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The roles of service encounters, service value, and job satisfaction in
achieving customer satisfaction in business relationships
Irene Gil , Gloria Berenguer1, Amparo Cervera 2
Faculty of Economics and Business, Department of Marketing, Avda. de los Naranjos, s/n. 46022 Valencia, Spain
Received 16 June 2006; received in revised form 4 June 2007; accepted 23 June 2007
Available online 16 August 2007
Abstract
Along with variables like the service process, perceived service value and customer satisfaction, job satisfaction of service employees plays a
vital role in customer evaluation of service result. However, there has been little in-depth research into the nature of this relation, in particular in
the context of B2B relations. In the sphere of an organization providing financial intermediation services to the banking sector and on the basis of
a literature review, hypotheses are developed which establish the mediator role of service value and the moderator role of job satisfaction of
service employees when delimiting customer satisfaction. Reliability and validity analysis give satisfactory results and our conclusions establish
firstly that service encounter directly and significantly affects perceived service value which is the final antecedent to customer satisfaction and
secondly, that the level of employment satisfaction moderates its effect on service value.
2007 Elsevier Inc. All rights reserved.
Keywords: Service encounter; Service value; Customer satisfaction; Job satisfaction of service employees; Financial sector
1. Introduction
There are fundamental differences between an organization
marketing to other organizations often referred to as industrial
or B2B marketing and an organization marketing to
consumers, that is, business to consumer (B2C) marketing
(Yanamandram & White, 2006).
The literature in general has mainly focused on consumer
services rather than business services (Parasuraman, 1998), but
driven by changes in the economy, marketing and purchasing of
business services have been receiving growing attention both inresearch and practice (Wynstra, Bjrn, & van der Valk, 2006).
Furthermore, the growth in business related services is the main
driver behind the increased share of the service sector in total
value added. In 2001, finance, insurance and business services
such as legal and consultancy services accounted for 2030% of
value added in the overall economy having doubled their
share since 1980 (Wlfl, 2005).
The study of concepts like quality, satisfaction and, more
recently, perceived value, with roots in early works by Carlzon
(1987), Grnroos (1982), Lehtinen and Lehtinen (1982),
Parasuraman, Zeithaml, and Berry (1988), and Oliver (1980),
provides new opportunities in organizational management. In particular, it becomes critical to identify and measure the
elements which contribute most to explaining satisfaction, thus
providing companies with a better understanding on how the
customer's point of view is built in an environment where
building more unique relationships with customers is vital
(Lindgreen, Palmer, Vanhamme, & Wouters, 2006). Moreover,
service marketing literature has argued that the service process,
or service encounter, may be the most important antecedent in
customer evaluation of service performance (Brown & Swartz,
1989; Lehtinen & Lehtinen, 1982). These service encounters are
considered as the basis for building customer satisfaction.
Industrial Marketing Management 37 (2008) 921939
The authors would like to express their thanks for the financial support
received under the Spanish Ministry of Education and Science Research Project
(SEJ2004-05988). Corresponding author. Tel.: +34 963 828329.
E-mail addresses: [email protected] (I. Gil), [email protected]
(G. Berenguer), [email protected] (A. Cervera).1 Tel.: +34 963 828319.2 Tel.: +34 963 828964.
0019-8501/$ - see front matter 2007 Elsevier Inc. All rights reserved.doi:10.1016/j.indmarman.2007.06.008
mailto:irene.%E4%A7%[email protected]:[email protected]:[email protected]://dx.doi.org/10.1016/j.indmarman.2007.06.008http://dx.doi.org/10.1016/j.indmarman.2007.06.008mailto:[email protected]:[email protected]:irene.%E4%A7%[email protected] -
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The literature on these topics is extensive, although the
precise nature of their content and of their relationships has not
been extensively documented, even less so in terms of business-
to-business relationships (De Ruyter, Wetzels, Lemmink, &
Mattsson, 1997; Eriksson & Lfmarck Vaghult, 2000; Yeung,
Chew Ging, & Ennew, 2002).
On the other hand, in service systems it has been stated thatemployees' satisfaction with their jobs is so important as
customer satisfaction for the results of an organization (Comm
& Mathaisel, 2000:43). Employees' attitudes, in general, have
been proved as a variable affecting customer satisfaction (Adsit,
London, Crom, & Jones, 1996) and, more specifically, this
satisfaction seems to intervene in quality perceptions held by
customers (Schneider & Bowen, 1985).
With the increased demand for professional services,
marketing and organizational structures are changing and the
importance of studying the antecedents of delivering service
quality in a professional service is crucial (Boyt, Lusch, &
Naylor, 2001: 321).Particularly, Storer and Rajan (2002) point out that survival
for financial services in an evolving workplace increasingly
relies not only on technical but also on behavioral skills and
knowledge relating to working methods characterized by
networking, inter-dependency and reciprocity.
Consequently, this paper will explore relationships among
service encounter (SE), perceived service value (SV), customer
satisfaction (CS) and job satisfaction of service employees (JS),
considering as the scenario of this research an organization
specialized in service provision to financial entities, where 90%
of its activity consists of preparing and processing house
mortgages. First, we review the literature on the concepts SE,
SV, CS and JS, and identify the links between them in order todefine the research hypotheses. Then, we present the research
methodology and the results of the study, followed by the
conclusions and recommendations for management.
2. Theoretical framework and hypotheses
2.1. Service encounters
From the customer point of view, the most vivid service
impression occurs during the service encounter or moment of
truth, i.e. when customers interact with the service company
(Zeithaml & Bitner, 2002:107). During these encounters, alsoknown as interactions which take place in a relation episode
(Ravald & Grnroos, 1996), the customer receives a sort of
snapshot of the organization's level of service provision. Thus,
the result of interactions between organizations, related pro-
cesses and services, employees who provide the service and
customers define the service experience (Bitner, Faranda,
Hubbert, & Zeithaml, 1997) and from the customer's point of
view, the service encounter is the origin of the whole chain
of evaluations on the service result (Lehtinen & Lehtinen,
1982).
The service encounter has traditionally been described as the
dyadic interaction between service providers and customers
(Surprenant & Solomon, 1987). There are different types of
service encounters (Shostack, 1985), the most frequently
studied being personal interactions. Armstrong (1992) proposes
defining this process of service delivery as a system which can
be broken down into a number of different stages. Customer
perception of service characteristics in each of these stages is
therefore the antecedent and origin of any process of service
evaluation, and each encounter contributes the same to thecustomer's general satisfaction and to his/her willingness to do
business with the company again (Zeithaml & Bitner,
2002:108).
2.2. Service value
The notion of value, from a marketing approach, has a clear
subjective orientation with most authors attributing an evalu-
ative judgment to it (e.g. Berry & Yadav, 1997; Flint, Woodruff,
& Gardial, 2002; Monroe, 1992; Woodruff, 1997; Zeithaml,
1984, 1988). Furthermore, value is not inherent to services
rather it is experienced by the customers (Woodruff &Gardial, 1996:7) and therefore perceived by them. This
perception in B2B interaction materialises in judgments or
evaluations of what the customer perceives as received from the
seller in a specific situation of purchase or use (Flint et al.,
2002:103). This approach to the notion of value is consistent
with the parameters and analytical methods proposed in the
literature on consumer value (Holbrook, 1999).
There is a tendency to define value as a two-way variable
following the proposal by Oliver (1999), using the term trade-
offas equivalent to compensation or balance between benefits
and sacrifices. The most basic approach to a two-way definition
of value is that of ratio or trade-offbetween quality and price
(Monroe, 1992), in other words value for money (Fornell,Johnson, Anderson, Cha, & Bryant, 1996; Gale, 1994).
However, increasingly, authors are suggesting that this vision
is too simplistic (Bolton & Drew, 1991), and other more
sophisticated measures are needed. Thus, it is suggested that
perceived value can be understood following the proposal by
Zeithaml (1988:14), as a global evaluation that the customer
develops concerning the usefulness of a product or service,
based on the perceptions of what he or she has received in
contrast to what he or she has given. Thus, value is a positive
function of what is received and a negative function of what is
sacrificed (Oliver, 1999:45), if indeed it is possible to use the
term value to describe perceptions that are exclusively positiveor negative.
On the above basis, service value could be the result, in part,
of quality, understood as a global judgment, or attitude,
relating to the superiority of the service (Parasuraman et al.,
1988: 16). In this line of research, a significant number of
contributions present value as an advance of quality and so, it
becomes a macro-concept which includes quality (Oliver,
1999). Thus, quality components are important elements of
value although service value also includes other components
(Lapierre, Filiatrault, & Chebat, 1999:236). These other
elements would consider both the price paid for the service
and the other costs incurred by the customer on acquiring the
service.
