Omar, Muhamad & Musa—Program Perceived Value and Program Satisfaction Influences on Store Loyalty
Gadjah Mada International Journal of Business
September-December 2007, Vol. 9, No. 3, pp. 355–378

PROGRAM PERCEIVED VALUE AND
PROGRAM SATISFACTION INFLUENCES ON
STORE LOYALTY
Insights from Retail Loyalty Progam
Nor Asiah Omar
Rosidah Musa
Muhamad Azrin Nazri
Investigations to determine whether program perceived value
could influence program satisfaction, program card loyalty and
store loyalty are critical to elucidate the roles and significance of the
constructs and advancing management practice. Accordingly, in
line with this research direction, this study aims to assess the effects
of program perceived value offered by few leading retail superstores
and departmental stores in Malaysia on its members’ loyalty towards
the store. The data set utilized in this study has been obtained via
quota sampling technique, where a sample of 153 retail loyalty
programs’ members was analyzed. An integrative conceptual model
was developed and tested using Structural Equation Modeling using
AMOS program. The results exemplify that program perceived value
is a strong driver of program satisfaction and program card loyalty.
Unexpectedly, program perceived value is not a significant predictor
of store loyalty but, it has an indirect effect on store loyalty mediated
by program satisfaction.
Continuous plea in marketing management is to make marketing instruments more efficient. In recent years introduction of
customer relationship marketing instruments is strongly advocated,
both in marketing theory and practice. Several researchers (e.g.,
Berry 1983; Berry and Parasuraman 1991; and Gronroos, 1994)
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have changed the focus of a marketing orientation from attracting
short-term, discrete transactional customers to retaining long-lasting, intimate customer relationships. In fact Roberts, Varki, Brodie
(2003), further suggested that it is best to describe relationship
marketing as the formation of “bonds” between the company and the
customer. Achieving an effective relationship in a consumer context
is considered to be even more challenging than it is in a business-tobusiness context, given the generally more polygamous character of
consumers as opposed to business customers (Keng and Ehrenberger
1984; Pressey and Matthews 1998).
Keywords: behavioral loyalty; perceived value; retail loyalty program; relationship marketing; satisfaction

Introduction
In late eighties and throughout
most of the nineties, relationship marketing became a focal point in much of
the business-to-business (Dwyer et al.
1987; Morgan and Hunt 1994) and
services (Berry 1995) literature. In
comparison with manufacturers, retailers have an advantage in establishing enduring relationships with consumers because they are in a better
position to detect consumer purchase
patterns and apply this knowledge in a
cost-efficient way (Sweeney et al.
1999). Moreover, collecting information from the consumer’s side of the
retailer-consumer relationship is considered an important future research
avenue (Sheth and Parvatiyar 1995).
Hence, in the past decade there has
been many firms (re)adopt a customer
focus –often through a formal program
of Customer Relationship Management
(CRM) (Brown 2000; Peppers and
Rogers 1997). The recent advances in
information technology have provided
356

the tools for marketing managers to
create a new generation of CRM tactics.
Accordingly, Bhattacharya (1998)
postulates that:
“In the current era of intense competition and demanding customers, many marketing relationship
strategies have been developed and
adopted, one such tactic that
tthousands of firms have considered, and which many have
adopted, is to establish a customer
loyalty card program.”
In fact, Liebermann (1999) assert
that loyalty programs are likely to prove
an effective tool within the relationship marketing framework. Accordingly, loyalty programs are defined as
the business process of identifying,
maintaining, and increasing the yield
from best customers through interactive, value-added relationships
(Capizzi, Ferguson and Cuthbertson
2004; Omar et al. 2007). Besides that,
loyalty programs are used as a means

