The Productivity of Services: A systematic literature review - RESER ...

The Productivity of Services:
A systematic literature review
Claudia Lehmann, Marcus Koelling
HHL - Leipzig Graduate School of Management
While a firm’s ability to pursue a productive orientation has been posited
as having positive performance effects (Slack et al. 2007), little is currently
known about the concept of productivity in the field of service research. To
that end, this paper focuses on the literature on productivity, efficiency and
effectiveness, published since 1989 and conducted a review with the purpose
of determining if and what contributions have been done to service
research. This study on service productivity draws upon the analysis of literature
from a systematic review perspective. The aim of this research is
to adopt the systematic review approach of Tranfield et al. (2003) as a tool
for highlighting an up-to-date landscape of the multifaceted dimensions of
service productivity.
Introduction
In this paper, we review the academic literature on the understanding of productivity,
efficiency and effectiveness in the field of service research. During the last decade,
the significance of service industries to the prosperity of modern economies has been
widely recognized (Vuorinen et al. 1998). Academic interest in issues relating to service
research is significantly growing. Productivity, although critical for the sustained
success of service organizations, has received relatively little service specific attention
as distinct from the more general phenomenon of productivity as the input to
output relation (Johnston & Jones 2004). Generally, the productivity of a process is
related to how effectively input resources are transformed into value for customers.
For the needs of manufacturers, there are widely used productivity concepts and
measurements instruments.
This paper is devoted to taking steps toward closing three significant gaps in the literature
on productivity, efficiency and effectiveness and its contribution to service
research. First, there has been inconsistent usage in terminology within service research.
Labels such as productivity, efficiency and effectiveness are used in different
ways by different scholars, resulting in a limited collective knowledge accumulation
about service productivity. In response, we propose clear definitions for key terms to
provide much-needed conceptual clarity that may help advance the literature. In doing
so, we seek to provide a categorization of productivity, efficiency and effectiveness,
which explicitly recognizes that there are different kinds of configurations and
each offers unique insights contributing to the field of service research. Second, there
exists no published systematic literature review in the field of service productivity.
1

Third, the use of the productivity concept beyond operations management theory has
been very limited, despite the potential to shed new light on diverse phenomena. On
this account, we develop future research ideas aimed at extending and defining productivity
thinking within service theory.
Theoretical base
The content of productivity
The uniqueness of productivity research relative to other research approaches can
be highlighted by considering how it pursues the goal of operations management.
Generally, operations management aims at ensuring that business operations are
efficient in terms of using as little resources as needed, and effective in terms of
meeting customer requirements (Markland et al. 1995). It is concerned with managing
the process that converts inputs (in the forms of materials, labor and energy) into
outputs (in the form of goods and services). Within this research area productivity is
the most common measure of competitiveness (Russell & Taylor 2000). Therefore,
productivity is defined as the ratio of what is produced by an operation to what is required
to produce it (Slack et al. 2007).
The predominant input in productivity calculation is labor hours. According to the Bureau
of Labor Statistics, even though labor is the only factor of production explicitly
considered, comparisons of productivity over time implicitly reflect the joint effects of
many other factors, including technology, capital invest capacity utilization, energy
use and managerial skills. Thus, productivity statistics provided in government reports
typically measure changes in productivity from month to month, quarter to quarter,
year to year or over a certain period (Russell & Taylor 2000). Operations management
assumes that improving quality by reducing defects will increase outputs
and reduce input. In fact, virtually all aspects of quality improvement have a favourable
impact on different measures of productivity. Improving product design and production
process, improving the quality of materials and parts, improving job design
and work activity, they will all increase productivity (Russell & Taylor 2000).
Problematic in this context is the general approach towards productivity as an umbrella
concept including efficiency and effectiveness. In order to develop a model of
service productivity it is important to provide some clarity and distinction between
these terms (Johnston & Jones 2004). Efficiency and effectiveness should be treated
as related but separate concepts. Efficiency describes the degree to which an activity
generates a given quantity of outputs with a minimum consumption of inputs, or generates
the largest possible outputs from a given quantity of inputs (Johnston & Jones
2004). Effectiveness, in turn, indicates the ability to attain a goal or a purpose. Effectiveness
relates the output to the goal set for the operation, whereas efficiency relates
the output to the resources used (input). Efficiency is about doing things right
and effectiveness is about doing the right things. There exists a clear distinction between
effectiveness and productivity: effectiveness is tied to the ability of an organization
to attain its specified objectives, whereas productivity concerns the relationship
between outputs and inputs (Vuorinen et al. 1998). Despite its apparent benefits,
the productivity function faced a series of critiques in the late 1980s. Blois argued
2

