A Literature Review and Research Agenda - RESER

Service Productivity: A Literature Review and
Research Agenda
Bilal Balci 1 , Alicia Hollmann 1 , Christoph Rosenkranz 1
1 Goethe-University Frankfurt, Information Systems Engineering, Dept. of Econonmics
and Business Administration
Until now, there exists no universal approach for measuring the productivity
of services. Various factors have different impacts on service productivity,
ranging from the relationship between service providers and customers
to service quality. So far, only some of these factors have been investigated
in detail. The purpose of this paper is to describe, synthesize, evaluate,
and integrate the results of prior research on service productivity by conducting
a literature review. We selected 13 leading management and economic
journals, covering the period of time from 1980 to date. We created
an initial catalogue of existing approaches focusing on the measurement,
validation, and controlling of service productivity. We categorize, consolidate,
and discuss the relevant papers accordingly. Based on this, we highlight
open issues and possible venues for investigation. As our final result,
we develop an agenda for further research on the productivity of services.
1. Introduction
During the last decade, the service sector has been the fastest growing segment and
represents a major and increasing part in the global economy (Russell, 2009). The
significance of services for the prosperity of the world economy has been widely recognized
(Vuorinen et al., 1998; Rai and Sambamurthy, 2006). For example, bundles
of physical products and services are increasingly offered as an integrated solution to
the customer (Spring and Araujo, 2009). Until recently, services have mostly been
understood as value-enhancing “add-ons” for tangible goods. In contrast, the emerging
service-dominant logic regards goods as mere appliances for service delivery
(Lanza and Ude, 2010). A service involves at least two partners: a service provider
applying competence and a customer that integrates the applied competences with
other resources; therefore value is always co-created (Spohrer et al., 2007).
Smarter service systems serve customers better and create more opportunities for
win-win, or benefit-benefit, interactions that result in value co-creation for both service
providers and customers (Spohrer and Maglio, 2010). This pushes the focus on
service science as an emerging discipline of high relevance to both practice and academia
that fosters a cross-disciplinary approach to the study of service systems
(Chesbrough and Spohrer, 2006). Understanding, creating, managing, and delivering
successful services calls for systematic studies of managerial, technical, and social
issues (Johnston, 1999; Johnston, 2005).
One major issue in the context of service science is how service productivity can be
measured and assessed (Grönroos and Ojasalo, 2004). The measurement and the
improvement of productivity are currently well established in the manufacturing sector
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(Den Hartigh and Zegveld, 2011), where productivity is defined as a ratio of the outputs
of a production unit to its inputs. In contrast, measuring productivity of a service
is not yet as well-developed or well-established. The assessment of service productivity
is not trivial, as services (in contrast to manufacturing) may, to a large extent, be
understood as co-creating configurations of people, technology, as well as internal
and external stakeholders connected by value propositions and shared information.
As a consequence, no universal definition of service productivity exists (Hilke, 1989;
Maleri and Frietzsche, 2008; Reichwald and Möslein, 1995).
The present paper reviews the academic literature on the problems and issues of
measuring as well as understanding productivity in the field of services. The purpose
of this literature review is to disclose the current state of research on service productivity,
and to develop a research agenda for future research activities in this area. In
order to measure and evaluate the findings of our review, we created a catalog of
prevailing approaches already applied in both research and practice. Categories that
serve as necessary preconditions for the formation of the concept of service productivity
are further investigated. The aim of this catalog is to show and categorize the
current state of research in the field of service productivity. More specifically, the
goals of this study are:
to identify, categorize, and critically display the existing approaches used for
measuring and evaluating the productivity of services;
to provide an overview of the most important dimensions which influence
service productivity, as well as to estimate their respective importance for the service
productivity;
to form a concept corresponding to the level of knowledge of the present
work for services productivity.
The reminder of this paper is organized as follows. Section 2 introduces related work
that provides the foundation for our analytical framework and categories. We then
present the framework of our literature reviews in section 3, describe the literature
review procedure, and present our findings in section 4. Finally, we summarize our
findings and discuss future research directions.
