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The relationship
Relationship between
between strategy
operations strategy and size in and firm size
engineering consulting firms
Daniel Arias Aranda
263
Universidad de Granada, Granada, Spain
Keywords Service operations, Strategy, Size, Engineering, Consultants
Abstract The relationship between strategy and firm size has been broadly considered and
studied in strategic management literature. However, this topic has not been paid as much
attention in the operations management field in manufacturing studies. The aim of this study is
to analyse the relationship between operations strategy and firm size in a sample of engineering
consulting firms. According to the results, there is a significant relationship between operations
strategy and size in consulting engineering firms. In this context, small firms tend to follow
customer-oriented operations strategies, medium sized firms tend to follow process-oriented
operations strategies and larger firms tend to follow service-oriented operations strategies.
Introduction
The relationship between strategy and firm size has been broadly considered and
studied in strategic management literature (see for example Andrews, 1971;
Argyris, 1985; Dess and Davis, 1984; Herbert, 1984; Miller, 1981; Rich, 1992).
However, this topic has not been paid as much attention in the operations
management discipline (Swink and Way, 1995). Moreover, when considering
service firms, studies directly relating to strategy and size are even scarcer
(Bozarth and McDermott, 1998). Most of them just do not consider size as a
moderating variable (see among others Ettlie, 1995; Mills et al., 1998; Morita and
Flynn, 1997; Smith and Reece, 1999).
The aim of this study is to analyse the relationship between operations
strategy and firms’ size in a sample of engineering consulting firms. Operations
strategy is measured through a set of items configuring nine dimensions. Size
is measured through firm turnover. Our main goal is to verify whether service
firms pursue different operations strategies according to different turnover
levels. Multivariate regression analysis is the statistical tool used for this study.
First we will review the concept of operations strategy and its possible
relationship with firms’ size in the context of service operations management.
Operations strategy and size
Operations strategy has received intense treatment for more than three decades
(Nieto AntolõÂn et al., 1999). Such interest has not excluded incorrect assumptions
about the environment. Moreover, many studies have neglected environmental
The author wishes to thank Professor Antonio RodrõÂguez Duarte (Universidad Complutense de
Madrid) for his inestimable help with the statistical processing of this paper. Nevertheless, the
author is the only person responsible for possible mistakes and omissions.
International Journal of Service
Industry Management,
Vol. 13 No. 3, 2002, pp. 263-285.
# MCB UP Limited, 0956-4233
DOI 10.1108/09564230210431974
IJSIM
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264
factors in operations strategy research (Flynn et al., 1995; Hayes and Schmenner,
1978; Skinner, 1969; Wheelwright, 1984).
Historically, operations strategy was not considered as a source of competitive
advantage until 1956 when Miller and Rogers (1956) distinguished between
operations and business strategy. The notion of operations strategy as part of the
business unit is relatively recent (Skinner, 1978; Hayes and Wheelwright, 1984). In
fact, the operations function was relegated in the past to the mere accomplishment
of efficiency standards through time, resources and space optimization
throughout the development of the scientific work management principles
(Abernathy and Corcoran, 1983; Chandler, 1991). The concept of operations
management (OM) considers that there is one only right approach to manage
production activities. Skinner (1969) was the first to set the basic principles for
elaborating an operations strategy:
Different firms have different strengths and weaknesses so they can
choose their own way to be competitive.
In a similar manner, different production systems have different operations
features so there is not necessarily a unique standard production system.
The main operations function goal is to develop a production system that
reflects the firm’s implicit priorities and tradeoffs related to its specific
competitive situation and strategy, all of that through interrelated and
internally consistent decisions.
OM literature identifies two main elements allowing the definition of operations
strategy. Those are established from a functional point of view. The first element
is related to those goals that the OM function must achieve (Skinner, 1978). This
element is known as the operations task, which is built from those capabilities
that the OM function must develop in order to create a competitive advantage for
the firm. Some of those tasks are quality, cost, reliability and flexibility (Heizer
and Render, 1996). Hill (1989) defines operations strategy considering the
development of those tasks that allow the firm to focus on the customer instead of
focusing on the production process.
As a result, operations strategy is defined by the group of decisions related to
the structure of the production system including the systems and policies that
define the infrastructure of the firm (Clark, 1996, p. 45). Hence, the operations
function confronts different alternative decisions, which configure the OM
performance (Hayes and Wheelwright, 1984). However, the operations strategy
must be consistent with all strategy levels (Anderson et al., 1989; Buffa, 1984;
Miller and Roth, 1994; Roth and Miller, 1990, 1992; Swamidas and Newell, 1987) in
order to support and be part of the whole firm’s strategy (Hayes and Wheelwright,
1984). In the long term, the operations strategy success depends on the capability
to generate abilities in order to achieve a competitive advantage for the firm in a
proactive way (Ferdows and De Meyer, 1990; Hayes and Wheelwright, 1984; Hill,
1989). Consequently, operations strategy can be defined as a vision of the
operations function that depends on the corporate management for decision
making. This vision must be integrated with the firm’s strategy and is frequently The relationship
reflected in a formal plan. Output of the operations strategy should be a consistent between strategy
standard for the decision-making process in order to achieve a competitive
and firm size
advantage for the firm (Schroeder, 1992, p. 2). Operations strategy also feeds back
the firm’s corporate strategy (Hayes, 1985).
Once the operations strategy concept has been defined, the different types of
265
operations strategies are to be determined. Strategic management as well as
organizational design academicians have analyzed this topic on many occasions
(Hambrick, 1983; Fahey and Christensen, 1986; McGee and Thomas, 1986). There
is a limited number of feasible strategies for each productive configuration (Miller
and Friesen, 1984; Miller, 1986), so strategic models based on productive
configurations are generally classified into taxonomies and typologies (Miller and
Friesen, 1984; Meyer et al., 1993). Typologies describe ideal models, each one
representing a unique combination of organizational attributes (Doty and Glick,
1994). Hence, there might not be any organization that fits perfectly in a
determined ideal model. Anyway, a firm’s identification with one of the ideal
models could imply significant improvements in the organizational performance
(Venkatraman, 1989; Venkatraman and Prescott, 1990).
On the other hand, taxonomies do not define ideal models, but they classify
organizations in mutually exclusive and exhaustive groups (Doty and Glick,
1994). Taxonomies are derived either from multivariate statistical techniques or
from mere observation (Wheelwright and Hayes, 1985). Bozarth and McDermott
(1998) review different taxonomies and typologies for productive configurations
(see Tables I and II).
Level of
analysis
Authors
Development
Stobaugh and
Telesio (1983)
Conceptual;
from case
study
Firm/strategic
unit
Wheelwright
and Hayes
(1985)
Conceptual
from field
work
Strategic unit
Miller and
Roth (1994)
Empirical,
from 164
firms clusters
Production
strategic unit
Grouping
Variables
Three strategic
types: low cost,
technological and
marketing
intensive
Four stages that
describe the
strategic role of
OM: internally
and externally
neutral and
internal and
external support
Three types of
strategy: risk
evaders, market
oriented and
innovators
Eight dimensions
based on decisions
about plant and
technology
management
Strategic focus
toward OM; level
of involvement in
strategic decisions
Source: Adapted from Bozarth and McDermott (1998, p. 432)
11 competitive
priorities
Table I.
