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Introduction
With the establishment of the Malcolm Baldrige Award in 1986 and the ISO
9000 standards in 1988, corporate interest in product quality increased.
Many firms acted to alter their corporate structures and make their
management cultures more quality oriented. Measures were developed to
monitor product quality – including Deming’s and Juran’s process control
methodologies. Firms began to develop monthly customer surveys to
monitor their performance in terms of delivery, inventory in-stock position,
technical support availability, damage incidence, and competence of
customer service personnel.
Unfortunately, the move to institute more quality in products greatly
outstripped action in the realm of service quality. The failure to measure and
control service quality may have been caused by two factors.
First, the intangibility of most services is problematic since it can cause
measurement difficulties and make research results unreliable. Service
quality perceptions may vary a great deal across any given set of
observations; while this could be related to actual variance in service
performance, the difficulty of perceiving relatively intangible end results
may also be at fault.
Second, service quality is considered by some to be impossible to model.
That is, because so many factors affect an individual’s perception of service
quality, some researchers have found it difficult to isolate causal factors and
draw any meaningful conclusions as to what influenced service quality
ratings.
Many of the initial attempts to measure service quality were modeled after
steps taken in product industries. As a result, those attempts tended to focus
primarily on the end result, or output, of the production process. For
example, the Ameritech Corporation in Chicago conducted a massive study
of the quality of service provided to their residential telephone customers
(Ameritech, 1993). The company looked at outputs of its service system
such as equipment performance, effectiveness of repair and maintenance
systems, clarity of voice transmission, and accuracy of its billing systems.
However, it failed to consider aspects of service production such as the
training of service personnel and the quality of employee-customer
interactions.
The service quality studies done by British Airways monitored customer
service through the use of customer surveys and audits. Focus was placed on
flight arrival and departure times, meal quality, in-flight service, check-in
experience, and baggage claim time (British Airways, 1991). Although the
company focussed its attention predominantly on the end result of the
6 JOURNAL OF SERVICES MARKETING VOL. 9 NO. 5 1995 pp. 6-19 © MCB UNIVERSITY PRESS. 0887-6045
Measuring service quality: a
systems approach
Rose L. Johnson, Michael Tsiros and Richard A. Lancioni
Focus on end result
Failure to measure and
control quality
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service, an attempt at wider consideration of the service process (e.g. in-
flight service) is evident.
Although the above examples are only two attempts to measure service
quality, they are representative of many other such attempts. They show that
when many companies measure service quality, they look primarily at the
end results of their service provisioning cycles and tend to neglect the
service components contributing to those end results. Ameritech looked
primarily at the outputs of its service system, and measured them. British
Airways used a more comprehensive consideration of the service, but still
fell short in some areas.
There are, however, companies that take a more holistic view of the service
production process. For example, McDonald’s audits the over 12,000
restaurants that operate under the franchise worldwide on a quarterly basis.
Included in the audit is an evaluation of physical facilities and other service
production resources (e.g. atmosphere, cleanliness, seating arrangements,
and operating hours), customer-employee interactions (e.g. politeness,
friendliness, and courtesy of the sales staff), and end results (e.g. correctness
of the order, quality and taste of the food, speed of order taking and
processing; see The McDonald’s Corporation, 1992).
Being able to measure all dimensions relevant to service production is
essential for a service company. With customers interacting with the service
provider and being an integral part of the service production, the need to
measure the customers’ perceptions of all three aspects of the service is
apparent. Just as essential is the ability to distinguish these aspects from each
other and to evaluate them separately. This is because the company may be
performing well in one area but not in another. By using distinct measures,
firms can identify the most appropriate action and resources can be allocated
more efficiently along the production process. The view of the whole picture
will not, however, be sacrificed by focussing on any specific attribute of the
service.
One instrument that was developed to satisfy these goals in service quality
measurement is Parasuraman et al.’s (1988) SERVQUAL scale. This scale
describes service quality as the difference between customer expectations
for, and perceptions of, actual performance along five dimensions –
tangibles, reliability, responsiveness, assurance, and empathy.
While the scale attempted to provide a generalizable measure of service
quality, a number of studies have shown that such a claim may be
inappropriate (e.g. Babakus and Boller, 1992; Brensinger and Lambert,
1990; Carman, 1990). In addition, despite initial popularity among both
practitioners and academics, SERVQUAL has recently been criticized on
both conceptual and methodological grounds (e.g. Brown et al., 1993;
Cronin and Taylor, 1994; Teas, 1994).
