
recommended criteria. This indicates that the reliability
and validity of the data are good. The Cronbach’s α and
the confirmatory factor loadings of each item can be
found in Appendix 1.
Hypotheses test results
The Amos 17.0 package was employed to run our structural
equation modeling using the maximum likelihood
(ML) approach. The overall fitness of the SEM is evaluated
using the same set of goodness of fit indices used for
the confirmatory factor analysis; Chi-square /df=2.029,
GFI, NFI, and CFI are all bigger than 0.9, which suggests
that the SEM fits the data adequately. All of the SEM
modeling and path coefficients are shown in Figure 2 and
Table 5. The results show that H1a and H1b are rejected;
thus, there is no significant relationship between
enterprise size and green awareness or size and green
strategy. For green awareness, the results indicate that
green awareness has a significant positive relationship (p
< 0.01) with green strategy, thus supporting H2a; but has
no relations with green practices. Also there is no
relationship between green awareness and business
performance, so we must reject H2b and H2c. For the
green strategy, the results show that the green strategy
has a significant positive effect on green management (p
< 0.01), accepting H3a, but it has no significant impact on
business performance, rejecting H3b. Finally, there is a
significant positive relationship between green management
and business performance (p < 0.01); thus, we
must accept H4.
DISCUSSION
Managerial implications
H1: As for the issues of size, the results show that H1a
and H1b were not supported. These results indicate that
the enterprise size does not play a significant role on the
green logistics awareness, enterprise size, and logistics

7570 Afr. J. Bus. Manage.
es3
es2
es1
1
1 s3
1 s2 1
s1
est1
1
st1
size
a6
1
ea6
est2
1
st2
est3
1
st3
1
a5
1
ea5
es
ea
1
1
est4
1
st4
1
a4
1
ea4
est5
1
st5
strategy
est6
1
st6
H2a: 0.957 ***
awareness
a3
1
ea3
est7
1
st7
H3a: 1.194 ***
a2
1
ea2
est8
1
st8
est9
1
st9
Manage
em
a1
1
ea1
ep1
1
ep2 1
p1 p2
1
ep3 1
p3
performance
H4: 1.184 ***
1
M1
M2
ep4 1
p4
1
1
1
em1
em2
M3 em3
1
M4 em4
M5
M6
1
1
1
1
em5
em6
M7 em7
Figure 2. Path coefficients in the structural equation model.
*** means p

China. Green leadership could be emphasized in large
logistics enterprises in China, but their leadership may
not be compensated for corresponding performance.
H2 and H3: As for the green awareness and strategy, the
results indicate that green logistics awareness has a
significant effect on green logistics strategy (H2a). However,
it has no significant impact on green logistics
management (H2b). The green logistics strategy has a
significant effect on green logistics management, which
confirms H3a; however, it has no significant effect directly
on business performance, which rejects H3b. These
results indicate that green awareness does not have a
direct effect on green management. However, it has an
indirect effect on green management through its effect on
green strategy. The empirical results imply that green
awareness only cannot lead to field-oriented green practices
in the enterprise, so the government should promote
official environmental strategies or policies to the logistics
enterprise to improve green logistics management. These
implications agree with studies by Hitchens et al. (2003)
and López-Gamero et al. (2010) in that green awareness
by the governance legislation has a positive effect on
environmental strategy. However, Hart and Ahuja (1996)
demonstrated a different view that firms with early awareness
may be opting for more advanced environmental
management, which results in low emissions.
Sarkis (2006) indicated that an early strategy for
pollution-reducing processing equipment offers more
benefits with a higher profit growth than companies who
are later planners. However, the findings in Table 5
indicate that the green strategy did not show a direct
effect on business performance, but an indirect effect via
its effect on green management. It implies that planning
or strategies only cannot bring environmental benefits.
The only factor that directly influences the business
performance is the practice of green management.
H4: The results show that there is a significant positive
relationship between green logistics management and
business performance. Thus, we can confirm H4. Our
findings coincide with Rao and Holt (2005) and Wu et al.
(2010); however, they disagree with Cordeiro and Sarkis
(1997). Rao and Holt (2005) suggest that the enterprise
with green supply chains may achieve a substantial cost
savings, enhance sales, and exploit new market opportunities,
which results in a better business performance.
Wanger (2005) also demonstrates that high levels of
environmental performance are only possible if the enterprise’s
green management has a proactive technological
pollution orientation. The results in Table 5 imply that
from the empirical evidence of the logistics enterprises in
China, it is necessary to adopt green practices as the key
element in their business model to extract more value
and enjoy better business competitiveness. These results
also imply that the role of government promotion policies
for green logistics is much more important for logistics
enterprises to mold their strategies via their awareness
(Choi and Lee, 2009).
Conclusion
Choi and Zhang 7571
Previous studies about green management and its
performance have focused mainly on manufacturing
enterprises, and they have only focused on the partial
relationship between the dichotomy of the business and
the environment. This study aims to contribute to current
literature by introducing a synthetic model that is based
on structural equation modeling to test the causal
relationship between green logistics management and
business performance of the logistics sector in China. As
a global factory, the role of the logistics network of China
becomes more and more important. Thus, the synthetic
analysis of diverse facets of green logistics related issues
shall shed light on the paradigm for the logistics
enterprises as well as the government promotion policies
about the competition between green or sustainable
logistics.
In this paper, we found that there are no significant
roles of enterprise size in either the green awareness or
green strategy. Thus, even large enterprises cannot
utilize the economies of scale or leading advantages in
logistics management. The result indicates that green
awareness has a significant positive relationship with the
green strategy, but has no relationship to green management
and business performance; this suggests that green
awareness only cannot lead to detailed green practices in
the enterprise. It implies that the Chinese logistics enterprises
are generally in the initial stage of green logistics
because even though they are aware of the importance
of green logistics, they are eager to apply these ideas to
their business practices. Therefore, the government must
promote the official environmental strategy or planned
policy for the logistics industry. Also, the results show that
the green strategy has a significant positive effect on
green management, and there is a significant positive
relationship between green management and business
performance as well. It shows the spirit of strong pragmatism
among the Chinese enterprises, suggesting that
the green practices are the key element for the logistics
enterprises to extract more value and to enjoy better
business competitiveness.
ACKNOWLEDGEMENTS
This work was supported by the Korea Research
Foundation Grant funded by the Korean Government
(KRF-2008-005-J01602) and Inha University Research
Grant.
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APPENDIX
Appendix 1: Measures of observed variables
Green awareness item
Your firm follows government policy on green
Logistics actively
The managers of firm pay close attention to green
Logistics
The managers of firm have a good knowledge on
green logistics such as carbon footprint
The staff has a good awareness of
green logistics
The firm follows green standardization well such as ISO 14001 and GRI
guidelines
The firm pays close attention to green training
for employees
Indicator in
Figure 2
Choi and Zhang 7573
Cronbach’s
α
Factor
loadings Mean
a1 0.832 0.904 3.867
a2 0.904 0.906 4.051
a3 0.932 0.917 4.143
a4 0.926 0.907 4.173
a5 0.903 0.851 4.296
a6 0.905 0.758 4.061
Green strategy item
Your firm takes great effort on logistics standardization St1 0.86 0.867 4.194
The firm takes effort on plan of green infrastructure St2 0.925 0.921 4.204
The firm takes effect on strengthening green infrastructure St3 0.929 0.926 4.265
The firm takes effort on control of pollution sources in logistics activities St4 0.942 0.945 4.143
The firm plans Integrated distribution St5 0.899 0.862 4.235
The firms takes great effort on logistics technological research St6 0.939 0.912 4.194
The firms takes great effort on technological
standardization in logistics
St7 0.861 0.837 4.357
The firms take many activities in logistics standardization St8 0.887 0.858 4.306
The firms take great effort on green marketing and green business
management
St9 0.936 0.939 4.214
Business performance item
Financial performance: Through green logistics management, cost
decreases as a result of energy savings
Financial performance: Return on Sales is significantly increased through
green logistics management
Environmental performance: The green brand image is increased by green
logistics management
Environmental performance: Green service satisfaction level improved by
green logistics management
Catalog Green management
The firm shares information with
manufacturing firms and retailers
well
Information sharing
The firm makes great effort on
efficient and accurate ordering
system
The firm takes effort on outsourcing
to cut costs
P1 0.949 0.932 4.306
P2 0.958 0.939 4.306
P3 0.961 0.951 4.306
P4 0.94 0.921 4.306
M1
0.841 0.895 4.153
0.876 0.929 4.439
0.813 0.868 4.286

7574 Afr. J. Bus. Manage.
Appendix 1. Contd.
Packing
Warehouse
Transportation
Loading and
unloading
Logistics networking
Logistics emissions
The firm use green packing
materials
The firm follows packing
standardization
The firm makes effort on
reducing packing material
amount
The firm emphasizes
warehouse’s efficient
management
The firm emphasizes the
reduction of warehouse fee
The firm emphasizes the
location selection of
warehouse
The firm pushes the
standardization of transport
The firm tries to optimize the
routing of vehicles
The firm tends to select
greener vehicles and greener
transport modes such as
shipping and air
The firm focuses on loading
and unloading efficiently
In order to improve efficiency,
the firm considers the
container or pallet
The firm pays attention to
construction of logistics
networking
The firm emphasizes
information technology input
and usage
The firm pays attention to
efficient logistics information
network
The firm tries hard to reduce
the pollution emissions in
logistics activities
The firm takes great effort to
reduce green house gas
(GHG)
The firm takes great effort to
save energy costing
M2
M3
M4
M5
M6
M7
0.91 0.931 4.357
0.888 0.862 4.418
0.903 0.928 4.357
0.864 0.903 4.653
0.877 0.895 4.673
0.886 0.929 4.602
0.888 0.868 4.786
0.897 0.931 4.633
0.857 0.862 4.306
0.824 0.928 4.276
0.878 0.903 4.480
0.913 0.895 4.571
0.921 0.929 4.520
0.913 0.862 4.531
0.859 0.928 4.388
0.86 0.903 4.367
0.853 0.863 4.388

African Journal of Business Management Vol. 5(17), pp. 7575-7578, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.640
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
The influence of the emotional intelligence on self
monitoring
Sandhya Rani C. 1 *, R. G. Priyadharshini 2 and T. Kannadasan 3
1 Sri Niketan Trust (SNT) Global Academy of Management Studies and Technology, Coimbatore – 641 105, Tamil Nadu,
India.
2 Amrita School of Business, Ettimadai, Coimbatore, Tamil Nadu, India.
3 Center for Research, Anna University of Technology, Coimbatore, Tamil Nadu, India.
Accepted 21 June, 2011
Self monitoring is an ability to consciously observe and regulate one’s own behaviour. Incorporating
self monitoring in today’s research and practice is beginning to yield a better understanding of how
organizational processes are substantially affected by individual issues of how they are seen by others.
Especially in service industries, the effect of outcome of interactions of the employees with the clients
is an inevitable part of portraying their identity. Most of the actions in the service industry having a
legal importance, it is highly essential that controlled image presentation should not cause any
deceptions. Hence, it is essential that the employees should know how they present themselves and be
able to use self monitoring in the best way possible by them. There are two approaches to the
measurement of emotional intelligence: as a mental ability or as a personality trait. Emotional
intelligence is the capacity for recognizing our own feelings and those of others, for motivating
ourselves, and for managing emotions effectively in ourselves and others. The findings of this study
confirm that emotional intelligence is related to self monitoring behaviour. This understanding can
contribute to practitioners in the areas of recruitment and in assessing the training needs of healthcare
professionals.
Key words: Self monitoring, emotional intelligence, healthcare industry.
INTRODUCTION
As in the stage play, our actors in real life, the managers,
need to be well versed in the art of stage acting and also
be good critics of their peers too. In other words, the
managers need to skillfully manage the impression they
create on others in a wide range of situations ranging
from such simple ones as meeting a colleague in the
lobby to more complex and delicate ones like dealing with
a troubled customer. This phenomenon of willfully
managing impressions is referred to as impression
management. It is the process through which individuals
attempt to influence the impressions others form of them.
Skill in this process - both to manage one’s impressions
*Corresponding author. E-mail: sandhyacyriac@gmail.com. Tel:
0091 9791680593.
and identifying the impression management techniques
of others - has become more significant to employees in
current organizational settings. Strategic attempts by
people to control images projected in real or imagined
social interactions have become to be known as
impression management or self monitoring (SM) (Snyder,
1979). Individuals high in self monitoring are used to
monitor self presentations. They seem inconsistent in
their responses across relevant situations, modifying
behaviour as a function of who is present, what situation
requires and what the results of such behaviour may be.
High self monitors thus adhere to a hedonistic principle:
they isolate pertinent social cues and mold their
behaviour so as to maximize their personals gains
(Danheiser and Graziano, 1982). It is not surprising that
when the tables are turned, that is, when high self
monitors are perceivers: they are skilled in detecting the

7576 Afr. J. Bus. Manage.
impression management tactics by others. This paper
attempts to understand how emotional intelligence affects
the self monitoring behaviour of healthcare professionals
Meaning of self monitoring
Self monitoring is an ability to consciously observe and
regulate behaviour (Snyder, 1974). This ability to control
self presentational behaviour varies considerably among
individuals (known as high self monitors) with some able
to change their attitudes and behaviours according to the
environment they find themselves in. Others who are less
attentive to situational cues and who behave more
consistently, with their actual feelings and beliefs, are
known as low self monitors (Montigliani and Giacalone,
1999).
Factor affecting self monitoring
A variety of environmental, actor, and audience
characteristics serve as stimuli that shape actor and
audience definitions of the situation (Schlenker, 1980).
The environmental factors could be the work place itself,
organizational culture, the work itself, etc. and the actor
characteristics could be gender, age, race, personality
traits, etc (Gardner and Martinko, 1988). One of the two
approaches to emotional intelligence (EI) views emotional
intelligence as a personality trait. This research intends to
investigate the effects of personality factors like emotional
intelligence on self monitoring on organizational
settings.
Meaning of emotional intelligence
From the time human beings have been conscious, we
have been trying to reckon how to feel better and to get
along with each other. The words of wisdom on these
topics have been documented over time. The disciplines
of philosophy (such as that supported by Aristotle, Sir
Thomas More and William James), religion, science,
fiction, and nonfiction are examples of humanity's
continued efforts to improve upon civilization. Thus, the
fundamental societal drive regarding the knowledge of
the intelligence of our emotions can be traced back a
long way. Emotional intelligence is the ability to monitor
one's own and others' feelings and emotions, to
discriminate among them, and to use that information to
guide one's thinking and actions. (Mayer et al., 1990) In
one of the earliest conceptualizations, Gardner (1983)
viewed emotional intelligence as consisting of adaptive
skills, whereby an emotionally intelligent person has a
deep awareness of his or her emotions and the ability to
label and draw upon those emotions as a resource to
guide behaviour.
Emotional intelligence as a personality trait
There are basically two approaches to the measurement
of emotional intelligence: as a mental ability or as a
personality trait. Mayer, Salovey and Caruso were
instrumental in initiating current interest in the concept by
their work in the beginning of the 1990's (Mayer et al.,
1990). They devised tasks in which people were
instructed to judge, among other things, the emotional
content expressed in art or music.
Emotional intelligence as a personality trait is
measured by personality test items of a fairly traditional
kind, and is close to many other questionnaire methods
for measuring various traits. The best-known example
has been devised by Bar-On (Bar-On, 2000; Bar-On et
al., 2000). Schutte et al. (1998) developed a framework to
explain emotional intelligence based on the model of EI
developed by Mayer et al. (1990). Petrides and Furnham
(2000) claim the self report emotional intelligence test
(SREIT) has a clear four factor structure comprising ‘self
management of emotions’, ‘self aware-ness of emotions,
‘social skills and ‘social competence’.
Objective of the study
This paper seeks to understand the effect of emotional
intelligence as a personality trait over self monitoring
behaviour in healthcare professionals.
Research hypothesis
The research hypothesis formed is as follows:
H1: There is no significant relationship between emotional
intelligence and self
Monitoring
In 1999, Abraham raised the question whether emotionally
intelligent employees engage in organizationally
functional behaviour from a genuine desire to promote
organizational goals or whether they are social
chameleons capable of organizationally dysfunctional
behaviour. In her work on developing a conceptual
framework of emotional intelligence, Abraham directed
that the future researchers should examine the motives
underlying impression management by clearly distinguishing
between positive organization-promoting and
negative self-serving motives. It was indicated that the
self monitoring aspect of the impression management
could be a motive for emotionally intelligent people. Self
monitoring is a form of impression management in its
ability to control expressive behaviour to match the
expression and self-presentation of others in social

Emotional intelligence Self monitoring
Figure 1. The Casual Model between the Emotional Intelligence and Self Monitoring.
Figure 2. PLS model showing the results of the relationship between Emotional Intelligence and Self
Monitoring.
situations (Snyder, 1974). Hence, in this research, the
research seeks to understand if highly emotionally
intelligent people are capable of better self monitoring
skills.
METHODOLOGY
Three hundred and thirty four healthcare professionals including
doctors, nurses and para-medicals from eight hospitals across
Tamil Nadu have participated in this study. Sampling frame is as
follows:
i. A to B2 cities in Tamil Nadu
ii. Private hospitals which are listed in Indian Medical Association
iii. Hospitals with more than 400 beds
iv. Hospitals which are multi specialty units including medical
colleges
The questionnaire used to measure self monitoring is Snyder’s self
monitoring scale developed by Mark Snyder. It is a 25 item self
administered questionnaire. Emotional intelligence was measured
using Scutte et al. Emotional intelligence scale. It is a 33 item
questionnaire called self report emotional intelligence test (SREIT).
The study uses partial least square path modeling technique.
This method does not make any assumptions about the distribution
of the data and is non parametric in nature (Wold, 1989; Wold and
Joreskog, 1982). After the data is collected, the scales are analysed
to achieve the following objectives: purification of scales, reliability
of scales, uni-dimensionality of scales and validity of the scales.
Purification is done using corrected item total correlation (CITC),
reliability is tested using Cronbach’s alpha, validity and unidimensionality
are tested using PLS Path modeling. Figure 1
depicts the casual model between emotional intelligence and self
monitoring.
FINDINGS
The relation was found to be highly significant (beta =
Rani et al. 7577
0.924, t = 31.344). The R 2 value is also sufficiently high
(0.854). This reinforces the theory that emotionally
intelligent people are also good in self monitoring. People
who are more aware of self and other’s emotions and
have the ability to manage the same, are more attentive
to situational clues. This also makes them more and
better equipped to change their feelings and beliefs
according to the situational demand. This in turn helps
them blend with the people and situations more
effectively. Figure 2 shows the PLS model and the results
of the relationship between emotional intelligence and
self monitoring
DISCUSSION OF FINDINGS
Graziano and Bryant (1998) suggested that it is possible
that a small, stable set of motives or emotional processes
underlie individual differences in self monitoring.
Individuals with higher self monitoring ability use social
cues to monitor how they present their self image. They
are also more likely to understand the self monitoring
behaviour of others. They also show inconsistencies in
their behaviour depending on the situation they are in.
Low self monitors on the other hand shows more
consistent behaviour. This study confirms the finding by
Venkatapathy and Sudhakar (2002) that individuals with
high self monitoring have higher emotional intelligence.
However, Bono and Vey (2007) had supported a nonassociation
between self monitoring and emotional
intelligence stating that it is possible, given sufficient
practice on the job, even individuals low in self monitoring
might learn to produce genuine, effective emotional
displays. The healthcare professionals work in an
environment where they come across a variety of

7578 Afr. J. Bus. Manage.
emotions by their patients and family. It is an advantage if
they are more emotionally intelligent and thereby have
better self monitoring abilities.
Conclusions
People, who are better social chameleons, have less
stress related problems and are better in interpersonal
relations. This being a desirable ability for managers in
the current globalized scenario, if institutions select and
develop people with higher emotional intelligence, they
will be more effective at work. Today’s organizations work
in highly varied and demanding people environment and
hence emotional intelligence is vital to effective working
environment. Future researchers should look into how
various measures of emotional intelligence are related to
self monitoring. This will provide further clues as to how
exactly, emotional intelligence helps self monitoring. A
further investigation of the same relationship, especially
in service oriented industries is also required to clarify the
role emotional intelligence on self monitoring in other
industries.
This research contributes to the understanding of the
relationship between emotional intelligence and self
monitoring. In service industry, ‘moment of truth’ is all the
more vital and is tied to survival. Employees who are
better in self monitoring become more desired in such
scenarios. This study provides key areas for
organizations to concentrate while recruiting people and
while deciding training needs especially for organizations
in healthcare industry.
REFERENCES
Abraham R (1999). Emotional Intelligence in Organizations: A
conceptualization. Genetic, Soc. Gen. Psy. Monograp., 125(22):
209-224.
Bono JE, Vey MA (2007). Personality and Emotional Performance:
Extraversion, Neuroticism and Self Monitoring. J. Occupat. Health
Psy., 12(2): 177-192.
Danheiser P, Graziano W (1982). Self Monitoring and cooperation as
self presentation strategy. J. Personal. Soc. Psy., 42: 497-505.
Gardner WL, Martinko MJ (1988). Impression management in
organizations. J. Manage., 14(2): 321-338.
Graziano WG, Bryant WHM (1998). Self Monitoring and the Self
Attribution of Positive Emotions. J. Personal. Soc. Psy., 74(1):
250-261.
Mayer JD, DiPaolo M, Salovey P (1990). Perceiving Affective
Content in Ambiguous Visual Stimuli: A Component of Emotional
Intelligence. J. Personal. Assess., 54 (3): 77.
Petrides KV, Furnham (2000). On the dimensional structure of
emotional intelligence. Personal. Individ. Differ., 29: 313–320.
Schlenker BR (1980). Impression Management: the Self-concept,
Social Identity and Interpersonal Relations. Brooks/Cole,
Monterey, CA.
Schutte NS, MalouJM, HallLE, HaggertyDJ, CooperJT, Golden CJ,
Dornheim L (1998). Development and validation of a measure of
emotional intelligence. Pers. Individual Differences, 25, 167–177.
Snyder M (1974). Self-monitoring of expressive behaviour. J.
Personal. Soc. Psy., 30: 526-537.
Venkatapathy R, Sudhakar B (2002). A Comparative Study on
Emotional Intelligence among Male and Female among
Management Graduates, South Asian J. Manage., 8(1): 29 -32.
Wold H (1989). 'Introduction to the Second Generation of Multivariate
Analysis,' in Wold H. (Ed.), Theoretical Empiricism. New York:
Paragon House, vii-xl.
Wold H, Jöreskog K (Eds.) (1982). 'Systems Under Indirect
Observation: Causality, Structure, Prediction', vol.2, Amsterdam:
North-Holland.

African Journal of Business Management Vol. 5(17), pp. 7579-7587, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.684
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Applying the extended theory of planned behavior to
predict the intention of visiting a green hotel
Kun-Shan, Wu 1 and Yi-Man Teng 2 *
1 Department of Business Administration, Tamkang University, Tamsui, Taipei 251, Taiwan.
2 Graduate Institute of Management Sciences, Tamkang University, Tamsui, Taipei 251, Taiwan.
2 Department of Food & Beverage Management, Technology and Science Institute of Northern Taiwan, Peitou, Taipei
112, Taiwan
Accepted 21 June, 2011
The study herein describes the use of the extended theory of planned behavior (TPB), together with the
additional variable of past behavior, to investigate the intentions of individuals to visit green hotels in
Taiwan. The aims of the present study were threefold: i) to use the extended TPB to identify the factors
that affect customers’ intentions to visit a green hotel; ii) to investigate the effect of past behavior on
customers’ visiting intentions; and iii) to examine the mediating role of the variables of the TPB on the
relationship between past behavior and the intention to visit a green hotel. Data collected from 250 faceto-face
surveys confirmed the hypotheses of the present study and the findings of the current literature
on this wider topic. The findings reveal that attitude, subjective norms, perceived behavioral control,
and frequency of past behavior, all positively affect the intention of a customer to visit a green hotel. In
addition, the influence of the frequency of past behavior on the intention to visit a green hotel, was
partially mediated by the variables of the TPB. The findings show that the modified TPB may be used to
understand behavioral intention in the context of visiting a green hotel. Some wider implications were
also derived, both from a theoretical point of view and from a practical one, for managers in the
hospitality industry.
Key words: Green hotels, theory of planned behavior, attitude, subjective norms, behavioral intention, past
behavior.
INRODUCTION
Tourism is generally recognized to be a ‘non-chimney’ industry
(that is, one that has a low environmental impact),
which is known to provide much in the way of significant
opportunities for employment and foreign income for the
host country. The longer that a tourist spends in a given
country or region, the greater the financial benefits to the
local economy, in terms of increased levels of trade for
local restaurants and shops. However, although tourism
provides business opportunities for local companies, it
nevertheless has an impact on the natural environment.
This can take the form of a greater consumption of water,
energy, and raw materials, as well as the increased emis-
*Corresponding author. E-mail: ymdeng@tsint.edu.tw
sion of greenhouse gases (for example, carbon dioxide),
and the generation of waste.
Indeed, although many of the products or services used
in the hospitality and tourist industry can damage the
environment during their production, operation, and disposal,
the provision of such services often relies on the
natural vibrancy of the surrounding area. In view of this
fact, the study contends that the hospitality industry can
no longer ignore its environmental responsibilities. As a
result, the development of so-called 'green’ hotels has
become one of the more important recent innovations in
the tourist sector. Green hotels may be distinguished
from ordinary hotels in that they aim to use products and
services that mini-mize the consumption of water and
energy, and reduce the output of solid waste, in order to
protect the environment from the further depletion of its

7580 Afr. J. Bus. Manage.
natural resources (GHA, 2010). Green hotels have
gained increasing prominence over the past 15 years,
with more mature markets such as those of the United
States and Canada having published ratings systems that
are specifically aimed at this emerging sector of the
tourist industry. For instance, the US implemented its
'Green Seal Hotel Plan' in 1995, and Canada introduced
its 'Green Leaf Eco-Rating Program' in 1998. Despite
these moves, green hotels in Taiwan are only at a
comparatively early stage of development.
Previous studies on this topic have focused on the
description of; (i) the management of environmental
practices in green hotels (Shen and Wan, 2001; Hung
and Lai, 2006), (ii) the reasons visitors choose to stay in
a green hotel (Yeh et al., 2003; Manaktola and Jauhari,
2007), and (iii) the green practices that visitors seek
when choosing between green hotels (Kung and Tseng,
2004; Chan and Ho, 2006; Park, 2009). However,
previous authors have paid little attention to the decisionmaking
of potential customers who may consider a stay
in a green hotel. In the context of a growing number of
consumers who seek 'green' alternatives, Manaktola and
Jauhari (2007) found that the environmentally friendly
practices of green hotels could provide them with a
competitive advantage. Han et al. (2010) were the first
authors to explain how customers frame their intentions
to visit a green hotel using the theory of planned behavior
(TPB). These au-thors found that attitude, subjective
norms, and perceived behavioral control all positively
affected their intention to stay at a green hotel. Han and
Kim (2010) subsequently extended the TPB to explain
customers’ intentions to pay a repeat to a green hotel.
In contrast, Ajzen (1988) suggested that the effect of
past behavior on behavioral intention was mediated by
the variables included in the TPB, namely attitude,
subjective norms, and perceived behavioral control. This
principle had also been demonstrated in the tourist
industry. Lam and Hsu (2006) found that when choosing
a destination, past behavior affects behavioral intention,
while Lee and Choi (2009) showed that past experience
was an accurate predictor of behavioral intention in their
research in the hospitality and tourism sectors. Kim et al.
(2010) further showed the positive impact of past
behavior on a person’s intention to visit a spa.
However, despite the findings in a number of studies of
the factors that influence the formation of intentions in the
context of green hotels, no researchers have yet
examined the effect of past behavior on the predictive
utility of the TPB to explain customers’ intentions to visit a
green hotel. In addition, no research has yet investigated
the mediating role of the variables of the TPB (that is,
attitude, subjective norms, and perceived behavioral
control) on the relationship between past behavior and
the intentions of customers to visit a green hotel.
In order to address this gap in the understanding of this
topic, the study herein proposes the extension of the TPB
in two ways: (i) by including the variable of past behavior
into the main framework of the TPB and (ii) by examining
the mediating role of the variables of the TPB on the
relationship between the past behavior and the intentions
of customers.
In view of the foregoing, the aims of the present study
were threefold: (i) to use the TPB to identify the factors
that affect customers’ intentions to visit a green hotel; (ii)
to investigate the effect of past behavior on the visiting
intentions of customers; and (iii) to examine the mediating
role of the variables of the TPB on the relationship
between past behavior and intention to visit a green hotel.
LITERATURE REVIEW
The relationship between subjective norms and
attitude
Yu et al. (2005) showed that ‘attitude’ has a mediating
effect on the variables ‘perceived behavioral control’ and
‘subjective norms’. Ryu and Jang (2006) found that subjective
norms are positively associated with a person’s
attitude to certain types of behavior. Wu and Lin (2007)
showed that attitudes are directly influenced by subjective
norms, which implies that when the subjective norms of
respondents are more positive, their attitudes are positive.
Han et al. (2010) demonstrated that a visitor's attitude
towards a green hotel is positively associated with his or
her subjective norms. Similarly, Tsai (2010) determined
that there exists a significant relationship between the
subjective norms and the participatory attitudes of tourists.
In view of the foregoing, we formulate the following
hypothesis:
H1: There exists a significant relationship between the
subjective norms and the attitudes of visitors who choose
to visit a green hotel.
The relationship between perceived behavioral
control and attitude
Previous studies have tested the strength of the link
between perceived behavioral control and attitude (Yu et
al., 2005; Tsai, 2010). After studying the behavioral tendencies
of Taiwanese tourists in Kinmen, Yu et al. (2005)
concluded that attitude has a mediating effect on the
perceived behavioral control and subjective norms of an
individual. This implies that when the perceived behavioral
control of respondents is more positive, so are their
attitudes. Tsai (2010) also showed a significant relation-

ship between a people’s perceived behavioral control and
his/her attitude. In view of the foregoing, the study
formulates the second hypothesis as follows:
H2: There exists a significant relationship between the
perceived behavioral control and the attitudes of visitors
who choose to visit a green hotel.
The effects of attitude, subjective norms, and
perceived behavioral control on behavioral intention
The TPB has been widely applied by researchers whose
aim was to use the behavior of individuals to predict their
intentions (Ajzen, 1991, 2002), and has often been used
to explain the specific behavior of an individual in a certain
environment (Hung et al., 2003; Teo and Pok, 2003;
Hsu and Chiu, 2004), such as in a restaurant (Cheng et
al., 2005), or when faced with decisions on purchasing
items such as genetically modified foods (O'Fallon et al.,
2007).
The results of these and other studies have demonstrated
the strong predictive power of the TPB. One of the
aims of the present study was to use the TPB to explain
the formation of customers’ intentions to visit a green
hotel. The study therefore hypothesized:
H3: Attitude has a positive influence on customers’ intentions
to visit a green hotel.
H4: Subjective norms have a positive influence on
customers’ intentions to visit a green hotel.
H5: Perceived behavioral control has a positive influence
on customers’ intentions to visit a green hotel.
The relationship between past behavior and
behavioral intention
Lam and Hsu (2006) determined that the frequency of
certain types of past behavior had a direct influence on
behavioral intention when choosing a destination, while
Lee and Choi (2009) showed that past experience was
an accurate predictor of behavioral intention in the
hospitality and tourist sectors. It is therefore reasonable
to assume that frequency of types of past behavior
influences behavioral intention under the following
hypothesis:
H6: Past behavior has a significant and positive influence
on customers’ intentions to choose to visit a green hotel.
Mediating effect of the TPB variables on past
behavior and behavioral intention
Ajzen (1988) demonstrated that the frequent repetition of
Wu and Teng 7581
a type of behavior can lead to the formation of a habit,
and that, in turn, a habit can increase a person’s
perceived control of a particular type of behavior. Ajzen
also suggested that the effect of past behavior on
behavioral intention was mediated by attitude, subjective
norms, and perceived behavioral control. Although a
number of researchers have shown that the frequency
with which a type of behavior has occurred in the past
can explain various types of social behavior and behavioral
intentions, few authors have discussed the mediating
role of these three TPB variables on past behavior and
behavioral intention (Cheng et al., 2005; Ajzen, 2001).
Cheng et al. (2005) examined the mediating role of these
variables of the TPB on the relationship between past
behavior and future intentions. They demonstrated that
the influence of past behavior on future behavioral intentions
was mediated by the variables of the TPB. In view
of this claim, the study formulates the following
hypotheses:
H7: Attitude mediates the effect of past behavior on the
intention to choose to visit a green hotel.
H8: Subjective norms mediate the effect of past behavior
on the intention to choose to visit a green hotel.
H9: Perceived behavioral control mediates the effect of
past behavior on the intention to choose to visit a green
hotel.
Based on the foregoing discussion, the proposed
behavioral model is outlined in Figure 1. This conceptualization
demonstrates how the study described herein has
extended the traditional scope of the TPB by adding the
frequency of past behavior as a fourth variable. Figure 1
also shows that our study considers the effects of
subjective norms and perceived behavioral control on
attitude, and examines the mediating role of attitude,
subjective norms, and perceived behavioral control on
the effect of the frequency of past behavior on customers’
intentions.
METHODOLOGY
Sample design and data collection
The quantitative data used in the present research were collected
by means of face-to-face surveys via convenience sampling. The
main criterion for the inclusion of potential respondents was the
ability to make their own purchasing decisions. Face-to-face
surveys were conducted by trained interviewers in a variety of
locations, including train stations, supermarkets, department stores,
shopping malls, and adult education classes, in order to obtain data
from a representative demographic profile. A total of 400 questionnaires
were distributed and 300 were returned. A further 50 of the
returned questionnaires were incomplete, and thus, 250 usable
responses were received from participants, which represented a
response rate of 62.5%. Almost two thirds of the respondents in

7582 Afr. J. Bus. Manage.
Past
behavior
H8
H9
H7
Figure 1. Research framework.
Subject
norm
Perceived
behavior
control
H6
H1
Represents direct effect
H2
Represents indirect effect
in the final sample were female (n = 158, 63.7%). In terms of the
distribution of ages, 74 subjects were aged 30 to 39 years (29.6%)
and 66 subjects were aged 40 to 49 years (26.4%). In terms of
educational background, 160 subjects (64.8%) were university
graduates, and 58 (23.5%) had completed their formal education as
far as senior high school level. Over half of the respondents (n=152,
60.8%) indicated that their individual incomes were less than TWD
50,000 per month.
Measurement instruments
The present study used previously established instruments to
measure each of the five constructs (that is, past behavior, attitude,
subjective norms, perceived behavioral control and behavioral
intention). The questionnaire included six sections. The first four
sections assessed attitude, subjective norms, perceived behavioral
control, and behavioral intention, respectively. The fifth section
assessed past behavior, and the sixth recorded the basic demographic
information of the respondents. The scales used for attitude,
subjective norms, and perceived behavioral control were adopted
from previous empirical studies that used the TPB (Ajzen and Driver,
1992). All the instruments were modified to reflect the context of
green hotels.
Attitudes towards green hotels were measured using the sevenpoint
semantic differential scale previously employed by Han et al.
(2010). Subjective norms were measured using three items, each of
which used the same seven-point rating scale from Han et al.
(2010). An example of a question in this section was 'Most people
who are important to me disapprove/approve when I visit green
hotels'. Perceived behavioral control was measured by means of
three items, each of which again used the same seven-point rating
scale. An example was 'I have the resources, time, and opportunities
to visit a green hotel when traveling'. The frequency of past
behavior was measured using two items. An example was, ‘In the
past 12 months, how many times have you stayed at a green hotel
when traveling?’ These responses were coded from 0 to 6 (0 =
Attitude
H9
H4
H8
H5
H7
H3
Behavior
intention
'none' to 6 = 'six times or more'). Behavioral intention was
measured by means of three items, each of which used the sevenpoint
rating scale. One example here was 'I am willing to visit a
green hotel when traveling'.
RESULTS AND ANALYSIS
Confirmatory factor analysis (CFA) was used to obtain
the factor loadings of the five constructs (past behavior,
attitude, subjective norms, perceived behavioral control,
and behavioral intention) and to assess the goodness-offit
of the model. The adequacy of the model was determined
by using the indices of goodness-of-fit suggested
by Hair et al. (2006). The convergent validity of the results
of the CFA must be supported by (i) the reliability of
each measure, (ii) the composite reliability (CR) of each
construct, and (iii) the average variance extracted (AVE;
Fornell and Larcker, 1981; Hair et al., 2006). Table 1
shows that the Cronbach's α of each item lay between
0.722 and 0.961, which was above the threshold level of
0.70 recommended by Nunnally and Bernstein (1994).
The CR of each construct lay between 0.76 and 0.96,
which was above the threshold level of 0.60 recommended
by Bagozzi and Yi (1988) and Fornell and Larcker
(1981), confirming that the research variables were
acceptable in terms of their reliability. In addition, the
factor loading t-value lay between 8.335 and 31.452, and
each of the measurable items reached significance
(p

Table 1. Analysis of the reliability and validity of each measurable variable.
Wu and Teng 7583
Construct Item Standardized factor loading t-value CR AVE Cronbach’s α
AT1 0.908 ---
AT2 0.927 25.207**
Attitude
AT3
AT4
0.914
0.876
24.054**
21.477**
0.96 0.81 0.961
AT5 0.905 23.428**
AT6 0.873 21.324**
Subjective norms
Perceived behavioral control
Behavioral intention
Past behavior
** p

7584 Afr. J. Bus. Manage.
Table 3. The recommended and actual values of fit indices.
Fit index 2
χ / df GFI AGFI CFI NFI NNFI RMSEA
Recommended value 0.90 >0.80 >0.90 >0.90 >0.90

Table 4. Results from hypothesis testing.
Hypothesis Path Path coefficient t-value Result
H1 SN�AT 0.577 9.189*** Supported
H2 PBC�AT 0.049 0.897 Not supported
H3 AT�BI 0.466 6.824*** Supported
H4 SN�BI 0.281 4.394*** Supported
H5 PBC�BI 0.196 4.002*** Supported
H6 PB�BI 0.201 2.850** Supported
** p

7586 Afr. J. Bus. Manage.
Past
behavior
***p

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African Journal of Business Management Vol. 5(17), pp. 7588-7592, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.755
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Role of rural production cooperatives in developing
non-oil exports of West Azerbaijan province, Iran
Farhad Lashgarara* and Nina Shaddeli
Science and Research Branch, Islamic Azad University, Tehran, Iran.
Accepted 8 July, 2011
One of the important functions of rural production cooperation is non- oil exports that is effective in
decreasing dependency to gained incomes of oil. The main purpose of this research is to study about
role of rural production cooperation in development of non- oil exports in west Azerbaijan province. It is
an applied research and the methodology is correlation. Questionnaire is the main instrument in this
research. The population of this research is 126 people, consisting of chairman and members of rural
production cooperation who were studied as survey. Statistical analysis is done with spssversion12
software. The result showed that majority of members believes that the rate of non- oil exports is in low
level. Results of regression analysis showed that the supportive policies, capital of production
cooperation and the faced obstacles determined 34% the development of non-oil exports.
Key words: Rural production cooperation, development of non- oil exports, west Azerbaijan province.
INTRODUCTION
Paying attention to the agriculture sector, according to
many experts and pundits, is a critical need of the country
and that agricultural sector has an important stage in the
country's economy (approximately 15% of the GDP is
produced in this sector). Importance of agriculture in
Iran's economy is undeniably critical but, however, the
production cooperatives’ total share of plans approved in
the central bank to provide early return facilities is only
4% (Ministry of Agriculture, 2008).
Rural production cooperatives, as one of the major
institutions of crop and livestock production, improve
business and, in addition to the cooperative economical
prosperity and development, make suitable conditions for
exporting goods and products particularly in border
areas. These cooperatives are non-governmental,
economical, and social organizations having a relatively
specialized scientific management based on popular
forces (members) and, with their seeking participation
decisions through public forum and the board, are
established, preserving the principle of ownership and
*Corresponding author. E-mail: f_lashgarara@srbiau.ac.ir
individual and family motivations so the needs of its
members in providing inputs and production such as
financial (money and capital), human (labor), inputs
(water, land, fertilizer, pesticide, machinery, etc.,) would
be satisfied (Abdullahi, 2005).
Non-oil exports are the rural production cooperatives’
important performances which is effective to reduce the
dependence on oil. After the first, second, and third development
plans, the country has not completely achieved
the anticipated objectives concerning the non-oil exports
and they still have a little share of earnings than oil
exports. Seriously revising production process in order to
improve export's chain has become inevitable (Tavassoli,
2005).
Non-oil goods are goods produced in rural production
cooperatives, including agricultural products and crafts
that can be exported abroad. Non-oil export growth is one
of the effective factors in the development of the country's
economy and because the Iranian economy is among the
oil-reliant economies, this reliance on oil revenue has
gone so far that many economists consider it as the main
cause of inflation and liquidity growth. The development
of non-oil exports against oil revenues’ rising are
considered as a strategy to reduce dependence and

mono production economy, and rural production cooperatives
are considered as one of the producer organizations
in the country which can be the best way out of this
process (Aran, 2005).
Various studies have been accomplished considering
the importance of rural production cooperatives as an
operating system with high productivity in the world.
"Calculating the productivity of production factors in
Hamadan province’s rural production cooperatives" has
been done by Rohani (1999). Results indicate that,
because of the using of seeding machine, mechanization
development of cooperatives, especially in rows cultivation
and land leveling, and educational/promotional services
by cooperatives` experts, efficiency of production
factors in the cooperatives, compared with the control
villages, has increased.
Nejatian (1999) studied the "factors affecting the
participation of cooperatives’ farmers and producers"; his
assessment has partly identified problems of farmers lack
of participation that include: low level of literacy and
culture in the region, farmers uncertainty of finance and
assigning tasks to the government, getting used to
constant subsidy and assigning tasks to the government,
culture's complex context and ethnic conflicts, cooperatives’
objectives fading and the land ownership issue, the
use of non-skilled technical staff, and lack of personnel
and marketing.
In a study entitled "The role of rural production cooperatives
in agricultural development, case study in Fars
province" by Nikbakht (2001), research findings indicate
that the studied rural production cooperatives were
somewhat effective in providing infrastructure services
but, in other cases of the process of agricultural production,
had a little influence. Other results of this study are
that these cooperatives were effective in providing input
not in the after production services and had not much
influence on the marketing and sale of agricultural
products.
Jafari and Paikani (2002) in their study entitled "The
role of export credit in developing non-oil exports of Iran",
the most important result of this study is that granting the
export credit is the most effective development lever of
the export growth and, by giving priority to the export
credit, the internal factors affecting non-oil exports
compared with the external ones would have a lighter
influence on the process of non-oil exports and, after the
credit factors, improving the external factors affecting the
export should be more considered.
Fallah (2006) studied the “factors affecting the participation
of members in the rural production cooperatives’
activities in Hashtgerd city”. Lack of adequate budget and
educational credit, covered villages dispersion, lack of
proper transportation for cooperatives, non-participation
of the cooperative's authorities for executing training
classes, illiteracy and low literacy of many members,
shortage of qualified training instructor, lack of the
Lashgarara and Shaddeli 7589
financial and credit for cooperatives, and necessary
support from the government are the main reasons and
restrictions that rural cooperatives are facing.
West Azerbaijan province, because of the God-given
potentialities, is one of the country's most important
agricultural poles and variety of garden products such as
vegetables and fruits; summer vegetables are produced
in it and, after the usage for the internal needs, considerable
amounts of productions are exported as various
kinds of fruit juice and concentrates, tomato paste,
raisins, and processed vegetables. The important point is
that the share of rural production cooperatives of these
exports is low including a small percentage of production
and export of the province. Considering that rural production
cooperatives have established more than two
decades in the West Azerbaijan region, only a small part
of the province's non-oil exports are performed by
cooperatives (less than 5%); and considering that many
regions’ cooperatives (including West Azerbaijan) and
their role in non-oil export development have not been
studied so far, it is necessary to study the different
aspects of the rural production cooperatives.
The main purpose of this is to evaluate the role of rural
production cooperatives in developing non-oil exports of
West Azerbaijan province. Specific objectives of the
study include: a review of the personal characteristics of
the cooperatives’ members, evaluating cooperative members’
knowledge and attitude to non-oil exports, evaluating
the rate of rural production cooperatives members’ of
non-oil exports, evaluating the members’ participation in
non-oil exports, evaluating policies sup-porting export in
rural production cooperatives, identifying the preventives
of rural cooperatives activities in developing non-oil
exports, and recognizing the effective factors of the
cooperatives’ activities in developing the non-oil exports.
MATERIALS AND METHODS
This is an applied and non-experimental (descriptive) research. The
methodology of research is correlation. Statistical population
consists of board members of all units of the rural production
cooperative. According to statistics obtained, the total number of
rural production cooperatives in the province is 21 units; each rural
production cooperative has a CEO and five board members which,
totally, the studied population is 126 persons. Census methods
were used for all 126 cases. The main tool used in this study is
questionnaire. Questionnaire consists of seven parts of members’
personal and professional characteristics, knowledge and attitude
of members, members’ participation, supportive policies of export,
factors affecting the performance of rural production cooperatives,
the barriers facing rural production cooperatives, and developing
the non-oil exports.
Content and face validity were established by a panel of experts
consisting of faculty members and some specialists in the Ministry
of Agriculture. Minor wording and structuring of the instrument were
made based on the recommendation of the panel of experts. To
measure the reliability, a pilot study was conducted with 30 rural
production cooperative members; computed Cronbach’s alpha
score was 78%, which indicated that the questionnaire was highly