that increasing productivity is not a sufficient condition for enhancing an organization’s
effectiveness. In fact, productivity may be increased at the cost of effectiveness
in meeting the goals set for the organization (Blois 1984). Efficiency is a common but
loosely defined concept in the business disciplines. It may be seen as a quantitative
(technical efficiency) or a value (economic efficiency) concept. Technical efficiency
may be considered synonymous with productivity as a ratio between output and input,
although efficiency has sometimes been defined as the inverse to productivity.
When efficiency is defined in value terms, one tries to make compatible the effects of
various input and output factors in the production process (Grönross & Ojasalo
2004). This interpretation has led to formulations in which efficiency is seen as costs
per product. Technical efficiency and productivity may be defined as distinct concepts
by taking the standard of comparison as a frame of reference: in the case of a productivity
ratio, the aim is to compare the output-input ratios across units and time,
whereas in the case of an efficiency ratio, the comparison is made against a predetermined
standard or ideal. If a meaningful interpretation can be given to ideal performance,
it is reasonable to perceive an efficiency ratio as an indicator of the extent
to which actual performance has achieved the ideal level (overall efficiency) or the
best observed performance (Frei & Harker 1999). According to the basic principle of
economic rationality, the purpose is to achieve a given result with minimal resources
or to get the maximum result with a given set of resources. However, given the variety
of definitions that describe performance in the production of services, we assume
that comprehensive understanding is needed. Given the importance of the productivity
concept to scholars and service organizations, there is a need to summarize extant
knowledge about this concept as the foundation for setting the stage for further
advances.
The content of services
While comparing productivity between service and manufacturing operations, one of
the basic claims has been that the special characteristics of services demand a more
holistic approach including a customer-orientation to productivity (Blois 1984). More
specifically, several researchers have argued that quality and productivity cannot be
dealt with separately in the case of services (Djellal & Gallouj 2008) (Grönross &
Ojasalo 2004). Despite the emergence of productivity as a central concept for service
researchers, little agreement exists about the definition and nature of service productivity
(Nachum 1999a) (Anderson et al. 1997). Consequently, there seems to be a
growing need for a thorough analysis of the productivity concept in the context of
services.
Whereas the bulk of traditional service research has mainly focused on the identification
of characteristic differences between goods and service (Lovelock 1991a), recently
the goods dominant logic considers services as type of (intangible) goods,
which implies differences between tangible goods and services in terms of production
and distribution practices (Vargo & Lusch 2008), (Vargo & Lusch 2004).
Productivity as a concept is used to manage production efficiency in manufacturing.
In services, for example, due to the nature of service production processes as open
systems and the participation of customers in those processes, such a productivity
concept is too limited (Grönross & Ojasalo 2004). Normally, only measurements of
partial productivity are obtained and no control of the overall productivity and its effects
on the economic results of the service provider and on customer value is exer-
3

cised. What appears to be improved productivity in terms of better production efficiency
may turn out to have a negative effect on perceived service quality, customer
value and, in the final analysis, on the economic result of the firm (Ojasalo 2003) (Parasuramam
2002).
Services are carried out in an organizational setting, which always refers to embodied
and especially emotional situations (Küpers 1998). This influence of embodiments,
emotions and the phenomenological significance of ways of expression on
the service productivity has not been a key focus in service productivity research so
far (Lasshof 2006) (Gummesson 1998). Therefore, the complexity of the relationship
between service provider and customer can be identified as an essential characteristic
of service processes (Ojasalo 2003). Rather than specifying a single type of relationship
from the service providers perspective the service process can be divided
into three separate processes (Grönross & Ojasalo 2004).
• producing the service in isolation (back office);
• producing the service in interaction with the customer (service encounter);
• the customer produces the service in isolation from the service provider (using
the provided infrastructure only).
Thus, all participants involved in either kind of these service processes are first and
foremost embodied beings, who are embedded in a specific service system. The
most fundamental way in which service providers are involved concerning these service
systems is their perceptual interaction. Especially the perceived quality and image
of service companies depend on the engagement and performance of the service
providers (Verbeke 2004) (Grandey et al. 2002).
The problems of using a traditional productivity concept in services discussed above
and highlighted the necessity of developing a productivity concept, which is geared
towards the nature of services. Managing productivity should be seen as a mutual
learning experience, where the service provider and the customer are aligning their
resources and production and consumption processes to each other. In summary, it
can be said that measuring productivity as an efficiency issue may be less appropriate
in services but rather to see service productivity as a profitability concept.
Given the importance of the service productivity concept to organizations, there is a
need to summarize extant knowledge about this concept as the foundation for setting
the stage for further advances. Therefore, it is crucial to identify the existing literature
on service productivity to shed some light onto the complex field of service productivity.
In order to achieve this aim we conducted a systematic literature review, which
consolidates past accomplishments and to sets the stage for future developments.
4

Systematic Literature Review
Methodology
In order to fully map the prior research in the field of service productivity, we conducted
a systematic literature review. As mentioned above the traditional ‘narrative’
reviews often lack rigor and in many cases are not undertaken with the required accuracy
(Pittaway et al. 2004) (Marr et al. 2003). In this study, we applied a method
similar to that described in Tranfield et al. (2003), which uses the principles of systematic
review methodology that are used in medical science in order to counteract
bias and produce transparent. It is also applicable for high-quality and relevant literature
reviews in management research.
Conducting a systematic review means adopting a replicable, scientific and transparent
process, minimizing the bias through exhaustive literature searches of published
and unpublished studies and providing an audit trail of the reviewers decisions, procedures
and conclusions (Cook et al. 1997). Thus, it is very important to ensure that
the review is both methodical and replicable.
Therefore, this systematic review will follow the three stages outlined by Tranfield et
al. (2003): First planning the review; second conducting the review and third reporting
and dissemination. The overall process of the review is summarized in Fig. 1.
Defining the
objectives
Descriptive reporting
of citations
Step A: Planningthe review
Preparing the
proposal
Step B: Conducting the review
Step C: Reporting the review
Thematic reporting
of journal articels
Developing the
protocol
Stage One Stage Two
Stage Three Stage Four
Activity
Define search words
used for coverage of
database
Define time period for
search
Activity
Selection of
biographical databases
Activity
Filtering of the articles
Activity
Analysis of the articles
Fig. 1: Summary of the systematic review process (following (Thorpe et al. 2005))
5