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dominant position, which establishes inverse causal order where
satisfaction is the consequence of quality.
The variables customer satisfaction and quality have also
been related to value. The concept of value, as we have shown,
goes beyond that of quality, and is an advance of quality as it
incorporates sacrifices and other additional benefits. In the
research which has observed the relationship between the two,the conclusion is that value is the consequence of quality (e.g.
Caruana, Money, & Berthon, 2000; Grewal, Monroe, &
Krishnan, 1998; Kashyap & Bojanic, 2000; Oh, 1999, 2000;
Cronin et al., 2000; Sirohi, Mclaughlin, & Wittink, 1998;
Sweeney, Soutar, Whiteley, & Johnson, 1996) and value can be
understood as a higher order construction. Referring to the link
between value and satisfaction due to the natural affinity
between the two concepts (Woodruff & Gardial, 1996:86) as
both are formed on the basis of evaluative judgments
(Woodruff, 1997), it is difficult to clearly differentiate between
them and price has arisen as the discriminant element. However,
as the number of in-depth studies on value in the literature hasgrown, the importance of price as a differentiating criteria has
started to diminish (Oliver, 1999). For Sweeney and Soutar
(2001:204), although value can easily be confused with
satisfaction, the difference is clear: these constructs are
different. While perceived value occurs in different stages of
the purchase process, including pre-purchase (Woodruff, 1997),
satisfaction is universally a post-use or post-purchase evalua-
tion. It seems clear that this statement introduces a causal order
which allows satisfaction to be understood as the result of the
perception of value, as shown in the research by, among others,
Fornell et al. (1996), Oh (1999, 2003), Caruana et al. (2000),
Babin and Kim (2001), and Gallarza and Gil (2006).
Furthermore, it could be concluded that there is a relation between the interactions which take place in what we have
called the service encounter and customer satisfaction. It could
also be stated, however, that customer judgments on these
interactions through performance scores could refer to service
value, which influences satisfaction. The issue now to be
considered concerns the nature of the relation between these
three variables. Empirical evidence is scanty and it seems that it
would be useful to confirm these relations in the sector and
sphere of activity in our research scenario.
In the service being studied, there are different interactions in
each episode which make up the service encounter. It would
seem reasonable for there to be direct effects on customerperceptions of said interactions on service value. Consequently,
the first working hypothesis we propose is as follows:
H1. The more positive the perceptions of episode interactions
the more positive the service value.
Our previous discussion hypothesized that perceptions of
service characteristics are antecedents to service value, but what
are the consequences of perceived service value? It would again
appear reasonable and in accordance with the above discussion
for perceived service value to directly affect overall customer
satisfaction raising therefore the issue of the effect of service
encounter perceptions on customer satisfaction. Thus percep-
tions of service characteristics in each interaction affect service
value which in the end affects overall customer satisfaction.
Consequently we propose the following hypotheses:
H2. The more positive the perceived service value, the more
positive overall customer satisfaction.
H3. Perceived service value mediates the effects of perceptions
of episode interactions on overall customer satisfaction.
In the competitive context of the financial services industry, it
is becoming more frequently pointed out that job satisfaction of
service employees is as important as customer satisfaction for an
organization's results (Comm & Mathaisel, 2000:43). Thus,
Schneider (1980) reports that job satisfaction is the main reason
why employees develop good service, influencing customer
satisfaction (Adsit et al., 1996;Koys, 2001; Rucci, Kim, & Quinn,
1998), their perceptions of service quality (Hartline & Ferrell,
1996; Schneider & Bowen, 1985) and competitiveness (Asif &Sargeant, 2000; Berry, 1981; Grnroos, 2001; Spinelli &
Canavos, 2000). The interactive nature of service delivery places
employees in an outstanding position to generate positive
perceptions (Zeithaml & Bitner, 2002), given that many
dimensions of service will be affected by their actions, attitudes
and emotions throughout the service encounter. In service
encounters, employees must be considered executors and
their behavioris the service quality which customers perceive
(Bitner, 1990). In this context, job satisfaction of service
employees may be understood as a motivator for service per-
formance, with this idea becoming almost an axiom in the
service literature (Wilson & Frimpong, 2004:471). Thus, and
althoughit is not the only element, Snipes et al. (2005:1330)pointout that currently most managers understand that to cause a
substantial impact on service quality in organizations, front-line
workers and customers need to be central to management con-
cerns. Introducing policies to increase job employee satisfaction
may well be worth it in the end.
Heskett, Sasser, and Schlesinger (1997) propose a theoretical
model in which employee job satisfaction begins a chain of
benefits leading to quality, productivity, service value, customer
satisfaction and loyalty which in turn leads to profits and growth.
Surprisingly, however, as Silvestro (2002) has pointed out, little
empirical evidence is given to support the validity of these
relations. The authors use the term satisfaction mirror to refer tothe fact that employee job satisfaction is reflected in terms of
customer satisfaction which in turn generates growth and profit
(Heskett et al., 1997). Similar observations are made by Heskett,
Jones, Loveman, Sasser, and Schlesinger (1994), Spinelli and
Canavos (2000), Bernhardt, Donthu, and Kennett (2000), and
Tornow and Wiley (1991). Schlesinger and Heskett (1991) and
Reichheld (1996) alsoargue that job satisfaction of employees has
the potential to improve customer service or increase customer
satisfaction. The underlying idea in these studies is that satisfied
workers will perform their work better than those who are not,
they will be in better disposition and will be more likely to behave
considerately towards colleagues and consumers (Motowidlo,
1984; Rogers, Clow, & Kash, 1994). In fact, Boshoff and Allen
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(2000) conclude, among other things, that front-line employees
who are more efficient at recovering consumers are more likely to
show higher levels of job satisfaction. In the context of financial
services, Ryan, Schmit, and Johnson (1996) suggest that con-
sumer satisfaction is the cause of employee satisfaction and
Reynierse and Harker (1986) conclude that employee job sat-isfaction derives partly from the opportunity to offer customers
high service levels and partly from positive customer feedback
after the interaction. In terms of the relation employee job
satisfaction-service quality, Yoon, Beatty, and Suh (2001)
conclude that variables in job climate contribute directly to job
satisfaction and effort of service employees and indirectly impact
customer perceptions of employee service quality. The work of
Snipes et al. (2005), Hartline and Ferrell (1996), and Schneider
and Bowen (1985) is on similar lines.
Other empirical evidence, however, indicates that this rela-
tion is very weak (Ellis, Gudergan, & Johnson, 2001; Loveman,
1998; Schneider, White, & Paul, 1998; Silvestro, 2002). These
studies and other data show that the univocal relationship between employees job satisfaction and business results or
between employees job satisfaction and customer satisfaction
is beginning to be questioned, hence the appropriateness of
continuing this line of research.
Thus, we establish that moderation hypotheses can be
plausible and that the intensity of the relation between perceptions
which develop in the relation episode and service value could vary
according to the level of job satisfaction of service employees and
thus we propose the following research hypothesis:
H4. Job satisfaction of service employees moderates the effect
of perceptions in interactions in an episode on customer per-
ceived service value.
Fig. 1 is a summary of the hypotheses on the relations under
consideration.
3. Research methodology
In this work we verify the hypotheses under consideration by
analyzing the particular case of the relationship between a
company providing management services to external finance
organizations in the banking sector and their clients, banks, in
Spain. The company specializes in house mortgage service pro-
vision to financial entities, with 90% of its activity dedicated to
preparing and processing mortgages, thisservice being the coreof
our study. The request for the services provided by the external
financial organization comes directly from the credit entities(banks), which act as intermediaries between the final consumer
and the company.
The quantitative methodology uses ad-hoc interviews
through two structured questionnaires: one focused on custo-
mers (i.e. banks) and the other on the service provider
employees. The questionnaire which focuses on the customers
was administered to the managers of bank offices which, the
month before the field work began, had processed at least one
mortgage with the service provider trying to achieve a
proportion in the whole companies' customer distribution and
the sample. Using the office manager as key informant, the
questionnaire provided two-way information. Firstly, percep-
tions of the sequence of stages making up the service provisionwere evaluated, characterizing each of the interactions in the
episode or service encounter cascade on the basis of procedure
indicators (how the service is delivered) and technical and
functional (what is delivered) (Lehtinen & Lehtinen, 1982;
Ravald & Grnroos, 1996). Secondly, issues concerning the
overall evaluation of the service were considered in order to
identify service value and satisfaction. A total of 194 valid
questionnaires were obtained for analysis.