7590 Afr. J. Bus. Manage.
Table 1. The attitudes member of rural cooperatives to the non-oil export (n=126).
Rate Frequency Percent Cumulative percent
Very little 60
47.6
47.6
Little 46
36.5
84.1
Moderate 20
15.9
100
Mode: Very little.
reliable. In addition to field practices, by using questionnaires,
reliability was gained through library studies such as documents
evaluation, reading books, journals, and theses. Independent variables
are the cooperative members’ awareness and attitude toward
non-oil exports, members’ participation, supportive policies for
cooperatives, capital of cooperatives, barriers facing rural
production cooperatives, factors affecting the performance of rural
production cooperatives, and members’ personal and professional
characteristics.
The dependent variable is the development of non-oil exports
measured by six questions in the form of Likert scale. The data
were analyzed by SPSS software.
RESULTS
Members’ personal and professional characteristics
The average age of this study was 38.42 years; the
youngest was 29 and the oldest, 61 years old. The most
frequent age was 37. 120 participants were male (95.2%)
and 6 (4.8%) were female. Educational degree of 51.6%
of respondents was diploma, 38.1% was bachelor and
higher and 10.3% was guidance.
Cooperative members’ knowledge and attitude about
non-oil exports
Most members (42.9%) have a lot of knowledge about
the benefits of rural production cooperatives non-oil
exports. Findings show that the attitude of 43.7% of the
members toward non-oil exports was moderate.
Members’ participation
Most members (38.9%) stated a moderate and 25.4%
stated a low participation in cooperatives.
Supportive policies for rural production cooperatives
1.61% of the respondents believed that policies are
inadequate, and only 6.3% believed that they are
adequate.
Barriers facing rural production cooperatives
According to the barriers facing rural production cooperatives
and their negative effects on the cooperatives’
non-oil exports, 46.8% of the members considered these
barriers at a very high level, but in order to prioritize the
barriers facing rural production cooperatives, it is seen
that the main obstacle facing rural production cooperatives
in developing the non-oil exports is the weakness in
processing the agricultural products which is at the top
priority. Also, lack of agricultural experts at the company,
changes in government financial policies, and instability
of regulations governing the exports are the next
priorities, respectively.
Developing the non-oil export
Table 1 illustrates the amount of non-oil exports development
of the rural production cooperatives. As shown,
47.6% of members, the highest rate, believed that non-oil
exports development of the rural production cooperatives
is at low level and 15.9% believed that it is at a moderate
level.
Factors affecting the cooperative's performance
45.2% of the respondents believed that the effect of
these factors on the cooperatives’ performance is at a
high level. But based on prioritizing the affecting factor on
rural production cooperatives’ performance, the most
important factor is agricultural machinery, which, having
the most average, is the top priority. Loans to cooperatives
and management priorities are the next priorities,
respectively.
Identifying factors affecting the activities of rural
production cooperatives in developing non-oil
exports
In this study, the multiple stepwise regression analysis
was used to identify factors affecting the activities of rural
production cooperatives in developing non-oil exports.
Correlation analysis results (Table 2) show that education,
knowledge, and factors affecting the activities of
rural production cooperatives have a significant positive
relationship with developing the non-oil exports at a95%
level. Barriers facing rural production cooperatives have a
significant negative relationship with developing the nonoil
exports at a 95%. Supportive policies for rural
production cooperatives and capital of rural production

Table 2. Pearson correlation between factors with non-oil export.
Research variable r P
Educational level 0.177* 0.034
Member knowledge 0.188* 0.021
Member attitude 0.063 0.554
Member participation 0.078 0.334
Factors affecting the activities 0.214* 0.038
Supportive policies 0.430** 0.000
Barriers of cooperatives -0.460* 0.008
Cooperatives capital 0.663** 0.000
**p < 0.01; *p < 0.05.
Table 3. Multiple regression analysis.
Variable B Beta Sig.
Constant 3.54 - 0.000
Supportive policies (×1) 0.326 0.435 0.002
capital of cooperatives (×2) 0.267 0.331 0.008
Barriers facing cooperatives (×3) - 0.241 - 0.293 0.042
R 2 = 0.34.
cooperative development have a significant positive
relationship with developing the non-oil experts at a 99%.
In order to explain the variance of non-oil export development
as shown in Table 3, at the first step, supportive
policies for rural production cooperatives variable were
entered the analysis. Results showed that the variable
with a determination coefficient of 0.3 has played the
most important role in the non-oil exports development. In
other words, about 30% of the variance of non-oil export
development is related to supportive policies for non-oil
exports. At the second step, after the supportive policies,
capital of cooperatives’ variable was entered into the
equation. Determination coefficient was 0.32. According
to the results, supportive policies for non-oil exports and
capital of cooperatives’ variables explained about 32% of
the non-oil development variance. Finally, at the third
step, barriers facing rural production cooperatives’ variable
was entered multiple stepwise regression analysis.
Determination coefficient was 0.34. Generally, supportive
policies for non-oil exports, capital of cooperatives, and
barriers facing rural production cooperatives’ variables
explained about 34% of the non-oil development
variance. According to the Table 3, multiple regression
linear equations are:
Y = 3.54 + 0.326(×1) + 0.267(×2) -0.241(×3)
Y = 0.435(×1) + 0.331(×2) -0.293(×3)
Figure 1 shows collections of determining and effective
factors in developing non-oil experts.
DISCUSSION AND SUGGESTIONS
Lashgarara and Shaddeli 7591
This study which is aimed to identify the role of rural
production cooperatives in developing the non-oil
exports show that most cooperative members believe
that the rate of non-oil export development in the rural
production cooperatives is very little. Results also show
that the supportive policies for non-oil exports, capital of
cooperatives, and barriers facing rural production
cooperatives are the most important factors affecting the
non-oil export development, while supportive policies for
non-oil exports have the most influence on the
development of non-oil exports. A study conducted by
Bani Lashaky (2004) shows that rising of capital in the
cooperative has a positive effect on the cooperatives’
performance which is confirmed by this study, too.
Nejatiyan’s (1999) study results showed that supportive
policies for cooperatives influence the cooperatives’
performance which is also approved by this study. In
order to support the rural production cooperatives:
i. Allocating a part of the funds of the Ministry of
Cooperation for the exporters,
ii. Manufacturing sector and business sector policies
synchronization,
iii. Decision making, setting the prospect, and offering
solutions by policy makers such as ministry of agriculture
and ministry of commerce to develop the non-oil exports,
and determining the appropriate tariff in the time they
needed are suggested.

7592 Afr. J. Bus. Manage.
Capital of
cooperatives
Developing Non-oil Experts
Barriers facing
cooperatives
Figure 1. Influencing factors on developing non-oil experts.
In order to improve the financial support for rural production
cooperatives, introducing the rural production
cooperatives to all financial institutions and financialcredit
institutions including the credit fund of the country
is suggested.
According to the effect of cooperatives’ capital on the
non–oil export development, allocating adequate share of
public budget credits of the country to rural cooperatives
is suggested to increase the cooperatives capitals.
Granting enough long-term facilities with low interest to
cooperatives, promoting the financial aspects and
domestic resources through increasing the capital of the
cooperative members, collecting and equipping the
members little savings in a form of local rustic loan fund
under the cooperatives’ cover (micro-credit approach) are
recommended
Guarantying members, by the cooperatives, for getting
the banks and financial institutions’ credits and loans,
providing appropriate conditions for cooperatives to use
the other cooperatives’ credit and facilities, and using the
cooperative fund's credits are factors strengthening the
rural production cooperatives.
REFERENCES
Supportive
policies
Abdullahi M (2005). Agricultural farming systems. Tehran: Ministry of
agriculture.
Aran GB (2005). Influencing factors on rural tendencies to
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African Journal of Business Management Vol. 5(17), pp. 7593-7602, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.761
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Behavioral approach to portfolio selection: The case
of Tehran Stock Exchange as emerging market
Farshad Heybati 1 , Freydoon Rahnamay Roodposhti 2 and Seyed Reza Moosavi 2 *
1,2,2 Department of Business Management, Science and Research Branch, Islamic Azad University, (IAU) Tehran, Iran.
Accepted 31 May, 2011
Behavioral finance is the study of the influence of psychology on the behavior of financial practitioners
and the subsequent effect on markets. In this paper, concepts of behavioral finance are surveyed and
then the portfolio selection model in framework of behavioral finance theories is presented and
compared with the Mean-Variance rational pattern. Historical data of TEDPIX for 10 years has been used
and separated to 2 parts of test and evaluation groups. The optimum weight for risky asset proposed by
standard mean-variance and behavioral model based on returns for the first 7 years (test data) in the 3
months periods. After that, returns of 84 optimum portfolios in a three year evaluation period are
calculated. Mean test (CL=95%) shows that in Tehran Stock Exchange, the research hypothesis return
of behavioral model is greater than return of standard mean-variance model, was rejected.
Key words: Behavioral finance, investment portfolio, mental accounting, asymmetric risk preference, loss
aversion.
INTRODUCTION
In standard portfolio selection model, optimal values are
determined regarding risk tolerance, investment limits,
financial goals and mean-variance optimization pattern.
But human being may not follow this process, because of
behavioral biases. For instance, people encounter shortterm
changes and long-term trends, change their
portfolio.
Several empirical studies about emotional biases have
been done. Kahneman and Tversky (1992) showed that
when encounter gain, investors are risk-averse, but
encounter loss, are risk-seeking (Asymmetric Risk-taking
Behavior). Also, lots of people have worse feeling toward
loss compared with the same amount of gain. This phenomenon
which is named risk-aversion is deeply related
to psychology of people and taken into account as one of
the fundamental concepts of prospect theory.
Most of financial theories are based on maximization of
expected utility and risk-aversion whereas empirical
studies about real world have criticized modern financial
*Corresponding author. E-mail: r-moosavi@iau-arak.ac.ir. Tel:
(+98)122276163.
theories and rational behavior hypothesis in recent years.
Psychologists’ studies show individuals’ behavior is
different from what modern financial theories draw for
rational human behaviors (Fernandez et al., 2009).
This paper surveys the hypothesis and frameworks of
behavioral finance theories and then, represents a portfolio
selection model based on behavioral finance
assumptions.
Statement of problem
Portfolio selection has always been one of the subjects of
financial theories. Before the 50th decade of 21st century,
most of financial theories were in form of case study
and nonsystematic. Harry Markowitz (1952) formulated
the first portfolio theory, in title of “Modern Portfolio
Theory” which was the first systematic financial theory.
Modern portfolio theory evaluates return and risk of risky
assets, using mean-variance pattern; and represents a
normative pattern for portfolio selection. This theory
assumes economic equilibrium, was the basis for other
financial theories like capital assets pricing model
(CAPM)developed by Sharp, Lintner and Mossine, and

7594 Afr. J. Bus. Manage.
and efficient market hypothesis by Fama. Fallow up
studies such as survey of behavior of stock price showed
some anomalies in reality and efficient financial market
hypothesis. So, researchers who are always looking for
behaviors and reasons of financial markets events,
attempted to explain behavior of decision makers in
financial markets, using behavioral science. They
explained the limits of rational financial theories such as
limits of arbitrage and human cognitive limits. So,
irregular behavior was known as an effective factor of
economic behavior as well as other economic variables.
Therefore, behavioral economics and behavioral finance
attempt to explain economic variables in the framework of
and normative theories, better and more accurate. The
most important questions in this field are:
1. How do cognitive limits affect on economic behavior
and investment decisions?
2. How the human behavioral biases could be modeled?
This paper attempts to explain irrational factors which
affect investment decisions and portfolio selection in
financial market of Iran and presents a behavioral model
based on frameworks of behavioral finance. Finally, this
model is evaluated and compared with rational portfolio
selection models.
LITERATURE REVIEW
Fernandez et al. (2009) classified behavioral biases into
two groups: cognitive biases and emotional biases.
These two groups cause irrational decision making.
Cognitive biases such as “anchoring” and “availability” is
caused by wrong reasoning and could be decreased by
getting more information. Emotional biases such as “loss
aversion” and “regret aversion” are caused by sudden
emotions and insight and could not be corrected easily.
Shefrin (2005) showed that portfolio selection in
framework of prospect theory is different from portfolio
selection in framework of expected utility theory. The
most important property of behavioral portfolio is that it
involves some risk free securities and some risky
securities and portfolio does not have enough diversification.
In this framework, an optimal portfolio is one which
covers the interests of decision maker instead of maximize
the expected return. Therefore, interests and
emotional biases are determinants in portfolio selection.
Kahneman and Tversky (1979, 1992) explained four
new concepts in financial behavior of investors in prospect
theory and in its newer model, cumulative prospect
theory:
1. Investors evaluate assets based on gain and loss, not
final value of investment (mental accounting).
2. Individuals are more averse to loss rather than gain
(loss aversion).
3. Individuals are risk-seeker encounter loss and riskaverse
dealing with gain (asymmetric risk preference).
4. Individuals assign higher weight to the events with less
probability and lower weight to the events with more
probability (probability weighting function).
Weber and Zuchel (2003) stated that investors, who have
started morning with gain, avoid evening probable loss. In
this way, they avoid probable risk and keep their gain.
Shefrin and Statman (1985) presented disposition effect
phenomenon, that individuals hold loser stocks for a long
time and sell winner stocks soon. This behavior is named
“fear of regret”. They showed that, individuals’ risk-aversion
decreases after a period of loss and they become
more risk-averse after a period of gain. This behavior is
named asymmetric risk seeking.
Odean (1998) analyzed around 10,000 transactions of
investors. His finding showed that, individuals are keen
on gain from winner stocks. Weber and Kamerer (1998)
showed that, individuals would like to sell winner stocks
instead of loser stocks. Nevertheless, some researchers
have observed a different behavior. Thaler and Johnsone
(1990) and Barberis et al. (2001) presented a model
which states that, individuals divulge less risk-aversion
after a period of gain, and more risk-aversion after a loss.
This phenomenon is known as “house-money effect”.
Odean (1999) stated that overconfidence is the reason
of high volume of individuals’ transaction. According to
his findings, overconfidence causes that individuals think
that other investors’ decisions are affected from disposition
effect and their decisions are more rational. This
behavior is specially intensified in some fields that,
individuals have knowledge. For instance investors prefer
local stocks or stocks related to their country instead of
foreign companies’ stocks because they feel they have
more information about them, whereas it is possible that,
this vision is incorrect. Another instant is that investors
suppose that, successes due to chance are due to their
skill. Individuals remember their successes but not their
failure. This phenomenon is named “hot hand”.
Shiller (1998) studied the intellectual background and
psychological, social and anthropological properties of
individuals’ decisions. He introduced some behavioral
biases such as anchoring, overconfidence and cultural
roots of investors’ decisions.
Barberis and Thaler (2003) stated that, behavioral
biases are the reason of deviation of decisions from
rational decisions. Table 1 shows a brief behavioral
phenomenon that contradict efficient market hypothesis.
Some of the most important theories in behavioral
finance are listed in Table 2. Although several empirical
studies about investors’ behavioral biases have been
conducted, there are a few comprehensive studies about
behavioral biases effect on assets selection in financial
markets (Fernandez et al., 2009). Barberis et al. (2001)
tried to explain stock price behavior in terms of riskaversion
concepts and mental accounting. Benartzi and

Table 1. Behavioral Phenomenon that Contradict Efficient Market Hypothesis.
Phenomenon Title Researcher(s) explanation
Risk-aversion Friedman and Savage (1948) -
Dependence to reference Kahneman and Tversky (1979) -
Regret-aversion Shefrin and Statman (1985) Holding the losers and selling the winners
Over weighting to recent experiences
Overreaction De Bondt and Thaler (1985) Over pricing for winner and vice versa
Hot hand Tversky and Gilovich (1989) To attribute chancy successes to skills
Overconfidence Odean (1999) To buy local stocks
Scapegoat Statman (1988) -
Table 2. The Most Important Theories in Behavioral Finance.
Title Researcher(s)
Prospect theory Kahneman and Tversky (1979)
Cognitive dissonance theory Festinger (1957)
Heuristics
Kahneman and Tversky (1974)
Kahneman, Slovik and at al. (1982)
Forming effect Kahneman and Tversky (1981)
Intellectual accounting Kahneman and Tversky (1981), Thaler (1985 , 1999)
Reflection Effect Kahneman and Tversky (1981)
Regret theory Loomes and Sugden (1982), Bell (1982)
Regret-aversion theory Statman (1988)
Disjunction Effect Tversky and Shafir (1992)
Herding Behaviors Shiller (2000)
Thaler (1995) explained individuals’ risk-aversion behavior
in framework of prospect theory and showed how
myopic behavior affects portfolio selection. Magi (2005)
used numerical calculations and explained the model of
international portfolio selection based on behavioral
preference. He also explained how investors prefer
national stocks rather than foreign stocks, even though
their performance is better.
Davies and Satchell (2004) showed the method of
optimal assignment of stocks based on prospect theory
concepts. Shefrin (2005) considered heterogeneous
investors to survey behavioral biases effects on asset
pricing.
Expected utility hypothesis as mental framework of
modern financial theories, is extracted from the answer
presented by Daniel Bernoulli (1954) to the paradox
stated by Nicholas Bernoulli (1738) in title of “St.
Petersburg Paradox”. Two fundamental concepts which
are extracted from this theory are:
1. Investors evaluate investment opportunities in terms of
utility of outcomes.
Heybati et al. 7595
2. Utility does not have a linear relationship with wealth
but increase at a decreasing rate with increase in wealth
(marginal utility).
The concept presented by Bernoulli, was expanded in
form of expected utility hypothesis by Von Neumann and
Oscar Morgenstern (1944). This theory presented a
descriptive model for method of individuals’ decision
making under risky condition. According to this model,
individuals’ utility function is specified in terms of their
preference on risky (probabilistic) condition. The hidden
concept of this theory is that unlike Bernoulli’s theory
which states investors consider outcomes of decision,
they consider objective probabilities of each decision.
Markowitz (1952) presented the concept of optimization
based on maximum of utility and minimum of risk, in form
of mean-variance efficient frontier. Efficient frontier
involves all portfolios that are economically efficient in
terms of expected return and risk trade off. He separated
systematic and non-systematic risks and offered portfolio
selection based on mean of returns and covariance of
assets to decrease non-systematic risk.

7596 Afr. J. Bus. Manage.
Tobin’s separation theorem (1958) explained the
process of assignment of assets and method of selection
between risky and risk free assets. He stated that,
portfolio selection should be done between risky and risk
free assets, and between different categories of assets
as well.
Paul Samuelson (1965) mentioned efficient market
hypothesis in his studies. He stated that, in the efficient
market, where information is available for all participants,
price change should be unpredictable. Fama (1970)
briefed this concept and stated price reflects all available
information and if there is no transaction cost, there
would not be any outcomes due to transactions based on
information. Roy (1973) and Locus (1978) tried to present
a new version of efficient market hypothesis and believed
return is not completely random.
Generally, financial theories have been presented
based on two fundamental hypotheses:
1. Individuals behave rationally.
2. They use all available information for decision making.
But there are several instances of irrational behaviors
and cognitive bias in real-world. So, some anomalies and
empirical studies about market efficiency resulted in
weakness of efficient market hypothesis and equilibrium.
Experts are going to explain behaviors in market and in
this condition, some researchers have used data driven
methods and dynamic systems to discover the relationship
between variables. On the other hand, some researchers
like the well-known biologist, Kaufman (1988) and
a computer scientist, Holland (1988) tried to explain and
predict behaviors in market, using adoptive systems
theory and finding the relationship between economic
behaviors, growth and completeness of systems. The
third path is behavioral finance development effort to
discover the effect of cognitive and emotional errors on
decision making. Behavioral finance theories states
financial markets are not efficient because participants’
decisions are affected from behavioral biases and framework
of decision presence and it finally causes asset
price deviate from intrinsic value.
METHODOLOGY
This research is a kind of applied research, in terms of explanation
of a mathematical portfolio selection model in framework of behavioral
finance hypothesis. In addition, empirical test of this model
and explanation of relationship between variables using Tehran
stock exchange is considered.
In this paper, after explanation of hypothesis of behavioral
finance theories, mathematical model of relationship between
variables is presented in framework of a mathematical model. In the
next step, empirical test of behavioral model is done and it is
compared with classic model using ten year TEDPIX data in 2000
to 2009. For optimization, the Mathematical software and for
statistical tests, SPSS is used. The hypothesis of research is that,
portfolio selection model based on behavioral finance hypothesis is
more efficient than rational model.
The model
This research evaluates a model of portfolio selection in framework
of behavioral finance theories in Iran Capital Market. The goal is
setting the optimal weights for risky asset. It is assumed that shortselling
is impossible. Investors are going to select weight of risky
assets so that, expected utility is maximized in framework of
prospect theory.
Portfolio selection model is presented in two periods and in a
market with two kinds of risky and risk free assets and investors’
behavior is explained using Kahneman and Tversky’s prospect
theory. Therefore, investor’s decision on weight of risky assets
dependent to reference point and wealth changes can be
explained. Weight of risky asset is θ and amount of return or loss in
the first period is:
The process of selection in prospect theory is done in two stages of
edition and evaluation, as mentioned in Kahneman and Tversky's
model. In the edition stage, investor recognize and separate benefit
and loss and modify the probability function of each outcome.
Empirical studies show that individuals assign higher weights to the
lower probabilities and vice versa. In this research, offered
weighting function of Giorgi et al (2004) is used.
γ is coefficient of probability weight adjustment. In evaluation stage,
investor attributes mental value to expected outcome. Giorgi et al
(2004) and Fernandez et al (2009) explained hypothesis of portfolio
selection based on Kahneman and Tversky's model. The value
function is defined as:
+ + − α x
⎪⎧
λ − λ e , if . x ≥ 0 ⎪⎫
v ( x ) = ⎨ − α x −
⎬
⎪⎩ λ e − λ , if . x p 0 ⎪⎭
In this model, α is general risk-aversion coefficient. Because λ - > λ +
> 0, the slope of value function is more in loss part and then λ
shows risk-aversion. x shows wealth changes and is representative
of investors’ mental accounting concept. This value function is
concave for points greater than reference point and convex for
other points (asymmetric risk-aversion).
An investor defines weight of risky asset to maximize expected
utility (V). Also his/her preferences are defined in framework of
prospect theory and based on wealth changes. So, expected value
is:
Where v(x) is expected value of event x and � (f(x)) is cumulative
weight of probability of event x, based on probability weighting
function. An investor selects weight of risky asset in each stage of
investment so that, expected value of investment is maximized.

Table 3. Test period data.
Table 4. Evaluation period data.
Number of periods Mean of return Standard deviation
4 12.52 4.98
8 11.03 4.37
12 11.06 5.55
16 14.52 10.05
20 12.37 11
24 9.77 11.85
28 8.88 11.24
Heybati et al. 7597
Period duration Mean of return Standard deviation Semi standard deviation
28-32 4.57 11.29 11.78
28-36 1.52 14.86 16.80
28-40 5.15 14.18 17.98
Prospect value
Prospect Value
0.200
0.195
0.190
0.185
0.180
Figure 1. Value function of behavioral and standard portfolio models.
RESULTS AND ANALYSES
V-Standard
V� Standard
V� Behavioral
V-Behavioral
0.0 0.2 0.4 0.6 0.8 1.0
In this research, two periods of investment is considered
to evaluate behavioral portfolio model. Therefore, data is
separated to two parts. One part is used for optimal
offered portfolio calculation and another part is used to
evaluate the results.
Evaluation of behavior and standard portfolio model
Return and risk of risky portfolio is estimated using 28
three month periods data. Mean of long-term interest rate
of bank deposits (15%) is used as risk free interest rate
(Table 3). Also Table 4 shows the valuation data
Weight of risky asset in optimal portfolio is calculated
using behavioral and standard models. If risk aversion
coefficient (α) is 3, probability weighting coefficient (γ) is
0.9, λ + = 1 and λ - = 2.25 (offered by Kahneman and
Tversky), mean return and standard deviation of test
period would be 8.88 and 11.24 respectively. Figure 1
shows the value function based on standard and
behavioral models.
Calculation shows that according to behavioral model,
weight of risky asset is 60.5% and according to standard
model, it is 78.4%. Table 5 shows optimal weights of risky

7598 Afr. J. Bus. Manage.
Prospect value
Table 5. Optimal weights of risky portfolio based on standard and behavioral models.
Period
Weight of
risky asset
Standard model Behavioral model
Weight of risk
free asset
value
Weight of
risky asset
Weight of risk
free asset
Value
1 0.874 0.126 0.307 0.597 0.403 0.305
2 0.720 0.280 0.277 0.545 0.455 0.277
3 0.758 0.243 0.275 0.337 0.663 0.273
4 0.763 0.237 0.325 0.491 0.509 0.324
5 0.816 0.184 0.280 0.354 0.646 0.272
6 0.674 0.327 0.220 0.400 0.600 0.214
7 0.455 0.545 0.209 0.343 0.657 0.207
0.8
0.6
0.4
0.2
0.0
� - 0.2
0.0 0.2 0.4 0.6 0.8 1.0
Mean risky portfolio Portfolio return
Figure 2. Expected value changes in terms of changes of expected mean return of risky portfolio.
portfolio based on standard and behavioral models and
using 28 investment periods data (or 7 year test periods).
Figure 2 shows value in terms of mean return. So it is
possible to survey the effect of mean return on expected
value. Also figure 3 shows the effect of standard deviation
(risk factor) on expected value.
Figure 4 shows the effect of both determinants (expected
return and risk) on optimal weight of risky asset.
Now, to evaluate Standard and Behavioral portfolio
models, return and risk of 7 optimal risky asset, calculated
through first period based on 28 periods of test
data, 12 optimall portfolio weights was calculated based
on 3 year evaluation data. So, 84 portfolios based on
behavioral model and 84 portfolios based on standard
model have been evaluated. Figure 5 shows the optimal
weight of risky portfolio in terms of return and risk
changes in evaluation period.
V� - Behavioral
Testing of hypotheses
0.6055
In this section, using deductive statistics, it is surveyed
that whether behavioral model is better than standard
model or not.
Null-hypothesis (H0): mean return of portfolios based on
behavioral models is not greater than mean return of
portfolios based on selected standard model.
Alternative-hypothesis (H1): mean return of portfolios
based on behavioral models is greater than mean return
of portfolios based on selected standard model.
Equality of means test (confidence level is 95%) has
been done to test equality of means of 84 offered portfolios
based on behavioral and standard models.
According to Levene’s test for equality of variances, sig.

Prospect value
Figure 3. Expected value changes in terms of changes of standard deviation of risky portfolio.
Figure 4. Expected value changes in terms of changes of and standard deviation of expected return
of risky portfolio.
is 0.003 and less than 0.05 (error level). So, it is deducted
that, the variances of two populations are not equal.
Therefore, equality of means has been tested in the next
step.
Results show that, sig. is 0.773 and greater than 0.05.
Therefore, H0 is not rejected. The lower bound (-0.47726)
and upper bound (0.64059) have different signs and it
shows that, there is no significant difference between
mean returns obtained from behavioral and standard
models, in 95% confidence level.
CONCLUSION
-
� 0.1
-
� 0.2
-
0.2
0.1
0.0
� 0.3
Risk-free Rate
V� Behavioral
0.0 0.2 0.4 0.6 0.8 1.0
Mean risky Portfolio Standard Deviation
This research explained behavioral finance concepts and
compared the model of portfolio selection based on
-
Mean risky portfolio standard deviation
Mean risky portfolio return
Mean risky Portfolio return
Heybati et al. 7599
0.6055
behavioral finance concepts and standard model. In this
paper, the most important financial concepts are mental
accounting, risk-aversion and asymmetric risk
preference. Other studies in other countries show that
mathematical model of portfolio selection based on
behavioral finance concepts leads to different results
versus Markowitz’ model. In this research, behavioral
portfolio model was evaluated using 10 year data of
TEDPIX. Although, point estimation of return of offered
portfolio and optimal weight of risky portfolio are different
in two models (it is the same as results of empirical
studies in other countries), equality of means test for 84
behavioral and standard portfolios does not reject nullhypothesis
(H0). In point estimation, behavioral portfolio
model suggests 60.5% as weight of risky asset in optimal
portfolio, whereas Markowitz model suggests 74.4%. One

7600 Afr. J. Bus. Manage.
Figure 5. Optimal weights of risky portfolio in terms of changes of expected return and standard deviation.
of the reasons of difference between point estimation
and result of statistical test in Tehran Stock Exchange
can be due to data. TEDPIX is modified after evolution
of capital market, especially entrance of new companies
and it leads to instability and incomparability of
index value. Finally, it is proposed to use more stable
indices (such as industry index) and other method of
risk evaluation such as semi standard deviation instead
of standard deviation.
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APPENDIX
Group statistics.
SB N Mean Std. deviation Std. error mean
1 84 4.2081 2.20937 0.24106
2 84 4.1264 1.35284 0.14761
Independent samples test.
Variable
Levene's test for
equality of variances
t-test for equality of
means
t-test for equality of means
t-test for equality of means
95% Confidence interval of the
difference
F Sig. t df
Sig.
(2-tailed)
Mean
difference
Std. error
difference
Lower Upper
Equal variances assumed 8.951 0.003 0.289 166 0.773 0.08167 0.28266 -0.47641 0.63975
Equal variances not assumed 0.289 137.569 0.773 0.08167 0.28266 -0.47726 0.64059

African Journal of Business Management Vol. 5(17), pp. 7603-7615, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.773
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
The functional relationship between mentoring
relationship, employee development and organisational
success
Jan Visagie* and Gideon J. Kruger
School of Human Resource Sciences, North-West University. Potchefstroom, South Africa.
Accepted 29 July, 2011
The dynamic relationship, such as mentoring relationships, has led to achievements and success in
organisations. Within the current financial constraints and skills shortages, the successes within small
groups, such as mentoring relationships, warrant investigation. This case study investigated the
success of mentoring relationships in the pulp and paper industry of South Africa. The purposes of the
mentoring programme, mentor-protégé characteristics and mentoring coordinator characteristics
emerged from the perceptions of the participants. The success of the mentoring programme of this
case study is experience as correlating to the characteristic of the mentors and protégés in the
mentoring relationship.
Keywords: World of work, employee relations, group dynamics, dyads, relationships, engineer, employment
development, qualitative research, mentor characteristics, protégé characteristics.
INTRODUCTION
The synergistic relationships that are found in groups of
people have led to achievements more than just above
the norm, such as the first people to reach the summit of
mount Everest, Edmund Hillary and Tenzing Norgay; the
first non-stop transatlantic flight by Captain John Alcock
and Lieutenant Arthur Whitten Brown; and the Internet
search engine, Google, that was founded by Larry Page
and Sergey Brin. Note that these examples of outstanding
achievements that were highlighted are called
dyads, that is, groups consisting of two members
(Forsyth, 2009). In the world of work that is facing a
global recession, the effective functioning of small
groups, such as dyads, is vital to just about all sectors of
the organisation (Elwyn et al., 2001; KPMG, 2009). Small
groups in organisations should be considered in terms of
the employment relationship. Employee relations,
*Corresponding author. E-mail: Jan.Visagie@nwu.ac.za. Tel:
018 299 1430.
Abbreviations: ECSA, Engineering council of South Africa;
KPMG, klynveld peat marwick goerdeler.
consisting of human resource management and industrial
relations, cover everything that impact on the employment
relationship (Nel et al., 2005). The mentoring
relationship is a form of employee development that falls
under employee relations. The personal relationship in
mentoring dyad can have an impact on the development
of high achievers (DeLong et al., 2007). Mentoring is
therefore used to develop talent. In a study of global
organisations, it was found that having a well-developed
system to identify, develop and effectively manage talent
within an organisation, has a distinct advantage over
organisations without such a system (McDonnell et al.,
2010). Mentoring relationships are such a system, as the
dynamic relationship of mentoring dyads can be one of
the means by which high achievers and you can be
helped (Stone, 2007).
The original focus of the mentoring relationship was
that of the mentor-protégé dyad, from which the peer and
group mentoring conceptualisations move away
(Bozionelos, 2004; Dansky, 1996; Eby, 1997; Kram,
1985). A dyad is a group consisting of only two members,
which is connected by and within a social relationship
(Forsyth, 2009). A mentor-protégé dyad is therefore a
mentoring relationship consisting of only two members,

7604 Afr. J. Bus. Manage.
namely the mentor and the protégé. Bozeman et al.
(2007) move back to the dyadic nature of the mentoring
relationship in numbering the participants in mentoring to
transmit work-related knowledge as dyads (including sets
of dyads). The dyadic nature of the mentoring relationship
limits the definition of mentoring to dyads or sets of
dyads (Bozeman et al., 2007). The last two decades have
provided a surge of interest and research into the topic of
mentoring and workplace mentoring, which is a relatively
new focus of study (Allen et al., 2008). The dynamic
relationship that guides, supports and influences the
developing person is known as mentoring (Haynes et al.,
2008). The profound effect that influential people can
have on our lives, as in the far-reaching effect of mentors,
can lead to the success of organisations, businesses,
churches, children, communities and our country
(Steinmann, 2006). The definition for mentoring used in
this study is based on the definition adopted by the European
Mentoring and Coaching Council, where mentoring
is “off line help by one person to another in making
significant transitions in knowledge, work or thinking”
(Clutterbuck, 2001). Note that coaching relationships go
hand-in-hand with mentoring relationships, because
mentoring includes coaching, guardianship, facilitating,
counselling and networking of the person being mentored,
in other words the protégé (Klasen et al., 2002;
Rhodes et al., 2002).
Mentoring is a process of transferring specific knowledge
from the mentor to the protégé (Hendrikse, 2003
cited in Janse van Rensburg et al., 2005). Bozeman et al.
(2007) define mentoring in the following way: Mentoring
is a process for the informal transmission of knowledge,
social capital and psychosocial support perceived by the
recipient as relevant to work, career, or professional
development; mentoring entails informal communication,
usually face-to-face and during a sustained period of
time, between a person who is perceived to have greater
relevant knowledge, wisdom, or experience (the mentor)
and a person who is perceived to have less (the protégé).
This definition, which will serve as one of the theoretical
bases for this research, limits mentoring to dyads (or sets
of dyads) and rejects some current meanings of the term
mentoring, such as the current meaning of group mentoring
(Bozeman et al., 2007). “Mentoring is an inclusive,
confidential relationship between two people who have
mutual personal growth and corporate success as
common ground” (Brown, 1990, cited in Hattingh et al.,
2005). Derived from these definitions, mentoring is an
offline relationship between two people for the transmission
of knowledge, social capital and psychosocial
support perceived by the recipient as relevant to professsional
development between a person who is perceived
to have greater relevant knowledge, wisdom or experience
(the mentor) and a person who is perceived to
have less (the protégé). From the above literature review,
the following purpose emanates: To gain the experience
of mentoring relationship success in a case study.
The aim of the study
Small groups, such as mentoring relationships, warrant
investigation within the current financial constraints and
skills shortages. According to Scott et al. (2008), the current
financial constraints and skills shortages challenge
the viability of using one-on-one mentoring models to
empower subordinates, and provide the group mentoring
team as a more viable option to support new graduate
nurses. On the other hand, recent mentoring theory
challenges the viability of the use of group mentoring, but
permits the use of sets of mentoring dyads and labels
group mentoring relationships under socialisation
(Bozeman et al., 2007). A major concern currently within
South Africa is the availability of employment (KPMG,
2009). This is reflected in the current unemployment rate
in South Africa, which is at 24% (Central Intelligence
Agency, 2009). Low levels of human development are
constraining economic growth potential in sub-Saharan
African countries, such as South Africa (Ranis et al.,
2000). Focused skills development is most beneficial
towards human development (Kingdon et al., 2007).
Mentoring relationships are a form of human development
and therefore take on the employment challenge.
Being proactive in taking on unemployment by means of
human development initiatives, such as mentoring
relationship programmes, is of importance for economic
growth in South Africa.
In the workplace, small groups, such as mentoring
relationships, relate to certain desires or needs of
employees. It is desired, and even expected by much of
the workforce today for organisations to provide opportunities
to fulfil career and psychological or developmental
needs, as well as role-modelling needs (Aryee et
al., 1996a; Kram, 1985; Scandura et al., 1993; Wang et
al., 2009). A more complete understanding of mentoring
relations may make satisfying these needs easier. The
mentoring relation can be facilitated by the use of a
mentoring programme within an organisation. Literature
sources describe contexts in which mentoring schemes
(or programmes) exist, including many situations where
knowledge, wisdom or experience need to be passed
from people with more of the required attribute to people
who need to acquire more of this for any reason (Colley,
2003; Klochan, 2002; Klasen et al., 2002). The purpose
and approach of this mentoring programme are diverse
within organisations using mentoring programmes. The
implementation of mentoring programmes is one of the
ways to promote empowering work environments, for
instance for promotion of subordinates, enriched performance
and diversity awareness (Table 1) (Cranwell-Ward
et al., 2004; Hattingh et al., 2005; Hegstad et al., 2005;
Nedd et al., 2006). The mentoring relationships should
not be investigated out of the context of the purpose and
the approach of a mentoring programme. This case study
on mentoring relationships also builds on one of the core
subjects in group dynamics, which is the study of