Step A: Planning the review
Prior to the beginning of the review, a review panel was formed with experts in the
areas of both review methodology and theory. The review panel helped to direct the
process through regular meetings and resolved upcoming disputes over the inclusion
and exclusion of studies.
Defining the objectives and preparing the proposal
At the beginning of the systematic literature review stood an iterative process of definition,
clarification, and refinement. Therefore, it was important to the authors and
reviewers to consider cross-disciplinary perspectives and alternative ways in which
the research topic has been tackled previously. This first overview included a brief
summary of the theoretical, practical and methodological history debates surrounding
the field service productivity.
Developing the protocol
The protocol for any literature review ought to contain a conceptual discussion of the
research problem and a statement of the problem's significance rather than a defined
research question (Tranfield et al. 2003). The aim is to produce a protocol that does
not, on the one hand, interfere the researcher's ability to be creative in the literature
review process, but, on the other hand, ensure that the review is less open to researcher
bias than a more traditional narrative reviews (Tranfield et al. 2003) (Phelps
et al. 2007). Condensed a systematic review enables scholars to provide an audit
trail of search terms and reasons for including/excluding articles (Lee 2009).
Step B: Conducting the review
Stage one: Define search words and time period
The systematic search began with the identification of keywords, regarding the productivity
of services on the scoping literature study and on their prior experience. The
list of keywords was completed in a brainstorming session with other academic researchers
and afterwards grouped into search strings. A search string is by definition
a list of root concepts and key words linked by operators such as AND or OR. The
following list shows the used search terms, which were linked by the Boolean operator
OR:
• productiv* / productivity / productiveness
• effectiveness / efficiency
• outcome / performance / capability / fruitfulness
• measur* / measurement / meter / gauging
The search with this root search string was always accomplished in connection with
service*(through Boolean phrase AND).
To cover an appropriate time period all scholarly articles from January 1989 until
June 2010 were considered.
6

Stage two: Selection of biographical databases
A number of key bibliographical databases were selected for this search: EBSCOhost;
ABI Proquest; Business Source Premier; Science Direct; Web of Science (ISI
Web of Knowledge); JSTOR database and Emerald. The database with the greatest
coverage coupled to functionality and full article access were: EBSCOhost and Web
of Science (ISI Web of Knowledge). These bibliographical databases were chosen
and reviewed using the search strings identified in step one. Therefore, the search
was conducted in title, abstract and keyword search.
Stage three: Filtering of the articles
The results of a first search, conducted at the EBSCOhost database with the search
string in the defined time period, lead to 92148 hits. In order to assess the relevance
and size of the literature and to state clearly the focus of the research study, the
scope of the literature review process have to be delimited further by other factors.
Tranfield et al. (2003) state regarding this problem: “…management researchers
usually rely on the implicit quality rating of a particular journal, rather than formally
applying any quality assessment criteria to the articles they include in their reviews
(i.e. refereed journals are 'better' than practitioner journals)…”. So the initial assessment
criteria for including studies into the literature review were: the specifically relation
to services, theoretical and empirical studies, quantitative and qualitative studies
and studies which were published in academic or high quality business journals. To
estimate the quality of journals the ranking of the German Academic Association for
Business Research (VHB) has been used. The ranking of the journals are subdivided
in different groups. In order to the relevance of the research theme the review team
decided to conduct the search in all Journals ranked A to D in two groups “General
business studies” and “Service and Trade Management”. These two subgroups cover
together a range of 80 journals.
The conducted search elicited over 3250 references. Evaluating the title and abstract
of the publications by relevance (present of service productivity) and the teams ‘a
priori’ knowledge enabled the team to reject approximately 2900 articles. The reviewers
then looked independently the remaining papers and further reduced the
amount to a list of 56 relevant studies in the end. These studies were cross-checked
by the reference section, which led to a list of 104 additional studies. These were reviewed
again independently and 24 studies were included in the literature review.
Before accepting a paper into the review the authors checked for repeated studies to
ensure there is no duplication; for example if the same study is published in two different
journals with different first authors, only one study would be included in the
review; usually the most comprehensive study or the most recent study. The different
stages involved in the selection process are shown in Table 1.
7

Selection Process Nb. studies
Studies extracted from database

Sources of publications
The total amount of the 74 as relevant identified articles was published in 31 academic
journals. Of which the majority (46%) were found in four academic journals.
Therefore, 19% of the articles were published in the Service Industries Journal, 15%
in the International Journal of Service Industry Management, 7% in the Management
Science and 5% in the Journal of Business Research.Table 1 gives a breakdown of
where the 74 articles are published.
Data Source Nb. of articles
Service Industries Journal 14
International Journal of Service Industry Management 11
Management Science 5
Journal of Business Research 4
Other 40
Table 2: Publication sources of included articles (34 out of 74 articles are published in 4 journals)
Type of study
Fig. 3 shows that out of the 80 studies, 61% are empirical, i.e. findings are based on
direct evidence or experiment. The 25% theoretical or conceptual studies are based
on an understanding of the field from experience or reference to other related work.
Only a smaller number of studies (14%) are either reviews of literature (11%) or reports
(3%).
theoretical/
conceptual
25%
report
3%
Fig. 3: Types of studies in accepted papers
review
11%
empirical
61%
Data collection methods used in the empirical studies include: surveys and questionnaires,
field studies, structured interviews, case studies, focus groups and data reviews.
9