Taxonomies of
strategic configurations
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Development
Hayes and
Wheelwright
(1979, 1984)
Conceptual
from case
study
Production
plant
Richardson
et al. (1985)
Empirical
from a
64-firm
sample
Firm
Hill (1989)
Conceptual,
based on
plant
research and
literature
review
Conceptual,
partially
based on
Porter (1980)
Production
plant
Strategic unit
Eight types of
strategy based on
combinations of
three dimensions
Conceptual,
based on
literature
review
Firm/strategic
unit
Four
configurations:
niche, market
scope, low cost
and lean
production
Kotha and
Orne (1989)
Ward et al.
(1994)
Table II.
Typologies of strategic
configurations
Level of
analysis
Authors
Grouping
Variables
Four types of
processes: shop,
batch, line and
flow
Six types of
strategy: three of
them based on
technology, two
based on product
customization and
one based on
costs
Five types of
processes: project,
job shop, line and
continuous
Process flow,
product volume,
and
standardization
Three dimensions:
volume, product
variety and degree
of innovation
More than 20
aspects about
products, markets,
production,
investment and
infrastructure
Three dimensions:
complexity of the
process structure,
product line and
organizational
scope
16 dimensions
measuring four
areas: strategy,
environment and
production
capabilities
Source: Adapted from Bozarth and McDermott (1998, p. 433)
Different studies relate operations strategy to other management variables.
However, firm size is not even considered in many empirical works (Berry et al.,
1991). Moreover, empirical models are tested and validated for manufacturing
firms of significantly different sizes without further analyses (see Minor et al.,
1994). For service industries and due to service heterogeneity, firm size turns
into a complex variable to consider in service operations management studies.
Hence, the size variable can be more effectively controlled in single sector
studies.
The relationship between operations strategy and firm’s size is supported by
the contingency theory (Lawrence and Lorch, 1967) according to which
environmental and structural contingencies make some strategies more
effective than others. Therefore, if firm’s size is a clear structural contingency,
it should influence operations strategy in some way. Nowadays, firm’s size as a
contingent variable is specially considered in studies related to finance and The relationship
industrial economics. Recent research shows how resources availability limits between strategy
R&D investments and acquisition of technology (Poyago-Theotoky, 1998;
and firm size
Garvey, 1994). Therefore, firm growth emerges as the key factor to reach new
and larger markets (Schutjens and Wever, 2000; Van Wissen, 2000). Process
technologies allow firms to produce and serve focused on higher volume
267
demands. Hence, larger firms display low degrees of asymmetry in their risk
across recession and expansion states, which makes them less sensitive to
credit market conditions (Perez-Quiros and Timmermann, 2000). Substitution
of workforce by technology is especially relevant for medium and large firms
because of over employment of smaller firms (Smith, 1998).
In this context, we deduce and suggest the following pattern of behaviour for
engineering consulting firms in order to state our hypothesis. Small
engineering consulting firms usually tend to focus on a few segments of
customers in such a way that service delivery systems are designed to
customize most service-products by combining general use technologies and
intensive workforce. These small firms specialize in delivering specific services
with a high customer orientation. Medium sized firms have larger capacities to
serve a wider range of customer segments. However, acquisition of specialized
technology is still not available to these firms. Such technologies are profitable
only to satisfy larger demands, for which these firms lack capacity. On the
other hand, the combination of general technologies and intensive workforce
does not allow these firms to customize services in the same way smaller firms
do. Therefore, medium sized firms focus on segments of customers with similar
needs, so service process optimisation can be achieved. Finally, larger firms are
able to combine both customisation and process optimisation through the
combination of general use and specialized technologies and workforce. These
larger firms try to offer customers integral services by standardizing early
stages of service delivery and customizing final specifications.
Consequently, the main hypothesis to be tested is:
H1. Operations strategy is closely related to firm size in engineering
consulting firms.
This main hypothesis can be split into the following sub-hypotheses.
H1a. Small firms tend to follow customer-oriented operations strategies.
H1b. Medium firms tend to follow process-oriented operations strategies.
H1c. Larger firms tend to follow service-oriented operations strategies.
Dimensions in service operations strategy
Literature on service operations management identifies three basic operations
strategies according to the firm’s focus of activities. Therefore, service
industries can pursue process, service or customer-oriented operations
strategies (see among others Johnston, 1994; Haynes and Du Vall, 1992; Bowen
and Youngdahl, 1998; Hart, 1995; Desatnik, 1994; Berry and Parasuraman,
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1997; Lusch et al., 1996; McCutcheon et al., 1994; Tersine and Harvey, 1998;
Collier, 1994, 1996; Sampson, 1996). From a reflective analysis of these studies,
nine dimensions configuring the basic service operations strategies were
extracted. These are:
(1) type of operations layout;
268
(2) push/pull orientation of the service delivery process;
(3) degree of process standardisation;
(4) number of different services offered;
(5) use of information technologies (cost reduction vs service improvement);
(6) back and front office activities relationship;
(7) human resources specialisation;
(8) degree of customer participation; and
(9) new service design and development.
Type of operations layout directly influences the way operations are configured
in the service delivery process. A process layout tends to organise service
delivery as a sequential activities process (Bowen and Youngdahl, 1998). On
the opposite side, product layout does not imply task sequentiality. This leads
to task development with no pre-established order (Johnston, 1994). Mixed
layouts in which only a part of the service delivery process is sequential while
other parts are developed according to service specific characteristics are also
considered (Haynes and Du Vall, 1992).
Push/pull orientation of the process determines the production philosophy of
the service delivery. Pull oriented service firms initially consider customer
needs when developing service activities. Activities do not end until the service
firm has satisfied perceived customer expectations (Bitran and Hoech, 1990;
Hart, 1995). Push oriented service firms undertake important investments in
production capacity in order to satisfy demand. Demand is fostered through
strong marketing efforts (Tersine and Harvey, 1998; Hart, 1995). Again, mixed
push/pull configurations are considered.
Degree of service standardisation is referred to as the extent to which task
procedures are pre-established. Therefore, it also influences employees’
empowerment (Bowen and Schneider, 1985; Mills and Morris, 1992).
Standardisation intends to minimise variability in the service delivery process,
so procedures of developing each task are limited (Hart, 1996).
The number of different services offers measures the degree of
diversification of the firm according to the final products/services delivered
(Desatnik, 1994). This dimension shows how the firm is oriented towards many
or few customer segments (Lewis and Klein, 1984). It also regards how related
the final products/services are, so a firm offering two products/services lines
with few similarities between them is considered to retain a higher degree of
product/service amplitude than a firm offering many related products/services The relationship
lines.
between strategy
Use of information technology (IT) is considered according to two
and firm size
parameters. On one side, IT can be used in order to reduce costs through, for
instance, substitution of workforce by technology (Berry, 1995). On the other
side, IT investment can be made for final service improvement, for instance,
269
through simulation technology to verify service quality and reliability.