Table 1. Components of a mentoring programme.
Visagie and Kruger 7605
Support structure Support culture Empowerment
Open physical environment Top management support. Loyalty
Mentor training Team emphasis Increased retention
Cross-functional work teams Open communication Satisfaction
Mentor and protégé team bonding weekend Employee collaboration Networking. Protégés’ access to resources
Mentor and protégé matching system Promotion/ advancement opportunities of protégé
Layered or flattened hierarchy Socialisation into organisational culture
Organisational learning
Improved moral
Diversity awareness
Enriched performance
Professional development desire
*Derived from three resent authors (Cranwell-Ward et al., 2004; Hattingh et al., 2005; Hegstad et al., 2005).
leadership (Forsyth, 2009). In a groundbreaking study of
five years, 1,435 companies on the Fortune 500
(between 1965 and 1995) were analysed (Collins, 2001).
According to Collins (2001), level-5 leadership is the style
of leadership that guided 11 of these companies from
mediocrity to greatness, with stock market returns
averaging at least 6.9 times the general stock market for
15 years. One of the reasons that the author chose to
take 15 years of spiralling success after a breakthrough,
as a cut for their study, was that 15 years exceed most
executive terms and can be seen as significant sustained
development.
The potential value addition of the study
Recent research on mentoring relationships in the workplace
revealed the problem area, namely that only 11.1%
(n = 178) of the research on mentoring was done qualitatively
or combined according to research on the state of
mentoring research done by Allen et al. (2008). There is
therefore a need for more qualitative investigation into
mentoring relationships, which is catered for by this
research.
The following research objectives are formulated based
on the above-mentioned description of the research
problem:
1. To obtain the purpose and approach of the mentoring
programme of a specific company.
2. To obtain, through literary study interviews, the dynamics
of mentoring success.
RESEARCH DESIGN
Research approach
The research, pertaining to the specific objectives, consists of a
literature review and the empirical study, which is a qualitative
research of this case study.
Research strategy
The literature review is based on the research of the relevant
literature, to gain an understanding of mentoring relations. Where
applicable, the relevant tables or figures were incorporated. Primary
and secondary sources that were consulted include various
publications such as text-books, journals, newspaper articles and
previous studies related to this research topic. The databases that
will be used are Nexus, SA journals, LexisNexis, Ferdikat, Emerald,
ProQuest and Google Scholar. This empirical study is designed as
a case study consisting of quali-tative interviews. In order to
achieve the aims of this study, a case study will be conducted in the
form of one-on-one interviews. The rationale in the primary use of
the qualitative one-on-one interview is that the study is of an exploratory
nature (Flick, 2009). The interview questions were reviewed
and critiqued by experts in related fields of study. The questions
were accordingly revised.
RESEARCH METHODS
Research setting
All the interviews were held behind closed doors. The interviews
were held on the premises of the specific mill within offices and a
conference room.
Entrée and establishing researcher roles
For the purposes of this study, the researcher worked closely with
an intermediator. An intermediator gave permission for the interviews
and arranged the interviews and interview locations. The
participants (n=10) were limited to mentors, protégés and relevant
participants in this case study within the pulp and paper industry.
Only employees of a specific pulp and paper mill are included who
are/have been in a mentoring relationship or have strong relevance
to the mentoring programme at this mill. The geographic location of
the participants is in the South African province of Mpumalanga.
The mentors of all the mentoring pairs are limited to middle or top
management.
Sampling
The sample size of the research is limited by the saturation

7606 Afr. J. Bus. Manage.
Table 2. Demographic characteristics of the participants.
Mentoring pairs Not in mentoring pair
Item Category
Mentor Protégé Mentoring custodian
Frequency Percent Frequency Percent Frequency Percent
Mentoring Pair 5 50 5 50 1 10
Gender Male 5 50 4 40 1 10
Female - - 1 10 - -
Ethnicity White 5 50 4 40 1 10
Black - - 1 10 - -
Occupation Engineers 4 40 4 40 - -
Engineering manager 1 10 - - - -
Lean manufacturing manager 1 10 - - - -
Maintenance manager* 1 10 1 10 - -
Manager electrical engineering 1 10 - - - -
Mechanical Engineer in training - - 2 20 - -
Senior technician - - 1 10 - -
Risk management 1 10 1 10 - -
Risk manager 1 10 - - - -
Risk superintendent - - 1 10 - -
Human resource management - - - - 1 10
Training superintendent
engineering
- - - - 1 10
*The maintenance manager is both a mentor and a protégé.
of the qualitative interviews as seen in Table 2. For the
purpose of qualitatively measuring the success of the
mentoring programme, five mentoring dyads/pairs and the
custodian of mentoring in the specific mill were interviewed,
as seen in Table 2. The results therefore convey
the perceptions of the mentors, protégés and a mentoring
custodian. The mentoring custodian promotes the mentoring
programme as a subtask in his job description. The
case study of the success of mentoring relations
consists of a limited population. Demographically, the
highest frequency of participants is male and ethnically
white, as seen in Table 2. Seventy present of the study’s
participants fall under the job category of engineering, as
seen in Table 2. The one female in the study is one of the
two participants that fall in the job category risk management,
as seen in Table 2. The fact that all the participating
engineers are male is not surprising, because the field of
engineering is male dominated (Faulkner, 2007). The
perceptions of participants in the mentoring relationships of
this study are therefore validly dominated by the perceptions
of males.
Data collection methods
The case study will be conducted in the form of structured
one-on-one interviews. For this case study, the interviews
are recorded digitally with the participants’ permission.
Data recordings
According to Silverman (1993), qualitative research should
most preferably be carried out by observations, text analyses,
interviews, recordings and transcriptions. This case
study will utilise interviews with the mentoring pairs and
mentoring custodian at the mill, which will be recorded
digitally with the participants’ permission. The recorded
interviews were safely stored on the digital recorder to

Table 3. Perceptions on the success of mentoring programme.
Item Category
Mentoring programme
outcome*
Visagie and Kruger 7607
Mentoring pairs Not in mentoring pair
Mentor Protégé Mentoring custodian
Frequency Percent Frequency Percent Frequency Percent
Successful* 5 50 5 50 - -
Failure - - - - 1 10
Total 5 50 5 50 1 10
*The Maintenance Manager is both a mentor and a protégé.
prevent a compromise of the quality of the data. Additionally, the
data was stored in duplicate in locations only accessible to the
researcher. The data captured on the digital audio will be
transcribed verbatim for content analysis by the researcher and
archived in duplicate for verification.
Data analyses
In this qualitative analysis, a thematic content analysis has been
done by the researcher on the transcribed interviews. The responses
from the qualitative data have been analysed by identifying
the relevant utility items. Major themes have been extracted out of
the utility items.
Strategies employed to ensure data quality and reporting
For reliability purposes, the researcher made use of Okun’s (2002)
communication techniques in order to conduct the structured oneon-one
interview. An example of one of the stipulations under
Okun’s (2002) communication techniques is the use of clarifying
questions. This method allows the researcher to follow the
participants’ lead, asking clarifying questions, and facilitating the
expression on the participants’ perceptions (Streubert et al., 1999).
The field notes were made in the form of journal entries. The field
notes delivered no relevant information to qualitatively add to the
research findings.
Reporting
The reporting style that is used for this qualitative study is that of
the American Psychological Association. The major themes and
closely related themes will be reported in the findings, discussion
and tables.
FINDINGS AND DISCUSSION
Dynamic relationships in dyads can produce a synergy of
great achievements. The success of the mentoring relationship
is the bottom line of the mentoring programme in
organisations. The purpose of this case study is to gain
experiences of success in mentoring relationships. The
outcomes of mentoring relationships or mentoring
programmes can be successful or not. The mentoring
programme is perceived as successful by both the
mentor and the protégé in the mentoring pairs (as seen in
Table 3). There is one interview participant who
perceives the mentoring programme as a failure, which is
from the perspective of coordination of the mentoring programme.
This one perception of mentoring programme
failure can be seen as an unexpected result that is
discussed in Theme 4 below. The four major themes that
emerged form the perceptions of the mentors, protégés
and mentoring custodian that are discussed in the
following. The findings were divided into four main areas
that will be:
Theme 1.Purpose of the mentoring programme
Theme 2. Characteristics of a mentor
Theme 3. Characteristics of a protégé
Theme 4. Characteristics of a mentoring programme
coordinator
The various themes will be discussed in the following:
Theme 1. Purpose of the mentoring programme
(Table 4)
The perception of mentoring relationship success was
gained within the context of the original reason, purpose
or approach of the organisation for the mentoring
programme. The reasoning, purpose or approach of the
organisation for the mentoring programme is gained to
clarify the rationale behind the mentoring programme
(Conway, 1998; Klasen et al., 2002; Hattingh et al.,
2005). The first and strongest theme that emerged from
the responses was the participants’ perception of the
purpose of the mentor programme of the case study
organisation. The purpose or approach of the mentoring
programme is mainly for the successful outcomes of the
mentoring relationships in the organisation. The purposes
of the mentoring programme that emerged from the
results include: the mentoring programme should
selectively include specific people into the mentoring
relationships, the mentoring programme should provide
for both formal and informal mentoring relationships and
that the mentoring programme should be geared towards
sustained development, as seen in Table 4. It emerged
from the perception of the participants that the gaining of
successful mentoring relationships in the mentoring
programme should be approached by selective inclusion
into the mentoring programme, as seen in Table 4.

7608 Afr. J. Bus. Manage.
Table 4. Purpose of the mentoring programme (theme 1).
Sub-theme Associated keywords
Selective inclusion
Protégés Potential development; Identification of certain protégés for mentors; We select the best of the best
protégés; Development of identified individuals; Different levels of success depending on individual
differences; Identification by twenty employees in the business and attempt to place protégés with
mentors, which is of the required quality.
Mentors People on specific levels of the organisation identified to take a person through the transformation
process; The impact of the mentoring programme depends on who is targeted.
Formal and informal mentoring relationships
Formal
Qualifying employees for engineering fields; 2-year compulsory mentoring period for compliance
with Technicon and University requirements; Qualifying for three engineering fields; To gain the
government competency certificate; Accommodating trainees for development into competent
engineers; For the formal mentoring programme the mentoring relationship may be a bit forced;
Encourage mentoring relationships after the compulsory mentoring period.
Informal Providing mentoring for employees who decide to study. The informal mentoring programme can be
better advertised or communicated, because there are employees who do not know about the
mentoring programme; Employees not utilising the informal mentoring programme prefer to do
things by themselves.
Sustained development
Promotion Filling an identified role; Filling new areas in the organisation that need focus and support; The top
management always looks at certain aspects such as what would be the best for the plant, e.g. at
the characteristics and technical ability of the protégé; Closing gaps.
Requirements During initial employment some of the protégés do not have an idea what they will do when they
arrive here and are not fully prepared for this organisation; Gaining achievement; Improving skill
levels of individuals; Achieve previously set standards; Improving productivity; To achieve a
successful plan by preparation of new employees; The mentoring programme ensures that the
mentor aims at what he wants to ask the protégé; Mentoring can be used as a formal action plan for
people who are wasting time.
Maximising Maximising potential to set a new standard in the junior workforce through replacing habits;
Exponential growth in the relationship was perceived; As the mentoring pair cooperates more, your
communication skills improve, which increases your creativeness; For reaching the company status
of being known as a "people organisation"; The mentoring programme is about being in line and
cooperation and thereby brain power, which will ensure this programme will have longer-term
success, because there is so much more support. Mentoring is there for reaching things that are
more specific and focused than measured goals. Mentoring takes on obstacles and bottle necks
faster and strains things forwards.
Knowledge Transfer of knowledge of the profession; Preventing the loss of information; Knowledge transfer that
is difficult to equip for; Socialising protégés into organisational structure; Mentors have the special
responsibility to train people that we might employ; If a protégé is mentored he can therein also
learn the process of mentoring.
Identification of potential of protégés is perceived to be
one of the purposes of the mentoring programme in this
case study. It is perceived that the identification of
mentors on specific levels of the organisation is needed
to take a protégé through the transformation process. In
literature, the main reason for this is that there often are
only a small proportion of mentors to protégés
(Finkelstein et al., 2010). The importance of selecting
specific mentors and protégés is especially emphasised
in formal mentoring programmes within workplace
mentoring, youth mentoring and university mentoring
programmes (Brien et al., 2010). The importance of the
selection of mentors and protégés can additionally be
emphasised through the following themes, namely

Table 5. Characteristics of a mentor (theme 2).
Visagie and Kruger 7609
Sub-theme Associated keywords
Actual mentor characteristics
Induction New employees are being brought into the organisational culture; Ensure thorough training of protégés; The
mentor is not there to teach the technical things, but to give direction in his career; Expect the protégé to apply
what he has learned.
Feedback A boldness to say to protégés that what he is doing needs to be done better; Preventing problems by feedback
and thereby saving money; The mentor monitors the progress of the protégé through the year; My perception is
that I can go to my mentor and he will give his honest opinion; Mentoring is a very powerful tool of correcting
thought processes; Being helped; The protégé will follow the example of the mentor in having an open
relationship; Actively giving feedback on projects.
Goals Actual assurance of the application of skills and competencies being trained for; By application producing a higher
quality of thought; Choosing the project of the protégé; Sending to the protégé projects that look interesting;
Setting practical goals for the protégé; A written agreement that is made on the end goals of the relationship; The
mentor has to approve the subjects that the protégé wants to study before the protégé can receive money; The
outcome of the protégé will reflect on the mentor.
Knowledgeable My mentor is very knowledgeable; Mentoring training directed me in the right direction when I was young; We
(senior employees who are mentors) have knowledge; A successful mentor can transfer knowledge that he has
built up; We (protégés) all to try to progress forward because my boss knows the business well.
Experienced I have been mentoring for many years and have successfully mentored a reasonable number of mentees.
Approachable My mentor is very approachable; Helps where possible; I learned a lot together with my protégé; The mentoring
relationship will go forward if you feel comfortable that you can go to your mentor with anything and he will help
you; Be available.
Networking Sending protégé to people who are strong in certain characteristics; Referring protégé to specific people with
specific skills; Mentor ensures that there is an overt positive image of the protégé towards the line manager and
upper management.
Ideal characteristics of a mentor
Induction Giving new employees guidance; For very young guys to be with seniors; Getting practical help to go in the right
direction; A person that can explain technical things well can be seen as a mentor.
Feedback When the mentor sees a shortcoming it should be tended to; Give attention to problem areas; Personal/Individual
support of protégés; A mentor should give feedback; The mentor facilitates learning of the protégé; Feedback
needs to be given to the protégé on what is expected of him; Healthy communication from both parties is needed;
The mentor and protégé should have open communication.
Trained The mentoring training needs to be applied; The mentor needs to make the mentoring programme content a way
of life; The mentor facilitates learning wider than the technical.
Experienced
mentor
A mentor who has important experience; The mentor should be able to do his work; Imparting the experience.
Relationship The right time or circumstances need to be searched out to convey information; The integrity of the mentor and
trainee should be in a way that both do their parts; There should be a proper relationship and understanding
between the mentor and trainee; The mentor needs to learn how to communicate with the protégé; Protégés are
placed with mentors who are not their line manager where possible; A give-and-take in the relationship that needs
to be used in wisdom; Mentoring pairs need to take accountability for their relationship; Mentors need to be able to
work with people, not just have a lot of technical ability; I think mentors need good personalities for relating with
the protégés; The life stage the mentor is in; Generational theories are applicable to mentoring, because the type
of mentorship that we did ten years ago differs from what we do now; The expectations of this current generation
differ; Do some research from his side for the relationship; A mentoring relationship cannot be successful if it is not
open, because all the development aspects should be touched on, including emotional and social aspects.

7610 Afr. J. Bus. Manage.
Table 5. Contd.
Goals Help that the protégé passes his course or diploma; Speeding up the training and development process through motivation
of the protégé; Development of protégé for sustained success such as the progression can go forward six years from now.
Support Moral support of protégé; Emotional support of protégé.
Table 6. Protégé success (theme 3).
Sub-theme Associated keywords
Actual protégé success
Senior Senior people in the organisation have been delivered.
Succeed Overall there are more successes than failures; Some protégés do fail.
Goals Protégés who have been officially successful in gaining their goals with their mentor; I have reached 80% of my set
goals; Protégé has gained accreditation; Protégé is in the final stages of gaining his degree.
Commitment Compliance to what my mentor proposes; Compliance to procedure. The mentoring relationship is successful if the
protégé relays on mentor’s experience and knowledge.
Ideal protégé success characteristics
Goals The individual reaching his goals at the end of the programme; That he keeps to his list; Getting employed in the
organisation automatically.
Commitment Success depends on the motivation of the protégé to want to help him to improve; The protégé needs to be willing
to develop; The protégé should not refuse to improve over time; A protégé needs senior and non-senior mentors;
Mentoring pairs need to take accountability for their relationship; The protégé does intend to leave the company
immediately.
mentoring characteristics and ideal protégé success
characteristics (Hu et al., 2008). These two themes were
also strongly reported by participants, as seen in Tables
5 and 6. A more in-depth discussion on the selection of
specific people for the mentoring relationship will be
expanded upon in Themes 2 and 3.
One of the purposes of the mentoring relationships in
the case study is that it caters for both a formal and an
informal mentoring programme that is provided for the
employees, as seen in Table 4. The purpose of the
formal mentoring programme is to enable the compliance
to the statutes of the Engineering Council of South Africa
(2009). A graduated engineering student, who wants to
register as an engineer at the Engineering Council of
South Africa (ECSA), is required to be reported on, by a
minimum of two ECSA referees, on his/her training and
experience period. The ECSA referees include the
protégés’ mentor(s), immediate supervisor and employer.
The formal mentoring programme complies with the
ECSA by ensuring that a mentor is provided to the recruited
engineering student. The formal mentoring programme
additionally ensures that recruited engineering
students are accommodated in completing projects as
well as in other areas of development under mentorship.
According to Finkelstein et al. (2010), the formal mentoring
programme can be defined in the following way: A
formal mentoring program occurs when an organization
officially supports and sanctions mentoring relationships.
In these programs, organizations play a role in facilitating
mentoring relationships by providing some level of structure,
guidelines, policies and assistance for starting,
maintaining and ending mentor-protégé relationships.
The formal segment of this case study’s mentoring programme
provides structure, guide-lines, policies and
assistance for starting, maintaining and ending mentoring
relationships. For the employees who are not part of the
formal mentoring programme, who decide to study, the
inclusion into an informal mentoring relationship is
available. The success of the informal mentoring relationship,
for which this case study caters, depends on the
willingness of the protégés to be helped. This is supported
by literature by emphasising the importance of having
mutually beneficial relationships in informal mentoring
programmes (Allen, 2004a; Dougherty et al., 2007). A
social exchange relationship is therefore of importance in
an informal mentoring programme. The purposes of the
mentoring relationships in this mentoring programme,
which emerged from the results of this case study in

terms of sustained development, are selective promotion
into specific gaps, producing employees who achieve onjob
requirements, maximising the junior workforce and
preventing a leak in organisational knowledge, as seen in
Table 4.
It emerged from the perceptions of the participants that
one purpose of the mentoring relationships is for the
promotion into specific gaps. Mentoring can be expected
to have a positive effect on promotion (Allen et al., 2006;
Cohen et al., 2007; Hattingh et al., 2005). This positive
effect that mentoring can have on promotion indicates
that having promotion to fill specific employment gaps as
a purpose for the mentoring programme is reasonable.
The mentoring relationships of this case study are
strongly perceived as producing employees that achieve
on-job requirements, which can be seen as sustained
development. Achieving job requirements can be included
in the evaluation of a mentoring programme, such as
in the protégé’s readiness for higher level responsibilities
(Cranwell-ward et al., 2004). The purpose of maximising
the junior workforce emerged from the results of this
study. Mentoring programmes contribute to the organisation
by means of the faster induction of protégés
(Freedman, 2008). The mentoring relationship additionally
proactively prevents organisational knowledge or
information from getting lost. Mentoring relationships are
there to ensure that there is knowledge capital protection,
which is of real benefit to the organisation (Hattingh et al.,
2005). The purpose of this mentoring programme is
therefore to provide successful development for selected
protégés in a formal and informal mentoring relationship.
Theme 2. Characteristics of a mentor
According to Dougherty et al. (2007), the characteristics
of mentors have not been investigated much within
literature. For a successful mentoring programme, mentoring
relationship mentors are perceived to have certain
characteristics. The characteristics of a mentor emerged
as a major theme from the results of this case study on
successful mentor relations. The importance of actual
and ideal characteristics of mentors for mentoring relationships
emerged strongly in terms of mentoring success
in the experience of the participants, as seen in Table 5.
The actual characteristics of a mentor that emerged, as a
theme experienced by participants of this study, are
experienced as being performed within the mentoring
relationships. The actual characteristics that can be
reported are the guidance of new employees in the induction
period, feedback on growth areas, guidance in the
setting of practical goals, having a knowledgeable
mentor, having an experienced mentor, having an
approachable mentor and networking of protégé with
specific people, as seen in Table 5. Participants of this
case study perceive there to be guidance of new employees
into the organisational culture through the mentoring
Visagie and Kruger 7611
relationships. Faster induction of employees is one of
many organisational benefits of mentoring that is conveyed
by the mentor (Chapman, 2008; Freedman, 2008).
A mentor must be able to give constructive feedback
provided on the growth areas of the protégé in the
mentoring relationship (Ludwig et al., 2008).
It is experienced by participants in this case study that
mentors are giving feedback on growth areas within the
mentoring relationship, as seen in Table 5. It emerged
that mentors collaborate with protégés in the setting of
practical goals, which ensures the application of skills
and competencies. The experience of having a knowledgeable
mentor is highly valued in mentoring
relationships and this characteristic of mentors is
experienced in this study. In literature, the experience of
having a knowledgeable mentor is highly valued in mentoring
relationships and this characteristic of mentors is
experienced in this study (Jackson et al., 2003). For
knowledge transfer to be supported in an organisation,
interpersonal trust can be used in the mentoring
relationship (Preece et al., 2007). Having an experienced
mentor, as expected, is ideal for the protégé and should
be seen as a favourable characteristic that is experienced
by the participants of this study (Jonson, 2008).
Successful mentors have the characteristic of being
approachable, which is perceived by the participants in
this study (Omary, 2008). Mentors can add to the mentoring
relationship by providing networking for protégés,
ensuring that protégés get referred to specific people
(Rabatin et al., 2004; Sambunjak et al., 2010).
Characteristics that are ideal for a mentor to have,
according to the participants of this study, are the
characteristics of giving guidance in the induction period,
giving feedback on the protégé’s growth areas, having
application of training in mentorship, having an understanding
relationship between the mentor and protégé,
having an experience, providing guidance in the setting of
practical goals, and providing social support, as seen in
Table 5. The guidance of new employees is perceived as
an actual and ideal characteristic of a mentor, which is an
organisational benefit of the mentoring relationship.
The guidance of new employees speeds up the induction
of new employees (Chapman, 2008; Freedman,
2008). The feedback given on growth areas of the
protégé is also perceived as an actual and ideal characteristic
of mentors, which should be provided by mentors
(Ludwig et al., 2008). The importance of the mentor
providing feedback and being approachable stood out the
most under the reasons for mentoring programme
success. Job-related feedback can be gained through
mentoring dyads (Liu et al., 2009). It is perceived by the
participants that the mentors should ideally integrate and
apply the skills that are learned into the mentoring
training. Training is used to increase the communication
skills, and other relevant skills, of mentors for having an
effective mentoring relationship (Anderson, 2009; Bally,
2007; Pfund et al., 2006). It is perceived that mentors

7612 Afr. J. Bus. Manage.
should ideally be able to have or form a proper
relationship and understanding with the protégé. This
characteristic came out strongly. It is favourable to have
an experienced mentor, which is perceived as an actual
and ideal characteristic of mentors in this case study
(Jonson, 2008). Mentoring is, per definition, used for the
imparting of experience and knowledge (Bozeman et al.,
2007). It emerged that it is ideal for mentors to collaborate
with protégés in the setting of practical goals,
which ensures the application of skills and competencies.
Social support, such as moral and emotional support, is
perceived to be a characteristic that a mentor should
have. Mentoring research could benefit from research
into social support as done in psychological research
(McManus et al., 1997; Scandura et al., 2010).
Theme 3. Protégé success
According to the results that emerged from the
perceptions of the participants of this study, the protégés
have achieved success and ideally should have certain
characteristics, as seen in Table 6. One of the criteria
that should be measured in a highly successful mentoring
programme is individual protégé and mentor development
(Cranwell-Ward et al., 2004). The individual protégé
is perceived to have success in his mentoring relationships.
The success of protégés that has been
experienced by the participants of this study understates
the mentoring relationship’s reaching of its bottom line of
success in the mentoring programme. The actual protégé
success is perceived in terms of promotion of senior
people through the mentoring programme, more protégés
succeeding than failing, protégés successfully reaching
their goals and the commitment of protégés, as seen in
Table 6. The testimony that senior people are delivered
by the mentoring programme is an indication of mentoring
success. This is supported by research findings
that found that the experience of mentoring is related to
contributing to promotion rates (Allen et al., 2006). The
perception of the participants that more protégés succeed
than fail is in agreement with the contribution of mentoring
towards promotion rates (Allen et al., 2006). One of
the perceptions that emerged from the participants is the
protégés successfully reaching their goals in their
mentoring relationship. Mentors are there to help the
protégé reach personal and profess-
nal goals (Phillips-Jones, 1982; Scott et al., 2007).
The goal of improved job application, for instance, has
been found to be one of the outcomes of mentoring
relationships (Hallam et al., 2006). Actual protégé
commitment was reported in this study and emphasised
the choice of compliance towards the mentor. Mentoring
and coaching can itself increase commitment of new
employees and current employees (Piansoongnern et al.,
2008; Pyane et al., 2005). The general perception of the
organisation in this case study is that protégés are
predominantly successful through the mentoring
relationships (Wanberg et al., 2003). The ideal protégé
success characteristics that emerge as experienced by
the participants of this study are the ideal of the protégés
successfully reaching their goals in the mentoring relationship
and the ideal of protégé commitment, as seen in
Table 6. Both of these two sub-themes that were
extracted were also experienced as actually preformed
characteristics of protégé success. The ideal of the
protégés successfully reaching their goals is relevant,
because their mentors are there to help protégés reach
their personal and professional goals in the mentoring
relationship (Phillips-Jones, 1982; Scott et al., 2007). The
protégé is expected to be committed to agreed-upon
goals or objectives in the mentoring relationship
(Rodenhauser et al., 2000). As supported by literature,
the ideal of the protégés having an attitude of commitment
is emphasised as a protégé characteristic for
informal mentoring relationships (Aryee et al., 1996b;
Wanberg et al., 2003). According to Welch et al. (2009),
the protégé characteristic of being motivated in the
finding of a mentor is of importance in informal mentor
relationships.
Theme 4. Ideal characteristics of mentor programme
coordinator
These ideal characteristics of a mentoring programme
coordinator that emerged are perceptions of mentoring
programme failure. The failure that is reported is a lack in
capacity of follow-up of the mentoring relationships. It
emerged from the experience of the mentoring custodian
that the need for following up on the mentoring relationships
should be met by means of monthly or quarterly
follow-ups. It is perceived that follow-up cannot currently
be properly provided for by the mentoring custodian, as
seen in Table 7. It should be the role of human resource
development (HRD) to follow up mentoring relationships
through periodic meetings (McDonald et al., 2005). The
importance of the follow-up of the mentoring relationship
should not be neglected and therefore recruiting a
mentoring coordinator for the mentoring programme is
recommended (Carroll, 2004; Morzinski et al., 1994).
RECOMMENDATIONS, LIMITATIONS AND FUTURE
RESEARCH
This research on mentoring relationship has the following
recommendations, limitations and future research. The
implementation and coordination of mentoring programmes
are recommended by this study, because of the
sustained development of new employees that it can
successfully produce. From this study it can be recommended
that the characteristics of mentors should be
taken into account within the coordination of mentoring

Table 7. Ideal characteristics of mentor programme coordinator (theme 4).
Visagie and Kruger 7613
Sub-theme Associated key words
Following up mentoring relationships
Follow-ups A mentoring agreement needs to be followed up monthly or quarterly; It should be good if there is
documentation of the HR and the mentoring meetings that are held.
Capacity At this stage it is impossible to give provision to all the mentoring pairs; Responsibility of the mentoring cannot
be on one person. It should come from the side of the mentoring pair in the current circumstances.
relationships. Ensuring regular follow-ups of mentoring
relationships can be recommended in coordinating mentoring
relationships. The primary limitation in this case
study is the relatively small population of this qualitative
study (n=20). This study is focused on an organisation
that experiences their mentoring programme as a successful
programme. This study is therefore limited in not
representing the perceptions of mentoring pairs in
unsuccessful mentoring programmes. Investigation of the
perceptions of mentoring relationships in unsuccessful
mentoring programmes can be done in a more in-depth
manner in the future. Mentoring research could benefit
from research into social support as done in psychological
research (McManus et al., 1997; Scandura et al.,
2010). There is a need for research in informal mentor
programmes in general. In the future, the need for the
role of the mentoring programme coordinator should be
assessed. The growing amount of research on the topic
of mentoring is mainly done as quantitative research and
more in-depth qualitative research may bring a more
rounded understanding of mentoring relationships (Allen
et al., 2008).
Conclusion
This case study supports the findings of the meta-analysis
of Allen et al. (2004b) that mentoring relationships
have a reliable, but small, effect on several career outcomes.
A most notable result is of the senior employees
who have been delivered through the mentoring
programme of this case study, as seen in Table 6. The
success of the mentoring programme of this case study is
experienced as correlating with the characteristic of the
mentors and protégés in the mentoring relationship.
Mentoring success and characteristics of the mentors
and protégés should be investigated within the context of
the purpose of the mentoring programme in the organisation
being researched. This is because the purpose
and approach of mentoring programmes are diverse
within organisations. The purpose of the mentoring
programme is what makes it possible to gauge success
of this mentoring programme in terms of the organisation’s
desired outcomes of the mentoring programme.
One of the purposes of the mentoring programme, as
indicated in Table 4, is the development of identified protégés.
The results indicate that protégés are successfully
developed in the organisation, but the results indicate
that certain characteristics of protégés should be taken
into consideration as causality towards the success of the
protégés, as seen in Table 6.
A second purpose of the mentoring programme, as
indicated in Table 4, is utilising identified mentors for the
mentoring relationships. The results indicate that mentor
characteristics should be considered as causality towards
the success of the mentors, as seen in Table 5. This
finding indicates the need for further research into mentor
characteristics (Dougherty et al., 2007). The importance
of the mentor giving feedback and being approachable
stood out the most under the reason for mentoring
programme success. For knowledge transfer to be promoted,
interpersonal trust can be used in the mentoring
relationship (Preece et al., 2007). Proper follow-up, by a
mentoring coordinator, of the mentor-protégé relationships
should not be neglected if sustained development
is desired (Carroll, 2004; Morzinski et al., 1994). Therefore,
proper follow-ups of the mentoring relationships are
recommended. A third purpose of the mentoring
programme is sustained development, which emphasises
the bottom line of what can be seen as mentoring
relationship programme success, namely: the promotion
of new employees into specific gaps, producing
employees who achieve job requirements and ensuring
knowledge and experience that have been built up in the
organisations over the years are retained. The mentoring
relationship can be successful or dysfunctional (Feldman,
1999; Wanberg et al., 2003).
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African Journal of Business Management Vol. 5(17), pp. 7616-7621, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.786
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Consumers’ attitudes towards different product
category of private labels
Shih Jung Wang 1 and Lily Shui-Lien Chen 2 *
1 Business Administration Department, Hsing Wu College, No. 101, Sec.1, Fenliao Rd., LinKou Township, New Taipei City
244, Taiwan.
2 Graduate Institute of Management Sciences, Department of Management Sciences and Decision Making, Tamkang
University, No. 151, Ying-Chuan Road, Tamsui, New Taipei City 25137, Taiwan (R.O.C.).
Accepted 6 July, 2011
This research attempted to investigate the consumer perceptions on product quality, price, brand
leadership and brand personality towards convenience goods and shopping goods based on
international private labels (IPLs) and local private labels (LPLs). Data were collected outside the
entrances of the main rail station of Taipei, Taiwan. A systematic sampling was adopted and 254
questionnaires were eventually collected. The findings revealed that the consumers in Taiwan believe
that international and local hypermarkets both produce better convenience goods than shopping goods
that have high quality and deliver more value. This research represents one of the few pioneer works
that empirically investigate the aforementioned issues.
Key words: International private label, local private label, convenience goods, shopping goods.
INTRODUCTION
In recent years, large retailers have exercised private
label (PL) strategies to reap the ever-increasing market
share in most consumers’ product categories when
competing with national brands (Cheng et al., 2007;
Ishibashi and Matsushima, 2009). For example, Wal-Mart,
a leading retailer in the USA, the sales volume of PL has
accounted for as much as 25% of the operating revenues.
In grocery outlets, they form over 15% of US supermarket
sales and over 44% grocery shoppers regularly buy PL
(Chen, 2007). In Switzerland, where the top 5retailers
capture up to 88% of the market, the number of PL (38%
of business is private labeled) makes Switzerland the
most PL country in the world. In Great Britain, 31% of total
business is composed of PL, which owns an 83% share of
*Corresponding author. E-mail: tzjunltk@yahoo.com.tw Tel:
886-2-86313221/886-926-973473, Fax: 886-2-86313214.
Abbreviations: IPLs, International private labels; LPLs, local
private labels; PL, private label; NBs, national brands; IG,
intergenerational; CFA, confirmatory factor analysis; CFI,
category for Inference;
RMSEA, root mean square error of approximation; CR,
composite reliability; AVE, average variance explained; SAS,
statistical analysis software.
sales in the retailing sector (Anonymous, 2004).
PL, also store brand, is the brand which retailers are
responsible for promoting, shelf placing, pricing, and
positioning its own brand in the product space. In this
study, we group the PL into two categories that is, the
international private label (IPL) for example, American
Costco and British Tesco, and the local private label (LPL)
for example, Taiwanese RT-Mart. Taiwanese consumers
perceive that these two categories of PL are different in
some ways. Meanwhile, product classification, for
example, convenience goods versus shopping goods, can
also affect consumers’ attitudes toward these brands.
The notion of national brands (NBs) and PL have been
heavily studied in the marketing literature (Sanjoy and
Oded, 2001; Karray and Martín-Herrán, 2009). Most of
them attempt to compare consumer perceptions of
product quality and price among different brands.
However, there are few articles that distinguish the
different effects on IPL and LPL and there are few
researches work that introducing or show the effect of
different product classification on such in this matter. This
research, therefore, investigates the attitudes of
Taiwanese consumers towards convenience goods and
shopping goods based on two types of brands: IPL and
LPL. This research is organized as follows: literature
review and research hypotheses are presented in the next

section. In Section 3, we will discuss the method used in
the paper. The data analysis and results are shown in
Section 4. This paper is then concluded in the final
section.
LITERATURE REVIEW AND RESEARCH
HYPOTHESES
Some companies license their PLs and then launch new
businesses. They sometimes search for manufacturers
with excess capacity to produce their PL at a lower cost,
and then earn a higher profit margin (Parker and Kim,
1997; Gómez and Benito, 2008). The past two decades
have seen manufacturers’ brands becoming less
important. Meanwhile, retailers have been growing in
influence and gaining power in the marketing channel
(Farris and Kusum, 1992; Shocker et al., 1994; Frederick,
2000; Suárez, 2005). The various arenas of NBs and PLs
take place and the PLs possess unique competitive
means to control the market power of NBs, including
price, shelf space, quality, innovation and brand
advertising (Steiner, 2004).
This research distinguishes two types of PLs namely
IPL and LPL. The purpose of this paper is to investigate
consumers’ perceptions towards convenience goods and
shopping goods based on IPL and LPL qualities. First, the
study defines the constructs used in this paper and their
application. It then proposes the viewpoints by raising a
number of hypotheses. There are four constructs to be
discussed namely, perceived quality, brand leadership,
price perception, and brand personality. These constructs
will be discussed in relation to two product categories
which are the convenience goods and shopping goods.
Perceived quality
According to Aaker and Joachimsthaler (2000), perceived
quality is “a special type of association, because it
influences brand associations in many contexts and has
been empirically shown to affect profitability”. It is also
defined as “the consumer’s judgment about a product’s
overall excellence or superiority” (Chueh and Kao, 2004).
Brand leadership
According to Aaker and Joachimsthaler (2000), “brand
leadership is an excellent, interesting, insightful and
thought-provoking draw that significantly extends the
boundaries of what we know about managing brands.”
Aaker (1996) develops three dimensions to interpret
leadership. These are syndrome, innovation and
dynamics of customer acceptance. Steiner (2004) regards
innovation as the most important of all. Stefan and Don
(2003) also indicate that innovation is one of the National
Brand American Core Values.
Price perception
Wang and Chen 7617
The price of an item plays a powerful role in marketing.
Consumers see price more than just the money that the
buyer hands over to the seller. The broader view is that
the price is the sum of all the values that the buyer
exchanges for obtaining the product. Thus price is a key
variable in communicating to the customer about the
value of the product. The shoppers’ perceptions of price
are regarded to influence their purchase behavior
(Miranda and Joshi, 2003). Thus, the lower the price, the
more favorable the brand perception.
Brand personality
Aaker (1997) defines brand personality as “the set of
human characteristics or traits that consumers attribute to
a brand”. Aaker (1996) describes brand personality as the
linkage to the emotional and self-expressive benefits of a
brand. Boyle (2003) advocates that, “a key aspect of a
brand’s personality is its values and therefore, one of the
tasks of brand builders is to find a way of imbuing the
brand with these values”. Though it is no easy work to
imbue a brand with the values, nevertheless, the brand
personality must be distinctive, robust, desirable, and
consistent enough to successfully differentiate it from
another brand.
Research hypotheses
Consumer products are those that are purchased by the
final consumer for his/her consumption. These products
are further classified into convenience, shopping,
specialty. This research will focus on convenience goods
and shopping goods. Convenience goods are those that
are purchased frequently with little planning or shopping
effort. They are usually at low prices and widely available.
Shopping goods are those which are purchased less
frequently, such as furniture and major appliances, and
are compared on the bases of suitability, quality, price and
style (Kotler et al., 1998).
Empirical evidence indicates that retail concentration
has increased dramatically throughout Europe as
supermarkets take an increasing share of the
convenience goods business (Cullen, 1997). Retailers
have offered convenience goods as their PLs for a long
time now in many countries. Sometimes these products
represent a prime product type for brand imitation.
Consumers will buy a brand imitator instead of an original
if they do not perceive significant differently on product
quality given the price difference. Astous and Gargouri
(2001) indicate “the goodness of the imitation may be of

7618 Afr. J. Bus. Manage.
less importance as long as the quality appears to be
there”.
In an empirical study done by Leblanc and Turley
(1994), only an average of 2.19 brands can be
remembered from a consideration set sizes of 23
shopping goods. In the research conducted by LeBlanc
and Turkey (1994) and LeBlanc and Herndon (2001), they
record that “consumers seem to have initial evoked sets
with only a single brand in them.” Baker and Wilkie (1992)
have the same results reporting that consumers have
small-evoked set sizes for shopping goods.
When they compared convenience goods and shopping
goods, Murphy and Ben (1986) found out that the former
has lower risk and effort than the latter. On a concept of
intergenerational (IG) influence research, Heckler et al.
(1989) discovered that consumers have stronger
preference effects for convenience goods than for
shopping goods (Moore et al., 2002). Therefore, the study
proposes the following hypotheses.
H1. Consumers perceive that the quality of convenience
goods is superior to that of shopping goods for private
label.
H2. Consumers perceive that brand leadership of
convenience goods is superior to that of shopping goods
for private label.
H3. Consumers perceive that the price of convenience
goods is higher than that of shopping goods for private
label.
H4. Consumers are more conscious of the brand
personality for convenience goods than for shopping
goods for private label.
RESEARCH METHODOLOGY
In this section, we discuss the research setting, scale development,
as well as the sampling framework.
Research setting
As mentioned earlier on, this research seeks to investigate
consumer perception of two product categories among two different
labels. We therefore compare consumer’s attitude toward IPL, and
LPL between convenience goods and shopping goods.
The study considers a liquid detergent as the convenience good
in the research based on Cullen’s (1997) work. There are many
hypermarkets in Taiwan. However, this research chose two of them
to be the research subjects. Not only are these hypermarkets well
known, but they also have their own store brands in many product
categories. TESCO (merged with Carrefour in Taiwan) liquid
detergent (one of the store-brand products of British Tesco Co.) and
FP liquid detergent (a PL by a local Taiwanese RT-Mart) are our IPL
and LPL, respectively. We choose the electronic appliance as the
item representing shopping goods based on the paper by Varinder
and Krish (2001). As pointed out earlier on TESCO and FP are our
IPL and LPL, respectively.
Scale development
The questionnaire was developed mostly according to the scales of
Aaker (1996) and Miranda and Joshi (2003), but with some minor
modifications that fit our research purpose. The measurement items
of price perception are cited from Miranda and Joshi (2003). In
addition, the study takes into consideration the classification by
Aaker (1996) on measuring brand equity across products and
markets. All items were measured as perceptions on a 7-point Likert
scale: 1=strongly disagree, 4=neutral and 7=strongly agree. The
interviewees were asked about their perceptions toward IPL, and
LPL products. Finally, the study adopted four sets of items that are
discussed below as follows.
Each scale of perceived quality, brand leadership, and brand
personality contain three items. The Item-total value of the price
construct suggested the elimination of item 2 and the amount of the
final measurement items for price perception is only one. The items
of perceived quality are “high quality”, “the worst brand”, and
“consistent quality”. Leadership scale contains “innovative”,
“growing in popularity”, and “the leading brand”. Price perception
scale is comprised of “lower”; “has a personality”, “interesting”, and
“clear image of the type of users”. These items are related to the
brand personality scale.
Sampling and data collection
Taipei, the metropolis of Taiwan, is selected as the target population
in this research. The survey was administered to the Taiwanese
residents at the public location (Taipei railway station) with the
systematic sampling method (one out of ten passing entrance). After
discarding some invalid respondents, we collected a total sample
size of 254 for the final data analysis.
DATA ANALYSIS AND RESULTS
A series of statistical procedures are used to analyze the
research questions. The respondents’ profile will be
reported first, followed by an examination of the reliability
of the scales. Testing of the research hypotheses will then
be placed at the end of this section.
Respondents’ profiles
The respondents included more females (60.63%) than
males (39.37%). Most of them were less than 30 years of
age. About 91.74% of the respondents held a
university/college degree or higher. As for their
occupation, white collar workers, blue collar workers, and
students all occupied around one third of the respondents.
In terms of income, about 45% earned total monthly
incomes of NT$15,000 or less. Finally, most of the
respondents were single. Detailed descriptive statistics
relating to the respondents’ profiles are shown in Table 1.
Measurement accuracy analysis
A confirmatory factor analysis (CFA) was conducted on
the sample data in order to get evidence on the
robustness and reliability of the scales in a brand equity
context. The CFA model had an overall Chi-square of
225.10, a category for Inference (CFI) of 0.97, an IFI of