Many other marketers have suggested the existence of multiple dimensions
within the service quality construct. For example, Sasser et al. (1978)
proposed three dimensions of service quality: material, facilities, and
personnel. Lehtinen and Lehtinen (1982) suggested that service quality
consists of the equipment used (physical quality), the image or reputation of
JOURNAL OF SERVICES MARKETING VOL. 9 NO. 5 1995 7
Neglect of individual
segments
Essential for a service
company
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the company (corporate quality), and the interaction between contact
personnel and customers (interactive quality).
Grönroos (1984) suggested that quality is a function of what the consumer
actually receives (technical quality) and the way the service is delivered
(functional quality).
LeBlank and Nguyen (1988) proposed five dimensions of service quality:
corporate image, internal organization, physical support of the producing
system, staff-customer interaction, and customer satisfaction. Edvardsson et
al. (1989) suggested that service quality consists of personnel skills
(technical quality), the coordination between the different portions of the
service delivery system (integrative quality), the manner in which the service
is delivered to the customer (functional quality), and the degree to which the
service product meets customer expectations (outcome quality).
These frameworks share the notion that service provision is multifaceted.
Despite the many typologies suggested, however, none except SERVQUAL
has received extensive empirical testing. Thus, service firms are still faced
with uncertainty when trying to identify an appropriate measure of service
quality. Given the importance of measuring and controlling service quality
and the shortcomings of existing efforts, additional work in this area seems
warranted.
The purpose of this article is to describe and test a framework for the
measurement of consumers’ perceptions of service quality. Applying
general systems theory, we will discuss the contribution of service inputs,
processes, and outputs to overall quality perceptions. Then, we will present
the results of two studies exploring the suitability of the framework.
Finally, the managerial relevance and implications of our approach will be
described.
A general systems approach to services
General systems theory is a research paradigm which attempts to facilitate
the generalization of behavioral principles across a wide range of
organizations (Sirgy, 1984). The theory suggests that an organization, such
as a service firm, consists of an arrangement of smaller subsystems (e.g.
departments) and acts within a larger system – the environment. Two of the
central themes of general systems theory are the interaction of subunits
within a system and the interaction of the system with its environment (Kast
and Rosenzweig, 1972).
In the case of a production operation, systems theory explains how inputs are
acquired from the environment; fed into the manufacturing cycle, where
transformation of the raw material results in finished products; and, as
finished products, marketed to customers as the output of the company.
Following the systems framework, inputs, processes, and outputs each play
an important role in the successful operation of the firm. This is true for
manufacturing firms where, for example, outdated or poorly maintained
equipment can cause an unacceptable level of product defects. However, the
systems approach is particularly relevant to the study of services and service
quality.
8 JOURNAL OF SERVICES MARKETING VOL. 9 NO. 5 1995
Service provision is
multifaceted
Systems theory
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In evaluating the quality of physical goods, consumers are concerned
primarily with the good (system output) itself. Because of the unique
characteristics of many services, however, consumers are exposed to and
affected by the organization’s inputs and processes as well as its outputs.
Thus, a measure of overall service quality should include judgments of all
dimensions of the service: inputs, processes, and outputs (see Figure 1).
As a result of services’ simultaneous production and consumption,
consumers often are present in the service production facility and are aware
of the quality of the equipment and overall surroundings. Input quality, the
first dimension, is the component of consumers’ overall quality evaluations
that includes consideration of these physical elements and other production
resources, both tangible and intangible.
For example, an assessment of input quality would include consideration of
whether the equipment seemed up to date and in good working order;
whether waiting areas were appropriately furnished, cleaned, and well lit;
and whether service providers were appropriately attired. The knowledge
and skills possessed by employees represent important inputs to service
production. Inputs may be acquired from the system under study or from
other systems (Schoderbek et al., 1990).
The second quality dimension, process quality, refers to the quality of the
interaction between provider and consumer; that is, how the service is
produced. Since service production and consumption are inseparable,
consumers frequently must interact with service personnel. Thus, consumers
often are directly affected by the service production process. Service
accessibility and availability and provider’s courtesy, friendliness, and
willingness to answer questions are aspects of process quality.