The relationship between front and back office activities is referred to as
physical location as well as to workforce information exchange. Such a
relationship directly affects customer perception of service delivery. When both
activities are physically separated, customer effort to obtain information about
back office activities is higher and will be moderated by the mechanisms of
information exchange between both front and back office activities (Price et al.,
1995; Lusch et al., 1996). However, physical closeness of both activities
increases information effectiveness and reliability for the customer (Chase,
1981).
Degree of workforce specialization intends to determine personnel
versatility when accomplishing various and different activities. Hence, the staff
can be prepared either to undertake one or few specific tasks, or else, to carry
out any activity totally or partially (George, 1990; McCutcheon et al., 1994;
Tersine and Harvey, 1998). A more versatile workforce responds more quickly
and efficiently to environmental changes, while highly specialized personnel
tend to be more rigid (Ashford and Humphrey, 1993; Schneider and Bowen,
1993; Bowen and Lawler III, 1995). This fact is especially relevant for those
service firms that have IT with a high degree of obsolescence at the basis of
their activity.
Degree of customer contact and participation relates to the level of
interaction between customer and service delivery process. Such interaction
can be utilised either to transfer some activities to customers in order to reduce
process costs or to customise service delivery (Bolton and Drew, 1991; Cadotte
and Turgeon, 1988). In the first case, the customer acts as staff by developing
tasks of the service delivery process (Lampel and Mintzberg, 1996). In the
second case, the customer exchanges information with the service delivery
activities, which will be developed in the firm (Collier, 1994, 1996; Gouillart and
Sturdivant, 1994).
Finally, intensity of design and development of new services refers to
whether or not the firm sets new service delivery procedures through new task
organisations and investments in specific resources. Therefore, it is possible to
know, through this dimension, the firm’s intention to innovate in new processes
and services (Bowen and Youngdahl, 1998; Berry et al., 1991; Sampson, 1996).
Methodology
Sample and the sampling procedure
This study was conducted in the context of engineering consulting firms in
Spain. The previously stated dimensions of operations strategy are of
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particular importance in this service sector. Three firm types (civil, industrial
and environmental) were considered, covering most activities of engineering
consulting firms. Table III shows the main activities of every type.
According to the Spanish Ministry of Industry (1998), the nature of the work
undertaken such firms in Spain is determined by the following intermediaries’
patterns:
Operations are design to primarily satisfy internal demand. Only 10 per
cent of average turnover of the sector comes from outside markets. More
than 55 per cent of turnover derives from public administration projects.
Intermediate demand plays a fundamental role as it allows constructors
to act as intermediate suppliers for final demands of infrastructures and
equipment.
It is a knowledge-intensive sector. Fixed workforce costs represent
about 65 per cent of all fixed costs of the sector due to the need to hire
professional staff.
Most projects performed are prototypes. Hence, production processes
are not easily industrialised.
Investments are written off in short periods of time, especially for
computer equipment that has to be continually renewed in order to
remain competitive.
These firms tend to centralise resources for service delivery. Only
multinational firms have offices abroad for commercial purposes, this is
why no distinction was made between overall firm size and average
office size (Table IV shows the operations patterns of these firms
according to the Spanish Ministry of Industry (1998)).
Initially, a copy of the questionnaire was sent to ten firms representing every
turnover and activity group as a pre-test. They were asked not to answer the
questionnaire but to remark on all doubts or possible mistakes detected. Only
Civil
Table III.
Main activities of
engineering consulting
firms
Transportation and
communications
Hydrology and
hydraulics
Geology and geodetics
Agronomy, fishing and
cattle
Town planning and
architecture
Main activities of engineering consulting firms
Industrial
Environmental
Energy
Mining
Industrial plants
Chemical plants
Source: Spanish Ministry of Industry (1998)
Environment
protection
Management and use
of natural resources
small syntactic changes were made but none of the firms remarked on The relationship
difficulties for concept understanding or misuse.
between strategy
The data for the empirical investigation of the model were obtained through
and firm size
a field study in Spain. Data were collected from participating firms
predominantly via e-mail to the operations managers/executives or equivalent
having a high level of responsibility in their companies. The Spanish
271
Association of Spanish Engineering Consulting Firms (Tecniberia) provided all
information about addresses and firm names. Initially, and in order to attract
the maximum number of participating firms, an e-mail was sent to all firms
registered in Tecniberia soliciting their participation while stressing the
importance of the study. The researchers considered a total of 129 firms with a
turnover higher than 150,000 euros. As a second step, a copy of the
questionnaire was sent to all of them. A total of 12 firms requested the
questionnaire to be sent via ordinary mail with a 100 per cent response rate.
Non-respondents were contacted as much as three times in order to get them to
participate in the study. Of these, usable data were collected from a total of 71
firms (55 per cent). The questionnaire’s original language was Spanish. Table V
shows a description of the sample according to the five turnover categories.
Comparing the sample distribution with the sector as a whole, no significant
discrepancies were observed. Most of the firms’ turnover ranges from 300,000
to 3,000,000 euros (60 per cent approximately of the total sample). On the other
hand, civil engineering firms represent the higher percentage of the sample (49
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
Customer needs and wishes detection for project configuration
Feasibility and environmental impact studies
Information exchange with customer for final technical and technological specifications
Plans and budgets elaborations
Project contract development with final specifications and project termination dates
Project development
Project delivery to customer
Post-sale services
Source: Spanish Ministry of Industry (1998)
Cat.
Turnover (euros)
1
2
3
4
5
< 300,000
300,000-600,000
600,001-3.000,000
3,000,001-6,000,000
> 6,000,000
Total
Source: Own processing
Civil
Firms Per cent
7
11
11
3
3
35
20.0
31.4
31.4
8.6
8.6
100.0
Group of activity
Industrial
Firms Per cent
3
3
4
0
2
12
25.0
25.0
33.3
0.0
16.7
100.0
Table IV.
Operations patterns
Environmental
Firms Per cent
7
7
8
2
0
24
29.2
29.2
33.3
8.3
0.0
100.0
Table V.
Sample distribution
(turnover and group
activity)
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per cent) compared to 17 per cent of industrial engineering and 34 per cent of
environmental engineering. Table VI shows the turnover distribution of the
firms according to Spanish Ministry of Industry (1998).
Measures
Questions related to operations strategy are based on a five-point Likert scale.
Every one of the nine dimensions of operations strategy was clearly
represented in differentiated blocks in the questionnaire. Control questions
were included in order to verify internal consistency of the questionnaire. For
every dimension, a set of items was included in the questionnaire. Questions
related to service strategies were developed after an extensive literature review
and inputs from a panel of service managers. For every item a Likert scale
ranging from 1 (completely agree) to 5 (completely disagree) was used to
measure agreement of the operations managers/executives with such items (see
Appendix).