Table 1. Participants’ demographic statistics.
Age Freq % Marriage Freq %
=51 9 3.54

7620 Afr. J. Bus. Manage.
Table 3. Comparison between convenience and shopping goods for IPL/LPL.
Factor
IPL (British Tesco)
Convenience Goods
LPL ( Taiwanese RT-Mart)
1 Shopping Goods 2 p-value 5 Convenience Goods 3 Shopping Goods 4 p-value 5
Quality 4.30 4.12 0.0270* 3.98 3.70 0.0003*
Leadership 3.77 3.74 0.7856 3.44 3.41 0.7532
Price 4.22 4.18 0.6611 4.63 4.43 0.0843
Personality 3.91 3.81 0.2771 3.62 3.58 0.6294
1, Mean values for convenience goods on IPLs, based on a 7 Likert-type scale with strongly disagree; 7, to strongly agree; 1, mean values for shopping
goods on IPLs, based on a 7 Likert-type scale with strongly disagree; 7, to strongly agree; 1, mean values for convenience goods on LPLs based on a
7 Likert-type scale with strongly disagree; 7, to strongly agree; 1, mean values for shopping goods on LPLs based on a 7 Likert-type scale with strongly
disagree; 7, to strongly agree; 5, significant level; *, significant different (at 0.05 level) for convenience goods and shopping goods.
experience on convenience goods are better than
shopping goods.
DISCUSSION AND CONCLUSION
This research investigated the consumer perceptions of
IPL and LPL on convenience goods and shopping goods
categories in Taiwan. Most of previous works have
focused on NBs and private brands only, but we
distinguish PL into IPL and LPL. Since Taiwan is getting
more internationalized, more and more international
businesses come to the island. Therefore, it is important
to understand how consumers perceive these private
branders.
The mean value of consumers’ perception on
convenience goods is significantly higher than that of
shopping goods. That is to say the consumers in Taiwan
believe that these two hypermarkets produce better
convenience products than shopping products in quality
and deliver more values to the customers.
IPL has the advantage of economies of scale and the
image of commodities of foreign make, which manifests
itself as exotic lifestyle and culture. LPL received the
lowest score in almost all aspects, which means that
consumers do not regard highly this label. But
convenience goods branders of this label can make use of
the advantage of their low price strategy. For shopping
goods, the study suggests the branders emphasize the
origin of those products.
Findings from the comparison of convenience and
shopping goods for IPL/LPL, show that customers
perceived shopping goods inferior to convenience goods.
Retailers should make more effort to create high value
shopping goods, especially on quality conception
enhancement.
LIMITATIONS AND DIRECTION TO FURTHER
RESEARCH
This paper tests the hypotheses by conducting the survey
method. The study adopts part of the constructs from the
work of Aaker (1996) and Miranda and Joshi (2003). Their
objectives are to measure brand equity without subject to
any specific product categories. Though the study adopt
only four constructs to measure Taiwanese consumer
perceptions on two different brand types, most of the
results support the viewpoint. That means, the study was
able to measure consumer perceptions using these
constructs. The study does not use the whole original
scale, but this could be an interesting issue for further
study.
There is little research distinguishing IPL and LPL from
PLs. The findings indicate that consumers have different
perceptions on these two brand types. This calls for
marketers to exploit the opportunities in these segments.
Finally, the research approach and findings of this study
can provide directions for future research. Future study
could follow the research approach to get more empirical
evidence by adopting different categories, brands, as well
as focusing on different countries other than Taiwan.
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African Journal of Business Management Vol. 5(17), pp. 7622-7631, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.826
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
The determinants of board size and composition:
Evidence from Taiwan banks
Pi-Hui Ting
Department of Business Administration, Chang Jung Christian University, No.396, Sec. 1, Changrong Rd., Gueiren Dist.,
Tainan City 71101, Taiwan, Republic of China.
E-mail: tphui@mail.cjcu.edu.tw. Tel: 886-6-2785123. Fax: 886-6-2785680.
Accepted 30 May 2011
Using panel data on banks publicly listed in Taiwan over 1997 to 2008, this paper examines the
determinants of board size and composition in an environment where most banks have concentrated
ownership and investor protection is weak. The result shows that board size and composition reflect
the bank-specific and ownership characteristics. First, bank size and bank age are the key determinants
of banks’ board size. Besides, board independence increase with the controlling shareholders’
ownership, but decrease with the ownership of outside directors. However, board size and structure are
both not sensitive to the benefits and costs of monitoring and advising. Thus, contrary to the finding of
US unregulated firms with disperse ownership, our results are not supportive of the view that banks
structure boards in an efficient response to their operating environment.
Key words: Board size, board composition, ownership.
INTRODUCTION
In the wake of the recent corporate scandals, corporate
governance practices have received heightened attention.
Among several governance mechanisms, board size
and board composition are especially the focus of many
attempts to increase corporate governance because they
are important characteristics that influence the effectiveness
of the board in solving the agency problem between
shareholders and managers. Are boards of directors
effective at monitoring managers? The results of existing
literature do not provide a satisfied answer to the
question. Several empirical analyses find that board
composition is not related to firm performance (Hermalin
and Weisbach, 1991; Mehran, 1995; Klein, 1998; Bhagat
and Black, 2002). However, other studies show significant
positive relationships between the proportion of
outside directors and firm performance (Rosenstein and
Wyatt, 1990; Daily and Dalton, 1993). Another line of
research that examines the association between board
size and firm performance also has mixed results. Some
studies report negative effect of board size on firm performance
(Yermack, 1996; Eisenberg et al., 1998; Bhagat
and Black, 2002). But, Belkhir (2009b) find positive
relationship between board size and banks’ performance.
These studies on the relation between governance mechanisms
and firm performance impliedly assume there
are common optimal board sizes and board compositions
for all firms, and the firms which diverge from the optimal
characteristics will have lower firm performance.
The alternative view is that corporate governance
mechanisms are endogenously determined according to
the cost and benefit of each governance mechanism and
the optimal corporate governance mechanisms vary
across firms. If every firm structures its board in an
efficient response to its operating environment, there will
likely be no empirical relationship between board size or
board composition and firm performance (Mak and Li,
2001; Hermalin and Weisbach, 2003; Belkhir, 2009a).
Belkhir (2009a) suggests that the empirical results of how
board structure affects firm’s performance will be misleading
if ignoring the fact that the optimal corporate
governance mechanisms vary across firms. Thus, in
order to understand the effect of the board on firm performance,
one must understand how a board is structured.
The literature on the determinants of board structure is
fast growing recently. One line of research build theoretical
model to explore the determinants of board structure
(Hermalin and Weisbach, 1998; Raheja, 2005; Adams
and Ferreira, 2007; Harris and Raviv, 2006). Hermalin
and Weisbach (1998) model board structure as the
outcome of a negotiation between the CEO and outside

directors and propose the board independence will
decrease with CEO’s influence. Raheja (2005) and Harris
and Raviv (2006) argue that board size and the proportion
of outside directors optimally increase with the level
of private benefits available to managers, but decline with
the cost of monitoring. Adams and Ferreira (2007) also
show that a management-friendly board can be optimal if
the importance of the information that CEO can provide is
high. Another line of research empirically examines the
determinants of board structure. Lehn et al. (2009) find
that both board size and the proportion of outside directors
are positively related to firm size and negatively
related to growth opportunities by using 81 US firms from
1935 to 2000. Coles et al. (2008) show that complex
firms, have larger boards, and more outsider directors,
but high R and D firms have a higher proportion of
insiders on the board. Boone et al. (2007) find that board
size increases with the level of private benefits available
to managers and decline with the cost of monitoring
managers. However, there is no evidence that the
fraction of outsider directors is related to the cost and
benefits of monitoring.
The focus of most studies on the determinants of board
structure has been primarily on large unregulated firms
(Shivdasani and Yermack, 1999; Boone et al., 2007;
Linck et al., 2008). Board of directors in banks has
received only limited attention. However, banking firm
governance differs from the governance of unregulated
firms. Adams and Mehran (2003) find that the boards of
bank holding companies are larger than those of manufacturing
firms. Besides, more board directors of BHC are
from outsiders. Contrary to the evidence found for nonfinancial
firms, Belkhir (2009b) also indicate that banking
firms with larger board do not underperform their peers.
Since the health of the overall economy depends on
banks performance (Adams and Mehran, 2003) and the
board of directors plays a crucial role on monitoring
banks’ performance, understanding the determinants of
banks’ board structures is more important than ever
before at the time when the banking industry becomes
increasingly deregulated. Thus, this paper examines the
determinants of board composition using a sample of
banking firms in Taiwan.
Moreover, Caprio et al. (2007) argue that most banks
are not widely held but rather controlled by families or the
State, except the few in countries with very strong shareholder
protection laws. In such condition, the controlling
owner may play important role in selecting the board
composition and expand their control power through
pyramid structures of firms and cross-holdings among
firms. Whether the results from existing researches can
be generalized to banks with concentrated ownership is
worth exploring. Taiwan offers an ideal laboratory that let
us address the issue about the determinants of banks’
board composition with concentrated ownership. As Yeh
and Woidtke (2005) point out, Taiwan features relatively
weak protection of minority shareholders, high ownership
Ting 7623
concentration, a predominance of family control, and an
abundance of pyramidal groups and cross-holdings –
characteristics common to many countries (La Porta et
al., 1999; Claessens et al., 2000; Faccio and Lang,
2002). Using panel data on banks publicly listed in
Taiwan over 1998 to 2007, the results from the study can
enhance the understanding as to how a bank’s board is
structured in an environment where most banks have
concentrated ownership and investor protection is weak.
Our empirical results indicate that larger and more
mature banks tend to have larger boards. Moreover, a
bank’s board structure is the outcome of a negotiation
between the controlling shareholders and outside directors
in Taiwan where most banks have concentrated
ownership and investor protection is weak. Banks, in
which controlling shareholders have substantial influence
and in which the constraints to controlling shareholders’
influence are weak, have more affiliated directors. However,
contrasting to the finding of US unregulated firms
with disperse ownership, we find no evidence that board
size is related to the costs and benefits of monitoring.
LITERATURE REVIEW AND DEVELOPMENT OF
HYPOTHESIS
Related literature
Hermalin and Weisbach (1998) are the first to develop a
model to explore how a board is structured. In their
model, board structure is the outcome of a negotiation
between the CEO and outside directors. Because CEO
prefer a less dependent board, the proportion of outside
directors decreases with the CEO’s bargaining power.
Boone et al. (2007) refer to this argument as the
“negotiation hypothesis”.
Raheja (2005), Adams and Ferreira (2007) and Harris
and Raviv (2006) formulate their theoretical model by
considering the monitoring or advising function of board.
In their model, boards are made of insiders and
outsiders. Boards monitor managers’ deed to prevent
them from expropriating shareholders, and provide their
expertise to advise management on the firm’s decision
that affects firm profits. Insiders have firm-specific information
relevant to the decision. However, due to private
benefits and lack of independence from the CEO,
insiders also have distorted objectives that lead them to
select a decision that does not maximize shareholders’
wealth. If the CEO or insiders have stronger incentive to
extract private benefit by expropriating shareholders, the
benefit of monitoring will increase. Contrary to insiders,
outsiders can provide better monitoring and advice
because they are more independent and have a variety
of expertise. But, outsiders have less information about
the firm’s constraints and opportunities, and may obtain
private, decision-relevant information at a cost. If the
firms face greater information asymmetry, the cost of

7624 Afr. J. Bus. Manage.
monitoring will increase. The larger board will also
increase the monitoring cost because of the free-riding
problems and higher co-ordination cost. All of the theoretical
models proposed by Raheja (2005), Adams and
Ferreira (2007) and Harris and Raviv (2006), point out an
optimal board structure of firm is a function of the cost
and benefit of monitoring and advising. The board size
and the proportion of outside directors increase with the
benefit of monitoring and advising, but decrease with the
cost of monitoring.
Hypothesis
The study uses board size and the proportion of outside
directors as two measures of board structure, and examines
the determinants of board structure. Based on the
previous theoretical models, the optimal board structure
depends on the CEO’s bargaining power and the cost
and benefit of monitoring and advising. Further, we develop
our primary hypothesis according to those above
attributes.
Board structure and benefits of monitoring and
advising
The benefit of monitoring and advising functions are
related to firm complexity and managers’ opportunities to
extract private benefits. Fama and Jensen (1983)
suggest firms with larger operation scope and complex
production process have larger and more hierarchical
organizations. Thus, in order to monitor managers’ decision,
the firms need larger board. The view is consistent
with Bhagat and Black (1999), Agrawal and Knoeber
(2001), Coles et al. (2008) and Lehn et al. (2009). They
also suggest that a firm will look for new directors to
supervise managers’ performance when it grows into a
new business area.
The scope and complexity of a firm's operations also
has an impact on the board's composition except on
board size. Because agency problems become more
significant with firm size, larger firms demand more
outside directors (Boone et al., 2007; Linck et al., 2008;
Lehn et al., 2009). Moreover, Anderson et al. (2000) and
Coles et al. (2008) show that diversified firms need more
independent outsiders to monitor their complex operations.
In summary, firms with larger operation scope and
complex production process need larger and independent
boards because of their stronger and more urgent need
of monitoring function. Boone et al. (2007) refer to such
an argument as the “scope of operation hypothesis”.
Following Boone et al. (2007) and Linck et al. (2008),
we use bank size and bank age to proxy for bank
complexity. Besides, in most countries, separated banks
and universal banks coexist (Vennet, 2002; Shen, 2005).
The separated banks focus on traditional intermediation
activities, but the universal banks also conduct the
services of credit cards, derivative designs, underwriting
and brokerage except traditional intermediation activities.
In other words, the operations of universal banks are
diversified and more complex. Chen (2004) and Shen
(2005) use the fee revenue ratio to divide banks into two
technology types-separated banks and universal banks.
Thus, we also use the fee revenue ratio to proxy for bank
complexity.
The fee revenue ratio will increase with banks’
complexity.
On the other hand, Raheja (2005), Adams and Ferreira
(2007) and Harris and Raviv (2006) proposed that the
higher level of private benefits available to managers will
increase the benefit of monitoring, and result in a larger
and more independent board. We use free cash flow to
measure managers’potential private benefits (Jensen,
1986; Boone et al., 2007; Linck et al., 2008) and argue
free cash flow can influence board size and board
composition.
Board structure and cost of monitoring
Many studies argue that high growth firms may increase
the cost of monitoring to outside directors because firmspecific
information is more important in such firms
(Raheja, 2005; Coles et al., 2008; Lehn et al., 2009).
Demsetz and Lehn (1985) contend that the monitoring
cost will increase with the noisiness of a firm's operating
environment.
Furthermore, Maug (1997) and Linck et al. (2008) suggest
that, in the firms with high information asymmetry, it
is costly to transfer firm-specific information to outside
directors, and the monitoring cost increases.
The prevailing literature usually uses the market-tobook
ratio to proxy for the firm growth opportunities
(Smith and Watts, 1992; Gaver and Gaver, 1993; Boone
et al., 2007). The standard deviation of stock returns can
be proxy for information asymmetry (Fama and Jensen,
1983) and reflect uncertainty of a firm's operating
environment about the firm's prospects (Demsetz and
Lehn, 1985). Finally, Chen (2004) argues that the outside
directors are ineffective in monitoring separated banks
because managers of separated banks have specific
knowledge about traditional intermediation activities.
Since the monitoring cost of separated banks is higher
than those of the universal banks, we also use the fee
revenue ratio to measure the cost of monitoring. Because
the board size and the proportion of outside directors
decrease with the cost of monitoring and advising, we
predict that these variables are negatively related to
board size and the proportion of outside directors.
Board composition and control shareholders’
influence
Hermalin and Weisbach (1998) argue that board

composition is the outcome of a negotiation between the
CEO and outside directors. In their model, CEOs wield
their influence to place insiders in board, and the proportion
of outside directors is negatively related to CEOs’
bargaining power. Kieschnick and Moussawi (2004) also
show that the proportion of outside directors decreases
with CEOs’ influence and increases with constraints on
CEOs’ influence.
Hermalin and Weisbach (1998) suggest that CEO’s
influence is increasing in firm performance. Boone et al.
(2007) use CEO ownership to measure CEO’s influence.
When ownership is more concentrated and investor
protection is weaker, the controlling shareholders have
enough control over the operations of the firm and strong
incentives to put pressure on managers (Claessens et al.,
2002; Shleifer and Vishny, 1997). So, it is possible that
the controlling shareholders will replace managers to
exercise power over the selection of board composition.
Since most banks are not widely held but rather controlled
by control shareholders (Caprio et al., 2007), the
study examines the role the controlling shareholders play
in selecting board composition and uses three measures
of control shareholders’ influence: banks’ past performance
and control shareholders’ ownership. Besides,
outsider directors’ ownership is used to proxy for constraint
on control shareholders’ influence because higher
outsider directors’ ownership can limit control
shareholders’ influence (Boone et al., 2007).
Board composition and ownership incentive
The theoretical model proposed by Raheja (2005) show
that the board size and the proportion of outside directors
optimally grow with the level of private benefits available
to managers, but decline with the cost of monitoring. He
contents that higher ownership will align the interests of
CEO with shareholders, thus CEO with higher ownership
is less likely to seek private benefits. On the other hand,
the outside directors have stronger incentive to exercise
monitoring function when they have higher ownership.
Therefore, the cost of monitoring is negatively related to
outside directors’ ownership. In summary, the board size
and the proportion of outside directors will decrease with
CEO’s ownership but increase with outside directors’
ownership. Because of the similarity between CEOs and
the controlling shareholders in banks with concentrated
ownership, the ownership of the controlling shareholders
will be used to replace the ownership of CEOs.
Moreover, the controlling shareholders are often able to
control a firm’s operations with only limited ownership –
cash flow right, through pyramid structures and crossholdings
among firms (La Porta et al., 1999). Claessens
et al. (2002) find that when there is a greater divergence
between control right and cash flow ownership, the
controlling shareholders have more power to expropriate
wealth from minority shareholders but just bear less cost
Ting 7625
of their actions. So, the controlling shareholders are more
inclined to seek private benefits. Thus, the divergence
between control right and cash flow is also used to proxy
for the controlling shareholders’ potential private benefits.
The board size and the proportion of outside directors are
predicted to be positively related to the divergence
between control right and cash flow.
Our hypotheses are based on the assumption that the
firm chooses the board composition as an efficient
response to the firm characteristics. Alternatively, board
composition may be a result of agency problem and
regulatory mandates about board composition may be
beneficial to investors (Linck et al., 2008). For example,
Yeh and Woidtke (2005) find that negative entrenchment
effects will induce the controlling shareholders to select
an inefficient board “when that shareholder: (1) has a
greater divergence in control and cash flow rights, (2)is a
member of the controlling family, and (3) is the firm’s
CEO and chairman”. If the alternative argument is true,
we will find that the board size and the proportion of outside
directors decrease with the level of private benefits
available to managers.
RESEARCH DESIGN
Sample
Our data includes banks publicly listed in Taiwan during the period
from 1998 to 2007. In the sample, we found that sixteen banks are
acquired by bank-holding companies from 2002 to 2007 and the
bank-holding companies almost have 100% ownership. Because all
the acquired banks’ board directors are representatives elected by
the bank-holding companies, we omit the sixteen banks observations
after they are included in the bank-holding companies to
avoid bias in the empirical results. As a result, our final sample
contains 233 bank-year observations.
We collect the board composition, control rights, cash flow
ownership and other company information data from the Taiwan
Economics Journal (TEJ) database, company prospectuses and
‘‘Business Groups in Taiwan,’’ a book published annually by the
China Credit Information Services Limited.
Variable definition
The paper examines how a bank’s board is structured in an
environment where most banks have concentrated ownership and
investor protection is weak. Following Boone et al. (2007) and Linck
et al. (2008), we focus on two important characteristics of board-
board size and board independence. Board size is measured by the
number of directors on the board. Board independence is measured
with the proportion of outside directors and outside directors are
directors that are not affiliated to the controlling owner. Following
Lin and Hsu (2008), the controlling owners are defined as the
shareholders, family group or government institution that have
ultimate influence over major decisions regarding the operation,
management, and allocation of company resources. Board directors
and supervisors, are defined as affiliated when they are held either
by the firm’s controlling owner, by the controlling owner’s identifiable
relatives, or by legal representatives from other companies or
entities controlled by the controlling owner (Yeh and Woidtke,
2005). The proportion of outside directors is calculated based on

7626 Afr. J. Bus. Manage.
the number of outside directors divided by the total number of
directors. Board size is measured with the total number of directors.
The rationales for each of the independent variables and the details
of the measures are explained further.
Bank size
The study measures bank size as the natural log of total assets as
of each fiscal year-end. Based on the “scope of operation hypothesis”,
bank size can measure bank complexity and is positively
related to board size and the proportion of outside directors.
Bank age
The “scope of operation hypothesis” proposes that bank complexity
increases with bank age. Thus, bank age is also predicted to be positively
related to board size and the proportion of outside directors.
Fee revenue ratio
Following Chen (2004) and Shen (2005), we use the fee revenue
ratio to divide banks into two technology types-separated banks
and universal banks. If the fee revenue ratio increases, the bank is
more toward universal banks. The scope of operation hypothesis
states that firms with more complicated production process need
larger and independent boards.
Because the operations of universal banks are diversified and
more complex, fee revenue ratio is expected to be positively related
to board size and the proportion of outside directors based on the
scope of operation hypothesis.
On the other hand, the monitoring cost of separated banks is
higher since Chen (2004) argues that managers of separated banks
have specific knowledge about traditional intermediation activities.
Because the board size and the proportion of outside directors
decrease with the cost of monitoring and advising, we can also
predict that fee revenue ratio is negatively related to board size and
the proportion of outside directors.
The fee revenue ratio is calculated based on fee revenues divided
by total revenues.
Market-to-book ratio
Raheja (2005), Coles et al. (2008) and Lehn et al. (2009) argue that
a small and less independent board is optimal for a high growth firm
because high growth firms may have more firm-specific information
and will increase the cost of monitoring to outside directors.
The market-to-book ratio can be proxy for the firm growth opportunities
(Boone et al., 2007; Linck et al., 2008), and is predicted to
be negatively related to board size and the proportion of outside
directors. he market-to-book ratio is measured as the book value of
debt plus the market value of equity, divided by the book value of
assets.
Standard deviation of stock returns
Demsetz and Lehn (1985) suggest that the standard deviation of
stock returns can measure a firm’s operation risk and can be proxy
for uncertainty of a firm's operating environment about the firm's
prospects. The monitoring hypothesis shows that the noisiness of a
firm's operating environment will increase the monitoring cost and
result in a small and less independent board. Thus, the study
predicts that the standard deviation of stock returns is negatively
related to board size and the proportion of outside directors. The
standard deviation of stock returns is the standard deviation of the
daily logarithmic stock return measured over the prior 12-month
period.
Free cash flow
Jensen (1986) show higher free cash flow will increase the level of
private benefits available to managers. Thus, it is better to increase
the board size and board independent based on the monitoring
hypothesis. If the monitoring hypothesis is true, free cash flow will
be positively related to board size and the proportion of outside
directors. Free cash flow is defined as the firm's earnings plus
depreciation minus capital expenditures, all divided by assets.
Bank prior performance
We use return on asset in the previous year to measure bank prior
performance. Hermalin and Weisbach (1998) show that CEO’s
influence increases with firm performance. Therefore, bank prior
performance is negatively related to the proportion of outside
directors.
Controlling shareholders’ ownership
Boone et al. (2007) propose that CEO with higher ownership is
more likely to wield his influence over board selection process.
Since CEO prefers inside directors, CEOs’ ownership is negatively
related to the proportion of outside directors. Raheja (2005) also
argues that higher ownership will align the interests of CEO with
shareholders, and decrease CEOs’ incentive of seeking private
benefits. In such scenario, there is less need for outside monitors
and a smaller and less independent board is optimal. Therefore,
based on the monitoring hypothesis, CEOs’ ownership is also
negatively related to the proportion of outside directors and board
size. Because of the similarity between CEOs and the controlling
shareholders in banks with concentrated ownership, the study use
the ownership of the controlling shareholders to replace the ownership
of CEOs, and expects the controlling shareholders’ ownership
is also negatively related to the proportion of outside directors and
board size.
As in Claessens et al. (2000), ownership is defined as cash flow
rights. The cash flow rights data are collected from the Taiwan Economics
Journal (TEJ) database. The cash flow right is the right of
the controlling owner to get the distributed earning of the bank.
Following La Porta et al. (2002), TEJ database defined cash flow
right as direct voting right based on the proportion of shares
registered to the ultimate owner plus the multiple of indirect voting
right in the chain of shares held by entities that in turn is controlled
by the ultimate owner.
Controlling shareholders’ excess control right
Excess control right is defined as control right less ownership.
Because the controlling shareholders have stronger incentive to
seek private benefits when the divergence between control right
and cash flow right increase, a larger and more independent is
optimal for banks with the higher excess control right. Thus, the
board size and the proportion of outside directors are predicted to
be positively related to the divergence between control right and
cash flow right. Control right is also collected from TEJ database.
Based on La Porta et al. (2002), they define control right as direct

Table 1. Descriptive statistics.
Ting 7627
Statistic Mean Standard deviation Minimum Maximum
Panel A. Board composition
Proportion of outside directors (%) 41.89 24.55 0.00 100
Board size(Number of directors) 15.08 5.27 6.00 30.00
Panel B. Ownership
Controlling shareholders’ Ownership (%) 19.83 18.39 0.02 100
Excess control (%) 4.41 12.50 0.00 99.89
Outside directors’ ownership (%) 6.35 10.28 0.00 93
Panel C. Bank characteristics
Bank size (billion) 412.04 400.76 41.76 2,422.54
Bank age 29.64 20.68 5.00 73.00
Fee revenue ratio (%) 17.90 10.80 2.06 89.11
Free cash flow ratio (%) 1.14 2.45 -5.68 12.59
Market-to-book ratio 1.01 0.11 0.88 2.39
Standard deviation of stock returns (%) 2.51 0.71 0.16 4.83
Prior performance (%) -0.05 1.77 -12.13 9.53
voting right plus indirect voting right. When calculating indirect
voting right, they take the last link in the control chain.
Outside directors’ ownership
Raheja (2005) shows that the monitoring cost will decline with
outside directors’ ownership and the less monitoring cost results in
a large and independent board. In the other hand, Kieschnick and
Moussawi (2004) argue that the proportion of outside directors
increases with constraints on CEOs’ influence. The higher outside
directors’ ownership will constrain CEOs’ influence, and thus
increase the proportion of outside directors. In summary, outside
directors’ ownership should be positively related to board size and
the proportion of outside directors.
EMPIRICAL RESULTS
Descriptive statistics
Table 1 shows the descriptive statistics for our sample of
Taiwan banks on key bank, board composition and
ownership variables. The average board size is 15.08.
This is much higher than that for US banks (Belkhir,
2009b) and for non-financial companies in Taiwan (Yeh
and Woidtke, 2005). The average value for the proportion
of outside directors is 41.89%. Contrary to the finding of
the prevailing literature (Booth et al., 2002, Adams and
Mehran, 2003), the banks tend to have more affiliated
directors and supervisors than non-financial companies in
Taiwan. Panel B is the ownership data. Average controlling
shareholders’ ownership in the sample is 19.83%,
and excess control right is 4.41%. Caprio et al. (2007)
define the banks as with concentrated ownership if they
have a shareholder that owns at least 10% of the voting
rights. Thus, most banks in Taiwan have concentrated
ownership. However, contrasting to Taiwan non-financial
companies, the ownership of banks in Taiwan is less concentrated.
The average outside directors’ ownership is
6.35%.
Panel C of Table 1 is the measures of bank characteristics
for the sample. The mean value of total assets is
$ 412.04 billion. The mean fee revenue ratio is 17.9%,
however, the maximum fee revenue ratio is 89.11% and
the standard deviation of fee revenue ratio is 10.8%. The
result shows that there exist large differences between
banks’ technology types. Mean free cash flow (FCF) is
1.14% of total assets, and mean MTB ratio is 1.01. The
sample has an average return on asset of -0.05%.
The determinants of board composition
To test our hypotheses and examine the determinants of
board size in Taiwan, we estimate multivariate regressions.
All regression equations include year dummy
variables to solve the possible problem that the contemporaneous
residuals are correlated across banks in panel
data set (Coles et al., 2008). The results are presented in
model (a) of Table 2. We use bank size and bank age to
proxy for bank complexity and find both variables are
positively related to board size. This is consistent with the
scope of operation hypothesis, which predict that
complex banks need larger board to monitor managers’
decision.

7628 Afr. J. Bus. Manage.
Table 2. The determinants of board size.
Model a b
Bank size 0.0783 *(0.0339 ) 0.0741 **(0.0345)
Bank age 0.1514 ***(0.0000 ) 0.1262***(0.0001)
Fee revenue ratio 0.0937(0.7799 ) -0.0695(0.8281)
Free cash flow ratio -0.0969(0.9276 ) 0.5396(0.5966)
Market-to-book ratio 0.0619(0.8442 ) -0.0204(0.9456)
Standard deviation of stock returns -12.4604**(0.0141) -11.8916**(0.0136)
Outside directors’ ownership 0.4174 *(0.0673 ) 0.2510(0.2505)
Controlling shareholders’ ownership -0.6676 ***(0.0000) -0.2253(0.1644)
Excess control -0.1422(0.4779) -0.0452(0.8131)
Lag (Proportion of outside directors) 0.5756 ***(0.0000)
Adjusted R-squared 0.1934 0.2777
F-statistic 4.0910*** 5.6737***
The results of a multiple regression analysis of the determinants of board composition are presented where the
dependent variable is board size measured by the number of directors on the board. Bank size is the natural log of
total assets as of each fiscal year-end. Bank age is the data year less the year a firm was founded. The fee revenue
ratio is calculated based on fee revenues divided by total revenues. Free cash flow is defined as the firm's earnings
plus depreciation minus capital expenditures, all divided by assets. The market-to-book ratio is measured as the
book value of debt plus the market value of equity, divided by the book value of assets. The standard deviation of
stock returns is the standard deviation of the daily logarithmic stock return measured over the prior 12-month
period. Outside directors’ ownership is the proportion of shares or cash flow rights owned by the outside directors.
Controlling shareholders’ ownership is the proportion of shares or cash flow rights owned by the largest shareholder
group. Excess control is control rights less cash flow rights and control right is the proportion of shares or votes
controlled by the largest shareholder group. Lag (the proportion of outside directors) is the proportion of outside
directors on the board in the previous year and outside directors are directors that are not affiliated to the controlling
owner. Data are obtained from the Taiwan Economics Journal database. p-values are given in parentheses, ***, **,
* represent significance at the 1, 5, and 10% level, respectively.
Except standard deviation of stock returns, the coefficients
for fee revenue ratio, market-to-book ratio and
free cash flow all are insignificant. It is inconsistent with
our hypothesis. Market-to-book ratio and standard deviation
of stock returns are used to proxy for information
asymmetry, and thus the results provide some, albeit not
uniform support for the hypothesis that board size
decreases for banks with high information asymmetry.
Fee revenue ratio flow is used to divide the banks into
different technology type. So, the results imply that the
board size is not related with bank operating type. Free
cash flow measure private benefits available to
managers, and is not the important determinant of board
size. In other words, the bank does not increase board
member to monitor managers that have more free cash
flow to use.
The coefficient on outside directors’ ownership is
significantly positive, and the coefficient on controlling
shareholders’ ownership is significantly negative, consistent
with the monitoring hypothesis. But the coefficient on
excess cash flow is insignificant. We also include
instrument variable for board independence to control for
the fact that board size and board composition are endogenous
to the firm’s environment. Following Boone et al.
(2007), we use the previous year’s proportion of outside
directors as the instrument variable for board
independence, and the results are showed on model (b)
of Table 2. We find that the significant coefficients on
bank age and banks size remain significant, but the coefficients
on outside directors’ ownership and controlling
shareholders’ ownership become insignificant. Contrary
to the finding of Boone et al. (2007) and Linck et al.
(2008), the results don’t support the monitoring
hypothesis. Thus, we find that the scope of operation is
the key determinants of banks’ board size.
In order to understand how a bank’s board is structured,
we also estimate multivariate regressions by using
the proportion of outside directors as dependent variable.
In model (a) of Table 3, the coefficients are not significant
on all bank’s characteristic variables except bank size.
However, consistent with our predictions, banks size is
positively related to the proportion of outside directors.
The results provide little support for the hypothesis that
board independent is a function of banks’ operating
environment, but indeed show that the bank selects more
outside directors as the bank size increases.
The coefficient on bank prior performance is significant
negative, consistent with the negotiation hypothesis
proposed by Hermalin and Weisbach (1998). The
negotiation hypothesis argues that the controlling shareholders’
influence is increasing in firm performance and
the controlling shareholders incline to select more inside

Table 3. The determinants of board composition.
Model a b
Bank size 0.0370*(0.0544) 0.0316*(0.0640)
Bank age 0.0203(0.2497) -0.0167(0.3128 )
Fee revenue ratio 0.2757(0.1405 ) 0.3551**(0.0336 )
Free cash flow ratio 0.3460(0.5341) 0.6243(0.2081 )
Market-to-book ratio 0.2042(0.2187) 0.1208(0.4130 )
Standard deviation of stock returns -3.7026(0.2165 ) -2.2391(0.4011)
Prior performance -2.2496 **(0.0401) -2.8045 ***(0.0042)
Outside directors’ ownership 0.3467 ***(0.0034 ) 0.2508**(0.0175 )
Controlling shareholders’ ownership -0.8772***(0.0000 ) -0.7187***(0.0000)
Excess control -0.1500(0.1479 ) -0.1281(0.1641 )
Lag (board size) 0.2588 ***(0.0000)
Adjusted R-squared 0.4567 0.5701
F-statistic 11.2629*** 16.3182***
The results of a multiple regression analysis of the determinants of board composition are presented where the
dependent variable is board composition measured by the proportion of outside directors. Outside directors are
directors that are not affiliated to the controlling owner. Bank size is the natural log of total assets as of each fiscal
year-end. Bank age is the data year less the year a firm was founded. The fee revenue ratio is calculated based
on fee revenues divided by total revenues. Free cash flow is defined as the firm's earnings plus depreciation
minus capital expenditures, all divided by assets. The market-to-book ratio is measured as the book value of debt
plus the market value of equity, divided by the book value of assets. The standard deviation of stock returns is the
standard deviation of the daily logarithmic stock return measured over the prior 12-month period. Bank prior
performance is return on asset, measured as the operation income over total assets in the previous year. Outside
directors’ ownership is the proportion of shares or cash flow rights owned by the outside directors. Controlling
shareholders’ ownership is the proportion of shares or cash flow rights owned by the largest shareholder group.
Excess control is control rights less cash flow rights and control right is the proportion of shares or votes controlled
by the largest shareholder group. Lag (the proportion of outside directors) is the proportion of outside directors on
the board in the previous year. Data are obtained from the Taiwan Economics Journal database. p-values are
given in parentheses, ***, **, * represent significance at the 1, 5, and 10% level, respectively.
directors, thus bank prior performance is negatively
related to the proportion of outside directors.
The controlling shareholders’ ownership is both
negatively and significantly related to board independent,
but the coefficient on outside directors’ ownership is
significantly positive. The results can be explained by two
views. The negotiation hypothesis shows that the proportion
of outside directors decreases with CEOs’
influence and increases with constraints on CEOs’
influence. Because the controlling shareholders’ ownership
can measure their influence, and outsider directors’
ownership is used to proxy for constraint on control
shareholders’ influence, and thus our results are consistent
with the negotiation hypothesis. Another view is
based on the monitoring hypothesis. The monitoring
hypothesis proposes that the proportion of outside
directors optimally grows with benefit of monitoring, but
decline with the cost of monitoring. The higher controlling
shareholders’ ownership aligns the controlling shareholders’
incentive with stockholder, thus the benefit of
monitoring will decrease. Moreover, the higher outside
directors’ ownership will increase the outside directors’
incentive of exercising monitoring function, and decrease
the cost of monitoring. Thus, based on the monitoring
Ting 7629
hypothesis, the proportion of outside directors is negatively
related to the controlling shareholders’ ownership,
but positively related to the outside directors’ ownership.
However, the coefficient on controlling shareholders’
excess control right is insignificant, which is inconsistent
with the monitoring hypothesis. In summary, the negotiation
hypothesis can provide better explanations for the
determinants of board independent than the monitoring
hypothesis.
Including the lagged board size as the instrument variable
for board size, the results are showed on model (b) of
Table 3. We find that the significant coefficients on bank
age, bank prior performance, controlling shareholders’
ownership and outside directors’ ownership also remain
significant, the same with the results of model (a) in Table
3. The results provide stronger support for the negotiation
hypothesis. In Taiwan, most banks’ ownership is high
concentrated and the mechanism of investor protection is
weak. Shleifer and Vishny (1997) point out that “Large
investors may represent their own interests, which need
not coincide with the interests of other investors in the
firm, or with the interests of employees and managers.”
Because the controlling owner has enough power to
control the operations of a bank and the controlling owner