Out of the 48 empirically studies 57% base on secondary data or re-examine empirical
work of other authors just 20 studies (43%) base on primary data (see Fig. 3). In
this primary studies different research strategies, such as quantitative (45%), qualitative
(40%) and mixed approaches (15%), where used.
secondary
studies;
57%
Fig. 4: Data origin in empirical studies
primary
studies;
43%
Geographical and service sector distribution of papers
The papers reviewed are also analyzed according to the countries that feature within
the studies. This analysis shows that a high percentage of the empirical studies are
concentrated on work carried out in the USA (25%) and the United Kingdom (19%),
as shown in Fig. 5: Countries represented in the empirical studies. One study even
compares the productivity of different service sectors in different time periods in the
UK to the USA [23]. Overall most countries, except the USA, the United Kingdom, the
Scandinavian countries and Spain, are not well represented. Thus, it is clear that
when we synthesize findings from all these studies we are giving a predominantly
Western view of the productivity of services.
Nb. of studies
12
11
10
9
8
7
6
5
4
3
2
1
0
Fig. 5: Countries represented in the empirical studies
10

The industrial focus of the studies included is presented in Fig. 6. The sample of studies
in the review is more or less balanced toward the different service sectors. In
particular the finance sector (banks and accounting), tourism sector (hotels, travel
agents and tour operators) and the retail service (grocery stores and fast food restaurant)
have been the object of investigation. However, most studies (31%) cover and
compare multiple service sectors.
Nb. of Studies
16
14
12
10
8
6
4
2
0
Multiple
service
sectors
Fig. 6: Service sectors analysis of studies reviewed
Consulting Finance Health ICT Public
Sector
Retailer Tourism
In summary, a number of key points can be made for the conducted review. First, the
evidence based of this literature review is somewhat dominated by empirical studies.
Therefore, the empirical studies are mostly based on secondary data. The methodologies
of productivity measurement are diverse. Primarily, the following two techniques
are used: Index measurement and linear programming. The most prevalent
concept, within the index measurement, is the Total Factor Productivity. Basically this
model proposes measuring productivity as a ratio of output to different inputs (Craig
& Harris 1973). The approach of linear programming constructs a production frontier
and evaluates each input’s contribution to the productive process based on past performance
data. The most prevalent programming technique used in the reviewed
studies is the Data Envelope Analysis (DEA). DEA is a flexible, non-parametric estimation
procedure which identifies the contribution of a set of inputs for achieving the
maximum quantities of a given set of outputs. This approach does not require price
data on inputs and products, quantities of inputs can be directly utilized (Banker et al.
1989) (Norman & Stoker 1991) (Sherman 1984). In particular 27% of all empirical
studies and yet 44% of all studies based on secondary data have been evaluated by
a data envelopment analysis. The disadvantages of DEA are two-fold. First, it requires
a fairly large series of data so that the optimization can be estimated with a
more general set of benchmarks. Second, being a non-stochastic procedure, tests of
statistical significance are harder to develop (Singh et al. 2000).
Furthermore, many studies (9%) concerning the “Productivity Paradox of Information
Technology”. This phenomenon describes the situation in which large investment into
communication technology has not led to productivity gains (Nachum 1999b). In the
short run, increased input devoted to the acquisition of new knowledge decreases
productivity because the productivity measure reflects increased input without a corresponding
increase in output (Lehr & Lichtenberg 1998).
11