It is not common in this kind of studies to use data verifying
the randomness condition (e.g. Asif & Sargeant, 2000; Brown
& Swartz, 1989; Comm & Mahaisel, 2000; Sirohi et al., 1998;
Yoon et al., 2001). This research is not an exception. Althoughconvenience sampling presents disadvantages, for our explor-
atory research, the sample represents the kind of relationship
that the organization has with their different bank customers.
Then, given a period of time loans managed during the last
month a census of bank offices that during the period has
processed at least one loan with the company was analyzed
(194). These 194 offices were moreover proportional to the
weight of each entity in terms of the total number of loans
managed during the previous year. In this sense, in our research,
the majority of those interviewed, 63.4% of the sample,
represent bank offices of financial entity 1, with an average of
8 house mortgages; 8 house mortgages have also been handled
by financial entity 2, representing 8.3% of the total sample.
Fig. 1. Hypothesis on the relations between service encounter, service value, customer satisfaction and job satisfaction of service employees.3
3 The continuous lines represent direct relations and the discontinuous lines
represent mediated or moderated relaciones.
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Finally, 28.4% of the sample are bank offices belonging to
entity 3, with 16 house mortgages handled during the last
month.
The questionnaire focused on the service provider aimed to
evaluate job satisfaction of service employees in order to
analyze its possible moderating effect on the other variables
considered. The questionnaire was administered to all the
employees in the organization. To guarantee confidentiality, it
was agreed that company managers would not be able to access
individual replies. Personal interviews were developed, during
working days. The organization under study suggested the orderof the interviews so that we would not distort the day to day
working rhythm. Questionnaires were administered by a person
hired and trained for the purpose. Data was processed and
analyzed using SPSS 11 software.
3.1. Measurement instruments
The evaluation measurements used were designed on the
basis of the literature review and through group discussions
with heads of the organization.
Our first aim is to investigate the relationships between the
provider and its organizational customer, evaluated from thislast perspective, taking, as a starting point the set of personal
interactions that take place in a service episode (Grnroos,
1990; Ravald & Grnroos, 1996) or service encounters (Bitner,
Booms, & Tetreault, 1990).
The service encounters (SE) or episodes which took place
between the provider company and the bank are direct and
indirect personal encounters. The sequence of interactions
which occurs in each of these encounters defines the service
being studied: processing a mortgage. A set of interactions have
been identified on the basis of 3 focus groups that were
composed by the organization executives and bank executives
which can be grouped around five stages which define the
service encounter: telephone service, preparation and assistance
with signing the agreement, the registering process, documen-
tation delivery and liquidation of the down payment on
expenses (see Fig. 2). Each of the five phases has been defined
on the basis of a set of service characteristics with a battery of
items (see the Appendix), evaluated through 5 possible replies
ranging from not at all appropriate (1) to very appropriate
(5), giving content to the SE scale (Service Encounter).
To evaluate service value (SV), we used a multi-item scale
which retains cost/benefit indicators in response to the need to
include multiple measurements, suggested among others by
Bolton and Drew (1991) and Sweeney and Soutar (2001). Thus,service value has been defined on the basis of quality, on the
understanding that SERVQUAL's research tradition (Parasura-
man et al., 1988) offers good opportunities as a starting point for
its evaluation. Our proposal (SV see the Appendix) is a scale
which retains one item per quality dimension and starts from
performance scores only on the lines of the research by
Brady, Cronin, and Brand (2002) and based on the recommen-
dations, among others of Novack (1997) for evaluating
organizational customers (items V1V5). After defining the
items which give content to quality, we considered including
other indicators in the original scale following the literature on
value. Thus, costs were included as effects, evaluated positively(see items V6V10 in the Appendix): (1) the perception of risk or
greater security in the experience through the indicator
confidence following the approaches, among others ofRavald
and Grnroos (1996), De Ruyter et al. (1997), and Sweeney,
Soutar, and Johnson (1999), trying to capture the emotional or
affective component of the relation's perceived value, (2) time
or effort, following the suggestion by De Ruyter et al. (1997),
defining energy or non-monetary sacrifices understood as effort,
time and convenience; (3) efficiency, considered as an element
in the value following Holbrook's proposal (1999), evaluated
through two indicators: a specific one for the organization's
staff (which Sweeney and Soutar (2001) consider is a deciding
factor in the perception of value) and another in relation to the
Fig. 2. Service encounter cascade: processing a mortgage.
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Table 1
Factorial analysis suitability indicators, rotated components matrix and factor specification on the scales
SE scale Components
1 2 3 4 5
I1 0.141 7.049E02 0.141 0.116 0.880
I2 0.250 0.185 4.940E02 8.537E02 0.834
I3 0.763 6.077E
02 0.228 0.256 0.184I4 0.687 0.239 0.164 0.285 0.106
I5 0.674 0.209 0.406 5.217E02 6.896E02
I6 0.709 9.534E02 0.228 2.836E02 0.205
I7 0.579 0.379 1.85E02 0.188 0.162
I8 0.551 0.299 0.249 0.144 5.253E02
I9 0.114 0.841 0.320 0.101 0.106
I10 0.212 0.783 0.366 0.156 6.869E02
I11 0.303 0.735 0.121 0.158 0.138
I12 0.406 0.518 0.230 0.298 0.160
I13 0.372 0.185 0.625 0.223 0.225
I14 0.257 0.208 0.790 6.652E02 1.402E02
I15 0.154 0.321 0.771 8.146E02 4.741E02
I16 0.226 0.171 0.689 0.372 0.151
I17 0.203 0.117 0.172 0.820 0.204
I18 0.285 0.342 0.223 0.724 1.282E04
Factor specification F1: FACASSIST F2: FACREG F3: FACDOCDEL F4: FACDEPSET F5: FACTELSERVCronbach's alpha 0.8516 0.8676 0.8505 0.7340 0.7779
Alpha: 0.9247; correlations between variables: significant (p = zero or close to zero in almost all cases); correlation matrix determinant: 3.588E05; 2:1905.463;
degrees of freedom: 153; Bartlett's Test: 0.000; KaiserMeyerOlkin index: 0.911.
SV scale Components
1
V1 0.814
V2 0.812
V3 0.823
V4 0.785
V5 0.800
V6. 0.835V7 0.633
V8 0.704
V9 0.798
V10 0.598
Factor specification F1:SV
Alpha: 0.9089; correlations between variables: significant (p =zero or close to zero in almost all cases); correlation matrix determinant: 1.952E03; 2:1178.115;
degrees of freedom: 45; Bartlett's test: 0.000; KaiserMeyerOlkin index: 0.916.
JS scale Components
1 2 3 4 5 6
S1 6.923E02 0.180 0.144 0.839 0.151 0.110
S2 0.183 6.849E02 0.292 0.834 0.149 0.160
S3 0.763 7.966E02 8.307E02 0.245 0.255 3.45E02
S4 5.874E
02 0.149
0.191 0.404 0.623 0.383S5 0.426 0.304 0.239 8.86E02 0.421 0.143
S6 0.181 6.310E02 0.270 0.182 0.763 2.337E02
S7 0.213 9.925E03 0.325 0.101 8.699E02 0.801
S8 0.168 8.940E02 0.255 0.187 7.252E02 0.833
S9 0.306 6.585E02 0.205 0.753 0.103 4.451E02
S10 0.435 0.118 0.442 0.326 0.437 0.198
S11 0.668 5.739E02 0.169 7.099E02 0.300 0.130
S12 0.170 0.803 4.720E02 1.068E02 0.103 0.188
S13 0.336 0.148 0.480 0.197 0.593 7.53E02
S14 2.47E02 8.948E02 0.719 0.224 0.247 0.195
S15 0.109 7.070E02 0.788 0.192 0.112 0.232
S16 5.787E02 0.848 7.984E02 1.846E02 0.112 2.17E02
S17 0.176 0.182 0.817 0.105 7.86E04 0.136
S18 0.228 0.829 0.160 0.139 1.29E03 0.156
(continued on next page)
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service provided; and (4) value-for-money, defined according to
the most classical proposals in the literature on value as
perceptions of the relation service quality/price, capturing thecognitive or rational component of the relation's perceived
value.
Satisfaction with the service provider (SP) was measured
overall, from a single-item scale following the conceptual
proposal by Anderson, Fornell, and Lehmann (1994). This
proposal is consistent with contributions, among others, from
Cronin and Taylor (1992), Bei and Chiao (2001), Jones and Suh
(2000), Yu and Dean (2001), and Maxham and Netemeyer
(2003), and in particular from Angur, Nataraajan, and Jahera
(1999), in the sphere of the banking industry. Overall
satisfaction was evaluated on a 10 point scale (SC).