Output quality, the third dimension, is a measure of what is produced as a
result of providing the service. It includes intangible benefits as well as any
tangible outputs of the service, and most frequently it involves a change in
the consumer’s physical or mental state or a change in some possession of
the consumer’s. It is concerned, for example, with whether a faucet still
drips after the plumber’s visit, or whether the consumer possesses a valid
will after the lawyer’s work is done, or the consumer’s mental and emotional
state after an evening of entertainment.
JOURNAL OF SERVICES MARKETING VOL. 9 NO. 5 1995 9
Input
Process
Output
Quality
Figure 1. A systems approach to service quality
Assessment of input
quality
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The outputs of a system may be acquired by consumers or other systems for
their own use, consumed by the same system in a subsequent production
cycle, or disposed of as waste (Schoderbek et al., 1990). When outputs are
consumed by the same system, they are referred to as feedbacks. An example
of feedback may be the knowledge and skills which are gained by employees
through service provision and are then used to produce future services more
efficiently. While some researchers view feedbacks as a separate system
object, we include them as one type of input (cf. Schoderbek et al., 1990).
The role of the environment – those things external to the system – should
also be noted. By definition, the system is unable to control the environment,
but the ability to monitor and respond to environmental forces is critical. If,
for example, a firm does not keep abreast of social trends which may affect
consumers’ wants and needs, the firm’s ability to produce outputs that
consumers evaluate highly may be compromised.
Again, since we are focussing on consumer perceptions of service quality,
the environment will have an impact only to the extent that it causes changes
to the elements of the system. It is those system elements (inputs, processes,
and outcomes) that will be evaluated here.
A number of marketing researchers have used the systems framework in
their work. For example, Reidenbach and Oliva (1981) conceptualize
marketing and its functions as a living system – where some departments are
responsible for the assembly of information and materials from the
environment and the dissemination of those inputs to the appropriate
departments, some departments are responsible for processing those inputs
and converting them into appropriate outputs, and other departments are
responsible for providing physical output and information back to the
environment.
Ruekert and Walker (1987) use the systems framework to conceptualize
marketing’s interaction with other functional units of the company. They
suggest three dimensions that describe these interactions. The input
dimension includes environmental conditions such as resource dependence,
complexity, and turbulence. The process dimension includes transactions,
communication flow, and coordination patterns between marketing and other
functional areas. The outcome dimension includes functional and socio-
psychological outcomes such as accomplishment of the marketing
department’s goals, perceived effectiveness of the relationship, and conflict.
Murphy and Ross (1987) advocate a systems approach to evaluating service
firms. They state that “the processing and feedback stages, as well as inputs
and outputs, are all crucial in gaining a complete evaluation of [service]
firms” (p. 365). They also note that the input dimension has been criticized
because of the sometimes tenuous relationship between a service provider’s
credentials and service performance, but then point out that for some
services (e.g. medical care), consumers’ lack of expertise for evaluating
outputs may make the input dimension the most reliable.
Also consistent with general systems theory, Grove and Fisk (1992) suggest
that the service process can be described in terms of inputs, throughputs (the
service experience itself), and outcomes. They argue that, owing to the
10 JOURNAL OF SERVICES MARKETING VOL. 9 NO. 5 1995
Role of environment
Marketing and its
functions as a system
Systems approach to
evaluating service firms
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unique characteristics of services (intangibility, perishability, heterogeneity,
simultaneity), the use of observational methods in services marketing is even
more appropriate. They also recognize that observational methods may be
most appropriate for researching throughputs but they argue that the
evaluation of all three elements is both possible and important.
Each of the above-mentioned studies specifically invoked the systems
framework. However, some overlap with general systems theory can be seen
even in studies prescribing different frameworks or service quality
dimensions. For example, in studying the relationship between advertising
agencies and their clients, Michell (1987) found that dissatisfaction with
agency performance is the main reason for campaign switching and that
agency performance is evaluated as a function of creativity, client service,
and campaign results. At a higher level of abstraction, these three factors
represent inputs, processes, and outputs, respectively.
The several characterizations of service dimensions described earlier in this
article also demonstrate some overlap with systems theory. The dimensions
of material quality, tangibles, corporate image, technical quality, and
physical support are consistent with the inputs dimension. Process includes
interactive quality, staff-customer interaction, functional quality, assurance,
and responsiveness. Finally, the output dimension is represented in outcome
and reliability.