Omar, Muhamad & Musa—Program Perceived Value and Program Satisfaction Influences on Store Loyalty

to communicate to the customers and
the company or/and a means to establish reciprocity between the customer
and the company (Kumar and Shah
2004). That is, reward from a loyalty
program may generate a feeling of
obligatory response from the customer
in the form of more business which in
turn may lead to more rewards offered
from the company and so on. Few
researchers noted that loyalty program
has become an important strategy and
mechanism for retailers to increase
revenue growth and has become a key
component of customer relationship
management (CRM), serving a critical
role in developing relationships, stimulating product and service usage, and
retaining customers (Kivetz and
Simonson 2003). Indeed, the program
has become a concentrated effort by
retailer to build store traffic, increase
basket size and increase frequency
which creating deeper relationship ties
with its customer base (Allaway et al.
2003).
Generally, the importance of loyalty programs has been recognized in
both the managerial and economic
modeling literature (e.g., Kim, Shi and
Srinivasm 2001). According to Fowler
(2004), more than half the U.S. (adult)
population currently participates in at
least one loyalty program. While, in
U.K around 80 percent of U.K. household participate in at least one customer loyalty program. According to
Bellizi and Bristol (2004) the use of
loyalty programs grew exponentially
in the U.S., U.K. and all around the

world. According to Reinartz and
Kumar (2002), during the year 2000
the top 16 retailers in Europe together
spent about $1 billion on retention/
loyalty initiatives and some supermarket chains even devote a yearly budget
of more than $150 million to its loyalty
programs. It is clear that the phenomenon is not restricted to the U.K., as
loyalty programs have been established
across Europe and in other parts of the
developing countries. Despite the popularity of these programs, little is known
about the underlying factors driving
consumer behavior relevant to these
kinds of relationship programs.
Liebermann (1999) and Palmer at al.
(2000) studies raise up conflicting evidence concerning the relationship between loyalty program and loyalty.
Bellizzi and Bristol (2004) examine
the role of loyalty program in creating
loyalty find that loyalty program is not
associated with loyalty. In addition,
findings revealed that 79 percent of
customers in casual apparel and 70
percent in grocery say they are always
seeking alternatives to their current
retailers (The McKinsey Quarterly,
2001). Gaughan (2006) further describe
that a blended approach of hard (reward) and soft (recognition) benefits is
the optimal way to improve retail loyalty program revenue and to reduce
customer attrition. As a result of this
worldwide glut of loyalty programs,
consumers are becoming more alert
than ever, and seek not those programs
that offer only a me-too approach to
loyalty, but rather those programs that

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bolster their overall value proposition
with a sophisticated and differentiated
rewards programs.
Based on Capizzi and Ferguson
(2006) and Noordhoff et al. (2004)
loyalty membership market is in its
maturity stage particularly in Europe
and U.S.A. Meaning, consumer is in
danger of entering prolonged phase of
boredom with loyalty programs. In
fact, this is one argument against the
effectiveness of loyalty programs in
the European market (Noordhoff et al.
2004). With static retail markets in the
USA and Europe, retailers have targeted Asia where markets are growing
twice as fast as at home (Strategic
Direction 2005). Accordingly,
Noordhoff et al. (2004) pointed that,
one advantage in the Asian market is
that customers have not had the opportunity to acquire loyalty program fatigue. Moreover, the Asian economic
crisis in the late 1990s have turned
Asians to be “bargain hunters” who
prone to be loyal to retailers offering
value for money, particularly in the
form of discounts, points and vouchers.
Accordingly, research done by
consulting firm Frost and Sullivan revealed that the loyalty program business in Malaysia is currently worth
RM2.4 billion, and is projected to grow
to RM3.5 billion by 2010 (Ganesan,
2006). Jaya Jusco (Aeon) in Malaysia
who stands at the forefront of customer
loyalty strategies in the retail sector
with flagship J-Card loyalty program
currently has nearly 580,000 program
members account for an average of 54358

58 percent of their monthly sales (Colloquy 2004). Over the years, the landscape of loyalty programs in Malaysia
has changed. It has moved from the use
of one program by one outlet to one
used by many outlets and now a multifunction program.
Because of the pervasiveness of
these types of programs, it is vital to
investigate the impact of program perceived value towards program satisfaction and finally its influence towards loyalty. The results of the study
will reveal the mechanism by which
the loyalty program operates such as
whether loyalty program induce loyalty to the program rather than loyalty
to the store. In addition, it will also
address the issues of whether loyalty to
the program leads to loyalty to the
store.
Generally, the result from this
study will have practical impact to
managers, since loyalty programs have
emerged as a popular marketing strategy for thousands of firms, including
many of the world’s biggest and best
known firms. The results derived from
this paper could offer many potential
implications for the retailers that offer
loyalty program to its customers. In
brief, the research findings could assist
the industry managers in formulating
effective strategies specifically in its
loyalty programs and consequently
better utilize these customers for additional marketing support and information resources that help firms to enhance their marketing performance.
The research framework which
identifies a six-stage path analytic