To measure job satisfaction of service employees (JS), there
is a particularly interesting measurement proposal from Meliand Peir (1989) who designed a set of instruments (S4/82; S20/
23, S10/12 and S21/26) with notable psychometric character-
istics which could be selected according to the context in which
the questionnaire was administered. Questionnaire S20/23 with
23 items was considered appropriate (see the Appendix). The
psychometric properties of this scale were contrasted in later
studies (e.g. Gil, Berenguer, Cervera, & Moliner, 2005),
confirming their usefulness, reliability and validity.
Given that some of the scales and the items were created in
English, and they have been tested in a different language
context, to ensure the validity of the item translation, a translate/
back translate procedure (Brisles, 1970; Laroche, Papadopou-los, Heslop, & Bergeron, 2003) was used.
Finally, the classification variables such as gender, age, level
of training, length of time in the company, department or type of
contract with the organization, makes it possible to identify
employee profile.
4. Analysis of data and discussion of the results
We carried out different procedures to examine the psycho-
metric properties of the proposed measurements. The items in the
different scales were analyzed on the basis of procedures recom-
mended in the methodology on scale design for evaluating
marketing constructs (Churchill, 1979; Diamantopoulos &
Winklhofer, 2001; Judd & McClelland, 1998), and, where
appropriate, of applying principal components analysis (herein-
after referred to as PCA) and confirmatory factor analysis (CFA).Reliability analysis, understood as internal consistency, was
carried out by calculating Cronbach's coefficient and using
measurements which relate each isolated item (item-total cor-
relation and inter-item correlation).
In the Service Encounter (SE) scale, the statistics analyzed
confirm scale properties, and the items appear to show correct
behavior and the measurements and typical deviations for each
item appear approximately equal. Correlations of the indicators
with respect to the total are moderate or high and positive in all
cases. Finally the coefficient reaches a value of 0.9247, which
is a good result, showing score stability and internal consis-
tency. The structure of the relations between the variables in the
scale was verified by PCA with orthogonal rotation using theVARIMAX method. The application of this statistical technique
to our data, was supported by different criteria based on the
correlation matrix. Both the KMO value (above 0.9) and
Bartlett's test of Sphericity (p below the critical level of 0.01),
indicate it is appropriate to develop a PCA. The results show
there are five factors which coincide with the 5 stages defined,
explaining 70.504% of the variance (see Table 1).
The first factor which emerges can be considered as the
preparation/assistance with the signature phase, it accounts
for 19.15% of the variance and groups six indicators on
assistance with preparing the signature, staff training, analysis
of register viability, mistakes in preparing the signature,information prior to the signature and speed of any modifica-
tion. The second and third factors describe respectively the
registration/processing process and the documentation deliv-
ery phase and account for 15% of the variance. The contents of
the four indicators in the second factor are related to the
information, time used and the response to any event during
deed processing. The contents of the indicators for the third
factor relate to correct documentation, the form and method of
delivering documentation and the time elapsing between the
date it is dispatched and received. The fourth factor includes
two items which explain 9% of the variance and refer to the
study for the coverage of funds and the settlement sheet and
has been termed settling the deposit. Finally we can identify
JS scale
JS scale Components
1 2 3 4 5 6
S19 0.691 0.195 0.267 7.337E02 0.230 0.329
S20 0.662 0.202 2.74E02 0.432 0.170 0.204
S21 0.363 0.627 9.670E02 0.176 3.34E02 1.118E02
S22 0.723 0.247
2.26E
02 0.121 0.345 7.020E
02S23 0.100 0.709 1.113E02 9.922E02 8.638E02 0.268
Factor
specification
SAP: satisfaction
with provision
SAPE: satisfaction with
physical working
environment
SAPAR:
participation
satisfaction
IS: intrinsic work
satisfaction
SIR: satisfaction
with inter-personal
relations
SASU: satisfaction
with supervision
Cronbach's
alpha
0.8744 0.8504 0.8238 0.8744 0.8073 0.8682
Alpha: 0.9155; Raju's : 0.8684; correlations between variables: significant (p =zero or close to zero in almost all cases); correlation matrix determinant: 1.150E07;
2: 998.646; degrees of freedom: 253; Bartlett's test: 0.000; KaiserMeyerOlkin index: 0.800. Those items in bold are the ones loading higher on each factor. An item
was considered to load on a given factor if the factor loading obtained in the rotated factor matrix was 0.4 or greater.
Table 1 (continued)
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Table 2
CFA results of measures
CFA results of measures for JS scale
Items (JS) R2 Reliability Factor
S3 0.59 0.35 Composed rel iability = 0.8504 AVE = 0. 5358 SAP: satisfaction with provision
S11 0.66 (5.54) 0.46
S19 0.75 (5.85
) 0.56S20 0.84 (6.21) 0.71
S22 0.76 (5.67) 0.63
S12 0.63 0.40 Composed reliability=0.8524 AVE=0.5440 SAPE: satisfaction with physical working environment
S16 0.76 (7.76) 0.57
S18 0.95 (4.99) 0.89
S21 0.74 (4.34) 0.54
S23 0.56 (4.97) 0.31
S14 0.75 0.57 Composed rel iability = 0.8286 AVE = 0. 6178 SAPAR: participation satisfaction
S15 0.85 (6.15) 0.71
S17 0.76 (5.28) 0.57
S1 0.8 0.64 Composed reliability = 0.8751 AVE = 0.7014 IS: intrinsic work satisfaction
S2 0.92 (9.57) 0.85
S9 0.79 (9.39) 0.62
S4 0.45 0.30 Composed reliability=0.7568 AVE=0.5265 SIR: satisfaction with inter-personal relations
S6 0.74 (3.10
) 0.55S13 0.91 (2.92) 0.82
S7 0.86 0.81 Composed rel iability = 0.8428 AVE = 0. 7284 SASU: satisfaction with supervision
S8 0.90 (7.60) 0.62
Discriminant validity Correlation2
SAPSAPE = 0.2570 SAPESASU=0.0936
SAPSAPAR = 0.1739 SAPAR IS=0.3169
SAPIS = 0.3226 SAPAR SIR=0.3844
SAPSIR = 0.4045 SAPAR SASU=0.3306
SAPSASU = 0.2285 ISSIR=0.3114
SAPESAPAR = 0.1163 ISSASU=0.2116
SAPEIS = 0.1102 SIR SASU=0.1459
SAPESIR=0.1399
Chi-squared (174)=206.43 p =0.04; GFI=0.806; CFI=0.947; RMSEA=0.053; BB-NNFI=0.935; BB-NFI=0.795
CFA results of measures for SE scale
Items (SE) R2 Reliability Factor
I3 0.79 0.62 Composed reliability = 0.8561 AVE = 0.5003 FACASSISTI4 0.77 (10.86) 0.56
I5 0.75 (10.38) 0.56
I6 0.67 (9.13) 0.47
I7 0.61 (7.36) 0.39
I8 0.63 (7.83) 0.40
I9 0.72 0.52 Composed reliability = 0.8398 AVE = 0.5675 FACREGI10 0.78 (17.69) 0.59
I11 0.75 (9.98) 0.56
I12 0.78 (9.92) 0.60
I13 0.77 0.59 Composed reliability = 0.8499 AVE = 0.5863 FACDOCDELI14 0.75 (12.07) 0.56
I15 0.76 (11.12) 0.60
I16 0.79 (10.34) 0.59
I17 0.69 0.47 Composed reliability = 0.7422 AVE = 0.5929 FACDEPSETI18 0.85 (8.21) 0.716
I1 0.73 0.53 Composed reliability = 0.7845 AVE = 0.6472 FACTELSERVI2 0.87 (6.79) 0.76
Discriminant validity Correlation2
FACASSISTFACREG= 0.4651 FACREGFACDEPSET=0.5595
FACASSISTFACDOCDEL= 0.4277 FACREGFACTELSERV=0.2285
FACASSISTFACDEPSET= 0.3819 FACDOCDELFACDEPSET=0.4624
FACASSISTFACTELSERV= 0.2873 FACDOCDELFACTELSERV=0.1616
FACREGFACDOCDEL= 0.4583 FACDEPSETFACTELSERV=0.1475
Chi-squared (125)=174.03 p =0.002; GFI=0.897; CFI=0.969; RMSEA=0.046; BB-NNFI=0.961; BB-NFI=0.900
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telephone service which accounts for 9% of the variance, a
value very close to factor four. As shown in Table 1, the
coefficient in the factors varies between 0.73 and 0.86. After
defining the factors and studying their internal consistency, we
proceed to analyze the validity of the proposed scale. In ouropinion, the measurement verifies content validity as the
domain of the construct has been specified and all the possible
dimensions and contents for the concept under analysis have
been considered. On the same lines, we can also state the
nomological validity of the scales using Pearson's correlations
between scale items and the overall evaluations for each of the
five stages (item-test correlation) through IGi indicators.