The validity of these frameworks is, as we suggested earlier, an empirical
question that has not as yet been adequately addressed. It is interesting to
note, however, that SERVQUAL includes five service quality dimensions,
but in refining their scale, Parasuraman et al. (1991a, p. 425) observed that
“the responsiveness and assurance dimensions show a considerable overlap
and load on the same factor”. Within our framework they would both be
parts of the process dimension.
A test of the framework
While systems theory has been discussed and its use by service marketers
has been advocated by some, there have been few efforts made to
demonstrate the appropriateness of the model empirically for this use. This
article attempts to close that gap. Two empirical studies were undertaken to
test the appropriateness of the systems framework for describing service
quality perceptions. One goal of the studies was to identify components of
each of the three quality dimensions and to determine to what extent these
dimensions explained variance in overall quality perceptions. A secondary
goal was to determine the extent to which the framework and measures
could be generalized across different service types.
Study 1
A survey was conducted to measure quality perceptions of firms in three
service industries: full service restaurants, banking, and public
transportation. Business students at a large East Coast university provided
195 service evaluations. To ensure that respondents were actual consumers
of the services they evaluated, respondents were asked to name and evaluate
a full service restaurant they had visited in the last four weeks, or the bank
they use most frequently. For public transport, respondents were asked to
evaluate the local transit system if they had used the system in the last four
JOURNAL OF SERVICES MARKETING VOL. 9 NO. 5 1995 11
Two empirical studies
were undertaken
Overlap with systems
theory
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weeks. The questionnaires were randomly distributed among the
respondents.
The survey included 29 service quality items measured on a five-point
Likert-type scale. Some elements were adapted from the SERVQUAL scale
while others were generated by the researchers. The service perception items
were the same for each service type. For the initial evaluation of the input,
process, and output scales, a factor analysis was run with three factors
specified a priori.
This specification was made (rather than the inclusion of factors with
eigenvalues greater than one) because three factors are specified by systems
theory. An orthogonal rotation was used in order to keep the factors as
independent of each other as possible. Bartlett’s test of sphericity (V= 4,870,
p< 0.001) indicates that the 29 variables are not independent and are,
therefore, appropriate for factor analysis. The eigenvalues for each factor are
provided in the Appendix.
Of the 29 initial items, nine were excluded because they did not load higher
than 0.5 on their expected factor and lower than 0.5 on the other factors.
Scale items and factor loadings are provided in Table I. Final Cronbach
alpha values were 0.85 for the input scale (five items), 0.96 for the process
scale (seven items), and 0.95 for the output scale (eight items). Several items
measuring the input dimension were dropped owing to their low correlation
with the input factor. Some of those items, such as measures of personnel’s
knowledge or training, may be hard for the customer to evaluate because of
low involvement and infrequent interaction. Overall service quality was
measured by a seven-point semantic differential item (very high quality/very
low quality).
12 JOURNAL OF SERVICES MARKETING VOL. 9 NO. 5 1995
Table I. Scale items and factor analysis results
Factor (
α
) Item Factor loading
Input (0.85) The firm has a reputation for quality 0.67
The firm has up-to-date equipment 0.64
The firm’s furnishings are in keeping with the type of
service provided 0.61
The physical facilities are visually appealing 0.58
The waiting area is comfortable 0.51
Process (0.96) The service providers are friendly 0.87
The service providers seem happy to be of service 0.81
The service providers take the time to answer questions
clearly 0.81
The service providers are responsive to my needs 0.80
The service providers are courteous 0.77
The service providers are attentive to my needs 0.75
I receive individualized attention 0.66
Output (0.95) The goals I had in seeking the service were fulfilled 0.82
I receive the service I expect 0.78
The service is performed right the first time 0.76
The service outcome meets my expectations 0.74
The service provides the benefits I desire 0.73
The firm provides reliable service 0.71
Service performance is dependable 0.66
Services are provided when promised 0.64
Orthogonal rotation used
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The next step was to test the model empirically (see Figure 1). We ran a
regression analysis with overall service quality as the dependent variable and
input, process, and output as the predictor variables. The overall model was
significant and explained 73% of the variation in overall service quality.
This compares favorably with SERVQUAL, which Parasuraman et al.