Omar, Muhamad & Musa—Program Perceived Value and Program Satisfaction Influences on Store Loyalty

Figure 1. Proposed Conceptual Model with Hypothesised Paths
Program Satisfaction


H5
H1

Store Loyalty


H3





H4

Program Perceived
Value
H2

H6
 

Program Card Loyalty

model delineating the factors involved
in a sequential model. The study explores the linkages between program
perceived value, program satisfaction,
program card loyalty and store loyalty
among loyalty program’s members in
a superstores and departmental stores.
Figure 1 depicts the integrative research framework among the constructs
in a path diagram format. The framework comprises of program perceived
value, program satisfaction, program
card loyalty and store loyalty. This
paper is organized as follows: Section
1 provides the introduction to this research, Section 2 discusses literature
review, Section 3 shows research design and method, Section 4 documents
research findings and discussion, and
eventually, Section 5 provides the limitations, future research and the conclusion.

Literature Review
Customer relationship marketing
is essential for success in today’s and
tomorrow’s retailing. This is particularly revealed in the huge investment
in customer relationship Winer 2001).
Achieving an effective relationship in
a consumer context is considered to be
more challenging than it is in a business-to-business context, given the
generally more polygamous character
of consumers as opposed to business
customers (Pressey and Matthews
1998). Today, the usage of loyalty
programs as a technique for firms to
enhance customer loyalty is seem to be
everywhere and become extremely
popular among both consumers and
firms (Luxton 1998).

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Howard-Brown (1998) found that
31 percent of consumers stated that
loyalty and store cards exerted an influence on them. Study by Cigliano et
al. (2000) indicated that 53 percent of
grocery customers and 21 percent of
customers of casual apparel retailers
are enrolled in loyalty programs, of
which 48 percent and 18 percent of the
grocery and apparel customers claimed
to spend more than they would otherwise. Another survey also found that
nearly half (49 percent) of the
program’s members pointed out that
the programs have influenced on where
they decide to spend their retail dollars, with the majority also indicating
that they are faithful to the loyalty
programs they choose to join.
On the other hand, Mauri (2003)
and Yi and Jeon (2003) find that not all
subscribes to a loyalty program are in
fact card loyal. Result from the study
indicated that some of the members
use more than one loyalty program;
other do not use the program; and most
customers seem not to know the mechanics of the reward schemes of loyalty programs (Sharp and Sharp, 1997).
Accordingly, Wright and Sparks (1999)
indicated 23 percent of the programs
studies by them were not used, 13
percent of the programs were not in
used in last 3 months of the period
taken into consideration and customers tended not to use the program when
they paid cash for small amounts of
goods/services. Being aware of the ‘laziness’ of customers, retailers often
reward their customers for continuous
usage of the program. These rewards
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often take the form of promotional or
incentives tied to specific desired behaviors. For example, customers who
want to receive the rewards may have
to use the program, but also have to
follow the retailer’s suggestions such
as spending a certain amount, buying
specific product types, choosing certain brands, visiting the store with a
certain frequency or sometimes at specific hours of specific days. The higher
is the cardholder’s conform to the
retailer’s demands the higher rewards
the customer will receive in return.
Due to the mix results researchers have questioned whether loyalty
programs are indeed a manifestation
of relationship marketing (Hart et al.
1999). Purist argues that loyalty building ‘techniques’ are nothing but mere
promotional gimmicks and that loyalty is only earned by consistent deliver superior value at every point of
contact with customers.
Sheth and Parvatiya (1995) have
noted that, marketers are constantly
challenged to increase the value of
their product/service by improving the
product/service benefits, reducing costs
through productivity or both. Superior
value of product/service represents a
significant competitive advantage for
the firm in building profits and customer satisfaction (Ulaga and Chacour
2001). Similarly, Mauri (2003) claimed
that consumers who decide to be loyal
cardholders are firstly intrigued by the
absolute value of the rewards targeted
at them. Interestingly, Lind and Tyler
(1988) indicated that loyalty programs
can increase the intrinsic motivation of

Omar, Muhamad & Musa—Program Perceived Value and Program Satisfaction Influences on Store Loyalty

participants thus deemphasizing the
need for rewards by providing identity-related ‘soft’ benefits such as ranking and congratulating top members,
fostering a sense of community, and
treating members as unique, valuable
individuals. Many authors have advocated that knowing where value resides from the standpoint of the customer has become critical for managers, because greater level of customer
satisfaction lead to greater levels of
customer loyalty and retention, positive word-of-mouth, a stronger competitive position, and ultimately, higher
market share (Fornell 1992; Bearden
and Teel 1983).