Finally, the research to date lacks some depth in terms of the very limited number of
studies based on primary data. The research is also fragmented as it is spread
across a large number of authors, journals and disciplines. The main conclusion,
which can be drawn from the sample used in this systematic literature review, is that
the subject area requires some prioritization by a ‘critical mass’ of academics over a
prolonged period if the evidence base is to be improved and expanded.
Step C: Reporting the review
Finally, a systematic review should make it easier for academics and practitioner to
understand the research by synthesizing extensive primary research papers from
which it was derived (Tranfield et al. 2003).
Therefore, the presented database should be used to highlight the up-to-date landscape
of the multifaceted dimensions of service productivity in the next step. On that
account the report of the literature review should be structured as follows: First, the
existing theoretical approaches should be reviewed and be reflected in an overview.
Second, the term of service productivity should be conceptualized in order to explore
the extent of influencing factors and interdependencies on the productivity of services.
Finally, managerial implications and key issues for the management of service
productivity should be summarized.
Theoretical Lenses in Service Productivity Research
Researchers studying service productivity have drawn on a wide range of theoretical
lenses commonly used in service research. The following section summarizes the
most common theories used in service productivity research. In many studies, researchers
chose to integrate two or more theoretical lenses to examine the issue under
study.
We summarize the key features of each conceptual article in Appendix 1. When reviewing
conceptual articles, we examined the theoretical base as well as capturing
an understanding of how the work contributes to knowledge about the service productivity
concept. Research in service productivity has been criticized for lacking adequate
theoretical bases (Shafti et al. 2007) (Grönross & Ojasalo 2004); however, we
found that research surrounding the service productivity construct is theoretically rich,
embracing a multitude of theories, including knowledge management theory, resourced
based management capacity theory, relationship theories and operations
theory. Our review of conceptual works suggests that the service productivity construct
holds a great promise as basis for theory building. For example, Drucker
(1991) developed a theory of knowledge circles and productivity development. Such
approaches could be used to build theory on other service productivity-related
processes, such as knowledge management for employees and clients. Anticipatory,
other forms of theory building can be used to move this research stream forward. For
example, the productivity output depends on capacity management, quality management,
and resource productivity or efficiency management (Armistead & Clark
1994) and is related to the Penrose assumption (1954) of management capacity. Different
definitions of service productivity in the literature (i.e., intellectual capabilities
(Quinn et al. 1996) vs. dependency of service-good combinations (Reichwald &
Möslein 1995) vs. phenomenology/expression (Küpers 1998) vs. client-service provider
interaction (Gummesson 1998)/(Parasuramam 2002) may be an appropriate
aspects to creating new theory.
12

Adding another aspect to existing conceptual frameworks to develop more complex
theoretical models is another fruitful avenue for future research. For example, Klassen
et al. (1998) show, that productivity measurement in concert with efficiency measurements
provides a stronger basis for evaluation than using productivity alone.
They suggest that efficiency and productivity measures may have less meaning in
services in which transaction size may not accurately reflect the value of the service
(e.g. financial service). Another possibility is considering how client activities (e.g.,
time, quality and value added inputs) can moderate service productivity (Martin et al.
2001). Therefore service productivity highly depends on customer knowledge, experience
and motivation (Ojasalo 2003). Johnston & Jones (2004) argue that it is important
to understand the relationship between operational and customer productivity. In
their model customer productivity includes satisfaction as one output variable. Other
authors like Anderson et al. (1997) or Gummesson (1998) have separated service
quality or satisfaction from productivity. Hence, (Grönross & Ojasalo 2004) define
service productivity as a function of internal efficiency; external efficiency and capacity
efficiency. In their model service productivity is defined as total revenues of the
service divided by total costs of the service. A third possibility is building a theoretical
framework for understanding and analyzing the productivity of service workers in a
system. Dobni (2004) argues that service productivity is most likely to be improved if
it is managed in a systematic way. Given this approach, Das, Sidhartha R.; Canel
(2006) show that the designing of a service process might be the foundation for improving
service productivity.
From a strategic perspective (Djellal & Gallouj 2010) identified three generic service
productivity strategies: First, assimilation strategies achieve productivity gains by
making the service as tangible as possible and minimize the degree of interaction
with the customer. Second, differentiation strategies try to implement rationalizations
methods for services (e.g. standardization, formalization of procedures and routines).
Third, integration strategies combine these two strategies by using a variety of arrangements.
13

Conclusion
We started this article by noting the importance of service productivity in today’s
business landscape. The service productivity phenomenon is a relatively new research
area in the widely researched field of operations management and service
research, and researchers from different domains have started to address a broad
set of research questions through a wide range of theoretical lenses, leading to a
certain level of fragmentation of the service productivity literature. Most of the articles
were published between 2004 till 2006. The objectives of this article were to review
the existing service productivity research, organize major findings by key research
areas, and develop a research agenda by identifying existing gaps in the present understanding
and highlighting future research opportunities.
The review of the service productivity literature suggested that the existing body of
research can be organized around a conceptual map comprising different major research
areas each representing important aspects. These areas are knowledge
management, operations management, management capacity/resource based perspective,
customer/client perspective and system and interaction perspective. Therefore,
we argue it is important to understand the perspective of operational and customer
productivity and the relationship in between. Although the interest among
service scholars in the service productivity phenomenon has grown significantly in
the past few years, many of the theoretically and empirically relevant and interesting
issues in these three research areas have not yet been investigated or have only
been addressed peripherally. Although the intention of this research effort was to
present a complete as possible review, there are some limitations to this study. Most
important, the literature search process was somewhat driven by a specific focus on
service productivity and not productivity in general. Nevertheless, we are confident
that this review covers the majority of the studies that are at the core of the research
issues related to service productivity. We summarize that the contribution of this article
rests in three areas: (a) the development of a conceptual map of the service
productivity literature comprising different research areas, (b) a review of the existing
service productivity research and discussion of major findings in each key research
area, and (c) the development of an agenda for future research. Overall, the relatively
new field of service productivity represents an exciting and promising area of research
that is rich of further research opportunities.
14