Partial indicators were developed in order to identify the firm positioning for
every operations strategy dimension. Such indicators combine the different
items corresponding to each dimension in order to measure the firms’ trends. A
global indicator was developed to measure operations strategy according to
such trends, taking into account that the indicator’s rank should flow between 1
and 5 values in order to be consistent with the Likert scale previously used. So,
it was designed as follows:
P
P
P
P
5‰… biˆa Ain ¡ diˆc Ain † ‡ j… diˆc Ain ¡ 5 biˆa Ain j ‡ 1Š
Ebn ˆ
P
P
P
P
‰j…5 biˆa Ain ¡ diˆc Ain †j ‡ j… diˆc Ain ¡ 5 biˆa Ain j ‡ 1Š
where:
Ebn = the indicator.
Ain = the score obtained in question i of block n in the questionnaire. Rank
[a,b] represents questions scoring towards one of the trends in each block.
Rank [c,d] represents questions scoring towards opposite extremes of rank [a,b]
in each block.
P
P
Hence, … diˆc Ain ¡ 5 biˆa Ain † represents the smallest reachable value,
supposing that one firm scores the highest (score 5) in all questions for one of
the trends and the
P lowest (score
P 1) in all questions of the opposite trend. On the
other hand, …5 biˆa Ain ¡ diˆc Ain † represents the smallest reachable value
for a firm positioned at one extreme, scoring the lowest (score 1) and the highest
Table VI.
Distribution in
percentage of
engineering consulting
companies in Spain
Turnover (euros)
Percentage of firms
<300,000
300,000600,000
600,0013,000,000
3,000,0016,000,000
>6,000,000
27.3
32.3
27.2
6
7.2
Source: Spanish Ministry of Industry (1998)
(score 5) for the opposite trends. Once the extremes and possible intermediate The relationship
values have been obtained, the indicator transforms this rank in a scale from 0 between strategy
to 5 by adding to the value obtained, the smallest reachable value plus 1. The
and firm size
value obtained is finally divided by the highest reachable value adding the
lowest value plus 1 in order make the scale positive. Finally, the obtained value
is multiplied by 5 to transform it to the 0 to 5 scale.
273
Partial indicators of the nine dimensions of operations strategy were
obtained, so combining these partial indicators into a global indicator; firms are
classified according to the operations strategy they pursue. Such indicator
intends to resume the multidimensional nature of operations strategy.
Therefore, it is possible to know every firm’s positioning in or near one of the
three basic strategies previously defined.
Inter-item analysis was used to check scales for internal consistency or
reliability. Specifically, Cronbach’s reliability coefficient (alpha) is calculated
for each scale (dimension), as recommended by empirical research in operations
by many researchers (Flynn et al., 1995; Swamidass and Newell, 1987; Smith
and Reece, 1999). Cronbach’s alphas and trends for every dimension according
to the indicator values are shown in Table VII.
Usually, a value of 0.7 in the Cronbach’s alpha is considered as adequate in
order to ensure reliability of the internal consistency of the questionnaire
(Nunnally, 1978). However, a margin of 0.5 to 0.6 is generally considered
adequate for exploratory work (Nunnally, 1978; Srinivasan, 1985). Construct
validation is a process of demonstrating that an empirical measure corresponds
to the conceptual definition of a construct (Schwab, 1980). Consequently, three
types of validity can be established: nomological or theoretical validity, vertical
validity and horizontal or criterion-related validity. We can argue that the
measurement instrument establishes the basis for nomological or theoretical
validity since all items are developed through an extensive review of the
Operations strategy dimension
I.
II
Type of operations layout
Push and/or pull orientation of the
service delivery process
III. Degree of process standardisation
IV. Number of different services offered
V.
Use of information technologies (cost
reduction vs service improvement)
VI. Back office and front office
interrelationship
VII. Human resources specialisation
VIII. Degree of customer participation
IX.
New service design and
development
Source: Own processing
Cronbach’s alpha Value near 0
Value near 5
0.5981
Fix
Moving
0.6530
0.6844
0.6240
0.6775
Pull
Low
Narrow
Service
improving
Push
High
Broad
Cost
reduction
0.8826
0.6310
0.7580
Close
Versatile
Cost
reduction
Separate
Rigid
Service
adaptation
0.9331
Low
High
Table VII.
Operations strategy
dimensions
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service operations strategy body of research. Factor analysis was used to check
unidimensionality of scales, which provides evidence of a single latent
construct (Flynn et al., 1995). Cronbach’s alpha values address vertical validity,
which describes the extent to which a scale represents its construct. Evidence
of criterion-related validity is presented through the Browne and Cudeck (1993)
cross-validation index for covariance structure modelling. Index value for this
research is 0.642, which indicates a high probability that the model results are
consistent with population parameters. Table VIII shows the definition of the
service operations strategies according to the nine basic dimensions.
Results
An initial scatterplot (see Figure 1) shows the spread of firms along the five
operations strategies considered. Strategies are shown in a continuum along
the possible values of the global indicator. This continuum lets us observe how
close firms are, according to the operations strategy pursued, so firms included
in a determined category with high values are closer to those firms with low
values in the next category. Three groups can be identified at a first glance.
First, a group of seven firms score values from 0 to 1 in operations strategy,
which means they pursue a customer oriented strategy or similar according to
the previous nine strategy dimensions and the value of the final indicator. A
total 26 firms pursue service oriented or similar strategies, scoring values from
1 to 3. Finally, a group of 28 firms are closely pursuing a process oriented or
similar strategy by scoring from 3 to 5.
An X-Y plot of operations strategy vs firm’s turnover lets us see how firms
are distributed along the different strategies according to size. As we can
observe, firms with the highest and lowest turnover tend to score between the
values 1 and 3 while medium sized firms tend to score between 4 and 5.
After an initial approximation to data distribution, a multiple regression
analysis was performed in order to test the main hypothesis and each of the
sub-hypotheses. Table IX shows the P-value in the previous ANOVA analysis
to be less than 0.01, so there is a statistically significant relationship between
the variables at the 99 per cent confidence level. The output shows the results
of fitting a multiple linear regression model to describe the relationship
between operations strategy and two independent variables. The equation of
the fitted model is
Operations strategy= 0.0604618 + 2.26107*Turnover
– 0.420298*Squared_Turnover
The R-squared statistic indicates that the model as fitted explains 31.646 per
cent of the variability for the operations strategy variable (see Table IX). The
adjusted R-squared statistic is 29.6356 per cent. The standard error of the
estimate shows the standard deviation of the residuals to be 0.979206. The
mean absolute error (MAE) of 0.837237 is the average value of the residuals.
The Durbin-Watson (DW) statistic tests the residuals to determine if there is
any significant correlation based on the order in which they occur in the data.
Dimension
Process oriented
Customer oriented
Service oriented
I
Process layout. Service
process activities are
mainly sequential.
Service location is
usually not movable.