2. Theoretical Background and Related Work
Until recently, the concept of service productivity has been conceptually underdeveloped
(Corsten, 2001). Simply transferring the traditional concept of productivity from
manufacturing and producing material goods to services is bound to fail because of
the immateriality and intangibility of services (Corsten, 2001). Immateriality refers to
both the intangibility of the output, as well as the heterogeneity of services. Furthermore,
the integration and involvement of customers in the value creation processes
is central to services (Lasshof, 2006). This means that the customer is inevitably a
key factor for service providers, which must also somehow be integrated and accounted
for in the concept of services productivity. This is in contrast to the classical
concept of productivity, where the customer usually is not an integral part during value
creation and the business processes often are a closed system (Grönroos and
Ojasalo, 2004). This implies that the quality of both material products and business
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processes can neither be perceived nor be influenced by the customer during the
value creation process.
Managing a service is different from managing goods and materials (Rust and
Chung, 2006). This is mostly due to the fundamental nature of a service – a service
is immaterial and relies on integrating customers’ inputs. Essentially, services management
is concerned with managing interactions of humans (Chase and Dasu,
2001). In the context of service management, the following five characteristics are
important aspects for assessing and measuring service productivity:
Managing demand: How related are customer demand and service productivity
(Grönroos and Ojasalo, 2004)? Because services cannot be produced
make-to-stock, predicting customer demand might be essential for assessing
service productivity.
Managing services: How related is well-structuredness and degree of standardization
of a service to service productivity (Lillrank, 2003)? Service providers
need to be able to provide customers with transparency regarding service
levels and service quality.
Gathering input and output: How important are input and output measurement
for service productivity? Especially the output of a service is hard to measure
(Grönroos and Ojasalo, 2004).
Service management is important for service productivity: Is service productivity
unrelated to quality? Service science has not created a parsimonious, general
and universal framework or concept for service productivity, yet. This is
especially the case with regard to the relation of productivity and quality.
Regarding the relationship between service productivity and service quality, some
researchers are of the opinion that productivity and quality are inseperable (Grönroos
and Ojasalo, 2004; Gummesson, 1998), whilst others argue that productivity is independent
from quality and can be used as an expression of qualitative yield that is
detached from the quantitative result (Lasshof, 2006; Nachum, 1999). Nevertheless,
all researchers agree that the customer determines the quality of a service (Lasshof,
2006; Grönroos and Ojasalo, 2004). To make the problem even more complicated, a
large number of different factors exist that are supposed to have an impact on service
productivity. Depending on the service process in focus, several different factors
might be crucial to determine service productivity, ranging from the relationship between
service providers and customers to service quality. Only a few of existing factors
representing service productivity have so far been subjected to research and
analysis.
Two main conceptualizations of service productivity exist throughout the literature,
which are exemplified by the models of Grönroos and Ojasalo (2004) and Lasshof
(2006) respectively. The concept of Grönroos and Ojasalo (2004) is based on the
specific characteristics of the service process, where service productivity is regarded
as a function of several factors of influence. The productivity of a service is determined
by how much the service supplier maintains the cost efficiency of his internal
structures (internal efficiency) and resources in the balance and in steering to the
quality perceived by the customers (external efficiency) and to the capacity utilisation
(capacity efficiency) (Grönroos and Ojasalo, 2004).
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Fehler! Verweisquelle konnte nicht gefunden werden. shows service productivity
according to Grönroos and Ojasalo (2004) as a function of internal efficiency, external
efficiency, and capacity efficiency. Grönroos and Ojasalo (2004) maintain that it is
meaningless to develop a service productivity concept based on the management of
internal efficiency and quantity of output only: “Because of the characteristics of services
and the service process, the management of external efficiency of the output
(how service quality is perceived) has to be an integral part of a service productivity
concept” (Grönroos and Ojasalo 2004, p. 417). A purely quantitative approach is not
performance-related for the evaluation of a service and does not describe how effective
a service contribution is. This means that the quality of the results is the focus.
Service productivity is understood mainly from the point of view of the service provider;
however, customer satisfaction plays a central role. The better the perceived quality
(as perceived by the customer – is the customer satisfied or not?) that is produced
using a given amount of inputs (service provider’s inputs and customers’ inputs), the
better the external efficiency is, resulting in improved service productivity (Grönroos
and Ojasalo, 2004).
Fig. 1: Service Productivity Model according to Grönroos and Ojasalo (2004).
A contrast to this model is exemplary given by the conceptualization presented in the
work of Lasshof (2006). The main difference is that service productivity is mainly
seen not from the service provider’s but from the customer’s perspective. Following
Lasshof (2006), service productivity from the client’s point of view is considered to be
independent of the quality component and as a measure for assessing the efficiency
used, so that the efficiency is referred to as a generic term for productivity.