Program Perceived Value
Perceived value is a trade-off between the benefits customers receive
in relation to total cost which include
the price paid plus other costs associated with the purchase (McDougall
and Levesque 2000). In the context of
this study, program perceived value is
conceptualized as the customer’s overall assessment of the loyalty programs
towards all the relevant benefits and
reward incurred by the program’s members. Prevalently, perceived value has
been positioned as the pivotal role
within the exchange concept of marketing (Eggert and Ulaga 2002). Research reveals that customers are less
likely to switch if they better understand the actual economics, time, and
energy-saving value of staying in a
relationship (Gwinner et al. 1998). In
fact Harnett (1998) advocated that,

“when retailers satisfy peoplebased needs, they are delivering
value which puts them in a much
stronger position in the long-term.”
O’Malley and Tynan (2000) document that, if the consumers do not
perceive value in building relationships with a firm, then they might only
engage in a relationship to the extent
that a better option is not available
elsewhere. Similarly, Dowling and
Uncles (1997) claimed that:
“…..loyalty programs must enhance the overall value of the product or service and motivate loyal
buyers to make their next purchase.”
In order to make a loyalty program effective it must have a structure
that motivates customer to view purchases as a sequence of related decisions rather than as independent transactions (Lewis 2004). The structure of
the program must be able to give customers an incentive to adopt a dynamic
perspective. For example, O’Brien and
Jones (1995) suggest that the major
factors that customer consider when
evaluating programs are the relative
value of awards and the likelihood of
achieving a reward. In addition, the
likelihood of achieving a reward is a
function of cumulative buying threshold and time constraints. Hence, the
design elements (e.g. rewards, time
constraints) combine with individuallevel requirements and preferences will
influence the customer’s expected benefits of participating in a loyalty program.

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As emphasized by Sirdeshmukh
et al. (2002) value a superordinate consumer goal, regulates consumer actions at the level of loyalty intention.
Consumers are expected to direct their
actions towards achievement of this
goal; they will indicate loyalty intentions toward a products or service that
can deliver superior value. Similarly,
Bolton and Drew (1991) that value is
an important determinant of consumers’ loyalty intention toward telephone
services. Moreover, perceived value
plays an important role in the determination of store loyalty; it will increase
consumers likelihood of recommending the supplier and reduce the tendency of seeking alternative information (Sirohi et al. 1998). Accordingly,
the first, the second and third hypotheses of this study are as follows:
H 1: In the retail loyalty program context, a higher level of program
perceived value leads to a higher
level of program satisfaction.
H 2: In the retail loyalty program context, a higher level of program
perceived value leads to a higher
level of program card loyalty.
H 3: In the retail loyalty program context, a higher level of program
perceived value leads to a higher
level of store loyalty.

Program Satisfaction
Lervik and Johnson (2003), and
Rust et al. (1995) define customer satisfaction as a cumulative evaluation of
a customer’s purchase and consump-

362

tion experience to date. The definitions imply customer satisfaction as an
overall evaluation based on the total
experience with a good or service over
time. Therefore, in the current study,
the authors specifically established that
the consumer experience with the retail loyalty program must occur at least
within twelve months prior to data
collection. Accordingly, program satisfaction is defined as: program
member’s affective state as a result of
cumulative evaluation of experience
with the loyalty program.
Mcllroy and Barnett (2000) express that, an important concept to
consider when developing a customer
loyalty program is customer satisfaction. Satisfaction is a measure of how
a customer’s expectations are met while
customer loyalty is a measure of how
likely a customer is to repurchase and
engage in relationship activities. Several prior researchers (e.g., Bolton
1998) find a connection between satisfaction and loyalty. The relevance of
satisfaction in gaining loyal customers
and generating positive word-of-mouth
is largely undisputed (e.g., Anderson
and Sullivan 1993; Oliver 1996). Indeed, few researchers identified that
satisfaction is one of the factor in determining loyalty (e.g., Anderson,
Fornell and Lehmann 1994). In addition, satisfaction has been recognized
as a main driver in determining positive word-of -mouth behavior (e.g.,
File et al. 1994). Hence, based on past
literature the fourth and fifth hypotheses of this study are as follows:

Omar, Muhamad & Musa—Program Perceived Value and Program Satisfaction Influences on Store Loyalty

H 4: In the retail loyalty program context, a higher level of program
satisfaction leads to a higher level
of program card loyalty.
H 5: In the retail loyalty program context, a higher level of program
satisfaction leads to a higher level
of store loyalty.

Loyalty
Sharp and Sharp (1997) explicitly
stated that the effectiveness of relationship marketing efforts should be
evaluated in terms of behavioral
changes they bring about. As a result,
few researchers (e.g., Hennig et al.
1997; and Reichheld 1994) accepted
behavioral loyalty as the ultimate relationship outcome.
Some writers, such as Bloemer
and Oderkerken-Schroder (2002), and
Shoemaker and Lewis (1999) describe
loyal behavior as customers who feel
so strongly that you (the company) can
best meet his or her relevant needs that
your (the company’s) competition is
virtually excluded from the consideration set; these customers buy almost
exclusively from you (the company).
Accordingly, the current study defines
program card loyalty as: a cardholder’s
drive to continue and maintain a relationship with a retail loyalty program
accompanied by the cardholder’s willingness to make additional efforts.
While, store loyalty is conceptualized
as, a high commitment to rebuy or
repatronize a preference product or
service consistently in the future, despite situational influences and mar-

keting efforts which have the potential
to cause switching behavior.
Bolton et al. (2000) documents
that the goals of a loyalty program is to
achieve a higher level of customer
retention particularly in profitable segments by providing increased satisfaction and value to certain customers.
For example, many supermarket loyalty programs have focused towards
heavy users; the justification for these
programs is to increase customer satisfaction and loyalty which in turn will
have a positive influence on long-term
financial performance (Anderson et al.
1994; Reichheld and Sasser 1990).
It has been widely documented
that, the store which offered loyalty
program to their customers is likely to
eenjoy benefits of store loyalty and/or
brand loyalty (Lieberman 1999;
Noordhoff et al. 2004; Ji and Jeon
2001). A valuable relationship is seen
as a ‘barrier to entry’ mechanism which
provides a powerful competitive advantage for a company. Sharp and
Sharp (1997) find that have a greater
effect on the average purchase frequency than on share-of-customer
(Sharp and Sharp 1997). Hence, based
on the level of customer participation,
most loyalty programs are arranged to
ensure that the highest spending members will receive the greatest rewards.
As the most prevailing relationship link is between loyalty program
membership and loyalty, it is essential
to highlight the mechanism by which
the retail loyalty program operates specifically the mechanism between program card loyalty and store loyalty. It
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Gadjah Mada International Journal of Business, September - December 2007, Vol. 9, No. 3

is noteworthy to highlight the recent
findings by Mauri (2003) in which she
discover that the more customers visit
a store, the higher the customers will
be loyal towards the program. It is
believed that members bonding with
the program have a concrete potential
of enhancing members’ patronage with
the store. Therefore, it is anticipated
that consumers who are loyal towards
a loyalty program will display high
loyalty towards the store. Inspired by
these ideas and findings, the author
investigates the hypotheses:
H 6:In the retail loyalty program context, a higher level of program
card loyalty leads to a higher level
of store loyalty.