Main process goal is
space optimisation.
Workforce is highly
specialised
Product (service)
layout. Service delivery
tasks are neither
sequential nor fixed
located. Tasks
allocation is flexible
Layout is hybrid,
although usually
process oriented.
Service delivery tasks
tend to be sequential,
though task variability
leads to a significant
degree of
customisation through
changes in location
II
High investments in
capacity satisfy large
demands supported by
strong marketing
efforts. Process is push
oriented
Service delivery
process is pull
oriented. Customer
satisfaction drives
service delivery
process
Operations are pull
oriented. Process
capacity tends to be
low. Only small
demands can be
satisfied
III
Most activities are
standardized. There is
one or few ways to
achieve service
delivery tasks. Task
variability is to be
minimised. Work
procedures are preestablished
Most service delivery
activities are
customised. There are
few pre-established
procedures to develop
service delivery tasks
Most process activities
are customized,
although customisation
range is small. There
are many different
ways to accomplish
tasks. Pre-defined
general procedures
drive service delivery
IV
Range of different
services offered is
short and services are
usually closely related
Differentiation of the
services provided is
high. Every service
delivered can be
considered as
unique
There are few different
services offered, all of
them being closely
related. Diversification
is low
V
New technologies
investments are
accomplished in order
to reduce costs.
Workforce tends to be
replaced by technology
Use of and investment
in new technologies
has as the main goal
to increase customer
satisfaction
Use of and investment
in new technologies
tends to balance cost
reduction and
customisation
VI
Back and front office
activities are
physically separated in
order to increase
efficiency
Back and front office
activities are
physically integrated
by sharing personnel.
Customer gets on line
information about
service delivery
Back and front office
activities tend to be
physically separated,
although they share
personnel. Such
separation is usually
due to space
optimisation
(continued)
The relationship
between strategy
and firm size
275
Table VIII.
Definition of the
service operations
strategies according to
the nine basic
dimensions
IJSIM
13,3
Dimension
Process oriented
Customer oriented
Service oriented
VII
Workforce is highly
specialized. Versatility
is low. Every worker
accomplishes one of
few very specific tasks
Personnel are not
highly specialised but
trained for versatility.
Anybody must be able
to develop any task
totally or partially
Personnel are very
specialized. However,
they are trained for
versatility and fast
adaptation to
organisational and
technology change
VIII
Low customer contact.
Customer participates
in the service process
only to reduce costs
for the firm
High degree of
customer contact in
order to customise
service
Degree of customer
contact is high.
Customer participation
in the service delivery
process is high in
order to customize
service
IX
Design and
development of new
services and processes
is not strongly
supported
High intensity in
design and
development of new
service. New services
and processes are
being developed
continually
Low intensity in
design and
development of new
services and processes
276
Table VIII.
Source: Own processing
Figure 1.
Plot of operations
strategy with predicted
values
Since the DW value is less than 1.4, there may be some indication of serial
correlation. However, after plotting the residuals versus row order no pattern
could be determined.
In determining whether the model could be simplified, the highest P-value on
the independent variables is 0.0000, belonging to the turnover variable. Since
the P-value is less than 0.01, the highest order term is statistically significant at
the 99 per cent confidence level. Figure 1 shows also the fitted line of this model.
Parameter
Constant
Turnover
Turnover^2
Dependent variable: operations strategy
Estimate
Standard error
T statistic
0.0604618
2.26107
–0.420298
0.535823
0.423928
0.0751008
0.0112839
5.33362
–5.59645
P-value
0.9105
0.0000
0.0000
The relationship
between strategy
and firm size
277
Source
Model
Residual
Total (corr.)
Sum of squares
30.1864
65.2014
95.3878
Analysis of variance
Df
Mean square
2
68
70
15.0932
0.958844
F-ratio
P-value
15.74
0.0000
Notes:
R-squared = 31.646 percent
R-squared (adjusted of d.f.) = 29.6356 percent
Standard error of est. = 0.979206
Mean absolute error = 0.837237
Durbin-Watson statistic = 0.569112
Source: Own processing
As it can be observed, an inverted U form configures the fitted model line
according to the quadratic equation.
Conclusions
According to the results, there is a significant relationship between operations
strategy and size in consulting engineering firms. Small firms tend to follow
customer-oriented operations strategies, medium firms tend to follow processoriented operations strategies and larger firms tend to follow service-oriented
operations strategies. So, the main hypothesis and the three sub-hypotheses are
positively contrasted for engineering consulting firms. Hence, we believe that
the results presented in this study provide valuable information related to the
management of service operations. Even though the current research was
exploratory in nature, it presented a better understanding of management
issues related to a determined service industries size.
Also, a pattern for the life cycle of consulting engineering firms can be
extracted from the results. Consequently, increases in firms’ capacity, use of
technology and customer segments seem to be the three key factors for
operations strategy changes and flexibility in this type of service industry.
Small engineering consulting firms perform customized and flexible operations
strategies. When they grow, standardised and more rigid operations strategies
are implemented. Finally, larger firms balance both flexibility and
standardisation in the service delivery system through higher investments in
technology and human resources.
Table IX.
Multiple regression
analysis
IJSIM
13,3
278
The conclusions of this study are also relevant to practitioners, not only for
operative decisions such as staffing, training and scheduling, but also for those
strategic decisions that position the firm in a determined service/market.
Hence, decisions related to firm’s growth should be closely attached to those
related to process technology investments in order to be competitive.
Practitioners should also consider that the firm’s operations strategy defines
the way firms are going to manage the service delivery process. So, acquisition
of new process technology is going to modify the way the firm serves
customers. Moreover, it can also change focusing patterns on customer
segments. Therefore, target segments can differ according to firm size or
elsewhere; the same customer segments may be served in a different way by
firms of different sizes. A competitive advantage can be obtained by
identifying the preferred service delivery system for customers.
Even though this paper presents interesting results related to service
management, the study contains limitations, which should be dealt with in
future research projects. Now we discuss some of those limitations and provide
directions for future research projects.
The current study implicitly assumes that the service, customer and processoriented strategies are a precise classification. Another related issue involves
the selection of the nine dimensions as classification scheme for analysis. As
mentioned earlier in the paper, service management literature contains a
number of typologies and taxonomies. However, there is not enough empirical
support for the proposed concepts. Therefore future research should be directed
towards empirically testing/validating the proposed ideas in different service
sectors. With respect to the current study itself, a few issues are of concern. For
example, since we developed the 53-item questionnaire based on service
operations literature, it is possible that certain other important operations
management issues were ignored.
Direction for future research
The findings of this study answer some of the questions about the
relationship between service operations strategy and size. It has been
observed that firm size affects operations strategies significantly. This
research also suggests the importance of concentrating on a few appropriate
strategies rather than implementing all the available ones. One of the areas
of future research is the investigation of the appropriateness of an individual
strategy or a combination of strategies that may benefit a particular service
industry. Recommendations can be made to implement a group of strategies
categorized by different classes and sizes of industry; these will be a
significant contribution to the literature on operations strategy.