Figure 2 illustrates the relationship between efficiency and productivity on the one
hand, and, on the other hand, the relationship between productivity and the customer’s
influence. Because the customer is a critical successful factor for the service
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provider, concurrent pursuing of the effectiveness and the efficiency must be guaranteed
(Lasshof, 2006). Lasshof (2006) further suggests a consideration of productivity
requires, at the same time, a focus on effectiveness in the form of customer satisfaction.
An increase of both variables simultaneously leads to a competitive advantage.
This concurrent pursuing expresses a concern with the efficiency, the effectiveness,
and the productiveness as independent dimensions, which can be evaluated separately
from each other (Lasshof, 2006).
Fig. 2: Service Productivity Model according to Lasshof (2006).
Figure 3 compares these two different views of service productivity. The one conceptualization
of service productivity considers productivity as a component of efficiency,
without neglecting effectiveness in the form of customer satisfaction. Consequently,
productivity is used as a quantitative expression for yield and is detached from the
qualitative component result (Fig. 3b, Lasshof, 2006). On the other hand, the other
perspective understands productivity as a single measure that integrates both effectiveness
and efficiency in itself (Fig. 3a, Grönroos and Ojasalo, 2004). According to
this view, productivity cannot be detached from the quality.
a) b)
Competitive advantage
Efficiency advantage
=
Provider benefit
Effectiveness advantage
=
Customer benefit
Productivity
Fig. 3:
Comparison of different Service Productivity Concepts
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These two fundamentally different views in the existing body of knowledge serve us
as a starting point with respect to the categorization of our literature review. We consider
the distinction of the underlying model as a key category.
3. Framework for Analysis
Our review is guided by the question which specific performance factors of measurement
and validation of service productivity can be identified throughout the whole
added value process. Therefore we created an initial catalogue of existing approaches
focusing on the measurement, validation, and controlling of service productivity.
The review investigates the categories that serve as necessary preconditions for the
formation of the concept of service productivity. The aim of this catalog is to show
and categorize the current state of research in the field of service productivity. It consists
of categories we identified as key factors with respect to service productivity in
the two different existing service productivity models (Grönroos and Ojasalo, 2004;
Lasshof, 2006).
The following constructs were thereby created: (1) service management, (2) customer
satisfaction, and (3) quality. In the frame of service productivity, it is worth investigating
to what extent the constructs service management, customer satisfaction, and
quality can be separated of each other. Besides, only few researchers have investigated
the nature and the extent of the relation between customer satisfaction and
quality (Hennig-Thurau and Klee, 1997). For instance, Cronin et al. (2000) assumed
that the subjective quality assessment can be equated with customer satisfaction.
However, there are only few empirical studies addressing this issue and indicating
that a direct relationship between these constructs is weak or even nonexistent
(Hennig-Thurau and Klee, 1997).
Our literature study is primarily based on an investigation framework that we created
for the classification of the selected literature. First, we examined the classification
schemes of similar studies of the “state of the art” and adapted relevant categories
for the present study (Urbach et al., 2009; Pahlke and Beck, 2010). The resulting
framework comprises two categories: “data basis” and “data analysis”. The category
“data basis” refers to the used empricial or non-empirical research methods that the
examined papers applied to gather data (e. g., conceptual paper, case study, survey
and so forth). If an empirical research method was used, the category “data analysis”
gives the methods and tools that have been used to investigate the data (e. g., structural
equation modeling, factor analysis and so forth). Afterwards we complemented
this with our three main categories: “service management“, “customer satisfaction”,
and “quality”. Fehler! Verweisquelle konnte nicht gefunden werden. gives an
overview of the categories.
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Fig. 4:
Investigation Framework and Criteria Catalogue
4. Literature Review
4.1. Literature search process
We conducted a literature review following the approach of Webster and Watson
(2002). In the first step we selected a detailed list of journals from the VHB Jorqual2
ranking (stage S0). The list consisted of a total number of 666 journals. We then
identified journals according to their specific field (stage S1): university management,
logistics, manufacturing, marketing, service management and retail management,
electronic commerce, as well as small and medium-sized companies. The remaining
174 journals were selected based on their rankings A+ and A (stage S2). The selection
was also investigated in consideration of our research topic. Consequently, this
restriction leads to eight relevant journals. Besides the eight relevant journals, we
included three well-known German journals and two other additional journals from
service science, rated as being in a category lower than A (stage S3). The following
table gives as an overview all of the 13 identified sources that were analyzed for
themes relevant articles.