(1991a) found to explain 57-71% of the variation in overall quality
depending on the type of service. Of the three dimensions, output was the
strongest predictor of overall service quality, followed by process. With the
effects of these two dimensions accounted for, the input dimension did not
have a significant effect on overall service quality. The results of the analysis
are provided in Table II.
While these initial results are encouraging, we recognize that there are
important differences across types of services which may be obscured in our
combined analysis. For example, owing to the greater interaction between
customers and service providers in a restaurant as compared to a transit
system, the process dimension may be a stronger predictor of quality in the
former. Thus, we repeated our analysis for each type of service (restaurant,
banking, and public transportation) separately.
Results of the separate analyses were quite similar to the combined results
(see Table II). R2s of 0.78, 0.70, and 0.52 were observed for restaurants,
transportation, and banking, respectively. Output was a strong and
significant predictor of overall service quality in each case, with process
significant for restaurants and transportation. As in the combined analysis,
input was not significant for any of the services.
Our results are consistent with others’ suggestions that outputs will be of
greatest importance to consumers (Murphy and Ross, 1987; Parasuraman et
al., 1991b). However, previous researchers have argued for the importance
of each of the three dimensions. As a caveat to interpretations of our results,
we must note that the three predictor variables were highly intercorrelated
JOURNAL OF SERVICES MARKETING VOL. 9 NO. 5 1995 13
Table II. Multiple regression results
Predictor variable
Input Process Output R2n
Combined analysis 0.73 193
Standard estimate –0.018** 0.393* 0.538*
Standard error 0.097 0.090 0.094
Restaurant 0.78 67
Standardized estimate –0.082** 0.551* 0.416*
Standard error 0.142 0.174 0.182
Banking 0.53 66
Standard estimate –0.012** 0.151** 0.610*
Standard error 0.194 0.245 0.206
Transportation 0.70 60
Standard estimate 0.042** 0.290* 0.635*
Standard error 0.212 0.145 0.151
Notes:
* p< 0.001
** p> 0.100
Differences across types
of service
Strong and significant
predictor
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and that those intercorrelations may have caused the lack of significance of
the input variable in the regression equation.
Given this, we wanted to carry out further investigation of the contribution
of each dimension to the evaluation process. This investigation was carried
out using two different methods. First, we ran the regression analysis both
for the combined dataset and for each industry using the factor scores as our
independent variables. Second, we conducted a series of focus groups. Study
2 provides a description of these interviews and the results that we obtained.
Factor scores are composite measures representing the contribution of each
scale item to each dimension in a factor analysis. Since an orthogonal
rotation was used, the use of factor scores keeps the three predictors
independent of each other. In this analysis, the overall model explained 71%
of the variation in overall service quality. In addition, all three factors were
significantly and positively related to overall quality (see Table III).
We repeated the analysis using factor scores for each type of service
separately. R2s of 0.77, 0.44, and 0.65 were observed for restaurants,
transportation, and banking, respectively. Output and process were strong
and significant predictors of overall service quality in all three types of
service. Input, however, was significant only for the transportation service.
The results from these analyses are presented in Table III. The inconsistency
between the overall and individual results may be due in part to small
sample sizes and resulting low power of the tests in the separate analyses.
Overall, these results are accepted as providing support for our framework.
Study 2
The wide use of systems theory in the marketing and management literatures
provided a basis for our expectations that each dimension would contribute
significantly to perceptions of service quality. However, as we noted earlier,
there have not been previous attempts to verify the framework empirically in
this context.
14 JOURNAL OF SERVICES MARKETING VOL. 9 NO. 5 1995
Focus group interviews
Table III. Multiple regression results (using factor scores)
Predictor variable
Input Process Output R2n
Combined analysis 0.71 193
Standard estimate 0.115* 0.547 0.582*
Standard error 0.069 0.062 0.064
Restaurant 0.77 67
Standardized estimate 0.019** 0.713* 0.474*
Standard error 0.083 0.081 0.082
Banking 0.44 66
Standard estimate 0.021** 0.269* 0.565*
Standard error 0.146 0.183 0.127
Transportation 0.65 60
Standard estimate 0.293* 0.458* 0.595*
Standard error 0.122 0.121 0.127
Notes:
* p< 0.001
** p> 0.100
Analysis of factor scores
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Given the partial support from study 1, we felt it important to study the issue
in more depth. In any empirical study, a failure to support expectations can
be due either to the framework (theory) or to the research method. Using a
different method gives us a better opportunity to identify the reasons for our
results. Thus, in order to understand better how consumers perceive service
quality, a number of focus group interviews were conducted.