7630 Afr. J. Bus. Manage.
may structure board just for his own interests, banks do
not structure boards in an efficient response to their
operating environment. Thus, the empirical results show
that the proxies for the costs and benefits of monitoring
and advising, for example fee revenue ratio, market-tobook
ratio and free cash flow, all are insignificant
determinants of board size and structure. The results are
consistent with Yeh and Woidtke (2005) and Ting and
Liao (2010), they also find the controlling owner select a
board for his own interests.
Conclusion
Using data on banks of Taiwan, this paper examines the
determinants of board size and composition in an environment
where most banks have concentrated ownership
and investor protection is weak. The results show that
bank size and bank age are the key determinants of
banks’ board size. This is consistent with the scope of
operation hypothesis, which predict that complex banks
need larger board to monitor managers’ decision.
However, contrary to the finding of US unregulated firms
with disperse ownership, we find little evidence that board
size is related to the costs and benefits of monitoring.
Moreover, the proportion of outside directors is negatively
related to measures of the controlling shareholders’
influence – including bank past performance and the
controlling shareholders’ ownership, and positively
related to constraints on such influence, including the
ownership of outside directors. The results provide some
support for the negotiation hypothesis, consistent with the
finding of US unregulated firms with disperse ownership.
The negotiation hypothesis proposes that corporate
boards reflect the outcome of a negotiation between the
CEO and outside board members. Our empirical results
show that board composition is also the outcome of a
negotiation between the controlling shareholders and outside
directors in an environment where most banks have
concentrated ownership and investor protection is weak.
When the controlling shareholders can exercise more
influence, they select more affiliated directors, but board
independence will increase if constraints on the
controlling shareholders’ influence. Nevertheless, our
empirical results are not consistent with the monitoring
hypothesis that firms choose board composition based on
the costs and benefits of monitoring and advising.
Overall, these results indicate that board size and
composition reflect the bank-specific and ownership
characteristics, but are not sensitive to the benefits and
costs of monitoring and advising. Thus, contrary to the
finding of US unregulated firms with disperse ownership,
our results are not supportive of the view that banks
select board size and composition in an efficient
response to the bank’s operating environment. Because
most banks have controlling owners in Taiwan and the
controlling owners may structure board just in ways that
are advantageous to themselves, banks do not change
board size and composition to respond to the benefits
and costs of monitoring and advising. Moreover, the
board structure is just the outcome of a negotiation between
the controlling owner and outside board members,
and the bargaining power depends on the ownership of
the controlling shareholders and outside directors.
However, for firms with disperse ownership, maximizing
shareholder wealth is their main objective. Hence, the
empirical results of US unregulated firms with disperse
ownership show that firms’ boards are indeed efficient
responses to the firms’ operating environment. The empirical
implication is that regulatory mandates for bank may
be beneficial to investors in an environment where most
banks have concentrated ownership and investor protecttion
is weak. However, the mandates must vary with bank
operating characteristics and uniform requirements could
be not appropriate.
One of the limitations of this study is the possible imperfect
proxies for the costs and benefits of monitoring and
advising. For example, market-to-book ratio and standard
deviation of stock returns may not be good proxies for
information asymmetry. Therefore, by using imperfect
proxies, the conclusions from the empirical results may
be misleading. Unfortunately, existing theory and empirical
research on the determinants of board structure are
not sufficiently complete to help taking into account the
proper proxies. The findings of the study suggest possible
avenues for future research. For example, we can
replicate the present study on unregulated firms from
Taiwan. It may aid us to understand whether the conclusions
which differ from US are caused by the ownership
structure difference between US and Taiwan, or, the
industry difference induces the different conclusions. A
multi-country study that incorporates a larger sample of
firms from across different countries also can provide
more powerful tests of the determinants of board
structure.
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African Journal of Business Management Vol. 5(17), pp. 7632-7641, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.858
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Monetary union for the development process in the
East African community: Business cycle
synchronization approach
Kamaludin Ahmed Sheikh 1 , Mohammad Nurul Azam 1 , Talukder Golam Rabby 1 , Gazi
Mahabubul Alam 2 *, and Issa Khan 3
1 Faculty of Economics and Administration, University of Malaya, 50603 Kuala Lumpur, Malaysia.
2 Institute of Education, International Islamic University, Malaysia, Kuala Lumpur, Malaysia.
3 Academy of Islamic Studies, University of Malaya, 50603 Kuala Lumpur, Malaysia.
Accepted 13 April, 2011
This paper empirically examines the suitability of monetary union in East African community members
namely, Burundi, Kenya, Rwanda, Tanzania and Uganda, on the basis of business cycle
synchronization. This research considers annual GDP (gross domestic product) data from IMF
(international monetary fund) for the period of 1980 to 2010. In order to extract the business cycles and
trends, the study uses HP (Hodrick-Prescott) and the BP (band pass) filters. After identifying the cycles
and trends of the business cycle, the study considers cross country correlation analysis and analysis
of variance technique to examine whether EAC (East African community) countries are characterized by
synchronized business cycles or not. The results show that four EAC countries (Burundi, Kenya,
Tanzania and Uganda) among five countries are having similar pattern of business cycle and trend from
the last ten years of the formation of the EAC. The research concludes that these countries, except
Rwanda, do not differ significantly in transitory or cycle components but do differ in permanent
components especially in growth trend.
Key words: Business cycle synchronization, optimum currency area, East African community, monetary union,
development.
INTRODUCTION
The criteria of collectivism and unity have always been
considered as one of the strength in the discourses of
development that either considered economic or social
development (Alam, 2009a; Alam et al., 2009b). Independence
of a state always does not necessarily reflect a
division or dispersion of the community. Therefore,
regional union for the development and cooperation has
played a critical role towards development, while many
regions are struggling to be independent, thinking a
microeconomic perspective (Bénassy-Quéré and Coupet,
*Corresponding author. E-mail: gazi.alam@um.edu.my,
gazimalamb@yahoo.com. Tel: + 603-6196533 . Fax: + 603-
-61964851
2005) when many regions, having same culture, attitude
and norms are trying to be in consensus of forming
monetary union in order to be a macro voice of development
(Cooper, 2000; Jabko, 1999). Considering these
views, European Union (EU) was formed, increase success
of EU shows a way that testify how unity, harmony,
team work and team spirit can play a rigorous role for the
development.
Later, EU realized the need of a common currency to
become a dominant voice in world economy. Due to
bilateral, multilateral or international business, currency
exchange and its impact towards the business have been
huge (Baldwin and Di Nino, 2006). Moreover, one
currency used by many people, strengthen business
community and reduces the unnecessary currency
inflation and some other negative impacts. Moreover, it

provides a wider response and swift service for the
citizens to work faster in the business and daily life at the
age of globalization.
Keeping this view, EU started a monetary union using
same currency which is Euro. While the education, culture,
tradition and other social gaps amongst different
countries of EU are very narrow, it still took a long
journey to adopt a common currency. Moreover, since a
national currency is in the market, a slow and steady
progression of a common monetary union currency will
progress rationally and logically ensuring its sustainability
(Jabko, 1999; Eichengreen et al., 1990).
Africa is a region which has a number of similarity and
disparity with EU. However, it has its own merits and
demerits in many ways. Thus, a direct currency union
model (monetary union model) borrowed from other
context may not work in Africa due to its political, social,
educational, ideological, cultural and other understanding
gaps (Masson and Pattillo, 2004). Considering these
point of views, the aim of this paper is to assess the
economic feasibility of the proposed Monetary Union in
the EAC by examining the synchronization of business
cycles (dynamics of trends and cycles).
In order to execute this argument, the research questions
are outlined and answered further. In the process of
finding the answers, a major research method of
business cycle synchronization has been adopted that
will be discussed. Conclusion and suggestion of this
paper will be followed after the discussion supplemented
through secondary literature.
Research questions
The focus of this study is to understand the linkage
between common monetary policy and its resulting developmental
output. For this purpose, the study considers
the five East African countries as a case. In this front,
given the importance on the argument discussed earlier,
the research questions of this study are as follows:
i. How do the business cycles and trends of EAC
countries behave?
ii. How significant are the mean differences between
business cycles of EAC member countries?
iii. What are the shares and trends of trade between the
EAC countries?
iv. How can the proposed monetary union benefit from
the development of the east African community?
Though the independent monetary functions are not
capable enough to bring development in EAC countries,
this study therefore purposively exposes the importance
and contribution of common monetary policy adaptation
which may persuade that development. In this context,
answering the aforementioned questions will help to
understand whether a monetary union for the EAC
countries can be feasible or not.
LITERATURE REVIEW
Sheikh et al. 7633
Discussions on the following sub-topics: the role of
monetary functions in business, the role of monetary
functions for human being, the preface of introducing
monetary union, the advantages of monetary union, and
the disadvantages of monetary union are presented here.
Before exploring the sub-topics mentioned earlier, let us
discuss the concept of economic development.
Concept of economic development
Primarily, the economists (for example, Bernstein, Shultz,
Psacharapolous) view development in terms of the
nation’s relative prosperity, which is measured by the
gross national product (GNP), as highlighted by Alam et
al. (2009b) and Rabby et al. (2011). However, there is a
concern that greater income does not guarantee greater
buying power, more choices or better quality of life. This
is partly due to globalization and free economic trade that
made it challenging to maintain a reasonable inflation
rate. An interesting point is noted by Alam (2009a, b) who
states that if there is an exceptionally high gap existing
amongst the value of GNI (gross national income) and
GNP and GDP (gross national product and gross domestic
income), national development will not sustain or
would halt the development ultimately for two reasons:
i. If the value of GNI is enormously lower than the value
of GNP and GDP, people of the producing nations cannot
survive since a higher cost has already been paid off for
the GDP and GNP.
ii. If the value of GNI is extremely higher than the value of
GDP and GNP, the competitive nation will take the advantages
supplying the desired products to the international
community once they find out that a specific producing
country sells a particular product at a higher cost
to the other nations. This is easer to find out as the recent
explosion of IT and ICT become available to all.
A further point was raised if a number of nation increases
their GDP, GNP and GNI with the help of importing raw
materials and other inevitable supports needed in the 21 st
century (such as, internet, global transit and protocol)
from one specific region or nation, it would not help them
greatly as it will provide compound escalating benefits to
that specific region or nation. Therefore, on balance,
those countries will face gruelling challenges on bilateral
and multilateral business competition due to shortage
and low value of foreign currency. This situation would be
graver with more globalisation and internationalization.
More importantly, growth in economy without development
in politics and society may lead to corruption
caused by lack of transparency, maturity of the society
and participation of the individuals within a nation (Alam,
2009b). Development in politics includes separation of
power among the executive, legislature, and judiciary,

7634 Afr. J. Bus. Manage.
judiciaries’ transparency, free and fair election, etc.
Development in society includes maturity of the society
wanting transparency, fairness, security, knowledge,
freedom of choice and participation in the decision making
for the society. The concerns from all these aspects
have led to the emergence of another school of thought,
that is, the sociologists’ perspective.
The role of monetary functions in business
Monetary policy consists of the decisions and actions
taken by the government to affect the supply of money
and credit within a jurisdiction. Monetary policy has two
basic goals: promoting the highest sustainable levels of
economic output and employment, and promoting stable
prices. Monetary policy is also used as a means by which
government may respond to shocks to its economy. A
stable money supply plays a crucial role in economic
growth. The monetary authority may expand or contract
the money supply in order to accommodate shocks. For
example, if the supply is too large, inflation results. And if
the supply is insufficient, it makes it more difficult for
consumers and firms to obtain credit to finance large
purchases and business expansions. Whether or not
monetary policy has real effects on the domestic
economy has been a matter of theoretical and empirical
debate among economists (Martin, 1999).
The role of monetary functions for human being
It is argued that monetary policy is a powerful tool for
affecting wealth accumulation, and has real effects on the
economic system. Monetary policy is important for economic
growth, as well as for domestic stabilization policy
(Martin, 1999). Monetary policy can facilitate growth by
pursuing policies conductive to increase production and
real wealth; thus, this economic growth is associated with
a more rapid reduction in poverty (Dollar and Kraay,
2002). Monetary policy can be used as a tool for stabilizing
the financial system and unemployment rate; this
would decrease the burden of debt and the poverty level
(Martin, 1999).
The preface of introducing monetary union
Monetary union is the 5 th stage of integration, thus, a
region should have to fulfil the preceding stages of integration
(African Development Bank, 2010). The following
are the steps of regional integration arranged chronologically:
preferential trade area, free trade area, customs
union, common market, then monetary union and lastly
political union are the ultimate stage of integration.
Feasibility of monetary union is discussed at length in the
literature of optimum currency theory (Mundell, 1961;
McKinnon, 1963; Kenen, 1969; Tavlas, 1993). The
criteria are factor mobility (Mundell, 1961), trade integration
(McKinnon, 1963), and a similar regional production
pattern (Kenen, 1969). Some of the important conditions
that would make possible an OCA (optimum currency
area) are (i) a large market size and a high degree of
openness in trade, (ii) a high degree of intra-zone trade,
and (iii) similarities in business cycles and shocks
(Kwack, 2004).
The advantages of monetary union
The adoption of a common currency leads to an increase
in the number of economic agents using the currency as
a medium of exchange. This eliminates the need for
exchanging one currency to the other currencies in the
union. Consequently, it reduces transaction costs and
increases the transparency of prices (Kwack, 2004). This
benefits consumers and raises the volume of trade in
goods and services. Empirical studies confirm that a
common currency zone saves transaction costs and
promotes intra-zone trade. For example, the Commission
of the European Community estimated savings of about
0.5% of GDP in exchange transaction costs for the Community
as a whole (Artis, 1991). Glick and Rose (2002)
states ‘‘a pair of countries that starts to use a common
currency experiences a near doubling in bilateral trade.’’
On the other hand, it reduces seigniorage revenues
created from issuing the currency by the central bank of a
member country. The reduction in these revenues is
usually expected to be smaller than the benefits
generated from its trade creation effects (Kwack, 2004).
The disadvantages of monetary union
Some of the costs faced by the countries members of a
currency union are: (i) loss of sovereignty of monetary
policy, which might be a problem when fighting inflation
or recession; (ii) loss of control over the foreign exchange
value of a national currency, which will eliminate the
opportunity to smoothly adjust domestic policies in case
of crises (Martin, 1999).
Exchange rates may be useful instrument for countries
to affect their balance on current account (Destler and
Henning, 1989); (iii) adjustment problems for the average
citizen to the new the currency (coins and notes) with
different denominations as compared to the old one; (iv)
loss of fiscal policy, fiscal policy may be useful for collecting
revenue, distribute income and finance government
purchases; these policies will encounter limitations if a
monetary constitution restricts fiscal policy (Martin, 1999).
RESEARCH DESIGN
Figure 1 provides the framework of analyzing the feasibility of

Correlation
“Customary
Approach”
Synchronized
Not-Synchronized
FEASIBILITY OF
MONETARY UNION
Business Cycle Analysis
(HP and BP Filtering)
Yes
No
Figure 1. Analytical framework of the study.
monetary union in EAC. In order to extract the business cycles, the
study uses HP and BP filters. After extracting the trends and cycles,
the study uses two alternative approaches of analyzing the feasibility
of monetary union in a region. The first approach is ‘simple
correlation analysis’ and the second approach is one-way ANOVA
(analysis of variance) analysis. If the cycles and trends between
countries are positively correlated, the less likely they are to lose by
forming a currency area. Also, for the ANOVA analysis, if the cycles
between countries are homogenous, then countries in that region
can form monetary union.
Methodological discourse
Probable methods
There are several key methodologies for testing the feasibility of
monetary union. Some of the popular methods are as follows: (i)
analysis of economic shocks using SVAR (structural vector autoregression),
(ii) analysis of synchronization of business cycle, (iii) G-
PPP (generalized purchasing power parity) analysis, (iv) trade
effects (gravity model), and (v) DSGE (dynamic stochastic general
equilibrium modelling), etc.
Most of these methodologies have not remained without criticism,
for example SVAR decomposition of the Blanchard and Quah technique
does not necessarily identify purely stochastic disturbances
(Zhang, 2002). Limitation for the generalized-PPP model is that
movements in the macroeconomic variables of G-PPP do not distinguish
disturbances from responses (Buigut, 2005). For the gravity
model, gravity model is used to predict the trade effects of monetary
and customs union, but theoretical justifications of the model are
the subject of some dispute (Adams, 2005). Dynamic stochastic
general equilibrium modelling (DSGE) appears to be a relatively
appealing methodology and have been applied on quite a wide
basis. However, DSGE analysis is a highly complicated process,
ANOVA
“New Way
Approach”
Homogeneity
Heterogeneity
Sheikh et al. 7635
Yes
No
reliant on detailed economic data which makes it currently unsuitable
for its application to Africa where such data is scarce. Thus,
DSGE model analysis of monetary union in Africa is beyond capacity
of this paper. Thus, business cycle synchronization analysis
had become the widely used method of analysing monetary unions,
because of its easiness to get the data it requires.
Adaptation of current method
Some of the aforementioned techniques of analyzing monetary
union have drawbacks and do not provide clear conclusion of whether
a successful monetary union is feasible or not. This method of
business cycle synchronization analysis is widely used in the OCA
literature as a tool to determine whether future members of a
monetary union face correlated trend and cyclical components of
their macroeconomic indicators such as GDP.
OCA theory, which is a tool for analyzing viability of monetary
union in a region, argues that the costs of using a common
currency depend on how symmetrical the economies are in terms of
business cycles (Alturki, 2007). If the cyclical fluctuations of two
economies present opposite phases, then the cost of their
participation would be much higher in comparison to the cost of
participation; but, if both economies experience the same phase the
cost of their participation is outweighed by the benefits induced by
the common currency (Filis et al., 2010).
Significance of current method
The theory of OCA had stressed the significance of business cycle
synchronization analysis for the future members in a monetary
union; because it gives a clear understanding if future members of
a currency union would be able to make a monetary union or not.
This method assesses the similarity of a broad range of OCA

7636 Afr. J. Bus. Manage.
Table 1. Correlation matrix of EAC countries permanent component (1980 to 2010).
Burundi Kenya Rwanda Tanzania Uganda
Burundi 1.000000
Kenya 0.834070 1.000000
Rwanda 0.656778 0.817003 1.000000
Tanzania 0.772366 0.985161 0.890077 1.000000
Uganda 0.733642 0.982154 0.867935 0.997003 1.000000
properties within a group of countries; it finds out subsets of
countries that share similar characteristics and may therefore be
more suitable for monetary union (Alturkey, 2007). This method can
assess the correlation of cycles and trends between the countries
and regions (Fidrmuc and Korhonen, 2006; Shin and Wang, 2003).
This method is also instrumental to understanding the effects of
international trade on the countries which intend to form a single
currency area (Gruben et al., 2002; Kose et al., 2003). Unlike other
methods of analyzing monetary unions, this method can
accommodate the data set which is easy to get and easy to
analyze, and this is why, business cycle synchronization analysis is
a widely used method of studying monetary unions.
Constrains of adopting the current method
Instead of using gross domestic product, it would be better to use
industrial production index (IPI) and unemployment rate which are
common business cycle indicators. As Artis et al. (2004) and
Camacho et al. (2006) note, industrial production indexes display
more cyclical sensitivity than GDP estimates and hence may be
more informative for monitoring business cycle fluctuations. But the
problem is that data availability of industrial production indexes for
the East African Countries is not possible.
Constrains of its influence to findings
Although business cycle synchronization is necessary, it is not
sufficient for a successful monetary union. Other factors such as
trade, financial and political may be just as important. The main
constrain on the findings are the length and frequency of the data;
bigger sample size and frequent data series such as quarterly data
may be more desirable to produce a better outcome. Annual data
may not pick up some short run interaction that occurs within a
year.
RESULTS
Synchronization of business cycles is a precondition for
forming monetary union in a region. Countries with highly
correlated business cycles tend to have higher propensity
to join in a monetary union. Increased intra-regional trade
in currency area would increase the synchronization of
the business cycles and shocks.
Dynamics of permanent and transitory components
in EAC
Table 1 shows simple correlation matrix of EAC
countries’ permanent component. The idea is, the higher
the synchronization of business cycles correlation coefficient,
the greater the degree of synchronization. Table 1
shows very high correlation coefficients of the permanent
components of EAC countries’ growth rates. With only
one exception, the correlation coefficients range from
73% (Burundi-Uganda) to 99% (Tanzania-Uganda). This
evidence supports the conclusion that EAC countries
experience similar patterns of growth over that period
considered (1980 to 2010).
To investigate whether the degree of business cycle
synchronization has increased after the EAC establishment
in 2000, we consider data from the years 2001 to
2010 (Table 2). During this period, the correlation coefficient
of the permanent component is higher than the full
data set of 1980 to 2010. Thus, we can say, in the last
decade (2001 to 2010), EAC countries had experienced
similar pattern of growth rate.
Table 3 shows correlation coefficients of the cycle components
of EAC countries’ growth rates. The table shows
more positive correlation coefficients of the EAC temporary
components. Temporary components of Rwanda
and Burundi are negatively correlated with Ugandan temporary
component. The rest of the correlation coefficients
show positive relationship among their temporary
components. To take a closer look at the results of
sample period of post EAC formation 1 (2001 to2010), we
consider data from the years 2001 to 2010. As we see
from Table 4, correlation coefficient of EAC temporary
(cycle)component had improved since it has higher
correlation coefficient than the full data set. As Table 4
shows, correlation coefficient of the GDP temporary component
in this sub sample ranges from 0.41% (Kenya-
Burundi) to 0.70% (Uganda-Burundi). But for the sample
period of 2001 to 2010, Rwandan temporary component
of GDP got negative correlation with all other EAC countries;
this can be interpreted as that Rwandan temporary
shocks are dissimilar with the rest of the region. Thus, the
costs of Rwandan participation in EAC monetary union
would be higher than the benefits of joining EAC currency
union.
On the other hand, we had also applied BP filter of the
Baxter and King to enhance the analysis of EAC
1 The East African Community was established in 2000, and since then they
had made some progress toward policy harmonization, thus, we need to test
whether they had made improvement in Business Cycle Synchronization (BCS)
after that period.

Table 2. Correlation matrix of EAC countries permanent component (2001 to 2010).
Burundi Kenya Rwanda Tanzania Uganda
Burundi 1.000000
Kenya 0.996013 1.000000
Rwanda 0.992091 0.999330 1.000000
Tanzania 0.994364 0.999853 0.999807 1.000000
Uganda 0.993321 0.999639 0.999939 0.999951 1.000000
Table 3. Correlation matrix of EAC countries cycles or irregular component (1980 to 2010).
Burundi Kenya Rwanda Tanzania Uganda
Burundi 1.000000
Kenya 0.325523 1.000000
Rwanda 0.308366 0.164188 1.000000
Tanzania 0.555251 0.711358 0.196737 1.000000
Uganda -0.461164 0.173362 -0.349380 -0.057127 1.000000
Table 4. Correlation matrix of EAC countries cycles or irregular component (2001 to 2010).
Burundi Kenya Rwanda Tanzania Uganda
Burundi 1.000000
Kenya 0.416211 1.000000
Rwanda -0.349135 -0.342805 1.000000
Tanzania 0.499987 0.534468 -0.307762 1.000000
Uganda 0.708651 0.546768 -0.040462 0.440760 1.000000
business cycles; and we compared them with the cycles
identified by the HP filter. We found that both the two
filters (HP and BP) show some similarities in the cycle
and trend components of GDP; thus, to conserve space
we limit our result only to the Hodrick Prescott results; the
band pass results would be available upon request.
Test of permanent and transitory components in EAC
As suggested by Kenen (1969), an alternative method of
analyzing synchronization of business cycle is the
analysis of variance test. It will check the equality of
means and variance of the permanent and transitory
components between EAC countries. If results show no
significant difference in means of the permanent and
transitory components, then EAC countries are having
similar business cycles and they can form monetary
union.
Table 5 gives the summary of Levene’s test of the EAC
business cycle of the period 2005 to 2010 2 . As the table
shows, the variances of both permanent and transitory
components of the GDP of the five east African countries
are identical. Thus, we can proceed to next step of the
2 This period of 2005 to 2010 is the period after EAC had made Custom Union
and Common Market.
Sheikh et al. 7637
analysis of variance analysis. Tables 6 and 7 provide the
summary results of both the transitory component and
the permanent component. Table 6, shows that the transitory
component (cycle) of the EAC countries means are
similar; in other words, EAC countries do not differ in their
temporary component or cycles in this given sample
period, thus, we can say EAC countries are having
synchronized business cycles.
Table 7 presents the test of whether the permanent
(trend) components of the EAC countries means are
same or not; it shows that EAC member countries are
having dissimilar mean as shown by significant p-value
(0.000). Thus, we can conclude that EAC countries differ
significantly in their growth path, as the analysis of
variance test reveals.
Intra-EAC trade intensity
One of the main benefits generated from the monetary
union is the reduction in transaction costs; the larger is
the intra-regional trade among EAC members, the
smaller the costs and larger the benefits of forming a
currency union will be, ceteris paribus (AlKharofey and
Alreshan, 2009). Table 8 shows that the intra-regional
exports of EAC are not so big; as East African region
absorbs 29% of Uganda’s exports, with Kenya being the

7638 Afr. J. Bus. Manage.
Table 5. Test of homogeneity of variances in business cycle of EAC 2005 to 2010.
Variable
df
Levene statistic
Value p-value
Transitory components (cycle) (4, 25) 1.578 0.211
Permanent components (trend) (4, 25) 1.936 0.136
Table 6. ANOVA analysis for transitory components (cycle) in EAC 2005 to 2010.
Transitory components (cycle)
EAC_cycle SS df Chi-square
Between groups 0.000345 4 8.62E-05
Within groups 0.007006 25 0.00028
Total 0.007351 29 0.00025
ANOVA F-statistic 0.007351
Sig. value 0.870
Table 7. ANOVA analysis for permanent components (trend) in EAC 2005 to 2010.
Permanent components (trend)
EAC_cycle SS df Chi-square
Between groups 54.52625 4 13.63156
Within groups 0.322784 25 0.012911
Total 54.84904 29 1.891346
ANOVA F-statistic 1055.78
Sig. value 0.000
Table 8. Intra-EAC exports as share of total exports, 2009.
Burundi (%) Kenya (%) Rwanda (%) Tanzania (%) Uganda (%)
Burundi -- 0.08 0.19 0.00 0.09
Kenya 1.53 -- 9.29 25.20 25.87
Rwanda 0.35 7.06 -- 0.06 0.39
Tanzania 0.85 2.57 2.71 -- 2.81
Uganda 2.53 9.13 7.62 1.69 --
EAC 5 19 20 27 29
Source: Direction of trade statistics (DOTS) of IMF, 2010.
single most important destination for its goods. Tanzania
is the second largest exporter within the region; 27% of
the Tanzanian exports went to EAC member countries;
Rwanda and Kenya are the third and fourth exporting 20
and 19% respectively.
On the other hand, Table 9 gives the share of intra-
EAC imports of the year 2009. As shown in the table,
Kenya is by far the largest importer within the region;
62% of the Kenyan imports are from the EAC countries
mainly from Uganda (26%) and Tanzania (25%). Also,
Uganda and Tanzania source a substantial portion of
their imports from East African Community, especially
from Kenya. Burundi imports are less dependent on the
EAC member countries.
As Table 10 shows, the share of intra-EAC trade to the
world trade is quite big, with a minimum of 7% to a
maximum of 38%. Rwanda shows high intra-regional
trade. Higher intra-trade indicates that potential gain from
trade and establishment of common currency is possible.
Endogeneity of OCA theory argues that highly intratraded
countries would become more integrated after
forming a monetary union despite being unsatisfied with

Table 9. Intra-EAC imports as share of total imports, 2009.
Sheikh et al. 7639
Burundi (%) Kenya (%) Rwanda (%) Tanzania (%) Uganda (%)
Burundi -- 1.54 0.16 0.85 1.75
Kenya 0.08 -- 7.08 2.58 9.16
Rwanda 0.31 9.33 -- 2.72 8.42
Tanzania 0.00 25.29 0.06 -- 1.69
Uganda 0.05 25.96 0.15 2.82 --
EAC 0.44 62.12 7.45 8.97 21.02
Source: Direction of trade statistics (DOTS) of IMF, 2010.
Table 10. Percentage of intra-EAC trade to world trade.
Year Burundi (%) Kenya (%) Rwanda (%) Tanzania (%) Uganda (%)
2000 15.03 11.16 26.00 8.15 19.25
2001 15.49 12.45 16.63 6.48 17.51
2002 25.36 12.56 32.50 5.84 26.26
2003 27.70 12.11 39.28 8.16 26.71
2004 26.71 11.73 33.15 7.62 18.84
2005 17.42 10.18 27.13 7.54 25.63
2006 13.59 8.94 27.44 7.38 16.78
2007 22.25 9.09 28.73 7.59 16.05
2008 20.01 9.25 38.37 7.11 13.57
2009 17.21 8.85 34.49 7.00 10.40
Source: Direction of trade statistics (DOTS) of IMF, 2010.
some of the OCA criteria.
Conclusion
This paper uses annual real GDP data of EAC member
countries, namely, Burundi, Kenya, Rwanda, Tanzania
and Uganda. Test of unit roots shows that data is stationary.
The study of the business cycle synchronization
using Hedrick-Prescott filter and the band pass filter gives
new insights on the subject. Using correlation coefficient
and analysis of variance procedure, it shows very high
correlation coefficients of the permanent components of
EAC countries’ growth rates with only one exception
between Burundi-Uganda, supporting evidence that EAC
countries experience similar patterns of growth over that
period considered.
Although our framework differs from the standard
approach found in the literature, some of the results are in
line with previous research. Bilateral trade and EAC
membership have a positive effect. We think that the
purposed framework unveils the short and medium term
effects. On the other hand, share of intra-EAC imports
shows that Kenya is by far the largest importer within the
region; Uganda and Tanzania source a substantial portion
of their imports from East African Community, especially
from Kenya. Burundi imports are less dependent on the
EAC member countries. This gives us a different perspective
of the financial mechanism. We confirm the finding
that trade intensity affects business cycle synchronization.
BP filter enhance the analysis of EAC business cycles.
After comparing them with the cycles identified by the HP
filter we found that both filters show some similarities in
the cycle and trend components of GDP. Test of analysis
of variance show no significant difference of the permanent
and transitory components, then EAC countries
are having similar business cycles and they can form
monetary union. Share of intra-EAC trade to the world
trade is quite big, Rwanda shows high intra-regional
trade. Higher intra-trade indicates potential gain from
trade and establishment of common currency is possible.
Endogeneity of OCA theory argues that highly intratraded
countries would become more integrated after
forming a monetary union despite unsatisfied with some
of the OCA criteria
One of the main questions in the empirical analysis of
the business is the synchronization of business cycles;
our findings confirm that both business cycles are
dominated by the same frequencies. However, Rwandan
component of GDP got negative correlation with all other
EAC countries; this can be interpreted as those Rwandan
temporary shocks are dissimilar with the rest of the
region. Thus, the costs of Rwandan participation in EAC
monetary union would be higher than the benefits of

7640 Afr. J. Bus. Manage.
joining EAC currency union.
Finally, our results suggest that the effect of trade on
business cycle synchronization is robust for outlying
observations, but the relationship between the correlation
of business cycles and bilateral trade is not robust. Our
results suggest that common monetary policy may not be
equally good for all countries in the union, may have lost
force due to the economic and monetary integration
process.
RECOMMENDATIONS
Compared to EU, EAC have lower level of economic
integration with respect to trade, financial and other factor
flows. There are greater disparities in context of monetary
growth rates, budget deficits, exchange-rate regimes,
inflation rates, and balance of payments deficits EAC
should implement a monetary policy harmonisation
programs that will lead to greater convergence.
EAC countries are small, relative to EU in terms of
GDP, trade flows, and money supply there should be a
common currency to avoid hassle of transaction time and
cost for intermediaries such as banks (or their informal
equivalents).
We emphasize EAC countries should have a common
currency that will facilitate trade and investment among
the countries and will increases income growth by
reducing transaction costs in cross-border business, also
will remove volatility in exchange rates. Lower transaction
costs (no market segmentation or no currency conversion
costs) and less difficulty of completing international transactions
within the union, it would create and accumulate
wealth. It will provide opportunity for inflation-prone
countries to enjoy lower inflation strategies.
There will be adjustment problems for the average
citizen to the new the currency (coins and notes) with
different denominations as compared to the old one. In
this situation, changes should be in phases.
Businesses would no longer have to pay hedging costs
which they do today in order to insure themselves against
the threat of currency fluctuations. Businesses, involved
in commercial transactions in different member countries,
would no longer have to face administrative costs of
accounting for the changes of currencies, plus the time
involved.
EAC countries are not significantly different in economic
performances and they do not have significant cultural
difference which would be an added advantage. Swahili
and English are widely spoken in that region (for example
Kenya, Uganda and Tanzania first national language is
Swahili; for Burundi and Rwanda, it is second).
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African Journal of Business Management Vol. 5(17), pp. 7642-7650, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.899
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Open business models: A case study of
system-on-a-chip (SoC) design foundry in the integrated
circuit (IC) industry
Po-Young Chu and Wan-Chen Chen*
Department of Management Science, National Chiao Tung University, Hsinchu, R.O.C. Taiwan,
Accepted 23 June, 2011
In the global IC industry, business models have evolved into design foundry models and manufacturing
foundry service models over the past twenty years. The concept of system-on-a-chip (SoC) refers to
integrating all components of a computer or other electronic system in a single integrated circuit (IC).
Due to the increasing complexities of SoC devices, it is impossible for one IC design house to have the
state-of-the-art expertise required to make all the hardware and software components required for an
SoC. Based on SoC needs for intellectual property (IP) reuse and design reuse, this study analyzes a
new open business model, called design foundry. Design houses must use a design foundry, an
innovation intermediary, to combine their internally generated IPs with IPs acquired externally. This
paper uses the SoC design foundry as a case to examine the evolution, SoC problems, and the core
value of innovation intermediaries in the whole IC industry. Further, it demonstrates how design
foundries create ecological benefits by teaming up with suppliers and customers in the IC industry. This
research is the first known study to explore the emerging service gaps, value creation, and value capture
processes created by an SoC design foundry.
Key words: Open business models, open innovation, design foundry, innovation intermediary, system-on-a-chip
(SoC), integrated circuit (IC) Industry.
INTRODUCTION
Embracing the trend of globalization, changes in
make-or-break rules are accelerating in the global market.
The concept of innovation is also undergoing
revolutionary modifications. Enterprises that concentrate
on their own strengths to create innovations are finding it
much more difficult to be successful, and the division of
innovative activities has become the key to an enterprise’s
future success. Adopting an open business model is
therefore a critical strategy for developing win-win
opportunities.
Previous research have emphasized on the develop-
ment strategy (Chang and Hsu, 1998; Chu et al., 2005),
collaboration strategy (Ku et al., 2007), the valuation of
*Corresponding author. E-mail: woanjenchen.tw@gmail.com,
woanjenchen.ms94g@nctu.edu.tw
intangible assets (Chu et al., 2008) and firm’s capability
on performance (Sher and Yang, 2003) for an IC
company. However, there have been few studies
available concerning the IC firm’s business model and
emerging service gaps of the IC industry. This paper is to
fill this gap by analyzing a new open business model,
called system-on-a-chip (SoC) design foundry. Especially,
this study also examines the processes of value creation
and value capture that created by an SoC design foundry.
Open business models integrate value chain activities
into various products or services. Open business models
have emerged as the new key to survival, transcending
geographical boundaries, accelerating the speed of
product life cycles, and resolving the lack of resources.
Firms that adopt the classical closed business model are
responsible for the product concept, product design,
product manufacturing, product marketing, and post-sale
services. However, firms with open business models only

participate in the highest degree of competitiveness and
earn the maximum company’s profit. Joint efforts are also
made to work with active partners to complete the product
or service. Through the division of work and integration at
the global level, consumers will be able to gain the
maximum benefits, while the most competitive firms in
each section of the value chain also benefit from the
dramatic increase in their economies of scale and
increased profit.
Many successful multinational corporations have
adopted open innovation and open business models,
including IBM, P and G, Apple, Intel, and a number of
companies that have been frequently mentioned in
relevant literatures (Chesbrough, 2006; Dodgson et al.,
2006). For example, in the context of the semiconductor
research and development (R and D), IBM has revised
the prior unilateral participation model by inviting Sony,
AMD, and several other companies to jointly raise more
than one billion US dollars for capital. IBM also recruited
hundreds of specialty research personnel to develop the
next-generation IC chip. This development not only
averted a tremendous increase in IBM’s research budget,
but also achieved better-than-expected collaborative
results.
A design foundry is a new business model in the IC
industry. The design foundry business model not only
provides the services of IP authorization and IC design,
but also offers turnkey solutions. Following Moore's Law,
the pace of semiconductor development is so fast that
most IC design companies can hardly catch up. Therefore,
reusable IC design, reusable IP configurability, and
programmability have evolved into an important trend in
the IC industry. As an innovation intermediary, a design
foundry integrates various IPs from different companies,
including itself, to create ecological benefits by teaming up
with suppliers and buyers in the IC industry.
In open business models, key supplier and customers
become business partners, entering into relationships in
which both risks and rewards are shared. A design
foundry is able to enhance the competitiveness of all of
the firms in it cluster against larger competitors, who do
everything their own. This study introduces successful
open innovation experiences and a case study of SoC
design foundry in the IC industry.
LITERATURE REVIEW
The concept of “Open Innovation” is defined as an
enterprise breaking through its traditional organizational
boundaries by extracting innovative ideas, knowledge,
and resources from the external environment and sharing
unused internal knowledge and innovations with the
outside world. This new division of labor drives the
organizational model of innovation. To tap into this new
division of labor, companies must adopt an open business
model. However, in searching and drafting contracts
Chu and Chen 7643
among collaborative partners, many companies
encounter the problems of uncertainty and transaction
frequency. Generally, this refers to the problems of
transaction costs. For these reasons, this section briefly
reviews the literature on transaction costs, classic closed
innovation models, open business models, and innovation
intermediaries.
Transaction costs and intermediaries
The concept of “Transaction Costs” was originally
presented in the article “The Nature of Manufacturers”
written by Coase (1937). Williamson (1975) further
elaborated on the concept by dividing product costs into
production costs and transaction costs. The sources of
transaction costs include information search costs,
contract costs, supervision costs, contract enforcement
costs, etc (Casson, 1982; Dyer and Singh, 1998).
Consider the example of information search costs. While
current international trade barriers have been gradually
reduced, it is still difficult for manufacturers to search and
select potential trade partners. Therefore, scholars
believe that cross-border trading often has the
characteristics of information asymmetry. As a result,
since the intermediary has a better understanding of both
the buying and selling part of the business, the transaction
costs of trading will be lower if a business is traded
through an intermediary. Therefore, both buyers and
sellers conduct business through an intermediary to
reduce the transaction costs for both parties (Anderson
and Coughlan, 1987; Klein et al., 1990; Spulber, 1996).
Spulber (1996) defined the intermediary as an agent.
The work of an agent is to buy products from suppliers,
and sell those products to customers or clients to
complete the transaction between the buyer and the seller.
To put it simply, the tasks of an intermediary are mainly to
(1) seek buyers, and increase their desire to purchase; (2)
assist suppliers and buyers in creating a balance price
negotiation; (3) ensure the smooth execution of
transactions, including payments, product delivery,
inventory, etc. A typical intermediary functions like a stock
or insurance trader, seeking potential buyers and sellers
in the market, and negotiating deals for both parties. The
market for intermediaries is called “secondary innovation
markets.” Ashish Arora, the marketing executive of
Logitech Company, referred to the secondary innovation
market as a market in which new products are invented
but not yet sold. In secondary innovation markets, sellers
develop creativity and techniques, which buyers transform
into products and services that are brought to market for
customers.
In terms of the relationship between the intermediary,
the supplier, and the buyer, scholars believe that the
intermediary plays the role of a broker for buyers and
sellers (Casson, 1998; Hennart and Kryda, 1998). The
key to maintaining this intermediary relationship is to

7644 Afr. J. Bus. Manage.
control the information held by the buyers and the sellers.
The existence of an intermediary is due to the inability of
the buyer or the seller to efficiently collect the necessary
information. At the same time, such abilities cannot be
sold via market mechanisms (Casson, 1998). The task of
collecting information is accomplished by the intermediary.
Therefore, if the intermediary can understand the
existence of information asymmetry, and then provide
appropriate guarantees by transmitting related information
regarding the quality of products, they would be able to
strike a deal by raising the confidence of both buyers and
sellers (Tellis and Wernerfelt, 1987; Kirmani and Rao,
2000; Skaggs and Snow, 2004).
Classic close innovation
Economist Joseph Alois Schumpeter first proposed the
concept of innovation in 1912. Schumpeter regarded
innovation as: (1) introduction of a new product; (2)
adoption of a new production method; (3) development of
a new market; (4) acquisition of a new supply source for
raw materials or semi-finished products; or (5)
implementation of a new corporate organization format.
Innovation causes new-market disruptions by creating
new product or services or recombining production
elements. Generally speaking, innovation is associated
with corporate management secrets and operational
uniqueness, and that technical innovation and R and D
should therefore be conducted by the corporation
internally. However, recent studies indicate that if an
organization can collaborate with external partners in joint
innovations or systemic innovations, more optimal
innovation effects can be achieved (Chesbrough and
Teece, 2002; Chesbrough, 2003; Duysters et al., 1999;
Teece, 1996).
Innovative firms must be capable of understanding
external knowledge and how various technologies differ
from internal corporate knowledge. Firms must also have
the foresight to apply this external knowledge and
technologies (Amin and Cohendet, 2004). Firms can
utilize various methods to proceed with the research and
development collaborations, including technology
licensing, joint ventures, or strategic alliances (Contractor
and Lorange, 2004). The foundation of R and D
collaboration among firms can also change over time and
due to variations in corporate activities (Hagedoorn, 2002).
Because of increasing technological development costs
and shortened product life cycles in severely competitive
markets, companies must concentrate on their core
competencies and work with other corporate
organizations in the industry.
Open business models and innovation intermediaries
Open innovation is the application of external knowledge
or technology by a firm in the innovation process
(Chesbrough, 2003). Chesbrough pointed out that open
corporations must be able to utilize external technology or
knowledge in the same way that they would utilize internal
knowledge. Firms can acquire more advanced knowledge
or technology through this mechanism. From their
external strategic partners, corporations can identify
customer needs and create more competitive products.
The utilization of external strengths for facilitating
innovations or transferring intra-firm research to other
firms to conduct innovation activities is known as “Open
Innovation.” Open innovation is different from the classical
innovation model. While the creation of all technological
innovations is conducted by the firm in a classical
innovation model, open innovation does not require
developing products or services from the beginning to the
end. On the contrary, existing accomplishments from
outside of the firm are utilized, enabling the acceleration
of technology and product developments. This is how
open innovation differs from closed innovation
(Chesbrough, 2003).
In comprehensive management models, the successful
implementation of open innovation depends on collabo-
ration. As an extension of open innovation, open business
models underscore a concept of industry ecosystem.
Excluding the external R and D viewpoint of open
innovation, open business models emphasize the inter-
organizational activities. Open business models are a new
type of innovative work division model that encompass
value creation and value extraction. First, open business
models define the development of new products or
services from raw materials to the final consumer. These
activities create net value. Second, open business models
capture value by establishing a unique resource, asset, or
position within that series of activities that allows the firm
to enjoy a competitive advantage (Chesbrough, 2006;
Vanhaverbeke and Cloodt, 2006).
If firms can cooperate with external partners in joint
innovations or systemic innovations, they can achieve
superior innovation results (Chesbrough and Teece, 2002;
Maula et al., 2006; Teece, 1996). Through external
strategic partners, firms will better understand customer
needs, and create much more competitive products. Open
business models are a framework for transforming
innovations and technologies into economic
accomplishments, and help firms learn how to transform
technological ability into economic value.
Secondary innovation markets and innovation
intermediaries have arisen to manage the outside-in
dimension and inside-out dimensions of open innovation
(Chesbrough, 2006). As business models become more
open, there will be more opportunities to introduce
external ideas and technology into business models.
However, whenever a company acquires an external
technology, its legal status must be known. For this
reason, intermediate markets for technology profoundly
change the management of IP in the world of open

innovation. A secondary innovation market refers to a
market emerging after the creation of a new technology,
but before that technology has been sold. In this inter-
mediary market, ideas and technologies are developed by
sellers and sold to buyers, who take these ideas and
technologies and sell them to consumers. Innovation
intermediaries function as brokers or market makers, and
try to bring parties together to complete a transaction.
They help companies of many different sizes participate in
the emerging secondary markets for innovation and IP,
and craft more open business models. Their chief
capability is their ability to create, own, market, and sell IP
to other firms.
RESEARCH QUESTIONS AND METHOD
This research is based on a case study. The case study research
method can be adopted in exploratory, narrative or explanatory
research (Yin, 2008). Our research questions of “what” and “how,”
are suitable for case study research. In the global IC industry,
business models have evolved into design foundry models and
manufacturing foundry service models over the past twenty years.
The concept of SoC refers to integrating all components of a com-
puter or other electronic system in a single IC. Due to the increasing
complexities of SoC devices, it is impossible for one IC design
house to have the state-of-the-art expertise required to make all the
hardware and software components required for an SoC. Based on
SoC needs for IP reuse and IC design reuse, this study aims to
answer questions that include:
1. What are the SoC problems for an IC industry company when it
develops an IC chip, especially those of a smaller IC company?
2. How a design foundry solve the SoC problems for all other IC
companies and how it create the ecological benefits for whole IC
industry.
To address these questions, we develop a case study that analyses
the evolution of the IC industrial infrastructure and the SoC pro-
blems in the IC industry. In particular, we explain the value creation
and value capture processes created by an SoC design foundry
from an ecological perspective. Our approach was to deconstruct
the basic framework and the challenges of the IC industry. We then
explains how a design foundry plays a key role in forming new
industrial partnerships in the IC industry and creating ecological
benefits through open business models.
Historical background of the IC Industry
Different companies in the same industry frequently adopt different
strategies and exactly opposite business models. Integrated device
manufacturing (IDM) and fabless strategies are both prevalent in the
IC industry, and both can be well justified. Due to changes in the
industrial environment, companies select different strategies
depending on their comparative strengths. The reasons for adopting
different strategies and business models, such as vertical
integration or outsourcing, are highly dependent on the size of the
market, converging technical standards, and a sufficient number of
vendors.
In the development of the semiconductor industry, three stages
followed immediately after the invention of multiple integrated
circuits. These transformations all resulted from different ways of
solving the problems of IC design. The revolution of the IC industry
can be traced back to the 1970s. In the first stage, IDM companies
Chu and Chen 7645
emerged and dominated other competitors. At that time, IDM
provides a comprehensive set of services in the IC industrial value
chain. IDM companies such as Intel, Motorola, National
Semiconductor, and Philips offer services to their customers from
the very start to the end, including designing and manufacturing their
own IC products. An IDM company adopts a vertically integrated
business model, and must allocate resources not only to R and D,
but also to building increasingly expensive manufacturing and
fabrication facilities (Figure 1).
In contrast, ‘fabless’ or IC design houses focus solely on
designing and selling products. After the IC industrial changes in the
1980s, each company began to focus on individual niche markets.
IDM started to outsource some activities to other IC companies.
These firms outsourced manufacturing to foundry service
companies, such as Taiwan Semiconductor Manufacturing
Company (TSMC) in Taiwan. The establishment of wafer foundries
completely revolutionized traditional IDM business models, allowing
fabless companies to reduce their costs and focus their attention on
IC design. Wafer foundries, IC assembly companies and IC test
com- panies could concentrate their attention on their core
competencies. Big IC design houses engaged in IC design and IC
marketing. Similar to IDM, big IC design houses also opened their
IPs to certain types of processes. In other words, IPs from big IC
design houses were, in a sense, more convenient than those from
IDM. At that time, small fabless companies gained the ability to
compete with large-scale IDM companies. As a result, the entire
industry has shifted from a manufacturing-centric market to a more
customer-oriented market.
Intellectual property (IP), at the same time, has become crucial to
the IC industry. The more functions and effects a semiconductor can
get, the more complex its design will be. Therefore a new business
model, IP vendors, was created in the 1990s. These examples
included MIPS and ARM. IP vendors in this stage simply provide
pure IP and IP libraries, and make money from patents and
patent-related fees.
Based on SoC’s needs for IP reuse and design reuse, a new
business model emerged in the 2000s. A typical case is a design
foundry, which is capable of providing IP and IC design services to
customers. Design foundries integrate the technologies of IC
manufacturing from wafer foundries, IC assembly companies and IC
test companies for small IC design houses, which do not have the
ability to seek their assistance for mass production of an IC chip.
Open business models provide an effective solution to the
problems of decreasing product life cycle and increasing R and D
expenses. As an extension of open innovation, open business
models integrate value chain activities into various products or
services. Once a company adopts an open business model and
cooperates with external organizations, the transaction costs are
realized. The costs are incurred in trading goods or services. High
transaction costs are often the cause of the problems. Furthermore,
a company is difficult to survive when it faces higher transaction
costs Therefore, the company requires an intermediary for the buyer
and the seller to collect the necessary information efficiently, thereby
reducing the transaction costs.
Through global division and cooperation, design foundries have
played the important roles of inter-mediator and integrator,
generating more value and mutual interest between foundries and
IC design companies. To explain the dynamic phenomenon of the IC
industry, this study focuses on the difficulties that IC companies
faced. This paper also explains why IC companies require an
intermediary when they confront high transaction costs.
The common service gap and SoC problems for every part of
the IC industry
The IPs of an SoC chip are usually developed by different
companies. When designing a new IC, companies can experience