Additionally, significant control variables should be identified in order to
develop new models that moderate the relationship between size and
operations strategy. In addition, the application of this model to different
service sectors remains to be tested.
As mentioned before, the current study contains several limitations, but at The relationship
the same time provides empirical analysis of some important service operations between strategy
management issues. We hope that this study, although exploratory in nature,
and firm size
would encourage others to reconsider generally accepted concepts and
hopefully motivate them to undertake empirical service management research
projects in different service sectors.
279
References
Abernathy, W. and Corcoran, J. (1983), ``Relearning from the old masters: lessons of the American
system of manufacturing’’, Journal of Operations Management, Vol. 3 No. 4, pp. 155-67.
Anderson, J.C., Cleveland, G. and Schroeder, R.G. (1989), ``Operations strategy: a literature
review’’, Journal of Operations Management, Vol. 8 No. 2, pp. 1-26.
Andrews, K.R. (1971), The Concept of Corporate Strategy, Irwin, Homewood, IL.
Argyris, C. (1985), Strategy Change and Defensive Routines, Pitman Publishing, London.
Ashford, B.E. and Humphrey, R.H. (1993), ``Emotional labor in service roles: the influence of
identities’’, Academy of Management Review, Vol. 18 No. 1, pp. 88-115.
Berry, L.L. (1995), On Great Service: A Framework for Action, The Free Press, New York, NY.
Berry, L.L. and Parasuraman, A. (1997), ``Listening to the customer – the concept of a servicequality information system’’, Sloan Management Review, Vol. 38 No. 3, pp. 65-76.
Berry, W., Bozarth, C., Hill, T. and Klompmaker, J. (1991), ``Market segmentation analysis in
formulating operations analysis’’, Journal of Operations Management, Vol. 10, pp. 363-87.
Bitran, G.R. and Hoech, J. (1990), ``The humanization of service: respect at the moment of truth’’,
Sloan Management Review, Vol. 31 No. 2, Winter, pp. 89-96.
Bolton, R.N. and Drew, J.H. (1991), ``A multistage model of customer’s assesment of service
quality and value’’, Journal of Consumer Research, Vol. 17, pp. 375-84.
Bowen, D.E. and Lawler, E.E. III (1995), ``Empowering service employees’’, Sloan Management
Review, Summer.
Bowen, D.E. and Schneider, B. (1985), ``Boundary spanning role employees and the service
encounter: some guidelines for management research’’, in Czepiel, J.L., Soloman, M.R. and
Surprenan, C.F. (Eds), The Service Encounter, Lexington Books, Lexington, MA.
Bowen, D.E. and Youngdahl, W.E. (1998), ```Lean’ service: in defense of a production-line
approach’’, International Journal of Service Industry Management, Vol. 9 No. 3, pp. 207-25.
Bozarth, C. and McDermott, C. (1998), ``Configurations in manufacturing strategy: a review and
directions for future research’’, Journal of Operations Management, Vol. 16, pp. 427-39.
Browne, M. and Cudeck, R. (1993), Alternative Ways of Assessing Model Fit, Kluwer Publishing,
Dordrecht.
Buffa, E.S. (1984), Meeting The Competitive Challenge, Dow-Jones-Irwin, Homewood, IL.
Cadotte, E.R. and Turgeon, N. (1988), ``Dissatisfiers and satisfiers: suggestions for consumer
complaints and compliments’’, Journal of Consumer Satisfaction, Dissatisfaction and
Complaining Behaviour, Vol. 1, pp. 74-79.
Chandler, A. (1991), Scale and Scope: The Dynamics of Industrial Capitalism, Harvard University
Press, Cambridge, MA.
Chase, R.B. (1981), ``The customer contact approach to services: theoretical bases and practical
extensions’’, Operations Research, Vol. 29, No. 4.
Clark, K.B. (1996), ``Competing through manufacturing and the new manufacturing paradigm: is
manufacturing strategy passeÂ?’’, Production and Operations Management, Vol. 5 No. 1,
pp. 42-58.
IJSIM
13,3
Collier, D.A. (1994), The Service-Quality Solution: Using Service Management to Gain Competitive
Advantage, Irwin, Homewood, IL.
Collier, D.A. (1996), ``Tight and loose comprehensive customer contact (3C) plans’’, Advances in
Service Marketing and Management, JAI Press, Greenwich, CT, Vol. 5, pp. 153-68.
Desatnik, R. (1994), ``Managing customer service for the 21st century’’, Journal for Quality and
Participation, Vol 17, pp. 30-6.
280
Dess, G. and Davis, P.S. (1984), ``Porter’s (1980) generic strategies as determinants of strategic
group membership and organizational performance’’, Academy of Management Journal,
Vol. 27, pp. 467-88.
Doty, H. and Glick, W. (1994), ``Typologies as unique form of theory building: toward improved
understanding and modelling’’, Academy of Management Review, Vol. 19 No. 2, pp. 230-51.
Ettlie, J.E. (1995), ``Product-process development integration in manufacturing’’, Management
Science, Vol. 41 No. 7, pp. 1224-37.
Fahey, L. and Christensen, H.K. (1986), ``Evaluating the research on strategy context’’, Journal of
Management, Vol. 12 No. 2, pp. 167-83.
Ferdows, K. and De Meyer, A. (1990), ``Lasting improvements in manufacturing performance: in
search of a new theory’’, Journal of Operations Management, Vol. 9 No. 2, pp. 168-84.
Flynn, B., Sakakibara, S., Schroeder, R., Bates, K. and Flynn, J. (1995), ``Empirical research
methods in operations management’’, Journal of Operations Management, Vol. 9 No. 2,
pp. 250-84.
Garvey, G.T. (1994), ``Should corporate managers maximize firm size or shareholder wealth? A
theory of an optimal trade-off’’, Journal of the Japanese and International Economies, Vol. 8
No. 3, pp. 343-52.
George, W. (1990), ``Internal marketing and organizational behavior: a partnership in developing
customer-conscious employees at every level’’, Journal of Business Research, Vol. 20,
pp. 63-70.
Gouillart, F. and Sturdivant, F. (1994), ``Spend a day in the life of your customers’’, Harvard
Business Review, January-February, pp. 116-25.
Hambrick D.C. (1983), ``Some tests of the effectiveness and functional attributes of Miles and
Snow’s strategic types’’, Academy of Management Journal, Vol. 1, pp. 5-25.
Hart, C.W.L. (1995), ``Mass customization: conceptual underpinnings, opportunities and limits’’,
International Journal of Service Industry Management, Vol. 6 No. 2, pp. 36-45.
Hart, C.W.L. (1996), ``Made to order’’, Marketing Management, Vol. 5, pp. 11-23.
Hayes, R.H. (1985), ``Strategic planning – forward in reverse?’’, Harvard Business Review, MarchApril, pp. 111-19.
Hayes, R.H. and Schmenner, R.W. (1978), ``How should you organize manufacturing’’, Harvard
Business Review, Vol. 56 No. 1, pp. 105-18.