As the Service Value (SV) scale was defined as additive, four
basic aspects were considered (Hair, Anderson, Tatham, & Black,
1999): (1) conceptual definition; (2) dimensionality; (3) reliabil-
ity; and (4) validity. In terms of conceptual definition, in our
proposal there is a correspondence between the individual items
and the concept, as shown in the literature review. In relation todimensionality, the scale shows a unidimensional behavior
achieving an explained variance of 58.417 (see Table 1). The
third underlying assumption is reliability, in this sense, the relation
statistics of each item with the other items behave correctly. Item
correlation with respect to the total is high in all cases. The
coefficient shows the test's high internal consistency, with a value
of 0.9089. Finallyin relationto scale validity, the scale shows high
criteria or concurrent validity as the correlation matrix between
items and a single-item criterion external to the test which we call
GV (Global Value) were all positive and neither very high nor
very low. Correlation of the resulting sum scale with the item GV
makes it possible to confirm concurrent validity of the SV scale.Finally, nomological validity, observedby correlating SV with the
SE scale is verified for both scales.
In relation to customer satisfaction, the correlation coeffi-
cient was calculated between items for the evaluation of each
stage and the overall evaluation, with significant correlations in
all cases.
Finally, the multi-item scales of job satisfaction of service
employees (JS) used were defined as additive, and checked for
concept, reliability, dimensionality and validity (Hair et al.,
1999:105106). The job satisfaction of service employees JS
scale was found to be satisfactory in terms of reliability.
Relational statistics showed correct behavior for all the items,
with moderate to high, positive correlations in all cases with
respect to the total. Internal scale consistency measured by
Cronbach's alpha was 0.9155 which is very close to the 0.92
obtained by Meli and Peir. A principal components analysis
(PCA) was performed to analyze scale components with
orthogonal rotation using the VARIMAX method. Applicationof this statistical technique to our data was supported by
correlation matrix based criteria.
As Table 1 shows, the 23 items were grouped into six factors
explaining 72.560% of the total variance, using latent root
criteria. The first component which clearly emerges relates five
items explaining 15.047% of the variance and is known as
satisfaction with provision SAP. The second factor which
can be termed satisfaction with the physical working environ-
ment SAPE, accounts for 11.588% of the variance explained,
grouping five items. The third factor, participation satisfac-
tion SAPAR, includes three items which explain 7.707% of
the variance. The fourth factor accounts for 6.552% of the
variance and has been called intrinsic work satisfaction IS.Two final factors emerge, the fifth factor which accounts for
5.5% of the variance and a sixth factor accounting for 5.2% of
the variance, both have two items each, denominated respec-
tively as satisfaction with inter-personal relations SIR, and
satisfaction with supervision SASU. The internal consisten-
cy of the set of items used to evaluate each type of job
satisfaction of service employees, defines an alpha in the factors
which oscillates between 0.80 and 0.87. If the small number of
items in each factor is taken into account, reliability can be
considered excellent. For each factor, correlations between the
different indicators item-total were greater than 0.5 in all cases.
Once the exploratory factor structure of the scales wasdelimited, we proceeded to confirm the obtained factors through
confirmatory factor analysis (CFA). The measurement model
estimation was performed with the Robust Maximum Likeli-
hood Method using the asymptotic variancecovariance matrix
and with the EQS 6.1 software package.
We firstly calculated the internal consistency of the
dimensions that compose each scale, considering simultaneous-
ly two indicators: composed reliability coefficient whose
minimum threshold value is 0.7 (Anderson & Gerbing, 1988;
Bagozzi & Yi, 1988), and the extracted variance in each
scalewhose value must exceed 0.5 (Fornell & Larker, 1981).
These indexes, all of them shown in Table 2, proved to be
acceptable for all factors obtained.
Discriminant validity
CFA results of measures for SV scale
Items (SV) R2 Reliability Factor
V1 0.76 0.57 Composed reliability = 0.9182 AVE = 0.5323 SV
V2 0.80 (12.65) 0.63
V3 0.80 (11.28) 0.64
V4 0.78 (9.98
) 0.61V5 0.75 (10.02) 0.57
V6 0.66 (9.76) 0.43
V7 0.56 (7.18) 0.31
V8 0.78 (17.87) 0.61
V9 0.59 (9.33) 0.34
V10 0.78 (15.10) 0.61
Chi-squared (35)=49.78 p =0.031; GFI=0.939; CFI=0.983; RMSEA=0.051; BB-NNFI=0.977; BB-NFI=0.952. Note: loadings are significative at 99%.
Table 2 (continued)
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Taking into account the global result obtained, we can state
that there is a sufficient level of internal consistency in the
items, what means that the ability of the set of items employed
to represent each of the latent constructs is satisfactory.
Finally, construct validity (convergent and discriminant
validity) of the scales was analyzed. In the case of the unidi-
mensional scale SV, convergent validity can be stated as all itsvariables are associated to significant and high loadings at least at
95% (tN1.96). In the case of the multi-dimensional scales, (SE
and JS scales), convergent validity was corroborated given that,
apart from the significant loadings obtained, correlations among
different dimensions loading on a second latent factor proved to
be significant at 95%. Therefore, it can be stated that scales have
convergent validity (Anderson & Gerbing, 1988).
Discriminant validity, which means that each factor
represents a separate dimension, was analyzed through lineal
correlations or standardised covariances among latent factors.
These values showed evidence of discriminant validity given
that they showed values well below the unit. Furthermore, it
was verified that extracted variance in each of the dimensionswas higher than square correlations (Table 2). It can be stated
therefore that constructs show discriminant validity (Fornell &
Larcker, 1981).
After the above analysis it can be concluded that factors are
stable, corroborating the exploratory structure, and dimensions
show validity, so they can therefore be retained for theory testing.
Given the global results obtained on the quality of the mea-
sures, we can state that the subscales employed in our ques-
tionnaire are validated.
At a global level, other indexes for corroborating the
goodness of fit of the model provided satisfactory results
(Chi-squared; RMSEAb0.08; GFI close to or higher than 0.9;Bentley Bonnet normed and non-normed (1990) indexes BB-
NFI, BB-NNFI close to or higher than 0.9; and Compared Fix
Index CFIN0.9 for all subscales).
After analyzing measurement accuracy, regression analysis
with mediation was used to contrast the hypotheses on the links
between the constructs analyzed. Regression analysis has
sometimes been used to evaluate the predictive capacity of
service quality measurements (Angur et al., 1999) or to researchthe influence of perceived price and service quality on satisfaction
(Mittal & Lassar, 1996; Novack, 1997) and on loyalty (Bei &
Chiao, 2001; Lee & Cunningham, 2001; Zeithaml, Berrry, &
Parasuraman, 1996), to determine the moderating role of value in
satisfaction (Caruana et al., 2000) and that of satisfaction on
loyalty (De Ruyter & Bloemer, 1999).
Modelling including mediation processes is common in
social psychology, other previous research focused on variables
in relation to satisfaction have recently applied this methodol-
ogy with success (e.g. Bei & Chiao, 2001; Gil et al., 2005;
Maxham & Netemeyer, 2003). In general, a variable can be
defined as a mediator to the extent that it influences the relation
between the predictor and the criterion. When the measurementmodel involves latent constructs, modelling through structural
equations provides the basis for the data analysis strategy. If the
measurement model only involves measured variables, the basic
analytical approach is multiple regression (Kenny, Kashy, &
Bolger, 1998). Whatever data analysis method is used, the steps
required to test mediation are the same. In accordance with
Baron and Kenny (1986:1177), three regression equations
should be estimated to contrast mediation: first the mediator is
regressed on the independent variable, second, the dependent
variable is regressed on the independent one and, third, the
dependent variable is regressed on both the independent vari-
able and the mediator. These three equations are the basis forobserving relations in a mediation model under the following
Table 4
Analysis of the association between interactions in the episode and customer satisfaction
Regression equation 2: SESC
Independent
variables
F1:
FACASSIST
F2:
FACREG
F3:
FACDOCDEL
F4:
FACDEPSET
F5:
FACTELSERV
Constant R R2 R2
corrected
Standard
error
F model Durbin
Watson
0.274 0.335 0.206 0.330 0.173 5.585
(177.582)0.675 0 .455 0 .441 0. 6733 31. 411 1.834
(5.657) (6.917) (4.252) (6.809) (3.573)
0.305 0.372 0.229 0.367 0.192
Significance less than or equal to 0.01; significance less than or equal to 0.05 but greater than 0.01; significance less than or equal to 0.10 but greater than 0.05.