7646 Afr. J. Bus. Manage.
Figure 1. Evolution of the IC industrial infrastructure (source: Industrial technology information services of the
Ministry of Economic affairs (MOEA, 1997).
even more complicated and numerous problems due to transaction
costs such as insufficient intellectual property rights (IPR), and a
lack mutual trust and cooperation in outsourcing. Getting all IP
providers’ heads together and working out IPR questions is one of
the first things that an SoC design foundry must do. From the
business perspective of the evolution of the IC industry, there are
several predicaments in integrating authorized IP coordinator for
majority of IC companies. IC companies can encounter several key
issues including the following:
1. IP vendors: Because they lack an innovation intermediary that
provides the infrastructure for IP networking, IP vendor companies
cannot service small IC design houses. Due to service complexity,
IP vendors incur high operation costs when they license IP to other
companies. Because some IP vendors cannot service all middle- or
small-scale IC design houses, they need a service agency or
innovation intermediary to provide their own IPs to those licensees.
2. Wafer foundries, IC assembly companies and IC test companies:
Due to limited resources, wafer foundries cannot pay attention to
small IC design houses. The difficulties that both parties experience
are the result of a poor communication bridge. There are same
problems among IC assembly companies, IC test companies and
small IC design houses. Wafer foundries, IC assembly companies
and IC test companies must always integrate diverse processes with
a lower budget. While designing their IC layouts, middle- or
small-scale IC design houses sometimes do not take IC
manufacturing innovations into consideration. Wafer foundries
usually do not have sufficient resources to “teach” small IC design
houses the process of combining various IPs. Thus, wafer foundries
often need a service agent to effectively communicate with small IC
design houses. In the same vein, IC assembly companies and IC
test companies also need the support of an innovation intermediary.
TSMC, following the 80/20 rule, focuses on big clients with a high
manufacture yield, and devotes fewer resources to servicing
thousands of small IC design houses. The problem of poor
communication between wafer foundries and small IC design
houses could be solved if small IC design houses would work with a
service agent and use the SoC model to eliminate tedious revision
and design rules.
3. IC design houses: IC design houses experience two major
problems. The first one is that small IC design houses often cannot
acquire licensed IP without the help of IP vendors and wafer
foundries. The other problem is that their customers might change
into potential competitors after acquiring the necessary IPs. Due to
the fact that no company can own all major IPs and other IP
specifications at the same time, it is important that IC design houses
choose suitable IPs and electronic design automation (EDA) tools.
In this case, super IC design houses might work. Alternately, it may
be possible to make a deal with IP vendors or wafer foundries, but
middle- or small-scale IC design houses can never get support from
these two. Furthermore, as soon as IC design houses start to
authorize and sell their IP products, their clients often become
potential competitors. This is also a problem that many IC design
houses have encountered. Other problems of IC design houses,
such as time-consuming design programs, complex design patterns,
and higher costs, still need to be solved. To solve these problems, IC
design houses need a mediator to integrate useful IPs from a larger
IP pool.
STUDY RESULT AND FINDING
Currently, companies in the IC industry are becoming

Figure 2. The switching ecology of design foundry
more and more open. To open up their business models,
firms in the IC industry should tap into intermediate
markets for ideas and innovations. The IC industry review
discussed earlier outlines some problems of an IC
company in the IC industry. These difficulties also include
the rising costs of technology development and the
emerging trend of decreasing product life cycles. These
difficulties make R and D investment under the closed
model of innovation increasingly non-sustainable.
The ecological benefit of the IC industry
Design foundries accelerate the process of production,
provide suppliers with customer information, and meet
their needs. This innovation intermediary allows all
organizations to enjoy various ecological benefits. Open
innovation takes advantage of the new division of inno-
vation labor. This division also appears in inter- mediate
markets for innovation. Within this international division
and cooperation, the design foundry has played the
important roles of inter-mediator and integrator.
Open business models: Design foundries play a key
role as an innovation intermediary
Design foundries not only provide the services of IP
authorization and IC design, but also offer turnkey
Chu and Chen 7647
solutions, namely a complete package from the very
beginning of the design stage to the very end. Design
foundries were established in response to the growing
trend towards IP and design reuse in SoC devices.
Compared with traditional IC design houses, design
foundries do not do their own brands’ development and IC
marketing. They do whatever their customers want, and
only cater to their specific needs. Design foundries make
money by charging their customers design fees, which
thus enjoying relatively lower competition than other
IP-related business. Wafer foundries are to IDM what
design foundries are to IC design houses. In short, a
design foundry is a bridge between foundries and
customers, creating new value and generating
collaboration interest.
Through design foundries, the whole IC industry can
form an integral IC industry ecosystem enjoying the two
functions of the open business model, value creation and
value capture. This approach would solve many service
gaps and problems. Each organization could earn profit
and derive benefit from the resulting integral IC industry
ecosystem (Figure 2).
The core value of design foundries
There are value creation and value distribution that is
created by a design foundry. It can create a total solution
for SoC design services to their customers. Through cost

7648 Afr. J. Bus. Manage.
sharing on most advanced IP and wafer manufacturing
among IC design houses, a design foundry also can
improve new product time to market rates. To reduce risks
of IP theft and piracy, design foundries can integrate IPs
through several different IC firms. IC firms can also
reduce their R and D investment costs and achieve a
faster time to market by cooperating with design foundries.
Different companies in the value chain of the IC industry
have their own specialties and unique IPs. If these IPs
could be used repeatedly and legally by solving issues
such as IP licensing and pirating, then good IC designs
could be widely circulated and made more profitable. As a
result, many design foundries are formed to provide IP
related services such as IP searching, designing,
integration, and authentication.
Before the recent developments in the industry, IC
design houses could not deliver a product to their clients
without the help of a wafer foundry. Furthermore, not all IC
design houses could directly collaborate with wafer
foundries. At that time, design foundries could help both
IC design houses and wafer foundries solve the problem
of poor cooperation.
At the beginning of the designing process, if IC design
houses could receive assistance and sufficient
information form design foundries, they would not only be
able to reduce the time and cost to produce a design, but
could also reduce manufacturing risks. The information
provided by design foundries includes which wafer
foundries have which certified IPs (including silicon
verification and production proven), what manufacturing
processes are suitable for a particular IP, and where the
appropriate design tools can be acquired.
If wafer foundries can understand the needs of IC
design houses, they could reduce production difficulties
and effectively manage products manufactured or certified
by IC design houses. This allows wafer foundries to
effectively manage their production, control their delivery
time, and expand their customer services, improving
overall wafer foundry performance.
Design foundries how to collaborate and share utility
with other IC companies
Figure 2 shows what good benefits that an IC company
enjoys when it cooperate with a design foundry.
IP vendors
An IP vendors’ primary business is to authorize usage
rights of developed IP to others. Through the coordination
and integration of IP by design foundries, IP vendors
would be able to occupy a favorable market position,
enhance authorization opportunities for IP, and coordinate
with other IP vendors to introduce packaged IP, thus
generating more profit. More specific benefits include xthe
following:
i. The nurturing of star IP vendors: Providing a favorable
environment to small IP vendors can nurture these IP
vendors into star IP vendors.
ii. Reuse IP: The reusable IP can help IP vendors reduce
costs and shorten product cycle time. Further, an IP
vendor can receive royalties from various companies only
through one design foundry.
iii. Industry standard: Creating the industry standard of
product IP.
Wafer foundries
For wafer foundries, the process of integrating the IP
market via design foundries, enhances business
opportunities and attracts more potential customers. With
design foundries taking care of the problems of authoriza-
tion and royalty payments for the customers, professional
wafer foundries can not only improve the utilization of the
manufacturing resources, but also actively provide
standard IP blocks for customers. The advantages that
design foundries afford to wafer foundries include the
following:
i. Design for manufacturing (DFM): If IC design engineers
followed DFM guidelines of wafer foundries, they can
locate and solve the problems of potential production yield
in the initial design process. For instance, TSMC
provides its customers with IC design rules in designing
the IC layout.
ii. Focused on silicon-proven IP and start-up: Wafer
foundries can attract more customers and create more
opportunities to cultivate customers by using
foundry-specific and silicon-proven IP.
iii. Reduce switching costs and enhance communication
efficiency: With the help of design foundries, wafer
foundries can decrease the frequency of communication
with customers.
IC assembly companies and IC test companies
With the help of the design foundries, IC assembly
companies and IC test companies can bring more
customers by providing system-in-a-package (SiP)
service. SiP is multiple integrated circuits (ICs) enclosed
in a single package or module. SiP service is to complete
the system integration in a single package. It provides
verification (testing) services, overall manufacturing
process support, and documentation and application
support for their customers. From product design to mass
production, design foundries integrate the technologies of
IC assembly and IC test with SiP service to provide higher
performance SoCs and shortening time-to-market that
make IC design houses’ products more competitive.

Table 1. Revenue growth rate and CAGR of IC companies.
Chu and Chen 7649
Revenue growth rate (%) Compound annual growth rate
IC companies
Year
(CAGR)
2004-2005 2005-2006 2006-2007 2007-2008 2008-2009 2004-2009 (%)
Design foundry Company A 58.14 111.08 108.08 32.81 -10.91 52.39
IP vendor Company B 53.71 15.50 6.35 6.20 -10.38 12.44
Wafer foundry Company C 7.58 18.59 0.72 7.93 -15.17 3.30
IC assembly/test Company D 11.69 19.50 0.74 -6.65 -9.17 2.66
IC design house Company E 16.25 32.66 17.87 25.60 -6.52 16.37
IDM Company F 13.50 -8.87 8.34 -1.95 -6.54 0.53
There benefits about cost effective develop by design
foundries also help IC assembly companies and IC test
companies reduce the problems of communication with
customers and create more opportunities to gather
customers.
IC design houses
After design foundries develop and integrate the IP
market, IC design houses can use basic IP modules to
make multiple products with diverse designs. To shorten
the time of IC design, IC design houses inevitably use
others’ IP components when designing a new IC chip.
After acquiring IP licensing from IP vendors, large IC
design houses can directly deal with IP vendors and wafer
foundries. However, smaller IC design houses were not
able to directly cooperate with IP vendors and wafer
foundries. Therefore, when design foundries integrate
majority of IPs and simplify the process of IP authorization,
small IC design houses can obtain IP licensing agree-
ments and reduce their R&D costs. For IC design houses,
further advantages of cooperating with design foundries
include the following:
i. Providing useful IP source: Simplifying the process of
authorization and obtaining IP license.
ii. Time to market: Accelerating new product time to
market by understanding advanced IP process.
iii. Total solution: Creating a total solution for SoC design
services that includes design foundries, wafer foundries,
and IP vendors.
In summary, the business models of IC companies need
to open up and incorporate the benefit of intermediate
markets for innovation and IP, while managing the risks
associated with those markets. Consider the example of
some IC companies. Table 1 shows that the revenue
growth rate and compound annual growth rate (CAGR) for
IC companies in the past five years since 2004. Through a
design foundry, Companies A to E formed an industrial
partnership in the IC industry. Company F is an IDM
company. We replaced Companies A to F with company
names, because of non-disclosure information. Company
A has increased at a CAGR of 52.39% over a five-year
period, representing impressive growth in the IC industry
for the period 2004 to 2009. Company B and Company E
grew at a 12.44% and a 16.37% CAGR, respectively,
while Company C and Company D had lower CAGR in the
same period. The lowest CAGR of 0.53% was shown by
Company F. These figures indicate that IP-enabled
business and fabless companies have grown faster than
IC manufacturers during the observed period (2004 to
2009). IDM companies grew even more at a lower CAGR
than did IC manufacturers. This data confirms that the
more business models open up, the more benefits IC
companies can create and capture. With the support of
design foundries, IC design houses can compete with
IDM companies. With IP reuse and IP integration from IP
vendors and design foundries, the design cycle of an IC
chip can be reduced. This, in turn, increases the speed at
which IC companies can achieve CAGR. Compared with
IDM, firms in the IC industry can create a win-win situation
by adopting open business models.
DISCUSSION AND CONCLUSION
If a company adopts an open business model, it can
create its business model as a platform to lead its industry,
including both suppliers and customers. Open business
model highlight the inter-organizational activities. In this
industry ecosystem, an innovative intermediary must have
not only sufficient industry knowledge to integrate value
chain activities into various products or services, but must
also have specialized abilities to solve problems efficiently
among collaborative partners. In the IC industry, design
foundries play a key role as innovation intermediary,
creating a platform for effectively organizing and coordi-
nating the work of many others. Through a platform like
design foundry, each organization can earn profit and
derive benefit from the ecosystem of the IC industry.
The SoC design foundry is an exemplar case of an
open business model in practice. In conclusion, the IC
industry has adopted many of the features of an open
innovation model, including how design foundries form a

7650 Afr. J. Bus. Manage.
bridge between buyers and suppliers in the IC industry,
providing a great benefit to the entire IC industry.
Open innovation increases the breadth of business and
technological interdependencies in partnerships. Open
business models contain various compound theories and
numerous innovation processes. Examining the roles of
innovation may assist the development and testing of
open innovation theory. An important continuing research
question is the extent to which industries justify the roles
of innovation intermediary, what their interdependent
characteristics are, how innovations can be applied, and
how innovation intermediaries enable open business
models to be managed economically.
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African Journal of Business Management Vol. 5(17), pp. 7651-7657, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.1094
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Firm characteristics and voluntary disclosure of graphs
in annual reports of Turkish listed companies
Ali Uyar
Faculty of Economics and Administrative Sciences, Fatih University, Istanbul, Turkey. E-mail: aliuyar@hotmail.com.
Tel: +90 212 866 33 00. Fax: +90 212 866 33 42.
Accepted 31 May, 2011
The purpose of this study is to investigate the association between firm characteristics and the
voluntary disclosure level of graphs in annual reports of Turkish companies listed on the Istanbul Stock
Exchange (ISE). The firm characteristics used in the study are auditor size, ownership structure, firm
performance (profitability), and firm size. The methodology of the study is content analysis of annual
reports of the corporations listed on the ISE-100 Index for the year 2006. The results of univariate and
multivariate analyses indicated that firm size, and auditor size has significant positive association with
voluntary disclosure level of graphs. On the other hand, profitability and ownership structure do not
have any significant association with graphical disclosure level.
Key words: Graphs, annual reports, auditor size, ownership structure, firm size, profitability, voluntary
disclosure, Turkey.
INTRODUCTION
Corporate reporting is evolving as technology advances,
and as report readers demand better and more complete
information. While currently used tools are improved, new
tools are being developed. Penrose (2008b: 91)
summarizes the situation saying “corporate reporting is
no longer restricted to only hard copy, periodic, templatedriven
financial and accounting reporting that includes the
income statement, the balance sheet, the statement of
retained earnings, and the statement of cash flow, but
now also extends to such dynamic media as internet web
sites and automated telephone systems”.
Corporations communicate with stakeholders through
various ways such as face-to-face meetings, written and
visual media, and corporate websites. However, one of
the most important communication tools corporations use
is annual reports they publish. A company’s published
annual report and accounts are important primary documents
for anyone who is interested in that organization
(Reid, 2002). Stanton et al. (2004) define the corporate
annual report as “the traditional, statutory formal communication
vehicle between a publicly listed corporation and
its interested constituencies”. The audiences of annual
reports include stockholders, financial specialists,
financial analysts, employees, lenders, and creditors
(David, 2001).
Corporate annual reports may be utilized in a variety of
ways. Many of the recent company collapses, such as
Enron, WorldCom, Tyco and Global Crossing, are
believed to have been predictable by the detailed
analysis of a company’s annual report and accounts over
a number of years (Reid, 2002). Penrose (2008a: 158)
states that one of the elements readers often use in
assessing whether to buy, keep, or sell stock in the
corporation is the annual report.
Although corporate annual reports are designed first
and foremost for financial disclosure and to fulfill the legal
requirements for financial statements (Ball, 2011), Beattie
et al. (2008) state that, during the past few decades, they
have been transformed from a rather dull financial document
to a colorful marketing and public relations vehicle.
Corporations used to publish paper-based annual
reports, but nowadays, they are made available on the
corporate websites. This enables more timely and, in
addition, less costly publication of annual reports.
The information published in the annual reports may be
classified as mandatory and voluntary. Mandatory disclosures
are disclosures required by laws and regulations.
On the other hand, voluntary disclosures are not
necessarily required; their availability is made possible by
corporate fiat. It depends on the decision of corporation.

7652 Afr. J. Bus. Manage.
For example, while disclosure of financial statements by
publicly traded companies is mandatory according to
legislations of most countries, environmental and social
responsibility disclosures are voluntary. One of the
voluntary disclosure areas is graphical presentation in
annual reports. It is increasingly becoming a common
practice for annual reports to include visual graphical
summaries of the company’s financial position/progress
(Ball, 2011). Amer (2005), Arunachalam et al. (2002), and
Chan (2001) state that graphical displays are increasingly
being used as decision aids. Companies use graphs in
disclosing both financial and non-financial information.
Among the variables disclosed by graphs are share
performance, sales revenues, net income, sales volume,
production, owners’ equity, number of customers, ownership
structure, energy consumption, water consumption,
number of personnel. The typical graphic forms found in
annual reports are pie charts, line graphs, column and
bar graphs, and histograms. Compared to studies
focusing on environmental and social disclosures,
disclosure of graphs is not studied at all despite being an
indispensable part of the majority of annual reports.
Beattie and Jones (2001) stress the inadequacy of
research studies about the subject despite the rising
popularity of graph utilization in annual reports.
While some earlier studies present guidelines for
proper graphing of variables (Chevalier and Roy, 1993;
Hill and Milner, 2003; Taylor and Anderson, 1986;
Fulkerson et al., 1999; Zekany and Elsass, 2004), several
have concentrated on empirical analysis of the nature
and extent of graph usage (variables graphed, graph
types used, graphic inclusion percentage of annual
reports), measurement distortions in graphs (Uyar,
2009a; Steinbart, 1989; Beattie and Jones, 1992b,
1999a, b, 2002), and the association between graph
usage and firm performance (Beattie and Jones, 2000;
Dilla and Janvrin, 2010).
Uyar (2009a) states that as most of the past studies
regarding graphic disclosure have been conducted in
developed countries such as U.S, U.K, Australia, and
Canada, there is a scarcity of similar analysis in
developing countries. This study aims at narrowing this
gap by investigating the subject in a developing country,
namely, Turkey. More specifically, the objective of this
article is to investigate the association between firm
characteristics and the voluntary disclosure level of
graphs in annual reports of Turkish companies listed on
the Istanbul Stock Exchange (ISE) (2008).
LITERATURE REVIEW
Graphical presentation of quantitative data within
corporate annual reports has become one of the
techniques used by management in disclosing quantitative
information (Courtis, 1997: 269). Beattie and Jones
(1992b) state that graphs are used in two fundamentally
different ways: to analyze data and to
present/communicate information to an audience. Ruchti
and Wasserman (1983) state in their articles that public
companies have to view themselves as publishers
assuming the annual report is a periodical. Therefore,
they say that the annual reports require “graphic ignition”
to make them successful periodicals. If drawn
appropriately, graphs serve many beneficial purposes. If
not properly constructed, however, graphs may become a
tool of deception with which companies distort numbers
to mask their poor performance (Uyar, 2009a). Since
graphs reduce the time and effort senior executives and
managers spend for analyzing tables, they are
increasingly opting for information generated by
computers in graphic form (Sullivan, 1988).
Voluntary presentation of graphics is increasingly being
used in the corporate annual reports of large companies
in many countries to reap the advantages graphical
presentation of information offers. Among these are
increasing the speed of decision-making (Sullivan, 1988),
being remembered better than tables (Smith and Bain,
1987), enabling visual comparisons (Smith and Bain,
1987), being effective for summarizing financial and nonfinancial
information (Fulkerson et al., 1999), being more
user-friendly than tables (Beattie and Jones, 1997),
simplifying complex quantitative data, and providing
immediate insight into operating, investing and financing
activities (Chevalier and Roy, 1993), being a visually
appealing and effective means of communicating
financial information to shareholders, regulators, and the
media (Chevalier and Roy, 1993), mitigating the adverse
effects of information overload (Chan, 2001), describing
the relationship between variables (Moriarity, 1979),
improving communicative effectiveness of annual reports
(Wilson and Stanton, 1996), and capturing attention and
allowing readers to scan the information (David, 2001).
While utilization of graphs in annual reports may offer
many advantages, they should be drawn properly in order
not to mislead report readers. Frownfelter-Lohrke and
Fulkerson (2001) cite eleven potential pitfalls
encountered in graphic presentations. Hill and Milner
(2003) provide 3-staged guidelines for improving
graphical displays: aims and objectives of graphing,
graph type choice, and graphical design. Fulkerson et al.
(1999) present three basic guidelines for preparation of
financial graphics constructed by the Canadian Institute
of Chartered Accountants. These three guidelines are:
choosing a graph type, preparing the graph, and making
sure the graph is not deceptive.
Earlier studies also provide information regarding the
most widely used graph types and the most frequently
graphed variables. According to the findings, line, bar,
and pie graphs are the most widely used types (Chevalier
and Roy, 1993; Davis, 1987), and the most frequently
graphed variables are sales, earnings, earnings per
share, and dividend per share (Beattie and Jones 1992a:
2002). These four variables are named as key financial

variables (Beattie and Jones, 1999a, b, 2002; Mather et
al., 2000).
Hypotheses development
Auditor size
Earlier studies have investigated the association between
auditor size and the disclosure level of corporations
(Wang et al., 2008; Patton and Zelenka, 1997;
Raffournier, 1995; Singhvi and Desai, 1971; Inchausti
1997; Wallace et al., 1994; Malone et al., 1993; Bonsón
and Escobar, 2006; Uyar, 2009b; Hossain et al., 1995;
Aripin et al., 2009). Malone et al. (1993) argue that
smaller auditing firms are more sensitive to client
demands because of the economic consequences
associated with the loss of a client; on the other hand,
larger firms have a greater incentive to demand adverse
disclosures from the client. A number of studies failed to
discover a significant relationship between the auditor
size and disclosure level (Wallace et al., 1994; Hossain et
al., 1995; Malone et al., 1993). On the other hand, many
earlier studies have found a positive association between
the auditor size and the extent of disclosure (Patton and
Zelenka, 1997; Singhvi and Desai, 1971; Raffournier,
1995; Aripin et al., 2009; Bonsón and Escobar, 2006;
Inchausti 1997). Hence, the following hypothesis is
stated:
H1: There is a positive significant association between
auditor size and the voluntary disclosure of graphs in
annual reports.
In testing this hypothesis, auditors of the corporations
were classified as Big4 and non-Big4. In Turkey, the
“Big4 auditors” are the following local affiliates of the Big4
international firms (Wikipedia, 2010);
i. Güney Bagimsiz Denetim ve S.M.M. A.S. - member of
Ernst and Young,
ii. Akis Bagimsiz Denetim ve S.M.M. A.S. - affiliate of
KPMG,
iii. Basaran Nas Bagimsiz Denetim ve S.M.M. A.S. -
affiliate of PricewaterhouseCoopers
iv. DRT Bagimsiz Denetim ve S.M.M. A.S. - affiliate of
Deloitte Touche Tohmatsu
Profitability
The association between profitability and voluntary
disclosure has also been investigated in previous studies
(Wang et al., 2008; Oyelere et al., 2003; Marston and
Polei, 2004; Marston, 2003). Marston (2003) argues that
the more profitable the companies, the more likely it is for
them to disclose financial information. Marston and Polei
Uyar 7653
(2004) also stress that “good news” firms are encouraged
to distinguish themselves out from other firms by
disclosing more information. This provides the basis for
the following hypothesis:
H2: There is a positive association between profitability
(as measured by return on assets) and the voluntary
disclosure of graphs in annual reports.
Firm size
Prior studies have investigated the association between
firm size and voluntary disclosure in annual reports (Gao
et al., 2005; Leventis and Weetman, 2004; Liu and
Anbumozhi, 2009; Hossain and Hammami, 2009; Uyar,
2009a; Patton and Zelenka, 1997; Inchausti, 1997;
Watson et al., 2002; Bonsón and Escobar; 2006;
Abdullah and Ku Ismal, 2008; Raffournier, 1995, Hossain
et al., 1995; Wallace et al., 1994). Several studies have
investigated the existence of a positive relationship
between firm size and voluntary disclosure due to agency
theory (Oyelere et al., 2003; Marston and Polei, 2004;
Marston, 2003). Marston (2003) claims that higher level
of disclosure is expected to decrease agency cost which
may arise from the conflicting interests of shareholders,
managers and debt holders. Furthermore, voluntary
disclosures are expected to decrease political costs that
are higher for larger companies compared to smaller
companies (Marston, 2003; Marston and Polei, 2004).
Hence, based on the literature, the following hypothesis
is stated:
H3: There is a positive association between firm size (as
measured by total assets) and the voluntary disclosure of
graphs in annual reports.
Ownership structure
Several studies have examined the association between
ownership structure and voluntary disclosure practices of
the corporations (Raffournier, 1995; Aripin et al., 2009;
Singhvi and Desai, 1971; Uyar, 2009b; Oyelere et al.,
2003; Malone et al., 1993). Among these, Raffournier
(1995) states that agency relations are likely to play a
major role in the disclosure policy of companies, because
annual reports can be used to reduce monitoring costs.
He argues that managers of firms whose ownership is
diffuse have an incentive to disclose more information in
order to help shareholders in monitoring their behavior.
Moreover, Malone et al. (1993) state that as the number
of shareholders increases, one would expect financial
disclosures to increase. Singhvi and Desai (1971) point
out that there may be positive relationship between the
number of stockholders and the quality of disclosure in
annual reports. Thus the following hypothesis is

7654 Afr. J. Bus. Manage.
Table 1. Descriptive statistics.
Variable Minimum Maximum Mean Standard deviation
Number of graphs 0 34 8.60 9.009
Auditor (1 for Big4; 0 for non-Big4) 0 1 0.71 0.458
Total assets (Turkish liras) 68,198,700 75,203,939,544 5,665,448,930 13,584,611,973
Return on assets -0.22 0.58 0.0578 0.108
% of shares held by unknown shareholders 0.03 1.00 0.3780 0.202
Table 2. Correlation analysis.
Variable
Number of
graphs
Auditor Total assets
Number of graphs 1
Auditor 0.329* 1
Total assets 0.264* 0.165 1
Return on
assets
% of shares held by
unknown shareholders
Return on assets -0.006 0.016 -0.117 1
% of shares held by unknown
shareholders
-0.020 -0.416* -0.148 -0.059 1
*Correlation is significant at the 0.01 level (2-tailed).
formulated:
H4: A positive association exists between a firm’s
ownership diffusion and the voluntary disclosure of
graphs in annual reports.
In this study, ownership diffusion is defined as the
percentage of shares not held by known shareholders
(Raffournier, 1995).
SCOPE AND METHODOLOGY
The sample of the study is the ISE-100 companies listed on the
Istanbul Stock Exchange (2008). Annual reports of the companies
for the year 2006 were downloaded from corporate web sites of the
companies. The web site addresses of the companies were
obtained from the official web site of the governmental regulatory
and supervisory body for capital markets (Capital Markets Board,
2008). Out of 100 corporations, annual reports of 4 corporations
could not be reached. Hence, final sample comprised 96
corporations.
The methodology of the study is content analysis conducted on
the corporate annual reports of the firms. Annual reports were
analyzed to determine the number of graphs disclosed by each
corporation. Firm characteristics such as auditor type, total assets,
net income, and ownership structure were also noted. In the
statistical analysis, univariate analysis and multivariate analysis
have been used in order to demonstrate the impact of firm
characteristics on the graphic disclosure level of the companies.
The research model includes one dependent variable
TOTGRAPHS (total number of graphs disclosed by the firms in
annual reports), and four independent variables: FSIZE (firm size
which is measured by total assets), PROFIT (profitability which is
measured by return on assets), AUDSIZE (auditor is either a
member of Big-4 or non-Big-4), and OWNERSHIP (ownership
structure which is measured by percentage of shares held by
unknown shareholders).
For the purpose of investigating the determinants of voluntary
disclosure level of graphs in the annual reports, the following model
was set up:
TOTGRAPHS= β0+β1FSIZE + β2PROFIT + β3AUDSIZE +
β4OWNERSHIP + ε
The model is explained in multivariate analysis part in greater
detail.
RESEARCH FINDINGS
Descriptive statistics
The results showed that 72 companies out of 96 (75%)
use graphic disclosure in their annual reports. Hence,
annual reports of 24 four companies do not include any
graphic disclosure. Total number of graphs in annual
reports is 826 indicating an average of 8.6 per annual
report. However, since in four annual reports, the auditing
firm was not stated, further analyses are conducted on
the basis of 92 firms. Out of these 92 firms, 27 worked
with non-Big4 auditing firms, while 65 worked with Big4 in
the year 2006. Table 1 presents the descriptive statistics
of the study.
Correlation analysis
Table 2 presents the correlation results between total
numbers of graphs disclosed and firm characteristics.
The results indicate that there is a significant correlation
between graph disclosure level, and auditor size (at 0.01

Table 3. Explanations of dependent and independent variables.
Variable Explanation
Dependent
TOTGRAPHS Total number of graphs
Uyar 7655
Independent
FSIZE firm size which is measured by total assets
PROFIT profitability which is measured by return on assets (that is, net income/total assets)
AUDSIZE type of the auditor (that is, 1 if auditor is a member of Big-4 auditing firms, 0 if auditor is not a member of Big-4
auditing firms)
OWNERSHIP ownership structure of the firm (that is, the percentage of shares not held by known shareholders)
level) and firm size (at 0.01 level). This means that the
larger the firm size, the more likely is the firm to disclose
graphs in annual reports. Furthermore, the firms who
work with Big-4 auditors are more likely to disclose
graphs.
Multivariate analysis
As in many previous disclosure studies, regression
analysis has been preferred to investigate the association
between firm characteristics and disclosure level of
graphs in annual reports. The independent variables of
the study contain both continuous and categorical data.
Since the dependent variable is count data which
indicates the number of graphs disclosed in the annual
reports, count regression is more appropriate than linear
regression statistically (Cameron and Trivedi, 1998; Coxe
et al., 2009; Zeileis et al., 2008; Saxton and Benson,
2005). Count regression model has also been used in
some recent publications in the accounting and finance
discipline (Boubaker and Labegorre, 2008; Kelton and
Yang, 2008; Farrel and Hersch, 2005; Wang et al., 2008).
For the purpose of investigating the determinants of
voluntary disclosure level of graphs in the annual reports,
the following model was set up:
TOTGRAPHS= β0+β1FSIZE + β2PROFIT + β3AUDSIZE +
β4OWNERSHIP + ε
The explanations of dependent and independent
variables are presented in Table 3.
Among count regression models, Poisson regression
(nonlinear regression model) is the standard one and has
provided a starting point for many analyses (Cameron
and Trivedi, 1998). However, Poisson regression model
has an important constraint which is the equality of mean
and variance (equidispersion) assumption (Boubaker and
Labegorre, 2008; Cameron and Trivedi, 1998).
Overdispersion occurs if the variance exceeds the mean
(Cameron and Trivedi, 1998). In order to overcome this
constraint of Poisson regression, negative binomial
regression which accounts for overdispersion is used
(Cameron and Trivedi, 1998; Coxe et al., 2009; Zeileis et
al., 2008; Saxton and Benson, 2005; Kelton and Yang,
2008; Boubaker and Labegorre, 2008). Therefore, in the
analyses, the existence of overdispersion was tested with
likelihood ratio test (Coxe et al., 2009). Due to the
existence of overdispersion, negative binomial regression
has been used in the analysis. Table 4 reports the
regression results.
H1 predicts that there is a positive significant association
between auditor size and the voluntary disclosure
of graphs in annual reports. As shown in Table 4, the
coefficient of AUDSIZE is significant at 0.01 level. Hence,
H1 is supported.
H2 posits that there is a positive association between
profitability and the voluntary disclosure of graphs in
annual reports. As shown in Table 4, the coefficient of
PROFIT is not significant. Hence, H2 is rejected.
H3 states that there is a positive association between
firm size and the voluntary disclosure of graphs in annual
reports. As presented in Table 4, the coefficient of FSIZE
is significant at 0.10 level. Hence, H3 is supported.
H4 states that a positive association exists between a
firm’s ownership diffusion and the voluntary disclosure of
graphs in annual reports. As indicated in Table 4, the
coefficient of OWNERSHIP is not significant. Hence, H4 is
rejected.
Conclusion
Although there are plenty of voluntary disclosure studies,
there are only a few focusing on voluntary disclosure of
graphs in annual reports. This study extends prior
research by investigating the influence of firm
characteristics on voluntary disclosure level of graphs in
the annual reports of Turkish listed companies.
In order to test the influence of firm characteristics on
disclosure of graphs in annual reports, four hypotheses
were proposed. In testing hypotheses, negative binomial
regression from count data regression models was used.
The results of multivariate analyses indicated that firm

7656 Afr. J. Bus. Manage.
Table 4. The results of regression analysis.
Variable Coefficient Standard error z P>z
AUDSIZE 0.96 0.30 3.21 a 0.001
FSIZE 1.74E-11 1.01E-11 1.72 b 0.085
PROFIT 0.40 1.23 0.33 0.744
OWNERSHIP 0.66 0.76 0.88 0.380
Constant 1.02 0.44 2.30 0.021
Log likelihood -286.82
Likelihood-ratio test χ 2 436.91 (p

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55.

African Journal of Business Management Vol. 5(17), pp. 7658-7664, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.351
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
How after-sales service quality dimensions affect
customer satisfaction
Alireza Fazlzadeh 1 , Fatemeh Bagherzadeh 2 and Pegah Mohamadi 2 *
1 School of Economics, Tabriz Branch, Islamic AzadUniversity, Tabriz, Iran.
2 School of management, Master of international Marketing management, Islamic azad university-tabriz, Iran.
Accepted 29 April, 2011
An understanding of the effect of after-sales services in satisfaction and post behavioural intentions is
important to services marketing managers because it allows them to differentiate their offering
substantially, in a way that strengths the relationship with their clientele in the short, as well as in the
long run. The purpose of this paper is to investigate the effect of after-sales services on customers’
satisfaction as well as on their behavioural intentions, namely “repurchase intention” and “word-ofmouth”
(WOM). The research conducted followed a quantitative methodology. The selected research
tool was a questionnaire. The study conducted was targeted at customers of a large retail chain
marketing home appliances in Iran and 302 usable responses were utilised. A path analysis was
performed using the “Amos 18” software. Findings show that after-sales service quality, affect
satisfaction, which in turn affects behavioural intentions. Hence, after-sales services affect the overall
offering and thus, the quality of the relationship with customers.
Key words: Retailing, after-sales services, service quality, customer satisfaction, word-of-mouth, repurchase
intention.
INTRODUCTION
The role of service quality is widely recognized as being a
critical determinant for the success of an organization in
today's competitive environment. Any decline in customer
satisfaction due to poor service quality would be a matter
of concern. Consumers being more aware of rising
standards in service, prompted by competitive trends,
have developed higher expectations. In other words,
service quality aspects possess a substantial strategic
role for companies. This does not happen only in the pure
service sectors, but also in many others where service is
a considerable part of the augmented product. Indeed,
the concept of “service quality” can be used by all
sectors, since practically everywhere, the total productoffering
is a mixture comprised of tangible and intangible
part (Shostack, 1977). This also emerges in the case of
retailing.
In addition, in a context of global competition and
*Corresponding author. E-mail:
Mohamadi.pegah25@yahoo.com. Tel: +98-914-348-4738.
decreasing profits from product sales, the after-sales
services and activities (that is, those taking place after
the purchase of the product and devoted to support
customers in the usage and disposal of goods) constitute
a relevant profit source as well as a key differentiator for
manufacturing companies and resellers (Wise and
Baumgartner, 1999; Levitt, 1983) profit generated by
after-sales services is often higher than the one obtained
with sales; the service market can be four or five times
larger than the market for products (Bundschuh and
Dezvane, 2003) and it may generate at least three times
the turnover of the original purchase during a given
product's life-cycle (Wise and Baumgartner, 1999).
In this paper, it is argued that after-sales services
appear to be exceptionally significant to the overall
“product-mixture” provided by retail companies, since
they affect both the customers’ satisfaction and their
behavioral intentions. We concur with the view that aftersales
services play a critical role in relationship building,
and as such, they should be examined and evaluated
attentively when obeying service quality theory. Besides,
although the topic of service delivery has been frequently

treated in the literature, its relation to the “product-service
mixture offering” has been relatively neglected and it is
even more so when the service quality aspect is also
brought into the discussion.
Emphasis has been given in the managerial implycations,
since it is managers who make decisions in the
retailing firms, regarding how to add value to the total
offering they bring to the market.
BACKGROUND
After-sales services and retailing
Retailing includes all the activities involved in selling
goods or services directly to final consumers for personal,
non-business use. A retailer or retail store is any
business enterprise whose sales volume comes primarily
from retailing. Any organization selling to final consumers
– whether it is a manufacturer, wholesaler, or retailer – is
doing retailing. It dose not matter how the good or
services are sold (by person, mail, telephone, vending
machine, or internet) or where they are sold (in a store,
on the street, or in the consumer home) (Kotler, 2008).
Peterson and Balasubramanian (2002), in their
extensive work on “retailing in the 21 st century”, suggest
that the role of retailing stands out clearly, as being to
serve as the interface between firm and customer, what
remains under-explored is to determine the ways to
“increase the value of the (retailing) firm”.
Besides, regarding the related issue of “what is the
basis of retail store choice and satisfaction”, various
authors suggest that academics should give emphasis to
the ways “satisfaction can be converted into higher retail
earnings”, which are the ways through which this
relationship will be proved beneficial in twofold, through
satisfaction and performance. Both remarks manifest a
need for further exploitation of the value-adding elements
of the total offering. These are elements that are
enhancing the core product-service offered and are
embodied in the total offering during the selling process,
prior as well as after the sale closing stage. According to
some authors, the search for sustainable competitive
advantages in retailing gives the after-sales services a
pivotal role in the relationship between customers and
sellers.
As a term, “after-sales services” has been used the
most, to describe services that are provided to the
customer after the products have been delivered
(Vitasek, 2005). The same services are sometimes also
called “field services”, when they are embodied in the
main characteristics that are located at a customer’s site
(Simmons, 2001). “After-sales support” (Agnihothri et al.,
2002) as well as “technical support” or even just
“services”, are terms also found in the literature (Goffin
and New, 2001). “After-sales services” are often (Lele
and Karmarkar, 1983) referred to as “product support
Fazlzadeh et al. 7659
activities”, meaning, all activities that support the productcentric
transaction. The after-sales service constitutes a
means to uncover customer needs and a strategic driver
for customer retention. It represents, in fact, “one of the
few constant connections that customers have with a
brand” (Gallagher et al., 2005), influencing customer
satisfaction and loyalty. Finally, after-sales service is a
way to allow a continuous improvement of product design
and quality (Armistead and Clark, 1992; Cohen and
Whang, 1997; Thoben et al., 2001). The perception of
after-sales as a source of competitive advantage and
business opportunity requires a shift from a traditional
product-centric view, in which after-sales is considered a
“necessary evil” (Lele,1997) to customer-centric view.
Furthermore, the term “after-sales services” has been
approached in the literature under two broad perspectives.
When referring to service providing companies,
after-sales services are being treated as one among
several supplementary service elements provided by
them (Oliva and Kallenberg, 2003). On the other hand,
when referring to tangible goods, they are mostly seen as
operative activities of some, or all members of the
distribution chain (Gaiardelli et al., 2007). Such services
are the transport/delivery to clients, the installation, the
product-related training, the hot line and advice by the
help desk, any repairing service and even the recycling
process.
The theory of distribution services argues that the
merchandise of explicit products or services is to be seen
embodied in a variety of distribution services (Betancourt
and Gautschi, 1988). According to the particular theory,
these services accompany the merchandise possessing
one of the two primary components or retailing (Barber
and Tietje, 2003) and can be split further into five
groups; assortment, information, location and ambiance
and “assurance of immediate product delivery at the
desired time and in the desired form” (Betancourt and
Gautschi, 1988).
This research adopts the view offered by Oliva and
Kallenberg (2003), under which both the tangible as well
as the intangible part of the offering are treated to their
full potential. Referring to the tangible and the intangible
combination of an offering, they distinguish between the
“product-installed base” as the “total number of products
currently under use”, and the “installed base services” as
“the range of product- and process-related services
required by an end-user over the useful life of a product
in order to run it effectively in the context of its operating
process”. According to this view, the relationship between
the seller and the buyer does not end in the store when
the tangible product is purchased, but goes beyond this
for as long as the offering lasts.
Along these lines, “delivery” is often the first among the
services offered after the sale. Besides installation which
follows, posses a distinct and remarkable after-sales
service, wherefore Goffin (1999) refers as being one
among the seven elements of customer support.