Hayes, R.H. and Wheelwright, S.C. (1979), ``Link manufacturing process and product life cycles’’,
Harvard Business Review, Jan-Feb, pp. 133-40.
Hayes, R.H. and Wheelwright, S.C. (1984), Restoring Our Competitve Edge: Competing through
Manufacturing, John Wiley & Sons, New York, NY.
Haynes, R.M. and Du Vall, P.K. (1992), ``Service quality management: a process control
approach’’, International Journal of Service Industry Management, Vol. 3 No.1, pp. 14-24.
Heizer, J. and Render, B. (1996), Production and Operations Management: Strategic and Tactical
Decisions, Prentice Hall, Englewood Cliffs, NJ.
Herbert, T.T. (1984), ``Strategy and multinational organization structure: an interorganizational
relationship perspective’’, Academy of Management Review, Vol. 9, pp. 259-71.
Hill, T. (1989), Manufacturing Strategy: Text and Cases, Irwin, Homewood, IL.
Johnston, R. (1994), ``Operations: from factory to service management’’, International Journal of
Service Industry Management, Vol. 5 No. 1, pp. 49-63.
Kotha, S. and Orne, D. (1989), ``Generic manufacturing strategies: a conceptual synthesis’’,
Strategic Management Journal, Vol. 10, pp. 211-31.
Lawrence, P.R. and Lorsch, J.W. (1967), Organization and Environment, Harvard University
Press, Boston, MA.
Lewis, R.C. and Klein, D.M. (1984), Taking Off on Service Intangibles: Theoretical and Practical
Implications for Marketing Service, Workshop on Research in Service Businesses, Institut
d’Administration des Entreprises, Aix-en-Provence.
Lusch, R., Boyt, T. and Schuler, D. (1996), ``Employees as customers: the role of social controls
and employee satisfaction in developing patronage’’, Journal of Business Research, Vol. 35,
pp. 239-52.
McCutcheon, D.M., Raturi, A.S. and Meredith, J.R. (1994), ``The customisation-responsiveness
squeeze’’, Sloan Management Review, Winter, pp. 89-99.
McGee, J. and Thomas, H. (1986), ``Strategic groups: theory, research and taxonomy’’, Strategic
Management Journal, Vol. 7, pp. 38-48.
Meyer, A., Tsui, A. and Hinnings, C. (1993), ``Guest coeditors’ introduction: configuration
approaches to organizational analysis’’, Academy of Management Journal, Vol. 36 No. 6,
pp. 1175-95.
Miller, D. (1981), ``Toward a new contingency approach: the search for organizational gestalts’’,
Journal of Management Studies, Vol. 18, pp. 1-26.
Miller, D. (1986), ``Configurations of strategy and structure: towards a synthesis’’, Strategic
Management Journal, Vol. 7, pp. 233-49.
Miller, D. and Friesen, P. (1984), Organizations: A Quantum View, Prentice-Hall, Englewood
Cliffs, NJ.
Miller, J.G. and Roth, A.V. (1994), ``Taxonomy of manufacturing strategies’’, Management
Science, Vol. 40 No. 3, pp. 85-304.
Miller, S. and Rogers, D. (1956), Manufacturing Policy, Irwin, Homewood, IL.
Mills, J., Neely, A., Platts, K. and Gregory, M. (1998), ``Manufacturing strategy: a pictorial
representation’’, International Journal of Operations & Production Management, Vol. 18
No. 11, pp. 1067-85.
Mills, P.K. and Morris, J.H. (1992), ``Some moderating effects of client-interaction need on
perceived technology and structure in service providers’ tasks’’, International Journal of
Service Industry Management, Vol. 3 No. 1, pp. 4-13.
Minor III, E.D., Hensley, R.L. and Wood Jr, D. (1994), ``A review of empirical manufacturing
strategy studies’’, International Journal of Operations & Production Management,
Vol. 14 No. 1, pp. 5-25.
Morita, M. and Flynn, E.J. (1997), ``The linkage among management systems, practices and
behaviour in successful manufacturing strategy’’, International Journal of Operations &
Production Management, Vol. 17 No. 9, pp. 967-93.
Nieto AntolõÂn, M., Arias Aranda, D., Minguela Rata, B. and RodrõÂguez Duarte, A. (1999), ``The
evolution of operations management contents: an analysis of the most relevant textbooks’’,
Industrial Management & Data Systems, Vol. 99 No. 7 and 8, pp. 345-53.
Nunnally, J. (1978), Psychometric Theory, McGraw Hill, New York, NY.
Perez-Quiros, G. and Timmermann, A. (2000), ``Firm size and cyclical variations in stock returns’’,
Journal of Finance, Vol. 55 No. 3, pp. 1262-93.
The relationship
between strategy
and firm size
281
IJSIM
13,3
282
Poyago-Theotoky, J. (1998), ``R&D competition in a mixed duopoly under uncertainty and easy
limitation’’, Journal of Comparative Economics, Vol. 26 No. 3, pp. 415-18.
Price, L.L., Arnould, E.J. and Deibler, S.L. (1995), ``Consumers’ emotional responses to
service encounters’’, International Journal of Service Industry Management, Vol. 6 No. 3,
pp. 34-63.
Quinn, J.B. and Paquette, P.C. (1990), Service Management Effectiveness, Jossey Bass, San
Francisco, CA.
Rich, P. (1992), ``The organizational taxonomy: definition and design’’, Academy of Management
Review, Vol. 17 No. 4, pp. 758-81.
Richardson, P., Taylor, A. and Gordon, J. (1985), ``A strategic approach to evaluating
manufacturing performance’’, Interfaces, Vol. 15 No. 6, pp. 15-27.
Roth, A.V. and Miller, J.G. (1990), ``Manufacturing strategy, manufacturing strength, managerial
success and economics outcomes’’, in Ettlie, J., Burnstein, M.C. and Fiegenbaum, A. (Eds),
Manufacturing Strategies, Kluwer Academic Publishers, Boston, MA, pp. 97-108.
Roth, A.V. and Miller, J.G. (1992), ``Success factors in manufacturing’’, Business Horizons, Vol. 35
No. 4, pp. 73-81.
Sampson, S.E. (1996), ``Ramifications of monitoring service quality through passively solicited
customer feedback’’, Decision Sciences, Vol. 27 No. 4, pp. 601-21.
Schneider, B. and Bowen, D. (1993), ``The service organization: human resources management is
crucial’’, Organizational Dynamics, Vol. 21, pp. 39-52.
Schroeder, R.G. (1992), AdministracioÂn de Operaciones: Toma de Decisiones en la FuncioÂn de
Operaciones, McGraw-Hill, MeÂxico. Original version (1989), Operations Management:
Decision Making in the Operations Function, 3rd ed., McGraw-Hill, New York, NY.
Schutjens, V.A.J.M. and Wever, E. (2000), ``Determinants of new firm success’’, Papers in Regional
Science, Vol. 79 No. 2, pp. 153-75.