Appendix 1
Author
(Year)
Drucker
(1991)
Colin./ Graham,
(1994)
Reichwald./
Möslein
(1995)
Quinn./
Anderson/
Finkelstein,
(1996)
Küpers
(1998)
Referring
theories
(Chase & Bowen
1991);
(Heskett et al.
1990);
(Lovelock &
Young 1979);
(Rhyme 1988)
(Brynjolfsson
1991);
(Picot &
Gründler 1995)
Definition of Service Productivity
Raising the productivity of knowledge and service work is
essential.
According to all the experience we have, the resulting
productivity increases will equal, if not exceed, whatever
industrial engineering, scientific management, or human
relations ever achieved in manufacturing. In other words,
they should give us the productivity revolution we need in
knowledge and service work.
Operations managers in a service organization will either
succeed or fail in the process of balancing quality of service
and resource management, expressed in terms of
resource productivity, depending on their skill in managing
capacity to match demand.
There is an interaction between capacity management,
quality management, and resource productivity or efficiency
management which is at the heart of the planning
and control process for operations management in services.
The productivity of industrial services and the provision of
goods are interdependent factors. They are the result of
rationalization processes which were concentrated only
on the production of goods.
Hence, the comparison between developments of productivity
in manufacturing and services is characterized by
systematic distortions.
The productivity of a modern corporation or nation lies
more in its intellectual and systems capabilities than in its
hard assets.
Intellectual and information processes create most of the
value-added for firms in the large service industries.
The extension of expressing feelings like sympathy, joy,
satisfaction, dissatisfaction, embarrassment, influences
the productivity of the service process in an essential
way.
In order to work out how emotions play a key role in organizational
and customer-related activities, a phenomenology
of working life is required.
15

Gummesson
( 1998)
Klassen/
Russell/
Chrisman,
(1998)
Martin/
Horne/
Chan
(2001)
Parasuraman
(2002)
(Lovelock &
Young 1979);
(McLaughlin &
Coffey 1990)
(Siegel 1980);
(Chase &
Aquilano 1992);
(Krajewski &
Ritzman 1993);
(Armistead et al.
1988)
(Lovelock 1991b);
(Schneider 1980)
Focus on the relationships between service providers
and customers as these stand out in the service encounter
and the service production process
Productivity is a ration between output and input. The
more we can reduce the input keeping up output, the
better is our productivity
Measurements of productivity are often ambiguous and
inadequate.
Productivity measurement in concert with efficiency
measurement, providing a stronger basis for evaluation
than using productivity alone.
Productivity cannot be defined by only one measure,
but may include any measure relating output value to
input value
An overall productivity measure for individual firms is
usually defined as output value/ input value with outputs
and inputs measured in dollars.
To meet the needs of individual operating units in a
firm, adjustments can be made by calculating productivity
of various input and output factors.
Focus on client productivity as any measure of service
productivity must include some component that focuses
on the client side of the service encounter.
Client productivity defined. In this context, high ”client
productivity'' can be regarded as timely, quality and
value-added inputs (e.g. data diagnosis or critical decisions)
made to consulting projects for transformation of
such into achievement of preset common objectives
(other things being constant).
Conceptual framework for understanding the interlinkages
among service quality and the various components
of the company-customer perspective of productivity
Definition productivity from the customer’s perspective
defined as the ratio of the service output experienced
by a customer to the inputs provided by that customer
in service production.
16

Ojasalo
(2003)
Johnston/
Jones
(2004)
Grönroos/
Ojasalo
(2004)
Dobni
(2004)
(Fuchs 1968);
(Lovelock &
Young 1979);
(Bateson 1985);
(Grönroos 1990);
(Ojasalo 1999)
(Johnston 1989);
(Lovelock &
Young 1979);
(Martin et al.
2001)
(Chase & Haynes
2000)
(Blumberg
1994)
Service productivity is strongly connected with the customer
participation in the service process.
Customer are not a passive recipient of service providers
output but an integrated part of the organization
Service productivity highly depends on customers’
knowledge, experience and motivation.
Distinction between “operational productivity” and “customer
productivity”
They argue that a major gap in our knowledge is in understanding
the relationships between operational and
customer productivity.
(It should be noted that most authors separate out service
quality or satisfaction from productivity (for example,
Anderson et al., 1997; Gummesson, 1998) their
notion of customer productivity however includes satisfaction
as one output variable.)
A service productivity concept can be defined in the
following way: Service productivity = f (internal efficiency;
external efficiency; capacity efficiency)
Service productivity and quality should not be managed
as separate processes. (costs of producing this service):
As a global productivity measure of the operations of a
service provider, the following measure can be used:
Improving productivity in services requires a focus both
on internal operational performance and external marketing
so that the search for efficiency can be balanced
against effectiveness from a marketing point of view.
Service productivity is most likely to be improved if it is
managed in a systemic way.
17

Das/ Canel,
(2006)
Djellal/
Gallouj
(2010)
Productivity as process objective that are derived from
the overall organizational objectives.
Design of service processes = foundation for improving
overall customer service, service quality, and productivity
The design of service processes begins with a statement
of process objectives that are derived from the overall
organizational objectives. These process objectives may
include customer service, service quality, productivity,
etc.
Three generic service productivity strategies:
First, assimilation strategies achieve productivity gains by
making the service as tangible as possible and minimize
the degree of interaction with the customer.
Second, differentiation strategies try to implement rationalizations
methods for services.
Third, integration strategies combine these two strategies
by using a variety of arrangements.
18