7660 Afr. J. Bus. Manage.
After-sales services and customer satisfaction
It is well known that the margin from after-sales service is
much larger than that from the product. That is, aftersales
service is considered a key revenue generator in
certain categories (Cohen et al., 2006; Cohen and
Whang, 1997). Hence, on one hand, offering a large
number of extra after-sales service plans to consumers,
leads to higher profitability. Recent marketing
management focuses on lifetime value of a customer and
maintaining long-term relationships with customers
(Gupta and Lehmann, 2007).
From this customer-relationship viewpoint, after-sales
service is regarded as an important factor that has an
impact on establishing good relationships with customers.
On the other hand, a default and free basic after-sales
service, also plays an important role in attracting more
customer attention in a market with severe brand
competition (Chien, 2005). Offering adequate after-sales
service to customers has become a major generator of
revenue, profit, and competency in modern industries
(Cohen et al., 2006; Cohen and Kunreuther, 2007).
Accepting the claim that returning customers are the
most profitable ones, as they require less marketing effort
and relationship building, after-sales service acquires a
critical role as a means to achieve customer satisfaction
and retention (Alexander et al., 2002).
After-sales services and service quality
Quality in services provides a competitive factor for
continued consumption, especially when intangibility
relations are tightened between quality and services.
Service quality plays a notable role as a source of
sustainable competitive advantage for the companies.
Several categorizations do exist in the literature
regarding the different kinds of service quality. Although
there is no conclusive agreement among the academics,
nevertheless, all views recognise that the overall service
quality is a multi-dimensional construct. One of the
pioneers was Gronroos (1978, 1982) who recognized the
need and usefulness of developing valid and distinct
measures of service quality. Groonroos (1984) categorises
service quality in the “technical” service, referring
to what service the customers are actually receiving and
to the “functional” service, meaning the process of the
delivery of the service. The first service quality
measurement model was developed by Parasuraman et
al. (1988). It was introduced by the name of service
quality (SERVQUAL). This particular view treats quality
as the construct constituted by different encounter
characteristics. Rust and Oliver (1994), among others,
claim that service quality is constituted by three broad
sub-dimensions; the personnel-related, the tangible
offering related and the service-scape-related.
When applying the quality theory to after-sales services,
the authors believe that after-sales services are
contributing to the “technical quality” of the overall
service, which is, influencing substantially the “what is the
customer receiving”? In parallel, influencing the way
(“How”) the central service is being delivered, playing
therefore, a critical role in the “functional” aspect of
service quality. If one utilizes as basis not the Nordic
model, but the “extended” “three-component model”,
proposed by Rust and Oliver (1994), again it seems that
after-sales services are closely related to both, the
“service product” and the “service delivery” dimensions of
quality.
With the on going discussion, two of the three main
drifts of interests regarding service quality are being
touched. The third, regarding evaluation matters of the
provided service quality, will be treated under the relation
of service quality dimensions with the construct of
performance.
The positive perceptions and attitudes of the target
customers towards the quality-elements offered by the
firm, leads to both attractions of new customers, thanks
to word-of-mouth (WOM) communication and
recommendations of the existing customers, as well as to
enhancement of the relationship of the company with its
current customers by making them more loyal and
committed.
Word of mouth (WOM) is informal advice passed
between consumers. It is usually interactive, swift, and
lacking in commercial bias. WOM is a powerful influence
on consumer behavior. Keaveney (1995) noted that 50%
of service provider replacements were found in this way.
WOM may be positive (PWOM), encouraging brand
choice, or negative (NWOM), discouraging brand choice.
Word-of-mouth is a frequently encountered variable in the
service literature. Typically, it is viewed as a component
in a satisfaction-profit framework (sometimes also labeled
as the service-profit chain; Heskett et al., 1994), in the
sense that satisfaction (or other global evaluations, such
as perceived service quality) is assumed to affect word of
mouth, which in turn is assumed to affect the firm’s
profitability. Several studies also show that other global
evaluation variables, such as perceived service quality
and perceived service value, are positively associated
with word-of-mouth transmission (Danaher and Rust,
1996; Fullerton and Taylor, 2002; Hartline and Jones,
1996; Sweeney and Soutar, 2001).
In this context, customer satisfaction has been the
subject of a substantial body of literature (Rust and
Oliver, 1994), because of its influence on customer
behavioural intentions and attitudes (Anderson and
Sullivan, 1993; Cronin and Taylor, 1992). Regarding
behavioural intentions, Zeithaml et al. (1996) suggest that
favourable behavioural intentions are mostly in the form
of customers’ referrals and recommendations, customers’
willingness for re-purchasing, as well as customers’
willingness to spend more money with the particular
company or to pay more for the products of this

company.
METHODOLOGY
Table 1. Questions measuring main variables.
Fazlzadeh et al. 7661
Latent variables Mean
Delivery service quality
Reliability in delivery times 3.43
Quality of the product packaging when delivered 3.42
Transfer of product to your place 3.33
Quality of the product itself when delivered 3.39
Reception of the proper invoice/delivery papers 3.27
Kindness and friendliness of the delivery personnel 3.57
Appearance of the delivery personnel (uniform, cleanness) 3.47
Installation service quality
Accurate information about time of installation 3.31
Time elapsed between delivery and installation 3.36
Attentiveness of installation personnel in order to avoid damages 3.16
Flawless of the installation 3.17
Kindness and friendliness of the installation personnel 3.22
Advice and instructions given by the technicians 3.28
Overall satisfaction
Level of satisfaction from their co-operation with the retailer in the context of the particular purchase 3.51
Re-purchase intention
Intention to prefer the same retailer in the next purchase of a new home
appliance
Word of mouth
Intention to recommend the retailer to friends and relatives 3.25
This study attempt to understand affect quality of after-sales
services on customer overall satisfaction and on their behavioural
intentions to re-purchase and to recommend (Word-of-Mouth).
According to the Rigopoulou et al. (2008), we used a behavioural
model in which the following latent variables are included:
1) “Delivery” service quality, that this variable is measured as a
latent one using seven indicators, including the “reliability in delivery
times” (D1), the “quality of the product packaging when delivered”
(D2), the “transfer of product” (D3), the “quality of the product itself
when delivered” (D4), the “reception of the proper invoice/delivery
papers” (D5), the “kindness and friendliness of the delivery
personnel” (D6) and the “appearance of the delivery personnel”
(D7).
2) “Installation” service quality, that this variable is measured as a
latent one using six indicators, including the “accurate information
about time of installation” (I1), the “time elapsed between delivery
and installation” (I2), the “attentiveness of installation personnel in
order to avoid damages” (I3), the “flawless of the installation” (I4),
the “kindness and friendliness of the installation personnel” (I5) and
3.49
the “advice and instructions given by the technicians” (I6). In the
model, the following measurement variables are included:
i. “Overall Satisfaction”, which refers to the customers’ level of
satisfaction from their co-operation with the retailer in the context of
the particular purchase.
ii. “Repurchase Intention” which is related to the customers’
intention to prefer the same retailer in the next purchase of a new
electric appliance.
iii. “Word-of-Mouth” which refers to the customers’ intention to
recommend the retailer to their friends and relatives.
The product category under examination is home appliances in Iran
that offer after-sales services to customers. The research
conducted was based on questionnaire as a research tool. Overall,
a total of 302 usable responses were included in the research
conducted. The variables (Table 1) were measured on five-point
scales anchored “completely dissatisfied” and “fully satisfied” or
“definitely yes” – “definitely no”, respectively. The structural
equation modelling (SEM) was performed using the “Amos 18”
software.
RESULTS
Table 1 show that, respondents feel quite satisfied from

7662 Afr. J. Bus. Manage.
Figure 1. The model.
Table 2. Goodness of fit test results for the model.
Variable � � GFI AGFI NFI TLI IFI CFI RMSEA
Value 96.3 0.963 0.940 0.986 0.997 0.998 0.998 0.022
Installation
both after-sales services offered, namely “delivery” and
“installation”. The mean score of the satisfaction
regarding the “delivery” is 3.45, while the respective
score for “installation” is slightly lower (3.25). The vast
majority of the specific quality elements of the
two services, were judged by the respondents to be
quite satisfactorily provided, with mean scores from 3.27
to 3.57 for delivery and 3.16 to 3.36 for installation, Mean
scores for “word of mouth” (3.25) and “repurchase
intention” (3.49). For the scales reliability analysis,
Cronbach α, were calculated for both latent variable
measurement scales. Results revealed that both
“delivery” (αD = 0.972) and “installation” (αI = 0.947)
scales were reliable.
According to the results, as presented in Table 2, all
the important indicators of the model fit, as suggested by
Hoyle (1995), have accepted values. For this reason, this
Overall satisfaction
model is considered as an acceptable one (Figure 1).
As (Figure 1) indicated:
1. “Delivery” and “installation” service quality positively
affect customers’ overall satisfaction.
2. “Delivery” and “installation” service quality positively
affect customer’s intention for recommendations.
3. “Delivery” and “installation” service quality positively
affect customers re-purchase intentions.
4. Overall, satisfaction positively affects customers’
intentions to recommend the retailer to friends and
relatives.
5. Overall, satisfaction positively affects customers’ repurchase
intentions.
Conclusion
Customer satisfaction has been studied and recognized

as an important factor in the management literature for
the past few decades. Studies indicate that there are
links among customer satisfaction, customer loyalty, and
profitability. Companies frequently concentrate on new
customers, as they assume that current customers are
satisfied. However, this is not necessarily the case.
Several researchers argue that investing in existing
customers is viable because of the lifetime value of the
customer and because many customers need afterpurchase
reassurance.
Our study examines the relationship between aftersales
services, customer satisfaction and customers’
behavioural intentions. Based on the main findings of the
literature review in the retailing context, it comes out that
after-sales service quality affect satisfaction, which in turn
affects behavioural intentions. Our results confirm
findings of the Rigopoulou et al. (2008), and these results
stated that after-sales services affect the perceived value
by the customer and thus, the quality of the relationship
between buyers and sellers. It became clear that the
importance of quality of after-sales services for customer
satisfaction could be crucial; furthermore, customer
satisfaction was measurable.
Therefore, the importance of the quality of after-sales
services and customer satisfaction were highlighted in
the present study. After-sales improvements can only
take place with a realization that customer satisfaction
would be strongly influenced by the quality of the aftersales
delivery. After-sales presents differentiation potential
that producers can use to strengthen their operations.
However, the difference between the existence of
potential and the actual achievement of competitive
advantage must be taken into consideration. Potential
can only be converted to competitive advantage if the
organization is able to persuade customers to place
equal subjective value on that aspect of the
organization’s offerings.
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African Journal of Business Management Vol. 5(17), pp. 7665-7673, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.1491
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
An empirical investigation into the extent of customer
satisfaction and customer loyalty at big retail stores in
King William’s Town, South Africa
Tafadzwa Machirori and Olawale Fatoki*
Department of Business Management, University of Fort Hare, Alice, South Africa.
Accepted 13 July, 2011
The study investigates customer satisfaction and customer loyalty in four big retail stores in King
William’s Town, South Africa. Customer satisfaction and loyalty are factors impacting on the
performance of firms. Data was collected through self administered questionnaires. Mall intercept was
used as the survey method. Data analysis included descriptive statistics, T-test, ANOVA and chi square
goodness of fit test. The results indicate that holistically, customers are satisfied and loyal to the retail
stores. However, the study identified one significant area of customer dissatisfaction which is the
queuing time. In addition, the study identified that courtesy is an area of concern for customer
satisfaction. Recommendations to improve customer satisfaction are suggested.
Key words: Customer satisfaction, customer loyalty, retail shops.
INTRODUCTION
In this new global environment where competition is
intense and trade has been liberalised, business enterprises
can no longer focus on profit maximisation only but
also on customer satisfaction. Customer satisfaction has
become the major success factor for business
enterprises to gain increased market share and to
successfully compete in the ‘new economy’. The ‘new
economy’ refers to the changes in business or market
activities that have occurred in the 21 st century. The
major distinction in the new global economy is the
business enterprise’s ability to change from the traditional
product oriented concept where business enterprises
expect customers to purchase what they produce to
being more customer oriented, where the focus is on
customer need satisfaction (Cant et al., 2003).
According to Kotler and Armstrong (2006), for business
enterprises to deliver customer need satisfying goods
and services profitably, they need to meet or exceed the
customers’ expectations of value. Where a business enterprise’s
value proposition meets or exceeds consumer
*Corresponding author. E-mail: OFatoki@ufh.ac.za.
expectations, customer satisfaction is high and this
impacts positively on the performance of the business.
Orth and Green (2009) add that higher customer
satisfaction relates to higher customer loyalty.
The purpose of this study is to investigate if customers
are satisfied with the services they receive at big retail
stores in King William’s Town (Eastern Cape Province,
South Africa). The study will investigate if there is a significant
difference between the expectation of satisfaction
and the perception of satisfaction. In addition, the study
will investigate the extent of customer loyalty. Customer
satisfaction is a major step towards customer relationship
management and is defined as a consumer’s feeling of
pleasure or disappointment resulting from comparing a
good or service’s perceived performance to the
consumer’s own expectations (Kotler and Keller, 2006).
Customer loyalty, on the other hand, is the relationship
the customer maintains with the business enterprise after
the first transaction (Hallowell, 1996). A satisfied
customer is likely to be a loyal customer who make
repeat purchases and provide positive word of mouth
publicity (Kotler and Armstrong, 2006).
This research was fuelled by the realisation that customer
satisfaction and customer loyalty are essential for

7666 Afr. J. Bus. Manage.
operating a profitable business in this global era. All
business enterprises strive to deliver superior value to
customers in order to be competitive in the market place.
The study focused on the following objectives:
1. To investigate if customers are satisfied with the
services they receive at big retail stores.
2. To investigate if customers are loyal to the big retail
stores.
LITERATURE REVIEW
Customer satisfaction
Central to the customer satisfaction theory, is the
expectations or predictions made by customers as
compared to the actual delivered value (Parasuraman,
1993). This implies that a measurement is required for
customer satisfaction. The SERVQUAL model introduced
by Parasuraman et al. (1985, 1988) provides one of the
most important basis in the theory of customer
satisfaction. The SERVQUAL model provides the basis
for the measurement of customer satisfaction with a
product or service by assessing and comparing both
perceptions and expectations across a range of different
service characteristics. As observed by Terblanche
(2002), superior service quality leads to customer
satisfaction. Therefore, service quality, as measured by
the SERVQUAL model cannot be separated from
customer satisfaction analysis.
Further development of the customer satisfaction theory
was conducted by Oliver (1977, 1980), who introduced
the expectancy disconfirmation theory (Nevo, 2005). The
disconfirmation theory suggests that customer
satisfaction with a product or service is related to the size
of the disconfirmation experience; where disconfirmation
is related to the customer’s initial expectations as
compared to the actual performance delivered (Thijs and
Staes, 2008: 15). The “gaps” between the actual delivered
value and customer expectations, consequently,
influence the level of satisfaction or dissatisfaction of the
customer. Therefore, where performance matches or
exceeds customer expectations there will be positive
disconfirmation and customer satisfaction. However,
negative disconfirmation will occur where performance is
below customer expectations and there is customer dissatisfaction
(Wirtz and Bateson, 1995). The gap between
customer evaluation or perceptions of performance and
customer satisfaction provide a solid measure of service
quality and determines the level of performance (Thijs
and Staes, 2008: 15).
Another relevant theory in customer satisfaction is the
queuing theory. The queuing theory was introduced by
Erlang in the early 1900s (Cooper, 2000). The queuing
theory utilises mathematical models and performance
measures to assess and improve the flow of customers
through a queuing system (Nosek and Wilson, 2001).
The importance of the queuing theory as a tool in
customer satisfaction theory can be viewed through Adan
and Ressing (2002) observation that “customers do not
like to wait”. Therefore, the queuing theory is essential in
improving the customer’s perception about waiting in line
and the associated level of satisfaction. Similar to the
queuing theory, the crowding theory provides substantial
insights to customer satisfaction. Perceived crowding is a
result of physical, social, and personal factors that
sensitize the individual to actual or potential problems
arising from limited space (Machleit et al., 2000). When a
customer perceives the environment as dense, he or she
will perceive the environment as confining and constraining,
which leads to the state of crowding. This can
lead to customer dissatisfaction (Eroglu et al., 2005).
Customer satisfaction plays a key role in a successful
business operation and strategy formulation by a
customer-centric business enterprise (Gomez et al.,
2004). Customer satisfaction is the mediator in the
relationship between relational benefits, customer loyalty
and word-of-mouth publicity (Molina et al., 2007). Retail
stores operate in a competitive environment facing
changes in customer needs, demographics, technology
improvement and retail ownership through mergers and
acquisitions. In such an environment, the understanding
and prediction of customer satisfaction is fast becoming a
competitive advantage factor (Theoridis and
Chatzipanagiotou, 2008).
The efficient satisfaction of customer needs is the
ultimate test of a business enterprise’s success and focus
of business activity should be to serve customer needs
and wants more efficiently than competitors (Jain, 2000).
The long term survival of a business enterprise depends
not only on the sales volume and the variety of business
enterprise’s products but also on the former’s ability to
satisfy the needs of customers efficiently. A business
enterprise’s ability to deliver superior value is thus the
starting point in efficient customer need satisfaction (Jain,
2000). A satisfied customer is the only true asset of the
business enterprise and represents the sole justification
of the business enterprise’s existence (Cant et al., 2006).
The notion of service quality is very important in
customer satisfaction (Gee et al., 2008). There is a direct
positive link between service quality and customer
behavioural intentions and strong customer service leads
to customer satisfaction, which will in turn, lead to loyal
behaviour. The perceived value of products relative to
price, staff friendliness and willingness to assist as well
as the quality and freshness of products, store appearance,
and the degree of customer service are some of
the factors affecting customer satisfaction (Gomez et al.,
2004). According to Clottey et al. (2008), the benefits of
customer satisfaction to a business include lower acquisition
costs of attracting new customers. Increased customer

satisfaction may also reduce the overall costs of a
business while increasing the base profit of the business.
However, the most important benefit of customer satisfaction
is customer loyalty which leads to positive word of
mouth publicity and referrals by satisfied customers.
Customer loyalty
The fundamental starting point of the theory of customer
loyalty can be traced to the behavioural theories which
analysed customer loyalty through brand loyalty (Kuusik,
2007). Behavioural theorists such as Cunningham
(1956), Farley (1964) and Tucker (1964) as cited in
Boora and Singh (2011), identified customer loyalty
through repeat purchase behaviour. The attitudinal theory
introduced by Day (1969) suggests that a customer's
willingness to recommend a service provider is often
presumed to be a surrogate indicator of customer loyalty.
Day’s (1969) theory argues that for true loyalty to be in
effect the customer must have a favourable attitude
towards a product and purchase it repeatedly. Consequently,
there is more to brand loyalty than just consistent
buying of same brand. The attitudinal approach infers
customer loyalty from psychological involvement,
favouritism, and a sense of goodwill towards particular
products or service (Boora and Singh, 2011). The attitude
component thus distinguishes between true loyalty and
spurious loyalty (Wallace et al., 2004).
The leaky bucket theory, introduced by Ehrenberg
(1988, 1990) is another theory that has its roots in
customer loyalty. The leaky bucket theory analyses
customer loyalty through a related concept of customer
retention. According to Raines (2005) the leaky bucket
theory refers to the rate at which businesses are losing
customers each year and an enterprise with a low
customer retention rate will lose customers from a very
leaky bucket. Thus, the leaky bucket theory suggests that
when an enterprise expects most of its customers to be
highly loyal, marketing strategies seem to be designed to
replace “disloyal” customers who leak away with new
customers to keep the sales level constant.
According to Hollensen (2003), the success of a
business is based on loyal customers who have a bond
with the business enterprise and this bond links the
customer to the enterprise to such an extent that the
customer develops a preference for the business enterprise.
When true loyalty exists, customers will regularly
conduct repeat purchase transactions with the business
enterprise for the sole reason that customers have a
strong preference for that business enterprise. Customer
loyalty is not merely based on quality, price, physical
facilities or satisfaction but is based more on customer
feelings and perceptions about the business enterprise
(Krell, 2005). The marketing maxim on customer loyalty is
that it costs five times more to acquire a new customer
than to retain an existing one (Gee et al., 2008). It makes
Machirori and Fatoki 7667
commercial sense to develop relation-ships with the
business enterprise’s current customers before acquiring
new customers. Keeping existing customers satisfied is
much more cost effective than acquiring new customers
(Parker et al., 2009). Customer loyalty results from
committed customers who display repeat purchase
tendencies or behaviour towards the business enterprise
will be committed to purchasing the goods offered by that
particular enterprise (Brink and Berndt, 2004).
RESEARCH METHODOLOGY
The study used the quantitative research methodology approach.
The target population was identified as customers that purchase
goods from four big retail stores in King William’s Town. The target
population was difficult to ascertain. Mall intercept survey, where
shoppers at a mall are intercepted and given self-administered
questionnaires to complete, was used to collect data. Convenience
sampling was used in order to ensure a high response rate given
the nature of the study. The respondents were selected randomly
as they exited the retail stores. The questionnaire included closeended
questions and Likert-scale questions. Close ended questions
were limited to demographic factors.
To measure customer satisfaction, a modified version of the
SERVQUAL model introduced by Parasuraman et al. (1985) was
used. According to the SERVQUAL model, an effective measure of
customer satisfaction requires measuring the differences between
customer expectations and the customer perceptions. Seven
dimensions of customer satisfaction were focused upon. These
include tangibility, responsiveness, courtesy, customer handling,
competence, accessibility and security. These dimensions were
presented both in terms of expectations and perceptions. T-tests
were performed on the mean scores of expectations and perception
items and dimensions to identify the existence of significant
differences in the mean scores.
To measure customer loyalty, the Harvard Business Review
Apostle model was used. Customers were asked to rate their
overall satisfaction on a scale of 1 to 10 and their likelihood to continue
to do business with the retail stores on a scale of “definitely
will” to “definitely will not” (on a scale of 1 to 10). According to the
Apostle model, loyalists report both high satisfaction and high
loyalty. Hostages report high loyalty despite low satisfaction.
Mercenaries report high satisfaction, but low loyalty. Defectors
report both low satisfaction and low loyalty. Furthermore, a five
point Likert scale detailing whether the customer would recommend
the retail stores to family and friends and whether the customer
would switch to competitors was also used to effectively measure
customer loyalty.
Data analysis included descriptive statistics, chi square goodness
of fit, T-test and ANOVA. To ensure validity, the study used
constructs such as the SERVQUAL model and the Apostle model
that have been empirically validated. The research instrument was
also pre-tested in a pilot study. The Cronbach’s alpha was used as
the measure of reliability.
RESULTS AND DISCUSSIONS
Three hundred and ten questionnaires were completed
by the respondents as they exited the retail stores. The
gender composition consisted of 53% males and 47%
females. Respondents below the age of 21 years constituted

7668 Afr. J. Bus. Manage.
16% while 46% represented respondents between the
ages of 21 and 30 years. Respondents between the ages
of 31 and 40 years represented 26% of the respondents
while respondents between the ages of 41 and 50 years
constituted 9% of the respondents. The remaining 3%
consisted of respondents over the age of 50 years.
Customer satisfaction
To determine the existence of customer satisfaction, the
difference between expectation and perception must not
be significant. Twenty five items were grouped under
seven dimensions. The scale means for customer
expectations and actual perceived were compared to
determine the level to which customers were satisfied.
The seven dimensions of customer expectations (Table
1), tangibility, reliability, courtesy, competence,
accessibility, security and customer handling had means
of 4.77, 4.76, 4.74, 4.28, 4.49, 4.92 and 4.41
respectively. The overall scale mean was 4.58. This
indicates that customer expectations are very high. The
significance was tested through the non-parametric chisquare
goodness of fit test. The chi-square goodness of
fit is the sum of the difference between the observed
outcome and the expected outcome. Using five point
Likert scale, the expected outcome is 20% for each scale.
The observed outcomes however significantly reflect
strongly agree as depicted by the p-values
The seven dimensions of customer perceptions (Table
2), tangibility, reliability, courtesy, competence,
accessibility, security and customer handling had scale
means of 4.16, 4.23, 3.26, 3.63, 4.06, 4.77 and 3.57
respectively. The overall scale mean for customer
perceptions was 3.96. This indicates that customers were
moderately satisfied. However, in examining the
individual items of the seven dimensions, the results
indicate that queuing time with a mean score of 2.94 has
the lowest mean of all the items. The results indicate that
customers are not satisfied with the queuing time. In
addition, the dimension of courtesy has the lowest mean
of all the dimensions which indicates an area of concern.
Table 3 compared the mean values and p-values for
customer expectations and customer perceptions to
measure if there was a significant gap between the
individual items and the grouped dimensions of
expectations and perceptions. Holistically, customers
were satisfied with the retail stores. Dimensions such as
tangibility, reliability, customer handling, accessibility and
security indicated that there was no real significant gaps
between expectations and perceptions. However, when
viewed individually, queuing time shows a significant
difference between customer expectation and customer
perception. In addition, courtesy though insignificant is an
area of concern with relatively low p value compared to
other dimensions. Holistically, there is no significant
difference between customer expectation and perception.
This indicates a high level of customer satisfaction.
Customer loyalty
The results in Table 4 indicate that customers are loyal to
the big stores. The mean score for recommendation to
friends is 4.75 and repeat purchase is 4.90. The mean
score for switching to another retailer is 1.01 The pvalues
of the chi square goodness of fit test tested at 5%
significance level were also significant confirming the fact
that customers are loyal to these retail outlets (Table 5).
Furthermore, based on the Harvard Business Review
Model, the scale mean is 8.6, indicating that customers
were satisfied with the retail outlets and would continue
doing business with the retail outlets. Customer loyalty
thus exists at the four big retail stores. These customers
are termed “loyalists”. Loyalists, in line with literature, can
also be termed apostles in the “Zone of customer loyalty
model” (Table 6).
The t-test was used to determine whether there are
significant differences in the mean scores of gender in
relation to customer satisfaction and customer loyalty.
The results are insignificant in terms of customer
satisfaction and customer loyalty. This indicates that
there is no significant difference in the mean scores of
males and females with respect to customer satisfaction
and customer loyalty (Table 7).
The ANOVA test was used to determine the differences
in the mean scores of the age groups in relation to
customer satisfaction and customer loyalty. The results
indicate that there are no significant differences in the
mean scores of the different age groups in relation to
customer satisfaction and customer loyalty.
RECOMMENDATIONS
The results suggest that holistically, customer satisfaction
and customer loyalty exist at the retail stores. However,
queuing time is the one significant area of customer
dissatisfaction. In addition, the courtesy dimension has
the lowest scale mean and depicts an area of concern.
Therefore, the recommendations of this study focus on
improving queuing time and staff courtesy
Communication with customers should be improved at
peak hours in the retail stores. Video communication can
be used to inform customers that due to the high volume
of shoppers, there can be delays in processing at
checkout points. The introduction of home delivery
system and online purchase may also improve customer
satisfaction and customer loyalty. Home delivery system
enables customers to make orders and have delivery to
their doorsteps within a specified geographical area for a
small additional fee. Removing the negativities of queuing

Table 1. Customer expectations on satisfaction ratings - descriptive statistics and chi-square goodness of fitness test.
Machirori and Fatoki 7669
Item Mean Standard deviation Chi-square Significance level (p-values)
Tangibles
Employee appearance 4.70 1.23 89.986 0.0043
Physical facilities 4.52 1.56 57.156 0.0053
Product quality 4.98 1.07 101.875 0.0025
Store layout 4.65 1.89 79.754 0.0031
Price of products 5.00 1.98 107.985 0.0067
Modern equipment 4.79 1.48 92.162 0.0059
Scale mean 4.77
Cronbach’s α 0.7433
Reliability
Keeping to designated operating
times
4.74 1.55 102.398 0.0047
Never runs out of stock 4.76 1.36 67.983 0.0043
Quality of service 4.69 1.34 89.563 0.0021
Consistent level of service 4.86 1.26 57.384 0.0035
Scale mean 4.76
Cronbach’s α 0.8234
Courtesy
Courteous employees 4.85 1.69 84.923 0.0015
Happy employees 4.67 1.34 98.793 0.0026
Politeness of employees 4.83 1.55 69.521 0.0035
Employee attitudes 4.63 1.39 87.524 0.0046
Scale mean 4.74
Cronbach’s α 0.8345
Competence
Short queuing time 4.94 1.21 102.398 0.0033
Knowledgeable employees 4.69 1.37 78.923 0.0013
Correct labelling of items 3.21 1.23 46.933 0.0046
Scale mean 4.28
Cronbach’s α 0.7234
Accessibility
Easy access to store location 4.76 1.33 107.046 0.0035
Ease of access to helpful
employees
4.21 1.36 63.089 0.0063
Scale mean 4.49
Cronbach’s α 0.7843
Security
Safe parking area 4.92 1.43 89.345 0.0097
In store safety 4.89 1.38 103.465 0.0043
Risk of robbery 4.94 1.35 134.923 0.0048
Scale mean 4.92
Cronbach’s α 0.7917
Customer handling
Complaints handling 4.78 1.28 104.945 0.0088

7670 Afr. J. Bus. Manage.
Table 1. Contd.
Individualised attention 4.04 1.68 100.244 0.0095
Communication 4.85 1.24 106.453 0.0085
Scale mean 4.41
Cronbach’s α 0.8532
Overall mean 4.58
Table 2. Customer perceptions on satisfaction ratings - descriptive statistics and Chi-square goodness of fitness test.
Item Mean Standard deviation Chi-square Significance level (p-value)
Tangibles
Employee appearance 4.39 1.23 34.337 0.0321
Physical facilities 4.09 1.55 109.345 0.0467
Product quality 4.34 1.07 111.956 0.0054
Store layout 4.56 1.26 105.233 0.0234
Price of products 3.87 1.56 98.087 0.0045
Modern equipment 3.72 1.31 56.455 0.0434
Scale mean 4.16
Cronbach’s α 0.8356
Reliability
Keeping to designated
operating times
4.78 1.34 108.677 0.0084
Never runs out of stock 4.45 1.48 45.497 0.0417
Quality of service 3.97 1.39 58.632 0.0345
Consistent level of service 3.74 1.33 84.243 0.0492
Scale mean 4.23
Cronbach’s α 0.7124
Courtesy
Courteous employees 3.25 1.78 34.034 0.0396
Happy employees 3.39 1.27 46.534 0.0421
Politeness of employees 3.22 1.03 33.065 0.0485
Employee attitudes 3.17 1.34 42.234 0.0419
Scale mean 3.26
Cronbach’s α 0.7341
Competence
Short queuing time 2.94 1.45 55.454 0.0367
Knowledgeable employees 3.61 1.36 36.788 0.0432
Correct labelling of items 4.34 1.57 112.904 0.0045
Scale mean 3.63
Cronbach’s α 0.7342
Accessibility
Easy access to store location 4.57 1.12 144.985 0.0065
Ease of access to helpful
employees
3.54 1.23 56.746 0.0334
Scale mean 4.06
Cronbach’s α 0.8319

Table 2. Contd.
Machirori and Fatoki 7671
Security
Safe parking area 4.78 1.74 104.345 0.0024
In store safety 4.67 1.65 99.054 0.0080
Risk of robbery 4.87
Scale mean 4.77
Cronbach’s α 0.8223
Customer handling
Complaints handling 3.74 1.25 37.453 0.0232
Individualised attention 3.35 1.48 59.346 0.0321
Communication 3.63 1.34 57.234 0.0312
Scale mean 3.57
Cronbach’s α 0.7145
Overall mean 3.96
Significance at > 0.05.
Table 3. Results of t-test to measure significant differences in the mean scores of expectations and perceptions.
Item Expectations mean Perceptions mean t-values Sig. (2-tailed) at 95% confidence level
Tangibles
Employee appearance 4.70 4.39 1.433 0.234
Physical facilities 4.52 4.09 1.345 0.102
Product quality 4.98 4.34 1.543 0.245
Store layout 4.65 4.56 1.567 0.124
Price of products 5.00 3.87 1.945 0.343
Modern equipment 4.79 3.72 1.456 0.156
Scale mean 4.77 4.16 1.989 0.347
Reliability
Keeping to designated
operating times
4.74 4.78 1.876 0.675
Never runs out of stock 4.76 4.45 1.076 0.295
Quality of service 4.69 3.97 1.787 0.543
Consistent level of service 4.86 3.74 1.344 0.379
Scale mean 4.76 4.23 2.256 0.371
Courtesy
Courteous employees 4.85 3.25 0.123 0.135
Happy employees 4.67 3.39 1.954 0.678
Politeness of employees 4.83 3.22 1.283 0.571
Employee attitudes 4.63 3.17 1.932 0.569
Scale mean 4.74 3.26 1.871 0.341
Competence
Short queuing time 4.94 2.94 0.023 0.003
Knowledgeable employees 4.69 3.61 1.387 0.567
Correct labelling of items 3.21 4.34 1.923 0.435
Scale mean 4.28 3.63 1.655 0.271

7672 Afr. J. Bus. Manage.
Table 3. Contd.
Accessibility
Easy access to store location 4.76 4.57 1.945 0.656
Ease of access to helpful
employees
4.21 3.54 1.439 0.359
Scale mean 4.49 4.06 1.983 0.274
Security
Safe parking area 4.92 4.78 1.934 0.362
In store safety 4.89 4.67 1.799 0.832
Risk of robbery 4.94 4.87 1.203 0.129
Scale mean 4.92 4.77 1.659 0.318
Customer handling
Complaints handling 4.78 3.74 0.234 0.045
Individualised attention 4.04 3.35 1.945 0.342
Communication 4.85 3.63 1.103 0.587
Scale mean 4.41 3.57 1.777 0.326
Overall mean 4.58 3.96 1.871 0.296
Table 4. Customer loyalty - descriptive statistics and chi-square of fitness of goodness test.
Question Mean Standard deviation Chi-square Significance level (p-value)
Would you recommend friends and family to
shop at the retail stores
4.75 1.34 89.071 0.013
Would you be returning to purchase goods? 4.90 1.45 102.234 0.004
Would you switch to another retail store 1.01 1.57 56.745 0.043
Table 5. Customer loyalty based on the Harvard Business Review model - Descriptive statistics.
Question Mean Standard deviation Chi-square Significance level (p-value)
Are you overly satisfied with your shopping
experience?
8.95 1.34 103.071 0.003
Are you likely to return to redo business? 8.34 1.45 101.234 0.007
Scale mean 8.6
Table 6. T-test results on gender, customer satisfaction and customer loyalty.
Factor
T-test
Gender
Significance
Customer satisfaction 1.2345 0.234
Customer loyalty 1.1923 0.545
Table 7. ANOVA results on age, customer satisfaction and customer loyalty.
Factor
T-test
Age
Significance
Customer satisfaction 1.2345 0.234
Customer loyalty 1.1923 0.545

and travelling may lead to satisfaction and improve
customer loyalty and retention. Employing more seasonal
employees to help deal with seasonal bursts of demand
would improve customer satisfaction. Furthermore,
investing in more till points will reduce queuing time and
lead to customer satisfaction and loyalty. Investment in
new technology, especially contactless payment systems
can help reduce customer queuing time. Training of staff
on customer relationship can help improve staff courtesy
and customer satisfaction. In addition, courtesy should be
built into performance measures for staff. Courteous staff
members should be rewarded and discourteous staff
members punished. Senior management must demonstrate
by example, the organisation’s commitment to
courtesy for junior staff members to follow. This will
ensure that the organisation’s cultural climate reflects a
commitment to courtesy. Courtesy must be practiced by
all the staff in the organisation. Screening techniques
must be used to hire employees with good skills in
courtesy.
AREAS FOR FURTHER STUDY
The research can be extended to a wide geographical
area in order to increase the representativeness of the
sample to the population. A larger sample is required in
order to improve the validity of the results obtained.
Further research can investigate the drivers of customer
loyalty in retail stores.
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African Journal of Business Management Vol. 5(17), pp. 7674-7682, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM10.569
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Identifying the challenges related to policymaking
institutions for entrepreneurship formal education in
Iran
Mohammad Hossein Rahmati 1 *, Hossein Khanifar 1 , and Seyed Mohammad Moghimi 2
1 Qom campus, Tehran University, Tehran, Iran.
2 Management Faculty, Tehran University, Tehran, Iran.
Accepted 27 July, 2011
In this paper, we are going to determine how the institutions play important role in policy making for
entrepreneurship education in universities of Iran. So, after a brief review on literature, research
analytical model is extracted by pointing out theoretical basics and research dimensions. In the
meantime, the way to test the model, initializing the dimensions and concepts, models of performing
the research project, data collection methods, data analysis, validity and reliability are addressed. Since
the opinions of 102 elites/connoisseurs in entrepreneurship field (including professors, experts of
entrepreneurship centers, offices at over 16 universities and official organizations) are measured
through questionnaire using the method survey-kind. Questionnaire items are designed by segregating
conceptual model dimensions into the types of entrepreneurship trainings, the components of
educational system, policymaking steps and policymaking institutions in the template of Likert’s five
option scale and null (no impact) option. To review the reliability, Chronbach's alpha (87%) is used. To
review the validity, elites’ poll is utilized. Research questions were responded to after collecting the
ideas and information through statistical techniques. Finally, the findings indicate the important
institutions and the challenges related to them that have the main influence on the process of policy
making in this field. At the end of article the verified challenges and some related recommendations
was proposed for improving this system.
Keywords: policymaking, policymaking institution, entrepreneurship education, Iran.
INTRODUCTION
The need for university engagement in entrepreneurship
education gets societies to make relevant policies for this
issue. Recent research has shown that universities have
not been successful in creating sustainable environments
that enhance technology transfer and in the commercialization
of intellectual property of the university (Bok, 2003;
Wright et al., 2004). In contrast, research universities
have been able to capitalize on generating revenue from
their research projects resulting in patents and other
*Corresponding author. E-mail: mhrahmati@ut.ac.ir.
Abbreviations: SMEs, small and medium enterprises; NGOs,
non-governmental organizations; OEM, organizational elements
model.
methods of technology transfer (Mosey et al., 2006)
Furthermore, as a result of bias that exists in academia,
regional universities may be viewed as institutions that
repress the growth of human and social capital and they
have not been able to capitalize on the large funding
models (Wright, 2004).
More recently, the role of universities in regional
development has been seen as transcending this narrow
technical and economic approach to embrace the role of
universities in enhancing human capital within a region.
Examples include certificate and degree programs in
entrepreneurship, workshops and seminars, technical
and administrative assistance, and resource referral, as
well as recruiting students from outside the region and
placing them in the local companies through internships,
co-ops, and part-time employment; conducting continual

and professionally developmental programs to enhance
the skills and knowledge potential of local managers;
embedding international businesses by targeted training
programs and research links; providing a gateway
between the broader and international knowledge base
with small and medium enterprises (SMEs); and
providing strategic analysis and leadership within local
civic society (Lundvall and Johnson, 1994).
One of the challenges of entrepreneurship education in
Iran is due to the problems coming from policymaking
institutions. That is to say, policymaking institutions do
not function properly. Therefore, this research project
aims at studying the present and optimal functions of the
policymaking institutions in entrepreneurship education,
examining the gap between the present and optimal
conditions, and identifying the challenges of reaching the
optimal conditions.
Research questions
1. Is there any difference between status quo and desired
situation of policymaking institutions in entrepreneurship
formal education?
2. How much difference exists in the role of policymaking
institutions in different sectors?
3. What are the current challenges in the entrepreneurship
education policymaking in Iran and their applied
solutions?
Research objectives
Primary objectives
Studying policymaking challenges in entrepreneurship
formal education in Iran
Secondary objectives
1. Documenting and drawing status quo of policymaking
in entrepreneurship formal education system in Iran
2. Designing and clarifying policymaking desired model in
entrepreneurship formal education system in Iran
3. Identifying current challenges of policymaking in
entrepreneurship formal education system in Iran
4. Providing solutions and applied suggestions in studied
field
LITERATURE REVIEW
Entrepreneurship defined
Entrepreneurship is a multidimensional concept, the definition
of which depends largely on the focus of the
research undertaken. An entrepreneur can fulfill different
functions (Fiet, 1996). Hébert and Link (1989) define an
entrepreneur as "someone who specializes in taking
Rahmati et al. 7675
responsibility for and making judgmental decisions that
affects the location, form, and the use of goods, resources
or institutions" (Hébert and Link, 1989). Sahlman
and Stevenson (1991) define entrepreneurship as "a way
of managing that involves pursuing opportunity regardless
of the resources currently controlled. Entrepreneurs
identify opportunities, assemble required resources,
implement a practical action plan, and harvest the reward
in a timely, flexible way".
What is meant with entrepreneurship? Entrepreneurship
and innovation are fuzzy concepts that have been
given multiple meanings. Innovation and entrepreneurship
are often regarded as overlapping concepts. This
can be traced back to probably the most well known
definition of entrepreneurship, by Schumpeter (1934),
who defines entrepreneurs as individuals that carry out
new combinations (that is, innovations).
The policy of entrepreneurship education
Comparing the level of entrepreneurship across nations
is difficult for several reasons. First, there is no generally
accepted definition of entrepreneurship (OECD, 1998a;
Lumpkin and Dess, 1996; Bull and Willard, 1993). No
wonder entrepreneurship is considered as the solution in
policy documents.
Entrepreneurship is a major driver of innovation, competitiveness
and growth. Due to their strong presence in
key sectors such as services and knowledge-based
activities, small enterprises and entrepreneurs play a
central role in the EU economy nowadays (European
Commission, 2004a).
The emergence of entrepreneurship education into the
educational sphere has forced the concept to be
interpreted in a broader view. This is, for instance, viewed
among the shared goals that the Ministers of Education
agreed upon to be achieved in 2010. The catch phrase
“opening up education and training system to the wider
school” put the spirit of enterprise as a central part in the
educational system.
Education and training should provide opportunities to
acquire skills needed to set up and run a business. Entrepreneurship
is wider than business activity, an active and
reactive spirit, something that society as a whole should
value and invest in. Education and training establishments
should therefore stimulate learners' skills and
enterprise spirit throughout their education and training.
Here, entrepreneurship is no longer just equated with
business creation but is talked more about as an
approach. Though, the connection to business creation is
still present, however indistinct. In defiance of the
ambition to widen the concept of entrepreneurship, it is
defined in a particular way at the different levels in
education. In the lower levels there is a focus on personal
characteristics; at the level of primary education, entrepreneurship
teaching will aim to foster in the pupils those
personal qualities such as creativity, spirit of initiative