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A+ ranked journals
A ranked journals
German literature
Additional literature
Table 1: Selected Journals
Journal of Marketing, Journal of Consumer Research,
Journal of Marketing Research, Marketing Science.
Journal of Service Research, Journal of Retailing,
Production and Operations Management, MIS Quarterly.
Zeitschrift für Betriebswirtschaft, Wirtschaftsinformatik,
Zeitschrift für betriebswirtschaftliche Forschung.
European Journal of Marketing,
International Journal of Operations and Production Management.
Afterwards, we identified topic-related papers from the selected literature sources. An
initial list of papers was generated using the key words “productivity” and/or “service”
to search for titles, abstracts, and keywords via electronic database search. This
way, we identified 971 papers containing the terms “productivity” or “services”. We
then subjected these papers to a content-based analysis. We manually reviewed the
papers of the initial list and selected only those papers that primarily deal with service
productivity. The resulting 65 papers were afterwards classified according to the criteria
of the catalogue (cf. Figure 4). Figure 5 gives an overview of publication outlets
and publication timeline for these 65 papers.
Journals
Article selection and identification
EJM
JCR
JM
JMR
JR
JSR
MktSci
MISQ
POM
IJOPM
ZfbF
ZfB
WI
0
2
4
3
6
4
5
5
Number of articles
0 100 200
4
8
3
7
7
7
All results
Identified
Number of articles
8
7
6
5
4
3
2
1
0
Investigated article according to
year of publication
1980 1985 1990 1995 2000 2005 2010
Fig. 5:
Article Overview and Timeline
4.2. Analysis and Results
We identified a total of 65 relevant articles for the in-depth analysis. These studies
discuss the measurement, validation, and evaluation of service productivity. The inspected
papers were classified according to the applied investigation framework as
defined in Section 3.
The results for the “data basis” category are shown in Fehler! Verweisquelle konnte
nicht gefunden werden.. According to our research approach, we classified 52 papers
as empirical and 13 papers as non-empirical papers. The 13 non-empirical papers
are primarily based on systematic library research (11 papers) rather than on
speculation (2 papers). The non-empirical papers were not categorized in more detail
because the focus is on the consideration of empirical studies with regard to service
productivity. Of the 52 empirical papers, 36 papers deal with surveys, 7 papers with
interviews and 4 papers with case studies. Furthermore, 7 papers could not be as-
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signed to any of these categories. These findings clearly show that survey research
is the dominant research method in the identified papers. This might be because survey-based
instruments are easier to distribute and because a under-developed concept
such as service productivity might lend itself more to perception-based
measures. Also, customer satisfaction and quality are not easily directly observable.
Both qualitative, in-depth studies and other quantitative methods such as controlled
experiments are under-represented. This might indicate a bias in the empirical studies.
Number of articles
40
35
30
25
20
15
10
5
0
2
Results of the data basis
36
11
non-empirical
7
7
4
empirical
Fig. 6:
Empirical Data Basis of Identified Articles
In the next step, we analyzed and summarized the chosen methods for data analysis
of the 52 empirical papers. Fehler! Verweisquelle konnte nicht gefunden werden.
shows that within the category of data analysis, a total of 22 papers were assigned to
structural test methods, 5 papers to discovering methods, and 12 papers to the category
“both methods”. Moreover, 13 papers could be assigned to none of these categories.
One may observe that test methods are more dominant than discovering
methods. This complements the dominance of survey-based studies.
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Results of the empirical data
analysis
22
Number of articles
20
15
10
5
5
12
13
0
structural
discovering
methods
both methods
none of the
methods
structural test
methods
Fig. 7:
Analysis Methods used in Identified Articles
Fehler! Verweisquelle konnte nicht gefunden werden. summarizes the findings
for our main categories “service management”, “customer satisfaction”, and “quality”.
The in-depth analysis of the 52 empirical papers based on the essential categories
shows that a high number of the empirical studies are focusing on either customer
satisfaction (20), quality (17), or service management (9) as being a determinant factor
for service productivity. Only two papers are mixed approaches.