Student's absolute t statistic value is shown in brackets under the respective estimated parameter which represents the non-standardised coefficient. The value whichappears below the t statistic is the standardised coefficient.
Table 3
Analysis of the association between interactions in the episode and service value
Regression equation 1: SESV
Independent
variables
F1:
FACASSIST
F2:
FACREG
F3:
FACDOCDEL
F4:
FACDEPSET
F5:
FACTELSERV
Constant R R2 R2
corrected
Standard
error
F model Durbin
Watson
2.468 1.765 1.628 1.617 0.839 44.146
(242.062)
0.841 0.707 0.699 2.54019 90.780 1.814
(13.498) (9.653) (8.906) (8.842) (4.587)0.533 0.381 0.352 0.349 0.181
Significance less than or equal to 0.01; significance less than or equal to 0.05 but greater than 0.01; significance less than or equal to 0.10 but greater than 0.05.
Student's absolute t statistic value is shown in brackets under the respective estimated parameter which represents the non-standardised coefficient. The value which
appears below the t statistic is the standardised coefficient.
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conditions: first, the independent variable must affect the
mediator in the first equation; second the independent variable
must affect the dependent variable in the second equation; and
third, the mediator must affect the dependent variable in the
third equation. If all the conditions are verified in the predicted
direction, then the effect of the independent variable on the
dependent one must be less in the third equation than in thesecond. Perfect mediation occurs if the independent variable
loses its influence when the mediator is included in the equation
(Kenny et al., 1998:260). In this case, the influence of the
independent variable on the dependent variable disappears
completely in the presence of the supposedly mediating variable
(Chumpitaz & Vanhamme, 2003:81).
Thus, to examine whether the proposed hypotheses are
fulfilled and the mediating effects associated with the sequence
SESVCS, first we regressed the variables related to
service value (mediator), to the predictive variables related to
service encounter. Thus, the regression 1 equation in Table 3
analyses the effect of the independent variable service encounter
on the mediators in service value. As can be seen, serviceencounter dimensions significantly and positively affect service
value. Thus, the first mediation condition has been satisfied for
most of the variables, verifying H1.
Secondly, we regress service encounter dimensions (predic-
tive variables) to overall satisfaction. The regression 2 equation
in Table 4 shows that service encounter dimensions signifi-
cantly and positively affect overall satisfaction. The second
mediation condition can therefore be said to be fulfilled, as the
predictive variable affects the dependent variable.
The third and fourth mediation conditions are observed in the
same regression equation, as the dependent variable is regressed
on both the mediator and the predictors. As in the above
sections, we carry out multiple linear regression analysis. The
first variable to enter is service value (SV) followed by factor 4
and factor 2 from the scale interactions in the episode, excluding
the other factors from the model as they are not significant. For
the entire mediation to be statistically supported, the effects of
the predictive variable in the dependent variable must not besignificant, dominated by the mediator. However, as we have
already indicated, complete mediation is not very common in
the social sciences (Baron & Kenny, 1986; Maxham &
Netemeyer, 2003) and in this context it is considered that
partial mediations can support a mediation hypothesis (Kenny
et al., 1998). Thus when the effects of the predictive variables in
the dependent variable decrease in equation 3 (dominated by the
mediator) with regard to those obtained in equation 2 (not
dominated by the mediator), mediation is supported (see Table
5). In regression equation 3, the mediator is significant and in
addition the beta coefficients for the predictive variables (the
factors which define interactions 2 and 4 which have been
significant) are smaller than regression equation 2 (its valuedecreases from 0.367 to 0.171 in FACPROCEL and from 0.372 to
0.159 in FACASSIST) and its significance decreases from 0.01 to
0.05 (Liu, Luo, & Shi, 2002). Thus the effect of the interactions
on satisfaction diminish in size and significance when service
value is controlled in the regression. Service value is shown as a
mediator which significantly decreases the relation between the
dependent and independent variable rather than eliminating it.
Finally, in the last model, tolerance, i.e. the proportion of
variance in each predictive variable not explained by the other
predictive variables takes values close to 0.8 and the inverse, the
variance inflation factor (VIF), takes values close to 1.2 which
Table 6
Values measured by department in the measures of job satisfaction which show different perceptions
Department Job satisfaction (JB) SAP: satisfaction
with provision
SAPAR:
participation
satisfaction
IS: intrinsic work
satisfaction
SIR: satisfaction
with inter-personal
relations
Average Standard
deviation
Average Standard
deviation
Average Standard
deviation
Average Standard
deviation
Average Standard
deviation
Reception 3.97 0.49 3.84 0.40 3.46 0.83 4.00 0.61 4.50 0.50
Authorization 3.18 0.48 2.61 0.67 2.95 0.71 3.43 0.78 3.67 0.99
Signings 3.63 0.55 2.72 0.96 3.53 1.06 4.25 0.63 4.25 0.82
Tax liquidation 2.97 0.49 2.42 0.88 2.66 0.56 3.25 0.85 3.06 0.62
External relations 3.74 0.64 3.44 0.88 3.76 0.78 3.65 0.81 3.80 0.58
Verification and control of documentation 3.33 0.44 2.75 0.83 3.54 0.61 3.31 0.65 4.00 0.75
Table 5
Analysis of the association between interactions in the episode, service value and customer satisfaction
Regression equation 3: SESC
Independent
variables
SV F1:
FACASSIST
F2:
FACREG
F3:
FACDOCDEL
F4:
FACDEPSET
F5:
FACTELSERV
Constant R R2 R2
corrected
Standard
error
F model Durbin
Watson
0.109 n.s. 0.143 n.s. 0.154 n.s. 3.769
(7.332)
0.710 0.504 0.496 0.6391 64.338 1.905
(9.404) (2.834) (3.093)0.561 0.159 0.171
Significance less than or equal to 0.01; significance less than or equal to 0.05 but greater than 0.01; significance less than or equal to 0.10 but greater than 0.05.
Student's absolute t statistic value is shown in brackets under the respective estimated parameter which represents the non-standardised coefficient. The value which
appears below the t statistic is the standardised coefficient.
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denotes little co-linearity with no redundant or superfluousvariable.
Overall, the results support the idea that service value par-
tially mediates the links between SE and SC. Thus, it can be
seen that: (1) variations in the perceptions of interactions
significantly influence variations in the levels of perceived
service value. Institutional customer perceptions of the technical
and functional characteristics of the encounter cascade therefore
do directly affect service value; (2) variations in the perceptions
of the interactions significantly influence variations in satisfac-
tion levels, with a partially mediated effect through service
value and (3) variations in service value significantly influence
satisfaction. Thus including service value in the model
intensifies its power of explanation as it supplies informationon how and why the interactions affect satisfaction. Thus, par-
tial mediation has been supported and H2H3 confirmed.
After studying the behavior of the mediating variable, wethen studied the effect of the service encounter on service value
and customer satisfaction to see if it was modified according to
the level of job satisfaction of service employees.
The variable job satisfaction of service employees shows
differences both overall and by satisfaction components, except
for intrinsic satisfaction and satisfaction with the physical
environment, according to the department the employee belongs
to. Table 6 shows the basic descriptives for these variables. The
highest averages in these departments are observed in satis-
faction with relations and the lowest for satisfaction with
benefits and participation. The tax liquidation department
shows the lowest levels of satisfaction while overall the most
satisfied employees are in reception and signing. All theseresults show that employee perceptions differ according to the
department where they work and that means we can focus on the
Table 7
Analysis of the associations between interactions in the episode and service value according to the level of job satisfaction of service employees
Independent
variables
F1:
FACASSIST
F2:
FACREG
F3:
FACDOCDEL
F4:
FACDEPSET
F5:
FACTELSERV
Constant R R2 R2
corrected
Standard
error
F model Durbin
Watson
JS HIGH
N=127
2.721 1.229 1.605 1.263 0.657 44.181
(193.081)0.834 0.695 0.683 2.4998 55.175 1.608
(11.145) (5.290) (6.687) (5.282) (2.902)
0.571 0.270 0.337 0.266 0.147JS LOW
N= 67
2.449 2.549 1.603 2.008 1.052 43.941
(141.413)0.889 0.791 0.774 2.3589 46.188 2.376
(8.645) (8.987) (6.103) (7.592) (3.588)
0.524 0.540 0.358 0.450 0.211
TOTAL
SAMPLE
N=194
2.468 1.765 1.628 1.617 0.839 44.146
(242.062)0.841 0.707 0.699 2.54019 90.78 1.814
(13.498) (9.653) (8.906) (8.842) (4.587)
0.533 0.381 0.352 0.349 0.181
Difference
analysis
t=0.7758 t=3.7058 t=0.0057 t=2.1325 t=1.0915
Significance less than or equal to 0.01; significance less than or equal to 0.05 but greater than 0.01; significance less than or equal to 0.10 but greater than 0.05.