For the focus group interviews, eight groups of undergraduate business
students discussed service quality for one of four service classes (restaurants,
oil changes, car washes, and air travel). Each service type was discussed by
two groups consisting of approximately eight members each. The allocation
of the students to the different service types was determined by an initial
survey geared to establishing their experience with each service type within
the past six months.
The interviews started with the group members sharing some of their recent
experiences with that type of service. The main part of the interviews
involved a discussion of those things each member perceived as being
important in evaluating quality in that particular service type.
To facilitate the discussion, group moderators recorded main ideas on a
blackboard. In addition, each group’s discussion was tape recorded.
Following the discussions, tapes were transcribed. Each individual idea or
phrase from the tapes was listed, but items deemed by the authors to be
clearly redundant were retained only once.
Analysis of the focus group output involved a ninth group, composed of
three doctoral students in business. The doctoral students were given a
background in general systems theory, and were asked to classify the focus-
group generated items individually and then to discuss the fit of the items to
the framework.
Some comments produced by the focus group members were felt by the
judges not to reflect quality issues (e.g. “I don’t like drive-thru carwashes
because I get claustrophobic”). The majority (83%) of the items, however,
were classified as input, process, or output by at least two out of the three
judges.
Of those items felt to represent elements of quality, 39% were classified in
the input category, 45% were classified as process, and 16% were considered
to represent outputs. Thus, the results from the focus groups were considered
to support the inclusion of the input dimension in service quality evaluation
and to provide additional evidence for the systems framework.
Managerial implications and recommendations
This article describes a general systems approach to measuring consumers’
service perceptions. Support for such a conceptualization of service quality
is provided both in the literature and by our empirical research. Our focus-
group interviews demonstrated that service consumers consider aspects of
service inputs, processes, and outputs when making quality evaluations. The
survey portion of our research showed that these dimensions together
explain a substantial portion of the variation in overall quality perceptions.
JOURNAL OF SERVICES MARKETING VOL. 9 NO. 5 1995 15
Generalizability of the
framework
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In addition, by studying six different services, we were able to show a
degree of generalizability for the framework.
The need for a theoretically sound and generalizable measuring system in
service industries is immense. Managers are often forced to use quality
measures which are appropriate for rating product quality but not service
quality, or that lack both conceptual bases and empirical generalizability.
This can result in faulty analyses which, in turn, may lead to poor decision
making. A more appropriate measuring system will help service managers
develop quality standards which more accurately represent the activities that
result in the provision of the service. A general systems approach suggests
that such quality standards should be established for the input, process, and
output elements of service production.
Schoderbek et al. (1990) identified a number of potential benefits of systems
thinking to the managers of organizations. Such thinking has at least four
benefits; it:
(1) frees the manager from taking a narrow functional viewpoint of
a task and helps him/her identify subsystems that cut across functional
areas;
(2) permits the manager to relate his or her goals to the overall
organizational goals;
(3) permits the organization to structure the different subsystems in a
manner consistent with the overall system’s goals; and
(4) allows for evaluations of both the overall system’s and the subsystem’s
effectiveness.
While we have focussed on the overall service production system, the
concepts can easily be adapted to address subsystems such as employee
training systems or complaint resolution systems.
In addition to facilitating a broad view of the organization, identifying
multiple dimensions related to customer perceptions of a service can be
helpful for identifying specific areas in need of improvement. On the input
side, more accurate quality measurement will enable firms to establish the
quality level of the inputs currently being used to provide service to their
customers. These inputs include atmospherics and the quality and
appropriateness of equipment. Measuring consumers’ perceptions of these
elements will enable the firm to understand how much investment is
needed in the service environment.
Inputs also include the type and quantity of training currently provided for
new service employees. For example, training in customer service can be
either formal or informal. Knowing the current level of quality the
company is achieving by using the informal, on-the-job, training approach
will enable them to adjust the mix of training they are providing.
Also, by understanding overall service production, the firm will be able to
determine whether it should upgrade a job position from an entry level to a
higher management position requiring candidates to be more experienced
in customer service before they are hired.