References
Anderson, E.W., Fornell, C. & Rust, R.T., 1997. Customer satisfaction, productivity,
and profitability: Differences between goods and services. Marketing Science,
16(2), 129-145.
Armistead, C. & Clark, G., 1994. The “Coping” Capacity Management Strategy
in Services and the Influence on Quality Performance. International Journal of Service
Industry Management, 5(2), 5-22.
Armistead, C., Johnston, R. & Slack, N., 1988. The Strategic Determinants of
Service Productivity. International Journal of Operations and Production Management,
8(3), 95-108.
Banker, R., Charnes, A. & Cooper, W., 1989. An introduction to data envelopment
analysis with some of its models and their uses. In J. Chan & J. Patton Research
in governmental and nonprofit Accounting. London: Jai Press, pp. 125-164.
Bateson, J., 1985. Self service consumer: An exploratory study. Journal of Retailing,
61(3), 49-75.
Blois, K.J., 1984. Productivity and Effectiveness in Service Firms. The Service
Industries Journal, 4(3), 49-60.
Blumberg, D., 1994. Strategies for Improving Field Service Operations Productivity
and Quality. The Service Industries Journal, 14(2), 262-277.
Brynjolfsson, E., 1991. The Productivity of Information Technology: Review
and Assessment.
Chase, R. & Aquilano, N., 1992. Production and Operations Management:
ALife Cycle Approach 6.th., Homewood, IL: Richard D. Irwin, Inc.
Chase, R. & Haynes, R., 2000. Service Operations Management. In T. Swartz
& D. Iacobucci Handbook of services marketing and management. Thousand Oaks,
CA: Sage Publications, pp. 455-72.
Chase, R.B. & Bowen, D.E., 1991. Service Quality an the Service Delivery
System. In S. Brown et al. Service Quality: Multidisciplinary and Multinational Perspectives.
Massachusetts, Toronto: Lexington Books.
Cook, D.J., Mulrow, C.D. & Haynes, R.B., 1997. Systematic Reviews: Synthesis
of Best Evidence for Clinical Decisions. Annuals of Internal Medicine, 126(5), 376-
380.
Craig, C. & Harris, C., 1973. Total productivity measurement at the firm level.
Sloan Management Review, 14(3), 13-28.
Das, Sidhartha R.; Canel, C., 2006. Designing service processes: a design
factor based process model. International Journal of Services Technology & Management,
7(1), 85 - 107.
19

Djellal, F. & Gallouj, F., 2008. Measuring and Improving Productivity in Services.
Issues, Strategies and Challenges, Northampton: Edward Elgar.
Djellal, F. & Gallouj, F., 2010. Services, Innovation and Performance. Journal
of Innovation Economics, 1(5), 5 - 15.
Dobni, D., 2004. A marketing-relevant framework for understanding service
worker productivity. Journal of Services Marketing, 18(4), 303-317.
Drucker, P.F., 1991. The New Productivity Challenge. Harvard Business Review,
69(6), 69-79.
Frei, F.X. & Harker, P.T., 1999. Measuring the Efficiency of Service Delivery
Processes. Journal of Service Research, 1(4), 300-312.
Fuchs, V., 1968. The service economy.
Grandey, A.A., Tam, A.P. & Brauburger, A.L., 2002. Affective States and
Traits in the Workplace: Diary and Survey Data From Young Workers. Motivation and
Emotion, 26(1), 31-55.
Grönroos, C., 1990. Service management and marketing, Lexington: Lexington
Books.
Grönross, C. & Ojasalo, K., 2004. Service productivity: Towards a conceptualization
of the transformation of inputs into economic results in services. Journal of
Business Research, 57, 414 - 423.
Gummesson, E., 1998. Productivity, quality and relationship marketing in service
operations. International Journal of Contemporary Hospitality Management,
10(1), 4-15.
Heskett, J., Sasser, W. & Hart, C., 1990. Service Breaktroughs, New York:
Free Press.
Johnston, R. & Jones, P., 2004. Service productivity: Towards understanding
the relationship between operational and customer productivity. International Journal
of Productivity and Performance Management, 53(3), 201-213.
Johnston, R., 1989. The customer as employee. International Journal of Operations
& Production Management, 9(5), 104-12.
Klassen, K., Russell, R. & Chrisman, J., 1998. Efficiency and Productivity
Measures for High Contact Services. The Service Industries Journal, 18(4), 1-18.
Krajewski, L. & Ritzman, L., 1993. Operations Management: Strategy and
Analysis 3rd., USA: Addison-Wesley Publishing Company.
Küpers, W., 1998. Phenomenology of embodied productivity in services. International
Journal of Service Industry Management, 9(4), 337-358.
Lasshof, B., 2006. Produktivität von Dienstleistungen. Mitwirkung und Einfluss
des Kunden., Wiesbaden: Deutscher Universitäts-Verlag.
Lee, R., 2009. Social Capital and Business and Management: Setting a Research
Agenda. International Journal of Management Reviews, 11(3), 247-273.
20