7676 Afr. J. Bus. Manage.
and independence that contribute to the development of
an entrepreneurial attitude, which will prove useful in their
life and in every working activity (European Commission,
2002).
At the higher levels, however, there is a shift of focus
towards starting a business; at the level of secondary
education, the development of the personal qualities
mentioned above will continue to be relevant. In addition,
entrepreneurship teaching will include raising the awareness
of the students about self-employment as a possible
career option for instance by running mini-enterprises;
specific training on how to create a business (especially
in vocational or technical schools). At the level of tertiary
education, entrepreneurship teaching will provide the
students with specific training on how to start (and run) a
business (European Commission, 2002).
The interest in entrepreneurship education has become
a central issue in the regional polices. The work on
changing attitudes towards enterprising must begin early
in the school. The school should give the students the
understanding that running an own company is as usual
as being employed.
In the later stages of school, education could be directed
more towards how to start and run an own company.
When the student has reached upper secondary school
he or she should not be unfamiliar with starting a
company throughout the rest of the school period
(Dalarna, 2003).
A change of attitudes towards enterprising is crucial to
create an increasing growth. Changing attitudes takes
time. School plays an important role and should develop
students’ spirit of enterprising regardless of their
perceptions about their future professional state as selfemployed
or employed. Children are creative and enterprising.
These characteristics should be encouraged at all
levels in the educational system (Gävleborg, 2003).
In these regional policy documents, as well as in policy
documents from the national and the European levels,
there seems to be total agreement upon what entrepreneurship
education should be at the different levels in the
educational system. The shift in focus from personal
characteristics (such as creativity, self-confidence,
responsibility, risk-taking, etc) in the lower levels to
business start-up in the higher levels is not really new.
Nevertheless, it is not discussed in the policy documents
but seems to be taken for granted. The conflicts are not
to be found here, though tensions, conflicts and closures
are pervasive when it comes to the processes of turning
policy into practice.
On the whole, government can train entrepreneurs and
small business owners by providing necessary facilities
and various resources such as:
1. Nongovernmental organizations (NGOs)
2. Governmental training institutes and universities
3. Local organizations (local governments)
4. Private training institutes
5. Trading and commercial chambers
6. Management development institutes
7. Commercial associations
8. Advising organizations
9. Self-running training institutes on small businesses
(Moghimi, 2002).
The components of entrepreneurship educational
system
To describe components of entrepreneurship educational
system, we can use organizational elements model
(OEM).
Organizational elements model (OEM)
The OEM was developed by Roger Kaufman as a tool
that can be used to identify the different elements within a
system. A system is “a set of interrelated components
that work together to achieve a common purpose”
(Porter, 2005a). The OEM also “provides a framework of
designing and implementing effective means to achieve
desirable end results” (Chyung, 2005).
The OEM model is consisted of five elements: inputs,
processes, products, outputs and outcomes. These
elements are used to link the resources within an organization
to the processes that it must develop to attain the
ends.
The OEM model can be used when an organization
has identified a performance or instructional gap within its
personnel or processes, in order to determine what
means are required to assure a successful attainment of
the ends. The following (Table 1 and Figure 1) visually
describes what the OEM model is and shows its five
elements . Before using the OEM model, it is important for
an organization to understand the difference between the
means and ends. The means are the inputs and processes
which the organization can use to obtain an end.
The ends are the by-products of the means to the
organization and to society.
The OEM model also takes into account three different
types of need levels, a mega level (or societal level), a
macro level (or organizational level), and a micro level (or
individual/small-group level). These needs allow an
organization to identify the different gaps of achieving the
end-result.
The OEM can be used by identifying a gap within an
organization and applying the above model to determine
the needs of the organization in getting an end. The
organization can then add the following elements to the
model and determine gaps within each element.
Elements of model
1. Inputs : these are the raw materials
2. Processes: this is the how-to-do-it

Table 1. Organizational elements model.
Means
Ends
Rahmati et al. 7677
i. Inputs(raw material)
Organizational efforts
ii. Processes (how to do it)
i. Products (learner/instructor accomplishments)
Organizational results
ii. Outputs (organizational accomplishment
Internal to organization
iii. Outcomes (effects in and for society) Societal impact External to organizational
Figure 1. Dimensions, components and indicators of conceptual model.
3. Products: these are the results while in the processes
4. Outputs: these are the organizational accomplishments;
the products delivered to society
5. Outcome: these are the effects in and for society
(Porter, 2005b).
Although this approach addresses educational system
comprehensively, in this research, six components are
identified, executed and prioritized in conceptual model
based on the experts' survey. These components are:
1. Human resource in education system
2. Financial resources and facilities
3. Plan and executive method
4. Amount of Graduates in each period
5. Job Creation for him\herself and others
6. Rules and regulations
Important variables defined
(I) Policy: decisions made by governments which determine
an aim and tools to achieve it (Hewlett, 2001).
Decisions and policies are taken by various public
authorities like Parliament, government and judiciary
which protect public interests (Alvani, 2006). (II) Entrepreneurship:
according to definition, entrepreneurship is the
use of opportunities to create changes. Entrepreneurship
means to establish a start-up firm through innovative and
risk-taking management (Moghimi, 2006). (III) Entrepreneurship
education: it means educating and training
business skills (including both specialized and general
educations) provided for various social levels. Based on
studies in Iran, there are two kinds of entrepreneurship
education: formal education and informal entrepreneurship
education. In this article we address formal education

7678 Afr. J. Bus. Manage.
that encompasses entrepreneurship education in high
schools and universities of Iran. Of course, informal education
in entrepreneurship deals with short term periods
of education, which is not considered in this article. (IV)
Policy making for entrepreneurship education: considering
aforementioned definitions, entrepreneurship education
includes all efforts, plans and programs executed
in various countries to increase tendency toward
entrepreneurship. Therefore, the policymaking process in
this field includes the steps of formation, execution and
evaluation the policies in entrepreneurship education. In
this article we address all three stages of policy making.
Conceptual framework
Based on evaluations in comparative studies, there are
many models and paradigms to train entrepreneurship.
To draw a conceptual framework of this research project,
dimensions, components and indicators of policymaking
in entrepreneurship education should be determined and
drawn in the format of schematic models. To draw this
model, it is necessary to have an exploratory study.
Therefore, conceptual framework is drawn by using
following methods:
1. Interviewing 10 entrepreneurship experts/professors.
2. Studying the documents while studying the documents
on policymaking literature, a broad study was conducted
regarding public policies on entrepreneurship development
in Iran and other countries (20 countries) and
entrepreneurship authorities in Iran.
To extract the challenges, it can be said that there are
many dimensions, components and indicators in designing
policymaking model. In this conceptual model, the
first dimension is entrepreneurship education, the second
one is policymaking and the third one includes policymaking
authorities. The title, role and status of each
authority in policymaking process are determined.
METHODOLOGY
Considering the type and nature of questions and data collection
methods, this research is an applied one in terms of utilization,
exploratory in terms of objective, longitudinal in terms of time (a five
year period form 2004 to 2009) and a mixture of qualitative and
quantitative methods in terms of data collection technique. Expert
selection method was used to measure research model. Factors
and indicators are tested by questionnaire.
To answer the questions, respondents should determine the role
of each policymaking institution in status quo and desired status
regarding each component of entrepreneurship education system in
each steps of policymaking. Hence, respondents should choose a
number between zero and six (from 0 = no role to 5 = high role).
Research scope
In terms of thematic scope, present research project aims at analyzing
policymaking in entrepreneurship formal education in Iran.
Additionally, the dimensions and types of entrepreneurship
education, policymaking institutions, entrepreneurship education
system components and policymaking steps are considered in this
research project. In term of time scope, this research has
addressed a five year interval (2004 to 2009). In terms of spatial
scope, required data are collected from 16 relevant institutions in
Tehran, since Iranian entrepreneurship education policymakers are
concentrated in the capital city.
Data collection methods
The main data collection method in present research project is to
study the documents/evidences and to fill in the questionnaire. If
necessary, documenting and library methods are also used to
complete research literature. Relevant documents and evidences
include:
1. The document of the fourth development plan of Iran
2. The 20year outlook (vision) of Islamic Republic of Iran
3. The structures and terms of references for ministries and relevant
organizations such as Labor and Social Affairs Ministry, Labor and
Social security Institute, etc in order to identify those institutions
which affect the policymaking in entrepreneurship education.
4. Minutes and approvals of relevant executing institutions on
entrepreneurship education.
The aforementioned documents and evidences are initially studied
to review and identify relevant policies and then to recognize the
authorities of developing, executing and evaluating the policies in
order to gather policymaking methodology in this field.
Statistical population and sample
Regarding the special traits of this research, statistical sample is
comprised of experts and connoisseurs of policymaking in entrepreneurship
education system, including managers and experts with
B.A., M. A. and Ph. D. degrees in policymaking organizations and
institutions. The statistical sample is consisted of 188 experts from
16 organizations.
Since the sample is not extensive, a questionnaire was distributed
among all members with the objective of enumeration.
Despite the persistent pursuing, only 102 questionnaires were
collected. This number is sufficient based on Morgan's table. On
this basis, all analyses were conducted by statistical analysis
techniques.
Data analysis and assumption tests
After collecting the data via referring to documents and evidences
by using qualitative analytical techniques such as content analysis
technique, all data were extracted and were categorized by
considering research theoretical framework. The data obtained from
experts' survey was analyzed by using relevant tests and software
such as SPSS and Microsoft Excel.
To analyze the data obtained from questionnaires, statistical
techniques such as Freedman analytical testing variance and
compare means T-Test (Student T-Test) were used. Through these
statistical techniques, we could generalize the statistics of sample
to parameters of population.
Validity and reliability of data collection instruments
To rely upon the validity in designing questionnaire items, connoisseurs
were used final development and completion so that

Table 2. Studying the demographical characteristics of respondents.
S/No. Institution Frequency Percent
1 Private sector (institutes) 9 8.82
2 Jahade Daneshgahi 6 5.88
3 Entrepreneurship faculties and departments 9 8.82
4 Karad 3 2.94
5 Scientific parks and incubators 4 3.92
6 Other universities 13 12.75
7 Parliament 3 2.94
8 Ministry of planning and monitoring 6 5.88
9 Labor and social security institute 10 9.80
10 TVTO 8 7.84
11 Ministry of education 4 3.92
12 Ministry of higher education 6 5.88
13 Ministry of Labor and social affairs 10 9.80
14 municipalities 4 3.92
15 Ent. centers in universities 5 4.90
16 High schools 2 1.96
Total 102 100
similar questions were designed for each component and indicator
of the conceptual model.
By using Chronbach's alpha, the reliability of the questionnaire is
87% which shows high reliability and validity.
RESULTS
Here, at first, we present descriptive statistic of the study.
Noteworthy, SPSS and Microsoft Excel software are used
to draw tables and graphs.
As seen in Table 2, from 190 questionnaire distributed
between population, 102 questionnaires were filled in and
returned. Following this, 16 institutions were asked which
managers and experts shape the research statistical
sample. Considering the importance of policymaking
institutions, just this demographical trait is provided here.
Considering research objectives and questions and
according to experts, it is illuminated in the analysis and
conclusions segment on how the status quo and the
desired status in entrepreneurship formal education are
different and what are the challenges and guidelines.
The policies of government in entrepreneurship
development in Iran
Arguments on entrepreneurship, particularly entrepreneurship
training, do not have a long life. In Iran, due to
the consideration of entrepreneurship in third and forth
national economical, social and cultural development
program, entrepreneurship development plan in domestic
universities was approved which led into activities in
some universities. Although training is not effective in
developing entrepreneurship and creating businesses by
Rahmati et al. 7679
itself, it is highly vital as a component of development
system (Talebi, 2005). Also, studies in USA, Europe and
South East Asia show that entrepreneurship trainings can
have a remarkable impact if they are provided along with
facilitating and encouraging operations (Jahanian, 2007).
Some policies in Iran have been formulated to support
entrepreneurial activities such as:
1. Entrepreneurship education for all ages
2. Various loans for entrepreneurship in different fields
3. Facilitating the conditions for those who start a new
business
4. Some structural changes in government to support
entrepreneurs easily
5. Fostering entrepreneurial culture
6. Holding festivals at a national level to glorify entrepreneurship
dignitaries (Moghimi, 2002).
Recognized challenges
Having analyzed the questionnaires, the challenges discerned
by experts' were extracted. One of the greatest
challenges in policy making system refers to the gap
between current and desired situation of institutions at
experts' view point in this field. These institutions are faroff
their desired role. To prove this claim, study results
have been presented in Table 3.
To answer the research question "how much is the gap
between status quo and desired status in entrepreneurship
education", single sample T-Test is used.
Table 3 is drawn to show the distance between status
quo and desired status which indicates the role of each
institution in each step of policymaking in terms of
entrepreneurship education components.

7680 Afr. J. Bus. Manage.
Table 3. The distance between status quo and desired status in entrepreneurship education
Institutions
Human resource in education
T-Test for policy formation T-Test for policy execution T-Test for policy evaluation
Financial resources
Plan and executive method
Amount of graduates
Job creation
Rules and regulations
Planning and strategic monitoring directorate 1/80 2/10 1/60 1/50 2/50 1/90 2/50 2/20 1/80 1/70 2/40 1/30 1/70 2/20 1/70 2/00 2/40 1/60
Parliament 2/20 2/10 2/00 1/60 1/90 1/70 2/30 2/10 1/80 1/30 2/30 1/80 1/80 2/50 2/00 1/60 1/80 2/20
High schools 2/00 1/80 1/70 1/90 1/40 1/80 2/20 1/50 1/80 1/90 1/40 1/70 2/10 1/80 1/80 2/20 1/90 1/30
Ministry of Education 2/40 1/80 1/80 2/10 2/10 1/60 2/60 1/90 2/00 2/00 2/00 1/80 2/40 2/10 2/20 1/90 2/30 2/00
Technical and occupational centers 1/90 2/10 1/70 2/00 1/90 2/10 1/90 2/20 2/10 2/10 2/20 1/50 2/10 2/40 2/50 2/30 2/30 1/80
Jahade Daneshgahi 1/70 1/70 1/40 1/50 1/70 1/90 2/00 1/90 1/70 1/40 2/10 1/80 2/00 1/90 1/60 1/70 2/00 1/60
Entrepreneurship faculties and departments 1/80 1/60 1/40 1/90 1/80 2/30 1/80 2/00 2/10 1/70 1/90 1/80 1/90 2/50 2/00 1/70 1/90 2/30
Karad (entrepreneurship education in universities) 1/80 1/50 1/60 1/60 1/40 1/80 1/70 1/50 1/50 1/60 1/60 1/30 1/80 1/50 1/40 1/50 1/20 1/20
Scientific parks and Incubators 2/00 1/90 2/20 1/70 1/80 1/80 2/50 1/70 2/40 2/00 1/70 1/50 2/30 1/80 1/90 2/10 1/80 1/70
Other universities 2/10 1/90 1/90 2/00 1/90 2/40 2/00 1/50 1/60 1/60 2/10 2/50 2/00 1/70 2/00 2/20 2/50 1/80
Scientific parks and incubators 1/80 1/80 1/60 1/30 1/50 1/80 1/90 1/40 1/90 1/90 1/90 1/80 1/60 1/70 1/60 1/80 1/90 1/80
GEM in Iran 1/50 1/70 1/50 1/60 1/80 1/80 2/20 1/90 1/50 1/30 1/50 1/00 2/50 1/40 1/10 1/80 1/50 2/00
Ministry of Higher Education 2/30 1/90 2/20 2/20 2/20 2/00 2/20 1/80 2/20 2/50 2/10 2/10 2/40 2/20 1/70 2/50 2/10 2/00
Labor and social security institute 1/80 1/90 1/80 1/80 1/80 1/90 2/00 1/80 2/20 1/90 1/80 1/90 1/80 1/80 2/00 1/70 1/80 2/40
Ministry of Labor and Social Affairs 1/80 1/40 1/50 1/50 1/50 1/20 1/70 1/40 1/50 1/50 1/30 1/80 2/30 1/80 1/60 2/00 1/50 1/70
Ent. Centers in universities 1/10 1/90 1/00 1/00 1/70 1/70 1/40 1/90 1/50 1/20 1/80 1/20 1/90 1/80 1/70 1/40 2/00 1/70
As mentioned within the research questions and
objectives, comparing the status quo with the
desired status of policy-making institutions has
been the objective of this research. The comparison
results show that some institutions are not
active in policy-making for entrepreneurship formal
education at the current status while they can
Human resource in education
Financial resources
Plan and executive method
Amount of graduates
play a very active role at the desired status.
The numbers written in the table next to the
institutions' names describe the amount of gap
between the status quo and the desired status. In
fact, the higher number of an institution shows
that it has more challenges. Therefore, the first
and the second question of the research are
Job creation
Rules and regulations
Human resource in education
Financial resources
Plan and executive method
Amount of Graduates
Job creation
Rules and regulations
answered here. And the third question of the
research in which the experts are surveyed will be
mentioned later.
Arguments
Policy-making for the entrepreneurship formal

education might involve plenty of challenges. Some of
these challenges are associated with policy-making institutions.
They also may be associated with the regulations,
job creation, the number the graduates, executive
programs, and plans and financial or human resources in
the education system. Therefore, in this research project,
the challenges of institutions in each of the abovementioned
components are considered and recognized
based on the experts opinions and some recommendations
are made about them. Most of the recognized
challenges are about the policy-making in job creation,
human resources and the regulations of the institutions.
In Table 3, higher rank of each institution shows that it
has more distance from its actual position. For example,
Planning and Strategic Monitoring Directorate of Presidency
has a high distance from its position in evaluating
HR policies. Other challenges are:
1. The lack of a specific organization in the field of
policymaking and even if it existed, it would be left
unaccompanied by other institutions.
2. The lack of a certain policy on defined indicators for
various dimensions of entrepreneurship education
3. The lack of knowledgeable, experienced and skilled
manpower in entrepreneurship and policymaking who
can train entrepreneurship.
4. The weakness of education policies in considering
specialized educations and emphasis on general
entrepreneurship education
5. Respecting efficiency rather than effectiveness in
evaluating adopted policies
6. Not considering the execution and evaluation in policy
formation step
7. The weakness in policy evaluation system due to the
lack of exact and comprehensive data and statistics
8. Centralization and avoidance of assigning necessary
power to institutions and provinces in executing the
policies
9. Instability in adopted policies
10. Non-execution of devised policies
11. The lack of proper policies in selecting and utilizing
education policies appropriate to the current national
conditions
RECOMMENDATIONS
Throughout the research and according to the discerned
challenges, some recommendations are made by the
experts that can decrease the challenges of the entrepreneurship
formal education effectively. These recommendations
which refer to the recognized challenges are as
follows:
1. Selecting a policymaking institution as the main
custody of policymaking in entrepreneurship education
2. Establishing a central headquarter to coordinate
entrepreneurship centers
Rahmati et al. 7681
3. Considering and emphasizing the execution and
evaluation of the policies when developing them
4. Making policymakers believe the status and importance
of entrepreneurship in social growth and
development
5. Having policymakers notice the systemic relationship
between entrepreneurship and other needed assistance
to entrepreneurship
6. Considering enculturation, announcement, and advertisement
to execute adopted policies
7. Developing proper policies to organize entrepreneurship
trainers and teachers
8. Emphasizing the knowledge and experience in the
policies of recruiting the training staff of the programs
9. Developing needs analysis policies targeted at learners
and audience of courses and adjusting the courses
based on the competencies and capabilities of learners
10. Developing the national document of
entrepreneurship education policies
11. Reforming baking official regulations to promote and
enhance the support for trained entrepreneurs
12. Emphasizing the process by orientation in policymaking
system of entrepreneurship education
13. Determining the exact role and status of each
institution in policymaking process of entrepreneurship
education
14. Developing executive regulations along with provided
educations to develop entrepreneurship culture among all
people
15. Thematic classification of policymaking institutions,
and determining the role of each institution based on a
special theme.
16. The governance in policymaking should be taken by
government and the executive
administration should be assigned to local and private
sectors
17. Policymaking to train entrepreneurship since childhood
in families, media and journals
18. Designing a local entrepreneurship education paradigm
by considering national requirements and conditions
19. Considering the evaluation of adopted policies in the
light of an effective education evaluation system
20. Developing policies to adapt and localize entrepreneurship
education materials
21. Undertaking surveys of learners and graduates as a
tool for effective policy evaluation
22. developing policies to support graduates of the
courses
23. Designing a system to evaluate the effectiveness of
entrepreneurship education
24. Designing incentive mechanisms for job creation as
an effective entrepreneurship education criterion.
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African Journal of Business Management Vol. 5(17), pp. 7683-7690, 4 September, 2011
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM10.863
ISSN 1993-8233 ©2011 Academic Journals
Full Length Research Paper
Understanding the mediating effect of cognitive and
emotional satisfaction on customer loyalty
Maznah Wan Omar 1 , Mohd Rizaimy Shaharudin 1 , Kamaruzaman Jusoff 2 *, and
Mohd Noor Mohd Ali 3 ,
1 Faculty of Business management, Universiti Teknologi MARA,Peti Surat 187, 08400 Merbok, Kedah, Malaysia.
2 Department of Forest Production, Faculty of Forestry, Universiti Putra Malaysia, 43400 UPM Serdang,
Selangor, Malaysia.
3 Faculty of Applied Science, Universiti Teknologi MARA, UiTM Pulau Pinang, 13500 Permatang Pauh,
P. Pinang, Malaysia.
Accepted 6 July, 2011
Studies have proven that businesses have to incur new and additional cost in order to attract new
customers as compared to retaining existing customers. Retaining loyal customers are crucial as they
eventually contribute to the increase in business organization’s revenue and are more likely to occur in
a form of word-of-mouth (WOM). In the compound and vibrant Malaysian home computer retail market
today, customer loyalty (CL) through word-of-mouth marketing tends to occur very slowly and is limited
geographically but is a very potent method of marketing. The influence of cognitive and emotional
satisfaction on the relationship between salesperson presentation skills and CL through intention to
promote by WOM is vital. This will then lead to increased benefits for the organization in the form of CL.
The cognitive evaluation of customer satisfaction (CS) was found to explain CL in a retail setting more
than the emotional reaction. This finding holds importance to those retailers who have been able to
generate high expectations in the eyes of their customers.
Key words: Adaptive selling skills, sales presentation skills, customer satisfaction, customer loyalty.
INTRODUCTION
As competition deepens, products and services become
more indistinguishable, and markets become established,
it is becoming increasingly tougher for companies in
retailing industries to distinguish themselves from other
stores. Simply offering customers with technical solutions
to problems does not be sufficient anymore to be competitive
and obtain and retain market share. Various valueadded
services, which commence before the actual
operation begins, had gone far beyond it, so as to stay
competitive and develop customer loyalty (CL). Research
and business customs have shown that upholding
*Corresponding author. E-mail: kamaruz@putra.upm.edu.my,
kjusoff@yahoo.com. Tel: +603-8946 7176.
Abbreviations: CL, customer loyalty; WOM, word-of-mouth;
CS, customer satisfaction.
customers through value-added services costs less than
obtaining new ones (Ramanathan, 2011). Studies conducted
by Vesel and Zabkar (2009); Yau et al., (2000)
have found that loyalty in customers eventually will lead
to a long-term relationships that comes is a form of
recurring purchase.
Prior researchers have found that the cost of attracting
new customers is much higher than the cost of retaining
old customers. Thus, the issue of keeping customer’s
loyalty is crucial in any business industry (Liu et al., 2011;
Athanasopoulou, 2009; Lin and Wang, 2006; Rauyruen
and Miller, 2007; Hu and Hwang, 2006; Athanasopoulou,
2009).
A prevailing belief holds that an essential key to
performance rests with the ability to sustain customer
relationships (Vesel and Zabkar, 2009). Correspondingly,
as relational value continues beyond price, customer
bond are particularly effective when involved in long-term
relationships (Yuksel et al., 2010).

7684 Afr. J. Bus. Manage.
LITERATURE REVIEW
Salesperson Behavior Performance
In recent years, a number of authors have been confronted
with this issue of the changing role of the sales force.
Up-and-coming trends of the extent and scope recorded
above require a re-evaluation of the activities that salespeople
must execute in order to successfully build and
manage CL. Marshall et al. (1999), interviewed a diversity
of professional salespeople to give evidence for 49 new
sales activities that were not pointed out in Moncrief’s
(1986) original list. These latest activities fall into the
following main categories: communication technology,
selling technology, activities related to adaptive and
consultative selling, and team-oriented activities. Many of
the specific activities within these categories involve skills
and content knowledge dissimilar from those traditionally
observed in the past as key salesperson success factors.
This study therefore will consider how cognitive and
emotional satisfaction mediates the relationship between
salesperson presentation skills and customer’s intention
to word-of-mouth (WOM). These situational factors have
not been considered in prior research and provide new
avenues for examining salesperson presentation skills in
Malaysian market and its consequences. Additionally, as
most studies have considered salespeople as their unit of
analysis, this study will add to the small but imminent
body of research that investigates performance and
effectiveness relationships at the customer’s level.
Formation of loyalty through satisfaction
It is by and large believed that satisfaction leads to repeat
purchase and positive WOM recommendation, which are
the main indicators of loyalty. Previous studies have
establish satisfaction to be an extensive reaction which is
exaggerated through good quality of service, good quality
product, price perceived by customers and the relative
and personal elements that is projected by the business
provider (Liu et al., 2011). Marketing literature has paid
much attention to the relationship between customer
satisfaction (CS) and CL (Chi, 2005). A number of studies
have confirmed a significant positive relationship between
CS and CL /retention (Chi, 2005). If consumers are
satisfied with the product or service, they are more likely
to carry on purchasing, and are more willing to spread
positive WOM.
Salesperson presentation skills
Churchill et al. (1997) define selling skill as a salesperson’s
“learned proficiencies at performing job activities,”
and describe Salesperson presentation skills as the skills
that are associated to successfully conducting the personal
selling process (that is, the series of interconnected
steps that salespeople generally use to link with the
influence customer).
Recognizing the importance of salesperson presentation
skills (Plouffe et al., 2010; Williams and Plouffe,
2007; Marshall et al., 2003) gathered and ranked sales
manager perceptions of “success factors” that contribute
to salesperson job performance. They report that managers
feel that six specific salesperson presentation skills:
listening, adaptive selling, handling objections, closing,
negotiating, and prospecting (in descending order of perceived
importance) are highly important to salesperson
performance (Johlke, 2006). Accordingly, this group of
salesperson presentation skills will be used at the heart
of the hypothesized model.
Customer satisfaction
The importance of CS to the success of consumer goods
manufacturers (Burns and Neisner, 2006) and to the
success of retailers (Darian et al., 2001) has been well
documented. CS is regarded as a primary determining
factor of repeat shopping and purchasing behavior. The
greater the degree to which a consumer experiences
satisfaction with a retailer, for instance, the greater the
probability the consumer will revisit the retailer (Burns
and Neisner, 2006; Wong and Sohal, 2003).
In summary, we note the distinction between
transaction-specific and overall satisfaction, and for this
study, we adopt the broader definition of satisfaction
whereby the overall measure is an aggregation of all previous
transaction-specific satisfaction, and involves both
cognitive and affective components. Recently, the overall
measure has been shown to be a better predictor of
repurchase intentions (Jones and Suh, 2000).
Research framework and hypotheses
Based on the review of literatures concerning the study
variables on salesperson presentation skills, CS, and
customer’s intention to, the theoretical framework for this
study was developed based on Oliver’s (1997) Cognitive-
Affective-Conative Behavior pattern model. This research
model has been adapted and used in this study.
Relationship between salesperson presentation skill
and Intention to WOM
Although a customer’s personality and the employee’s
customer orientation were considered an important antecedent
to relationship strength, salesperson presentation
skill rather than his/her personality would perform a
greater part in determining relationship strength (Seo et
al., 2008). Salespersons are social actors who learn
behaviors that are appropriate to the positions they take
up (Kassim and Abdullah, 2008). In other words, salesperson
can be motivated to adapt their behavior to
situational requirements in spite of personal preferences

(Deng et al., 2010).
To date, there is a lack of studies investigating the
numerous aspects of service that are imperative to
customer retention (Maznah et al., 2009)? Furthermore,
the different outcomes (i.e. attitudinal and behavioral) of
relationship strength are left predominantly unexplored in
the relationship marketing literature. In addition, there is a
lack of studies that explore the impact of factors such as
salesperson presentation skill on customer’s intention to
WOM.
Conclusively, there is little empirical work investigating
customer relationship economies, which is the link
between attitudinal measures (that is, salesperson presentation
skill, CS) and behavioral measures (that is, CL,
intention to repurchase, intention to WOM, and long-term
customer relationship profitability), Wong and Sohal
(2006). Therefore, in line with the above reasoning’s and
findings, it is conjectured that:
H1: There is a direct positive relationship between salesperson’s
presentation skills and intention to WOM.
Relationship between CS and customer’s intention to
WOM
CS is important to marketers because it is usually
assumed to be a significant determinant of recurring
sales, positive word-of-mouth, intention to repurchase,
and CL. It is worthy to consumers because it reflects a
positive outcome following the outlay of limited resources
and/or the positive accomplishment of prior needs. As a
consequence, maximizing satisfaction is seen as a
significant objective, collectively for both the firm and the
consumer (Mouri, 2005).
Likewise, theory suggests that satisfaction feeds back
into the system to influence ensuing intentions and behaviors
(Wallace et al., 2004; Deng et al., 2010). CS with
the shopping experience should reflect well on the retailer.
An increase in satisfaction has been shown to result in
increased CL (Donio et al., 2006). From the above
arguments, it is hypothesized that:
H2: There is a direct positive relationship between customer
satisfaction and intention to word-of-mouth.
H2a: There is a direct positive relationship between
cognitive satisfaction and intention to word-of-mouth.
H2b: There is a direct positive relationship between
emotional satisfaction and intention to WOM.
The mediating effect of CS on salesperson
presentation skill and customer’s intention to WOM
relationship
Overall satisfaction with an experience does lead to CL
(Vesel and Zabkar, 2009). Deng et al. (2010) argue that
CS is imperative to the marketer because “it is generally
assumed to be significant determinant of repeat sales,
Omar et al. 7685
positive WOM, intention to repurchase, and CL”. Similarly,
Yuksel et al. (2010) have also argued that “satisfaction
can be thought of as an important determinant of CL”,
while Omar et al. (2007) argue that it is satisfaction with a
brand or service that leads to CL. Maznah et al. (2009)
have established in their study that there is a significant
association linking cognitive satisfaction with WOM.
Cognitive satisfaction in due course will lead to positive
WOM and thus maintaining CL.
This view is also supported by Han and Back (2008).
Back (2005) empirically show that brand and service loyal
customers had a lower probability to substitute brands or
service due to higher levels of satisfaction. On the basis
of the aforementioned findings, CS is indicated as having
a function and acting as a mediator in the link between
salesperson presentation skills and CL (Deng et al.,
2010). Therefore, in line with the above reasoning’s and
findings, the following were hypothesized:
H3: CS mediates the relationship between salesperson
presentation skills and intention to WOM.
H3a: Cognitive satisfaction mediates the relationship
between salesperson presentation skills and intention to
WOM.
H3b: Emotional satisfaction mediates the relationship
between salesperson presentation skills and intention to
WOM.
METHODOLOGY
Sampling design
To have a representative finding, the sampling technique used must
be objective. This is an important effort adopted by most researchers
in order to furnish a finding pertinent to the general. To
choose the sample for this study, probability random sampling was
used.
A probability sample is necessary if the sample is to be representative
of the population (Pallant, 2005). Therefore, a two-stage
systematic sampling technique is employed in this study.
Population and sample size
In determining the sample size for this study, sample size selected
was based on the criteria set according to Sawyer and Ball (1981).
According to Sawyer and Ball (1981), it is estimated that a proportion
of 13% of the explained variance to effect size values is a
medium effect size for regression analysis. One common measure
of effect size is eta squared. Eta squared represents the proportion
of variance of the dependent variable that is explained by the
independent variable (Pallant, 2005).
According to Cohen (1988), the strength of the effect size are
interpreted as follows; 0.01 = small effect size, 0.06 = moderate
effect size, and 0.14 = large effect size. Thus five independent
variables were used and using the statistical significance of 0.05
(95% confidence level) and an effect size values of .13 is found to
be truly sufficient and not by chance.
Goodness of measure
In determining the goodness of data for the study, factor analysis

7686 Afr. J. Bus. Manage.
Table 1. Reliability coefficients for the variables in the study.
Construct/Variable Number of item Cronbach’s alpha Mean Standard deviation
Sales presentation skill/knowledge 3 0.75 3.78 0.72
CS/ Emotional satisfaction 4 0.84 4.10 0.64
Cognitive satisfaction 4 0.76 3.85 0.58
Customer loyalty/WOM 2 0.70 3.93 0.59
Note: All items used a 5-point Likert scale. 1, Strongly disagree; 5, strongly agree.
and reliability analysis were performed. Factor analysis was used to
assess the convergent validity of the items used in the questionnaire
while Cronbach’s alpha was performed to examine the
internal consistency of the factors obtained. The result of the
reliability test are presented in Table 1.
The result of the reliability analysis sum up in Table 1 confirmed
that all the scales shown, reveal a high internal consistency and
reliability with Cronbach’s alpha values higher than the minimum
perimeter, (Cronbach’s alpha > 0.60).
RESEARCH FINDINGS AND DISCUSSION
Hypotheses testing
Multiple regression tests were conducted in order to test
the relationship between the predictor variable and the
criterion variable. Respondents’ demographic variables
such as salesperson are younger or older than the customers,
gender, and ethnicity were statistically controlled
(Connel et al., 2003; Hemdi, 2006). Hence, these variables
were entered into the regression equation in the first
step. The predictor variables were entered in the second
step. The following Table’s below summarizes the result
of the analyses.
Regression analysis with control variables
The relationship between salesperson presentation
skills and intention to WOM
From Table 2, salesperson presentation skills have positive
and significant association with intention to WOM;
salesperson presentation skills (β = .16, p < .01), and
thus, the results provide evidence that H1 is fully
supported.
The relationship between CS and Intention to WOM
To test for hypothesis 2a, another set of regression analysis
was performed. The purpose of this analysis is to
test for the effect of cognitive satisfaction on intention to
WOM. The predictor variable was cognitive satisfaction.
The criterion variables relates to intention to WOM.
Salesperson’s demographic variables such as younger or
older than the customers, gender, and ethnicity were
statistically controlled. Hence, these variables were
entered into the regression equation in the first step.
Cognitive satisfaction was entered in the second step.
Table 3 summarizes the results of the hierarchical regression
analysis. These results provide evidence that H2a is
accepted.
Additionally, to test for H2b, another set of regression
analysis was also performed. The purpose of this
analysis is to test for the effect of emotional satisfaction
on intention to WOM. The predictor variable was emotional
satisfaction. The criterion variables relates to intention
to WOM. Salesperson’s demographic variables such as
younger or older than the customers, gender, and ethnicity
were statistically controlled. Hence, these variables
were entered into the regression equation in the first step.
Emotional satisfaction was entered in the second step.
Table 4 summarizes the results of the hierarchical regression
analysis. These results provide evidence that H2b is
accepted.
The mediating effect of cognitive satisfaction on the
relationship between salesperson presentations
skills and intention to WOM
H3a posits that cognitive satisfaction mediates the
relationship between salesperson presentation skills and
intention to WOM. Results in Table 4 shows that none of
the control variables had significant influence on intention
to WOM in step 1, however, salesperson presentation
skills (β= .25, p

Table 2. Results of hierarchical regression analysis of salesperson presentation skills on
intention to WOM.
Predictor
Step 1: Control variables
Model 1
Std. β
Model 2
Std. β
Younger or older -0.05 0.01
Gender -0.01 -0.01
Ethnicity 0.09 -0.02
Step 2:
Sales presentation skills 0.16**
R² 0.01 0.43
Adj. R² 0.01 0.42
R² Change 0.01 0.42
F-Change 1.09 68.19**
Note. Significant levels: *p

7688 Afr. J. Bus. Manage.
Table 5. Summary of mediating effects of cognitive satisfaction on the relationship between Salesperson presentation skills and
intention to WOM.
Predictor
Significant level and beta
before mediating (Regression
Equation II – DV on IV)
Criterion variable
Significant level and beta after
Mediating (Regression Equation
III – DV on IV and MV)
Step 1 Step 2 Step 1 Step 2
Control
Younger or older -0.05 0.02 -0.05 -0.00
Gender 0.00 0.00 -0.01 -0.01
ethnicity 0.10 -0.01 0.06 0.01
Result
Independent
Salesperson presentation skills 0.25** 0.07 Full mediation
Mediating
Cognitive satisfaction 0.31**
R² 0.01 0.43 0.01 0.49
Adj. R² 0.00 00.42 -0.00 0.48
R² Change 0.01 0.42 0.01 0.49
F change 1.09 68.19** 0.70 70.39**
Note: Significant levels: *p

WOM. The comparison can be seen in Table 6. These
results provide evidence that hypothesis H3b is partially
supported.
DISCUSSION
H3 deals with the mediating role of CS in the relationship
between salesperson presentation skills and intention to
WOM.
Results of this study found that cognitive satisfaction
partially mediates the relationship between sales presentation
skills on intention to WOM. This implied that sales
presentation skills have an indirect impact on customer’s
intention to WOM via cognitive satisfaction. This result
suggests that salesperson who posses an overall sales
presentation skill, plus an ability to applied these skills
during their interaction with the customers is vital in
enhancing customers intention to WOM.
The result of this study is consistent with the findings of
previous study by Shemwell et al. (1998); Vesel and
Zabkar (2009); Solomon et al. (2002); Bennett and
Rundle-Thiele (2004); Oliver (1997); Yu and Dean (2001),
which suggest that satisfaction is a more central
construct which mediates the effect of service quality
perceptions on behavioral intentions and other outcomes.
The published research in the field of service marketing
universally acknowledges a strong positive correlation
between salesperson service quality and satisfaction,
some early works depicted salesperson service is perceived
as an antecedent of satisfaction (Levy and Weitz,
2009).
Thus the results of this study suggest that efforts to
increase customer’s loyalty should focus on enhancing
customer’s cognitive satisfaction during the salesperson/
customers interaction, this is in line with research
conducted by Egan (2000); Mcllroy and Barnett (2000);
Bennet and Rundle-Thiele (2004). Special attention
should be given to the enhancement of sales presentation
skills, which were found to have significant effects
on customer’s intention to WOM.
Limitations and future research
Future research may benefit if some limitations of this
study are noticed. Although we have examined a number
of important issues in this study, there are several
limitations inherent in the study. Firstly, only computer
retailers in the northern states of Malaysia were
examined. As a consequence, and regardless of the fact
that the customers of the firm represent a wide range of
industries, the generalization of the findings to other retail
organizations is limited. However, as noted by Foster and
Cadogen (2000), the generalization of studies undertaken
in a single firm must be viewed with some skepticism; the
results are likely to have increased internal validity.
Clearly future research which provides more
Omar et al. 7689
information on the external validity of our study would be
most welcome.
Conclusion
The present study confirms that cognitive satisfaction
was able to explain customer’s intention to WOM in a
retail setting in the Malaysian market. The finding suggest
that computer retailers whose customers possess high
expectations on the salesperson’s sales presentation
skills may need to place explicit attention on their
customers’ cognitive evaluations since their customers’
cognitive reactions to performance appear to contribute
to their assessments of satisfaction.
Finding in this study shows that, loyalty defined by
personal positive experience (that is, affective loyalty), is
most associated with WOM. Because person-to-person
communication is touted as “one of the most powerful
types of media”, and affective loyalty is the largest correlate
to WOM, therefore, successful business strategies
will have to include creating situations where emotional
attachments to services provided by the salesperson are
developed. Consumers who believe in the salespersons
or are involved in the purchase process tend to participate
in WOM because it enhances commitment to their
own attitude.
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