Student's absolute t statistic value is shown in brackets under the respective estimated parameter which represents the non-standardised coefficient. The value which
appears below the t statistic is the standardised coefficient.
Table 8
Analysis of the association between interactions in the episode, service value and customer satisfaction in situations of high and low job satisfaction of service
employees
Regression equation 2: SESC
Independent
variables
F1:
FACASSIST
F2:
FACREG
F3:
FACDOCDEL
F4:
FACDEPSET
F5:
FACTELSERV
SV Constant R R2 R2
corrected
Standard
error
F model Durbin
Watson
JS HIGH
N=127
0.324 0.440 0.218 0.323 0.187 8.541
(107.634)
0.767 0.538 0.550 0.6025 17.433 2.009
(4.481) (6.074) (3.251) (4.780) (2.497)0.381 0.513 0.268 0.397 0.206
JS LOW
N= 67
0.251 0.282 0.198 0.334 10.170 8.610
(131.889)0.629 0.396 0.371 0.7132 15.858 2.032
(3.602) (4.259) (2.897) (4.898) (2.626)
0.260 0.306 0.206 0.347 0.187
Regression equation 3: SESC
JS HIGH
N=127
n.s. 0.137 n.s. 0.195 n.s. 0.108 3.828
(5.714)0.682 0.465 0.452 0.6656 35.648 2.032
(2.110) (2.894) (7.174)
0.149 0.202 0.532
JS LOW
N= 67
n.s. n.s. n.s. n.s. n.s. 0.135 2.625
(3.955)0.741 0.550 0.543 0.6105 79.298 1.730
(8.905)
0.741
Significance less than or equal to 0.01; significance less than or equal to 0.05 but greater than 0.01; significance less than or equal to 0.10 but greater than 0.05.
Student's absolute t statistic value is shown in brackets under the respective estimated parameter which represents the non-standardised coefficient. The value whichappears below the t statistic is the standardised coefficient.
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perceptions of employees in the authorization department, the
one with the maximum responsibility for providing the service
being studied. Thus for each customer request there is an
employee in that department who monitors the different stages
of the service and acts as contact employee, in other words as
the service's front-line employee for the customer. In this
context and in the light of the literature review, we understandthat the attitudes expressed by these employees could influence
customer perception of the value of the service provided. Thus
we went on to examine whether job satisfaction of service
employees is a moderating variable for the relation defined
between the interactions in the episode and service value. In this
way, we established dyadic relations between these employees
and the banks involved in the analysis.
There are different analytical procedures for testing modera-
tion. Moderation implies that the causal relation between two
variables changes according to the moderating variable. The
statistical procedure should therefore measure and test the
differential effect of the dependent variable on the independent
oneas a function of the moderator. The channelfor comparing and
measuring this effect depends in part on the measurement levelfor
the independent variable and the moderating variable. In our
research scenario, we considered it appropriate to distinguish
between employees with the highest satisfaction scores and those
with the lowest, defining two groups of employees: those above
average and those below average. Thus in overall job satisfaction
of service employees we differentiate two levels and, followingBaron and Kenny (1986), we measure the effect of the
independent variable on the dependent variable through non-
standardised regression coefficients. We then test the difference
between these coefficients(see Cohen & Cohen, 1983). Theresult
was a group of 127 banks which work with the employees we
have named as more satisfied and a second group of 67 banks
working with those less satisfied. After identifying the groups
the objective is to observe whether the associations between the
predictive variables and the criterion are significantly different.
Table 7 shows the relations between the variables for the two
levels of job satisfaction of service employees identified by
regression analysis. Following Sharma and Patterson (2000) wefirst contrasted the two groups using Chow's test.
Chow's test shows that the forms and slopes of the two
regression models are significantly different, the value of the
statistic F=3,2534NF(6,182) at 0.05 means that H0 on
structural stability can be rejected while also verifying that the
dependent variable service value is explained in a significantly
different way in both models. Chow's test evaluates whether
there are global differences in intra-group parameter values but
it does not evaluate the significance of the individual estimated
parameters. The statistically significant differences between the
individual regression coefficients were analyzed using tests
recommended by Cohen and Cohen (1983). The analyses used
to investigate the significance of the differences in the definedregression coefficients in the two groups (see the last row in
Table 7) identify differences in the regression coefficients
associated to the perceptions of the bank in the stages identified
by process of registering/processing and settlement of the
deposit. Observation of the corresponding estimated para-
meters shows that both interactions have a lower impact on
service value in the banks with more satisfied employees than in
those with less satisfied employees, thus confirming the
moderating character of job satisfaction of service employees
and consequently H4. Note that these factors were the ones
which showed direct effects on overall customer satisfaction,
which suggests that in the two groups, service value contributesdifferent explanations for overall customer satisfaction. A
regression analysis with mediation was then considered for
both groups. Table 8 shows the last regression model for the two
mediation assumptions, and it can be seen that for the group
with low job satisfaction, service value completely mediates the
effect of interactions on overall satisfaction while in the
situation of high job satisfaction there are direct effects on
factors 2 and 4 in global satisfaction. This second sequence is
identical to the behavior observed overall.
The global statistics for each of the groups (Table 9) in the
variables in scales SE and SV, show that banks with more
satisfied contact employees perceive slightly higher levels of
service value in all the indicators, with higher perceptions of
Table 9
Analysis of average differences in the groups
JS
high
JS
low
I1. Waiting time before the switchboard takes your call 4.34 4.36
I2. Waiting time before being able to speak to the appropriate
person
4.14 4.30
IG1. Overall evaluation of the telephone service 4.40 4.52
I3. Service provided during preparation of the signing 4.36 4.17
I4. Preparation and technical training of the staff 4.53 4.29
I5. Pre-authorization or legal report with analysis of register
viability
4.33 4.15
I6. Mistakes or errors in preparing the signing 4. 39 4.31
I7. Information provided before the signing 4. 28 4.23
I8. Speed of attending to any last minute change or
modification
4.37 4.30
IG2. Overall evaluation of in-company service 4.24 4.17
I9. Information provided during processing the deeds 4.23 4.15
I10. Information provided in the operations processed 4.20 4.18
I11. Time used in the processing phase 3.96 3.86
I12. Response to any event 4.38 4.36
IG3.Overall evaluation of behavior in the processing phase 4.23 4.19I13. Accuracy in the documents we deliver 4.37 4.45
I14. Form of delivering documentation (packaging, order, etc.) 4.41 4.45
I15. Method of delivering documentation 4.28 4.36
I16. Period between the date of dispatch and reception 4.14 4.20
IG4.Overall evaluation of documentation delivery 4.31 4.41
I17. Coverage of funds study 4.10 4.09
I18. Settlement sheet 4.30 4.02
IG5.Overall evaluation of the liquidation phase 4.29 4.08
V1. Reliability 4.62 4.51
V2. Professionalism 4.63 4.57
V3. Shows interest 4.52 4.49
V4. Rapid response 4.47 4.43
V5. State of the art management services 4.29 4.27
V6. Trust 4.64 4.47
V7. Problem solving 4.39 4.26V8. Efficient service provision 4.39 4.32
V9. Efficient staff 4.57 4.52
V10. Quality/price relation 3.95 3.69
Significance less than or equal to 0.05.
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service value and in general more positive perceptions with
regard to the interactions in the episode.
A t test on the averages for the technical and functional
characteristics which describe each service stage shows that the
service provided during the preparation of the signing, the
report and the preparation and training for staff providing the
service to the bank are significantly different in the two groups,with a lower value in the group of employees with a lower level
of job satisfaction.
Thus, we can state that job satisfaction of service employees
moderates the effect perceptions on the interactions in an episode
have on service value, such that in situations of low job satisfaction
the effect of the predictors process of registering/processing and
settlement of deposit on the service value intensifies, with service
value acting here as interveningvariable. While in situations of high
job satisfaction of service employees the interactions occurring in
the relation episode affect overall customer satisfaction thus
generating proof that high employee job satisfaction permits
encounters with the bank that contribute to explaining satisfaction.