Lehr, W. & Lichtenberg, F.R., 1998. Computer use and productivity growth in
US Federal Goverment Agencies, 1987-92. Journal of Industrial Economics, XLVI(2),
257-280.
Lovelock, C.H. & Young, R.F., 1979. Look at consumers to increase productivity.
Harvard Business Review, 57(3), 168-78.
Lovelock, C.H., 1991. Services Marketing, Engelwood Cliffs, NJ: Prentice Hall.
Lovelock, C.H., 1991. Services marketing 2. ed., Englewood Cliffs, N.J.: Prentice-Hall.
Markland, R.E., Vickery, S.K. & Davis, R.A., 1995. Operations Management.
Concepts in Manufacturing and Services, Saint Paul: West Publishing Company.
Marr, B., Gray, D. & Neely, A., 2003. Why do firms measure their intellectual
capital? Journal of Intellectual Capital, 4(4), 441-464.
Martin, C.R., Horne, D.A. & Chan, W.S., 2001. A perspective on client productivity
in business-to- business consulting services. International Journal of Service
Industry Management, 12(2), 137-157.
McLaughlin, C. & Coffey, S., 1990. Measuring productivity in services. International
Journal of Service Industry Management, 1(1), 46-64.
Nachum, L., 1999. Measurement of productivity of professional services:An illustration
on Swedish management consulting firms. International Journal of Operations
& Production Management, 19(9), 922-949.
Nachum, L., 1999. The Productivity of Intangible Factors of Production: Some
Measurement Issues Applied to Swedish Management Consulting Firm. Journal of
Service Research, 2(2), 123-137.
Norman, M. & Stoker, B., 1991. Data Envelopment Analysis: The Assesment
of Performance, New York: Wiley.
Ojasalo, K., 1999. Conceptualizing productivity in services, Helsinki: Swedish
School of Economics and Business Administration.
Ojasalo, K., 2003. Customer influence on service productivity. SAM Advanced
Management Journal, 68(3), 14-19.
Parasuramam, A., 2002. Service quality and productivity: a synergistic perspective.
Managing Service Quality, 12(1), 6-9.
Phelps, R., Adams, R. & Bessant, J., 2007. Life cycles of growing organizations:
A review with implications for knowledge and learning. International Journal of
Management Reviews, 9(1), 1-30.
Picot, A. & Gründler, A., 1995. Deutsche Dienstleister scheinen von IT nur
wenig zu profitieren. Computerwoche, 10, 10-11.
Pittaway, L. et al., 2004. Networking and innovation: a systematic review of
the evidence. International Journal of Management Reviews, 5/6(3/4), 137-168.
21

Quinn, B., Anderson, P. & Finkelstein, S., 1996. Leveraging intellect. Academy
of Management Executive, 10(3), 7-27.
Reichwald, R. & Möslein, K., 1995. Wertschöpfung und Produktivität von
Dienstleistungen? Innovationsstrategien für die Standortsicherung,
Rhyme, D., 1988. The Impact of Demand Management on the Service System
Performance. Service Industries Journal, 8(4).
Russell, R.S. & Taylor, B.W., 2000. Operations Management. Third Edition,
Upper Saddle River, New Jersey: Prentice Hall.
Schneider, B., 1980. The service organization: climate is crucial. Organizational
Dynamics. AMACOM, 52-65.
Shafti, F., Van Der Meer, R. & Williams, T., 2007. An Empirical Approach to
Service Classification for Productivity Management Studies. The Service Industries
Journal, 27(6), 709-730.
Sherman, H., 1984. Improving the productivity of service businesse. Sloan
Management Review, 25(3).
Siegel, I., 1980. Company Productivity: Measurement for Improvement, Michigan.
Upjohn Institute for Employment Research: Kalamazoo.
Singh, H., Motwani, J. & Kumar, A., 2000. A review and analysis of the stateof-the-art
research on productivity measurement. Industrial Management & Data Systems,
100(5), 234-241.
Slack, N., Chambers, S. & Johnston, R., 2007. Operations Management. Fith
Edition, Harlow: Pearson Education.
Thorpe, R. et al., 2005. Using knowledge within small and medium-sized firms:
A systematic review of the evidence. International Journal of Management Reviews,
7(4), 257-281.
Tranfield, D., Denyer, D. & Smart, P., 2003. Towards a Methodology for Developing
Evidence-Informed Management Knowledge by Means of Systematic Review*.
British Journal of Management, 14, 207-222.
Vargo, S. & Lusch, R., 2008. From goods to service(s): Divergences and convergences
of logics. Industrial Marketing Management, 37(3), 254 - 259.
Vargo, S.L. & Lusch, R.F., 2004. The Four Service Marketing Myths: Remnants
of a Goods-Based, Manufacturing Model. Journal of Service Research, 6(4),
324-335.
Verbeke, W., 2004. The Adaptive Consequences of Pride in Personal Selling.
Journal of the Academy of Marketing Science, 32(4), 386-402.
Vuorinen, I., Järvinen, R. & Lehtinen, U., 1998. Content and measurement of
productivity in the service sector: A conceptual analysis with an illustrative case from
the insurance business. International Journal of Service Industry Management, 9(4),
377-396.
22

Authors
Claudia, Lehmann, Dipl.-Wi.-Ing.
HHL - Leipzig Graduate School of Management
Center for Leading Innovation & Cooperation (CLIC)
Jahnallee 59 | 04109 Leipzig | GERMANY
claudia.lehmann@hhl.de
Marcus, Koelling, Dr.
HHL - Leipzig Graduate School of Management
Center for Leading Innovation & Cooperation (CLIC)
Jahnallee 59 | 04109 Leipzig | GERMANY
marcus.koelling@hhl.de
We agree that the submitted paper is published as Working paper.
23