16 JOURNAL OF SERVICES MARKETING VOL. 9 NO. 5 1995
Specific areas for
improvement
Broad view of the
organization
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Measuring the process components of a firm’s service system (e.g. the level
of service provided, the quality of employee-customer interaction) will
enable management to determine how much investment is needed to
maintain or improve the service experience. For example, a key element
affecting the process component is the reward system a company uses to
stimulate its employees to be service oriented. Reward systems may include
employee of the year programs, management awards for outstanding
service employees, monetary bonus programs based on service
performance, etc. By reviewing process quality on a regular basis, a
company can make better judgments as to when to update or replace service
incentive programs.
Measuring the output aspect of service programs enables a company to
determine what has been the return from the investments it has made in
service production. The measuring devices used here include customer
service surveys, focus group assessments, and direct one-to-one interviews
with customers. These output measures enable a company to focus in on the
areas where it has been successful and where it has failed in customer
service. For example, in the health-care industry many hospitals frequently
interview discharged patients regarding the quality of service they received
while patients in the hospital. This enables the individual hospitals to
pinpoint which departments in the hospital have failed and which ones have
excelled. Based on this information corrections can be made and rewards
given out.
Although the notion of feedback does not enter our model of service quality
measurement, it is inextricably linked to the systems approach to
management. Feedback from customer perceptions can affect decisions to
adjust certain aspects of each dimension (input, process, and output). For
example, if a service quality survey showed that customers perceive input
quality to be poor while the other two dimensions are rated highly, then
building input quality should be the main concern of the organization. In
addition, feedback from employees is an important element in continuous
improvement of service production.
By understanding the dynamics involved in high-quality service processes,
managers will be able to develop service plans which contain realistic
objectives, adequate budgets and achievable outcomes for their firms.
Their plans then can be used to develop operational quality service
strategies that produce returns for the organizations. The service plans can
be short, medium, or long term in perspective and contain the ingredients
and resources necessary to redress any of the problems pinpointed in the
measurement process.
Input, process, and output factors should be contained in the service plan.
Often, service plans are not developed by companies on an annual basis.
Any planning that is done is cursory in nature and short term in scope.
Measuring service quality on a regular basis will encourage firms to pay
closer attention to their service operations.
References
Ameritech (1993), “New developments in customer service management”, in Gecowets, G.
(Ed.), Proceedings of the Council of Logistics Management, Council of Logistics
Management, Chicago, IL.
JOURNAL OF SERVICES MARKETING VOL. 9 NO. 5 1995 17
Operational quality
service strategies
Measuring the output
aspect
Downloaded by University of Miami At 12:17 21 November 2018 (PT)
Babakus, E. and Boller, G.W. (1992), “An empirical assessment of the SERVQUAL scale”,
Journal of Business Research, Vol. 24, pp. 253-68.
Brensinger, R.P. and Lambert, D.M. (1990), “Can the SERVQUAL scale be generalized to
business-to-business services?”, in Parasuraman, A., Bearden, W., Deshpande, R., Folkes,
V.S., Madden, T.J., Stewart, D.W., Varadarajan, P.R. and Wilkie, W.L. (Eds), Enhancing
Knowledge Development in Marketing, Vol. 1, American Marketing Association, Chicago,
IL, p. 289.
British Airways (1991), Industry Report #43, International Customer Service Association,
November, pp. 43-9.
Brown, T.J., Churchill, G.A. Jr and Peter, J.P. (1993), “Improving the measurement of service
quality”, Journal of Retailing, Vol. 69, Spring, pp. 127-39.
Carman, J.M. (1990), “Consumer perceptions of service quality: an assessment of the
SERVQUAL dimensions”, Journal of Retailing, Vol. 66, Spring, pp. 33-55.
Cronin, J.J. Jr. and Taylor, S.A. (1994), “SERVPERF versus SERVQUAL: reconciling
performance-based and perceptions-minus-expectations measurement of service quality”,
Journal of Marketing, Vol. 58, January, pp. 125-31.
Edvardsson, B., Gustavsson, B.O. and Riddle, D.J. (1989), “An expanded model of the service
encounter, with emphasis on cultural context”, Research Report 89:4, CTF, Services
Research Centre, University of Karlstad, Sweden.