5. Conclusions and future lines of research
For more than two decades, scientific research has dealt with
the issues analyzed in this work the service encounter,
service value, customer satisfaction and job satisfaction of
service employees and some of the relations between them,
occasionally in the scenario of B2B relations, with fruitful but
not conclusive results (Yeung et al., 2002). We consider that this
is therefore an opportunity to develop research which will help
to further this line of study and at the same time respond to
Parasuraman's (1998) call for research.
In fact, as pointed out in the introduction to this paper, theliterature in general has shown a predominant focus on consumer
services rather thanbusiness services, but fundamental differences
between B2B and B2C marketing invite for specific research in
this area. Moreover, changes in the economy, with the growing
importance of both business related services and professional
services gives rise to specifically developing research in this area.
From a conceptual point of view, the contributions of this
study relate to the definition conceptualization and oper-
ationalization of the constructs analyzed and empirical
analysis of the relation between all the proposed concepts.
We consider that the definition and operationalization of
perceived value is of particular interest. The literature review hasestablished the basic proposition that value can be defined on the
basis of quality, incorporating another type of benefits and
sacrifices. Furthermore, in the sphere of inter-organizational
relations, the origin of the evaluations of this perceived value are
to be found in the interactions between the service provider and
the customer in each episode of the relation. The development of
a measurement scale for this construct adapted to the context
under study (Eriksson & Lofmark Vaghult, 2000) and, in this
case, a B2B relation may be an interesting contribution.
In the sphere of the relation between the concepts of value,
customer satisfaction and job satisfaction of service employees
throughout the service encounter, verification of the hypotheses
has led to several conclusions.
Considering the service encounter as a dyadic provider
customer interaction has provided a suitable framework for
analyzing the contributions of perceptions from both collectives
to service evaluation. Thus in the sphere of intermediation
services for a mortgage, the stages in the service encounter have
been defined and service value proved to be a variable which
partially mediates the effect of the interactions in each episodeon overall customer satisfaction. Perceptions concerning the
encounter cascade generate direct, mediated effects through
service value, on institutional customer satisfaction. Thus, the
evaluation process originates in the interactions which take place
in the relation episode and this suggests that this process can be
better understood by including service value as a mediating
variable in these perceptions and customer satisfaction.
Furthermore, considering the encounter as dyadic underlines
the determining role of the employee in service provision. The
literature suggested the mirror of satisfaction concept to
describe the relation between job satisfaction of service employ-
ees and customer satisfaction, establishing that satisfied employ-ees perform their work better and contribute to increasing
customer satisfaction levels. Thus the employee has a decisive
role in service provision. If employees are part of a solid service
culture and receive management support for delivering improved
service to the client, this more positive experience may lead to
increased job satisfaction of service employees and thus influence
customer perceptions. Our hypotheses proposed analyzing
whether employee job satisfaction moderated the existingrelation
between the perceptions which occur in the relation episode and
service value. Empirical evidence found in the literature sug-
gested that this relation is very weak and the results were not very
conclusive and even the reverse and therefore analysis of the
proposed relations was a research opportunity.
The empirical results indicate that the level of employee job
satisfaction for those in charge of monitoring the service being
studied appears to moderate the relation between customer per-
ceptions in episode interactions and service value. We can
thereforesuggest that a way of addingservice value and increasing
customer satisfaction is through employee job satisfaction.
Finally, despite the fact that the objectives considered have
been verified, this work presents a series of limitations which
open lines for future research. Firstly, the use of just one
company for the research invites a repeat study in other
companies in the sector and in other service contexts in order
to confirm or reject the relations found here. Replica studies arenecessary to validate the scales used with larger, random
samples. The non-randomness of the process for selecting the
units for research and their limited size, generate reservations on
generalizing the results. Secondly, cross-cultural approaches to
the constructs analyzed would be interesting to check for
differences in conceptualization and operationalization. Thirdly,
the line of research opened provides the opportunity to observe
how the constructs under investigation evolve with time. It may
well be relevant to use longitudinal approaches for a better
understanding of the dynamic behavior of the variables
analyzed. Fourth, future research needs to be done on the links
between variables analyzed and the expected relationships
which turned out to be weaker.
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One important element for further research would be related to
theimportance of emotion andof the affective side in perceptionsof
relationships among providers and customers in industrial settings,
as previously analyzed in bank customers by Barnes (1997).
All these aspects underline the importance of front-line
employees in the creation of value and satisfaction for customers
as also proved in industrial settings, and, therefore, the criticalnature of human resources management for companies, not only
in consumer settings, but also in industrial spheres.
Finally we should emphasize the need to try out new
analytical methods to enrich and confirm the present results,
both with regard to measurement capacity and the relations
identified among them all. The problem of measurement in
marketing has been approached with two main types of indexes
(Diamantopoulos & Winklhofer, 2001): reflective and forma-
tive. This study was developed based on formative indexes
which, because they are aggregates of simple items means there
are no measurement errors and they can be incorporated directly
into explanatory techniques such as the regression model. Theycannot, however, recognize the existence of latent factors. A
future line of research would therefore be to study alternative
methodologies in-depth which make it possible to unite the
capacities of both types of index such as for example specific
developments of LISREL to incorporate formative indexes with
latent variables. These developments, based on MIMIC models
are very interesting and are a line of research to be followed. The
problem with them and the reason why they were difficult to
apply in this study is that a large sample size is needed to provide
a robust approach to the multiple relations which emerge.
Appendix A. Measurement scales in the model
SE. Service encounter
Customer perceptions of technical and functional characteristics of the service
provided by the provider organization, reflecting the service encounter
cascade or interactions in a relation episode
I1. Waiting time before the switchboard takes your call
I2. Waiting time before being able to speak to the appropriate person
I3. Service provided during preparation of the signing
I4. Preparation and technical training of the staff
I5. Pre-authorization or legal report with analysis of register viability
I6. Mistakes or errors in preparing the signing
I7. Information provided before the signing
I8. Speed of attending to any last minute change or modification
I9. Information provided during processing the deedsI10. Information provided in the operations processed
I11. Time used in the processing phase
I12. Response to any event
I13. Accuracy in the documents delivered
I14. Form of delivering documentation (packaging, order, etc.)
I15. Method of delivering documentation
I16. Period between the date of dispatch and reception
I17. Coverage of funds study
I18. Settlement sheet
SV. Service value
The advantages perceived in exchange for the charges borne (Berry and Yadav,
1997: 29)
Judgments or evaluations of what the customer perceives he has received from
the seller in a specific purchase or use situation (Flint et al., 2002: 103)
V1. The service provider is reliable
V2. The service provider is professional
V3. The service provider shows interest
V4. The service provider responds quickly
V5. The service provider has state of the art equipment and infrastructures and
equipment in management services
V6. I trust the service provider
V7. The service provider solves problems for me
V8. Efficiency of the service provided
V9. The service provider's staff are efficient
V10. Quality/price relation of the service they provide
CS. Overall client satisfaction/IGi. Satisfaction by stages of service delivery
This is a global evaluation based on total consumption experience ( Anderson
et al. 1994: 54; Fornell, 1992: 11).
A global measurement of a set of satisfactions with specific previous
experiences (Yu & Dean, 2001: 235)
CS. Overall client satisfaction
IG1. Telephone service
IG2. In company service
IG3. Behavior in the processing phase
IG4. Documentation delivery
IG5. The liquidation phase
JS. Job satisfaction of service employees
Positive, pleasurable emotional state resulting from the evaluation of one's own
work or of one's employment experiences (Locke, 1969)
S20/23 (Meli & Peir, 1989)
S1. The job itself (in general).
S2. The opportunity your job offers to do the things you do well
S3. The salary you receive
S4. The objectives. goals you must reach
S5. The training opportunities offered by the company
S6. Personal relations with your superiors
S7. Supervision of your work
S8. The proximity and frequency of that supervision
S9. The chance to do things you enjoy in your job
S10. The way your supervisors (or superiors) judge your work
S11. Equality and Fairness in the way you are treated by the company
S12. Physical environment and the space you have in your workplace
S13. The support you receive from your superiors
S14. The capacity for autonomous decisions on aspects of your job
S15. Participation in the decisions made by your department or section
S16. Lighting in your workplace
S17. Participation in working group decisions concerning the company
S18. Ventilation in your workplace
S19. Opportunities for Promotion
S20. The extent to which the company complies with the collective agreement.
labor law and regulations
S21. The temperature in the workplace
S22. How negotiation on employment aspects is carried out in the company
S23. Cleanliness and hygiene in the workplace.
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