Schwab, D. (1980), ``Construct validity in organizational behaviour’’, Research in Organizational
Behaviour, Vol. 2 No. 1, pp. 3-43.
Siehl, C., Bowen, D.E. and Pearson, C.M. (1992), ``Service encounters as rites of integration: an
information processing model’’, Organizational Science, Vol. 3, pp. 537-55.
Skinner, W. (1969), ``Manufacturing – missing link in corporate strategy’’, Harvard Business
Review, May-June, pp. 136-45.
Skinner, W. (1978), Manufacturing in the Corporate Strategy, John Wiley and Sons, New York,
NY.
Smith, E. (1998): ``Search, Concave Production, and Optimal Firm Size’’, Review of Economic
Dynamics, Vol. 2, pp. 456-471
Smith, T.M. and Reece, J.S. (1999): ``The relationship of strategy, fit, productivity and
business performance in a services setting’’, Journal of Operations Management, Vol. 17,
pp. 145-161
Spanish Ministry of Industry (1998), El Sector de la Ingenieria Civil en Espan
Ä a, Ministerio de
Fomento, EspanÄa.
Srinivasan, A. (1985), ``Alternative measure of system effectiveness: associations and
implications’’, MIS Quarterly, No. 9 Vol. 3, pp. 243-53.
Stobaugh, R. and Telesio, P. (1983), ``Match manufacturing policies and product strategies’’,
Harvard Business Review, Vol. 61 No. 2, pp. 113-20.
Swamidass, P.M. and Newell, W.T. (1987), ``Manufacturing strategy, environmental
uncertainty and performance: a path analytic model’’, Management Science, Vol. 33 No. 4,
pp. 509-24.
Swink, M. and Way, M.H. (1995), ``Manufacturing strategy: propositions, current research,
renewed directions’’, International Journal of Operations & Production Management,
Vol. 15 No. 7, pp. 4-26.
Tersine, R. and Harvey, M. (1998), ``Global customerization of markets has arrived!’’, European
Management Journal, Vol. 16 No. 1, pp. 79-90.
Van Wissen (2000), ``A micro-simulation model of firms: application of concepts of the
demography of the firms’’, Papers in Regional Science, Vol. 79 No. 2, pp. 134-57.
Venkatraman, N. (1989), ``The concept of fit in strategy research: toward verbal and statistical
correspondence’’, Academy of Management Review, Vol. 14 No. 3, pp. 323-444.
Venkatraman, N. and Prescott, J. (1990), ``Environment-strategy coalignment: an empirical test of
its performance implications’’, Strategic Management Journal, Vol. 11 No. 1, pp. 1-23.
Ward, P., Bickford, D. and Leong, K. (1994), ``Configurations of manufacturing strategy,
business strategy, environment and structure’’, Journal of Management, Vol. 22 No. 4,
pp. 597-626.
Wheelwright, S.C. (1984), ``Manufacturing strategy: defining the missing link’’, Strategic
Management Journal, Vol. 5, pp. 77-91.
Wheelwright, S. and Hayes, R. (1985), ``Competing through manufacturing’’, Harvard Business
Review, Vol. 65 No. 1, pp. 213-23.
Appendix. Set of items used to measure operations strategy dimensions for service
management
Block A.I. Layout
Aspects of a fixed layout:
(1)
Service delivery activities are performed in a pre-established and fixed place.
(2)
Production resources are sequentially located.
(3)
Resources for service delivery are located in order to optimise space and maximise
efficiency.
(4)
Downstream tasks are never performed until upstream tasks are over.
(5)
Every worker is assigned to an exclusive task.
(6)
System efficiency goals have priority when designing service delivery process.
Aspects of a movable layout:
(7)
Service delivery activities are performed where it is more convenient for the customer.
(8)
Production resources can move to those places where service is delivered.
(9)
Resources for service delivery are located in order to optimise customer satisfaction and
final service delivery.
(10)
Workers assignation is made on a rotation basis.
(11)
Workers perform different tasks in the same shift.
(12)
Customer satisfaction goals are to have priority when designing service delivery process.
Block A.II. Push/pull orientation
Push orientation:
(13)
Important marketing efforts are made in order to attract new customers.
(14)
A crucial marketing goal is that customer is delivered as much services as possible.
(15)
Production output is always maximised.
The relationship
between strategy
and firm size
283
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284
Pull orientation:
(16)
Important service delivery efforts for improvement are made in order to increase
customers’ satisfaction.
(17)
A crucial marketing goal is that customer is satisfied.
(18)
Customer satisfaction is more important than output optimisation.
Block A.III. Level of standardisation
(19)
Service delivery system is designed so there is one or a few ways to perform every
task.
(20)
Variability is continually decreased along the service delivery process
(21)
Most work procedures are pre-established and cannot be modified.
(22)
Empowerment degree is very low.
(23)
All incidents not prevented in the work procedures must be communicated to a superior
for resolution.
(24)
There is a procedures book, which is known by all workers.
(25)
Most service delivery activities are oriented towards service customisation.
Block A.IV. Different services offered
(26)
The firm offers a wide range of different services.
(27)
All offered services are customised.
(28)
New services are continually offered to customers.
(29)
The firm delivers one of few very specialised services.
(30)
Services are delivered to satisfy one or a few small customer segments.
Block A.V. Use of information technologies
(31)
Acquisition of information technologies is oriented towards costs reduction.
(32)
Workforce is replaced by new technologies when possible.
(33)
Customers can send or receive information about service delivery through information
technologies such as Internet, EDI, WAP etc.
(34)
Acquisition of information technologies is oriented towards customer satisfaction.
(35)
Decisions about information technologies adoption are made on the basis of tasks
improvements from the worker’s point of view.
(36)
Decisions about information technologies adoption are made on the basis of service
customisation.
Block A.VI. Back and front office activities
(37)
Front office activities are physically separated and differentiated from the back office
activities.
(38)
The customers cannot access those service activities in which they are not required.
(39)
Personnel of front office activities works exclusively there and never in back office
activities.
Block A.VII. Human resources
(40
Personnel are highly specialised.
(41)
Personnel are able to perform various and different tasks.
(42)
Job rotation is commonly used.
(43)
More than half of our personnel are university graduates.
(44)
Training is given crucial importance in the firms budgets.
Block A.VIII. Customer participation
(45)
Service delivery process is designed so customer performs by him/herself those
activities he/she is qualified for.
(46)
Customer performs part of the service delivery activities in order to reduce costs.
(47)
Customer is informed in detail about all previous activities he/she has to perform before
service delivery.
(48)
Customer knows about cost reductions due to his/her participation in the service
delivery process.
(49)
Customer participates in the service delivery process in order to customise service.
Block A.IX. Design and development of new products
(50)
New procedures for service delivery are continually developed.
(51)
New services are continually developed.
(52)
Customer opinions are indeed considered when designing new services.
(53)
There is an exclusive team for service design and development.
The relationship
between strategy
and firm size
285