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Central categories of service
productivity
2
4
9
Service management is important
for productivity
Customer satisfaction is important
for productivity
17
Quality is important for
productivity
20
mixed methods
No match
Total: 52
Fig. 8:
Articles dealing with Categories of Service Productivity
The 20 papers of the first category see customer satisfaction as determining quality,
which in turn determines service productivity (e. g., Bolton and Drew, 1991). In contrast,
the 17 papers of the second category see quality separated from customer satisfaction
(e. g., Chenet et al., 2000), where service productivity always includes a
qualitative component.
Finally, we summarize the main classification results in Figure 9 with regard to topics
in time. The papers reviewed were published between 1980 and 2010. A first increased
interest in evaluating service productivity appears in the period between
1996 and 2000 (18 papers). A next spike can be observed between 2001 and 2005
(16 papers) and from 2006 up to 2010 (17 papers). This seems to indicate an increased
interest in service productivity and pointing to the relevance of the area.
Number of articles
16
14
12
10
8
6
4
2
0
The investigation focused
according to year of publication
non-empirical
empirical
Service
management
Customer
satisfaction
Quality
Fig. 9:
Interest in Service Productivity and Categories over Time
5. Discussion and Conclusion
This paper gave an overview of the existing literature with regards to measurement,
validation, and controlling of service productivity. We highlighted which approaches
of validation exist, which research designs are used in empirical studies, and what
underlying models or theories are applied throughout the literature dealing with service
productivity. According to our results, different performance factors can be assigned
to different phases of a service process. Furthermore, productivity of services
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is more than the relation between output and input. The concept of productivity must
include the effectiveness in terms of customer satisfaction and quality. Service
productivity therefore requires both measures of efficiency – how effectively input
resources are transformed to outputs in the form of services – and measures of effectiveness
– how well the quality of the service process is perceived – because a
service process will not be productive if it is only efficient but not effective, or if it is
effective but not efficient (Rutkauskas and Paulavičienėm, 2005; Vuorinen et al.,
1998).
Therefore we conceptualize service productivity as a function of efficiency, effectiveness,
and demand. The focus is on the concepts of customer satisfaction and quality,
where we also investigated to what extent both concepts can be separated from each
other. Our results indicate that customer satisfaction and quality are not identical
constructs. From this process of literature search and elimination, we found 52 empirical
papers. Of these 17 articles identified quality as the decisive factor of service
productivity, whereas 20 articles confirmed that customer satisfaction is the dominant
factor. To sum up, our results show that service productivity and service quality
should not be managed in a separate process. In services, quality and productivity
are truly two sides of the same coin (Gummesson, 1998).
There were two limitations with respect to the analysis and data that may affect the
accuracy of the results. The first limitation is that our study was based on a limited
number of journals as a publication source. This might have also lead to missing a
series of relevant studies. The second limitation is the objectivity of the selection process
and in addition to this our search strings are not capable to identify all relevant
articles.
The results of the present literature review reveal the need of valid measures and
instruments for assessing and evaluating the service productivity. Additionally, it is
necessary to build a framework for understanding and analyzing the service productivity,
which allows companies to evaluate and measure service productivity.
The next step within our service productivity research program is to conduct an emprical
study based on interviews with project managers from service management.
On this basis, we would be able to proceed with explanatory as well as prescriptive
research on service productivity.
6. Acknowledgements
The German Federal Ministry of Education and Research funded parts of this work
within the scope of the research project “ProMIse” under the promotional reference
number “01FL10060”.
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Authors:
Bilal Balci
Dipl.-Wirt. Inform.
PhD Student, Research and Teaching Assistant
Information Systems Engineering
Dept. of Econonmics and Business Administration
Goethe-University Frankfurt
Campus Westend Grüneburgplatz 1
D-60323 Frankfurt am Main
bbalci@wiwi.uni-frankfurt.de
www.ise.wiwi.uni-frankfurt.de
Alicia Hollmann
Information Systems Engineering
Dept. of Econonmics and Business Administration
Goethe-University Frankfurt
Campus Westend Grüneburgplatz 1
D-60323 Frankfurt am Main
Aliciahollmann@yahoo.de
Dr. Christoph Rosenkranz
Information Systems Engineering
Dept. of Econonmics and Business Administration
Goethe-University Frankfurt
Campus Westend Grüneburgplatz 1
D-60323 Frankfurt am Main
rosenkranz@wiwi.uni-frankfurt.de
www.ise.wiwi.uni-frankfurt.de
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