Grönroos, C. (1984), “A service quality model and its marketing implications”, European
Journal of Marketing, Vol. 18, pp. 36-44.
Grove, S.J. and Fisk, R.P. (1992), “Observational data collection methods for services
marketing: an overview”, Journal of the Academy of Marketing Science, Vol. 20, Summer,
pp. 217-24.
Kast, F.E. and Rosenzweig, J.E. (1972), “General systems theory: applications for organization
and management”, Academy of Management Journal, Vol. 15, December, pp. 447-65.
LeBlank, G. and Nguyen, N. (1988), “Customers’ perceptions of service quality in financial
institutions”, International Journal of Bank Marketing, Vol. 6, pp. 7-18.
Lehtinen, J.R. and Lehtinen, O. (1982), “Service quality: a study of quality dimensions”,
unpublished working paper, Service Management Institute, Helsinki.
Michell, P.C.N. (1987), “Auditing of agency-client relations”, Journal of Advertising Research,
Vol. 26, December-January, pp. 29-41.
Murphy, P.E. and Ross, S.C. (1987), “Evaluating service firms: approaches with policy
recommendations”, Journal of Consumer Policy, Vol. 10, pp. 363-81.
Parasuraman, A., Berry, L.L. and Zeithaml, V.A. (1991a), “Refinement and reassessment of the
SERVQUAL scale”, Journal of Retailing, Vol. 67, Winter, pp. 420-50.
Parasuraman, A., Berry, L.L. and Zeithaml, V.A. (1991b), “Understanding and managing
customer expectations of service”, Sloan Management Review, Vol. 32, Spring, pp. 39-48.
Parasuraman, A., Zeithaml, V.A. and Berry, L.L. (1988), “SERVQUAL: a multiple-item scale
measuring consumer perceptions of service quality”, Journal of Retailing, Vol. 64, Spring,
pp. 12-37.
Reidenbach, R.E. and Oliva, T.A. (1981), “General living systems theory and marketing: a
framework for analysis”, Journal of Marketing, Vol. 45, Fall, pp. 30-7.
Ruekert, R.W. and Walker, O.C. Jr (1987), “Marketing’s interaction with other functional units:
a conceptual framework and empirical evidence”, Journal of Marketing, Vol. 51, January,
pp. 1-19.
Sasser, W.E. Jr, Olsen, R.P. and Wyckoff, D.D. (1978), Management of Service Operations:
Text and Cases, Allyn & Bacon, Boston, MA.
Schoderbek, P.P., Schoderbek, C.G. and Kefalas, A.G. (1990), Management Systems:
Conceptual Considerations, Irwin, Boston, MA.
Sirgy, M.J. (1984), Marketing as Social Behavior: A General Systems Theory, Praeger, New
York, NY.
Teas, K.R. (1994), “Expectations as a comparison standard in measuring service quality: an
assessment of a reassessment”, Journal of Marketing, Vol. 58, January, pp. 132-9.
The McDonald’s Corporation (1992), Restaurant Evaluation Audit Guide, The McDonald’s
Corporation, Chicago, IL.
18 JOURNAL OF SERVICES MARKETING VOL. 9 NO. 5 1995
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Appendix. Eigenvalues and percentage of variance explained by each factor
Factor Eigenvalue Percentage of variance
1 15.86 54.7
2 1.88 6.5
3 1.52 5.2
4 1.08 3.7
5 0.83 2.9
6 0.79 2.7
7 0.71 2.4
8 0.62 2.1
9 0.58 2.0
10 0.51 1.8
11 0.47 1.6
12 0.42 1.4
13 0.40 1.4
14 0.37 1.3
15 0.35 1.2
16 0.30 1.0
17 0.28 1.0
18 0.25 0.9
19 0.22 0.8
20 0.22 0.7
21 0.21 0.7
22 0.20 0.7
23 0.18 0.6
24 0.16 0.5
25 0.14 0.5
26 0.13 0.4
27 0.12 0.4
28 0.10 0.4
29 0.08 0.3
■
JOURNAL OF SERVICES MARKETING VOL. 9 NO. 5 1995 19
Rose L. Johnson is Assistant Professor of Marketing; Micheal Tsiros is a Doctoral
Student in Marketing and Richard A. Lancioni is Professor of Marketing, all at
Temple University, Philadelphia, USA.
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