Review of Methodology
Research Design
A survey was carried out in the
Klang Valley of Malaysia, which was
reported to have the highest number of
modern retail stores such as supermarkets and hypermarkets (Euromonitor
2004). Moreover, it is also noted that
loyalty programs are still in its early
days in Southeast Asia with plenty of
room for expansion (AcNielsen 2005).
The data for this study were collected
by using self-administered questionnaires distributed using quota sampling technique by undergraduate marketing students as a part of their “subject pool” requirement. The guidelines
for respondent’s eligibility were clearly
provided to insure a varied sample and
to exclude participation that was not
364

eligible (Mick 1996). The population
of interest for this study was defined as
consumers (over 16 years of age) who
a member of any retail loyalty program
(superstores and departmental stores)
within the last twelve months prior to
data collection (June 2006-August
2006) and who live or work within
Klang Valley, Malaysia. The survey
instrument used a comprehensive set
of 17 questions that were directly tied
to the four constructs of the study. The
interval scale was anchored using a
Likert type measurement approach.
Five response categories with properties labeling established only for the
scale end points from (1) which denotes “strongly disagree,” and (5) for
“strongly agree.” This scale approach
was favored in order to maintain the
scale interval-level properties (Allen
and Rao, 2000). Before conducting the
study, the author pre-tested the survey
instrument by personally administering it to 10 lecturers to verify the suitability of the terminology used as well
as the clarity of the instructions and
scales.
Generally, the students were divided into 5 groups and each group
was instructed to have more adults to
complete the survey. In order to obtain
richer insights, the respondents need to
join the program for at least a year.
This length of membership time was
reported to be sufficient to regard respondents as quite experienced, a factor that contributes to the validation of
the data (Liebermann 1999). This data
collection technique has resulted in
165 respondents, but only 153 were

Omar, Muhamad & Musa—Program Perceived Value and Program Satisfaction Influences on Store Loyalty

valid to be used. The ratio of man to
womaen in the sample was set at 1:3,
based on few studies conducted in Malaysia and many other countries that
suggested that women make up a significantly larger percentage of purchasers (Harmon and Hill 2003) compared to men. Amongst the 153 usable
questionnaires, 68 (44.4%) represented
cardholders who owned at least 2 loyalty programs and 50 (33%) represented cardholders with one loyalty
program. In term of program membership, majority of the cardholders owned
their card membership for 2 years and
more. This majority represented 97
cardholders (63%). All variables in
this study were measured by multiitem scales, and operationalized based
on previous research, such as Bolton
and Drew (1991), Feng (2004), Crosby
and Stephens (1987), Musa (2004), Yi
and Jeon (2003), and Zeithaml et al.
(1996).

Data Analysis Methods
The measures utilized in this study
initially were purified via item-to-total
correlation and exploratory factor
analyses with varimax rotation. Item
which loads 0.50 or greater on one
factor and did not have cross-loadings
greater than 0.30 on other factors were
accepted for further analysis (Rentz et
al. 2002). Moreover, parameter estimates of item factor loading and communalities were consulted to identify
ways that each sub-scale might improve from an empirical perspective.
According to Byrne (2001) to be a

good measure of an underlying construct, an item needs to have a significant factor loading and a decent communality. Items which exhibited loading and cross loadings of less than 0.5
were deleted. Moreover, small communalities (relative to other items) were
targeted for removal to enhance model
parsimony. However, theoretical concerns related to item content were given
first priority in model modifications.
This initial purification exercise resulted in the deletion of 3 items on the
basis of high cross loadings on multiple factors. To assess the instruments,
all the items were factor analyzed, and
the result revealed that the KaiserMeyer-Olkin Measure of Sampling
Adequacy (KMO) presented an index
of 0.896, which is considered good for
carrying factor analysis. The Bartlett
Test of Spericity, a statistical test to
determine the presence of correlations
among the variables, was also employed in this study, and it was statistical significant. These results indicate
the suitability of the factor analysis
technique for this study. A four-factor
solution was initially extracted with
accounted for 66.09 of the total variance explained. Cronbach’s alpha
which was utilized to test for internal
consistency for all dimensions extracted from exploratory analysis, were
above the minimum acceptable score
of 0.70 (Gerbing and Anderson 1988),
ranged from 0.72 to 0.85 (see Table 1).
This clearly indicates that the scales
used in this study were highly reliable
(Nunnally 1978).

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e1

e2

e3

e4

.47

.72

PV5_1
.75

PV4_1

.59

.56

.85

.69

.41
.77

PV3_1

PV2_1





.77

e 16

.60

Prog Perceived
Value

e 14

.87



.15
.23
.53

e9

.49

e8

Standardized estimates

.67

.48

PL3_1

.72

Store
Loyalty

.51

.78

.61

.60

PL3_1

.70

Prog Card
Value

.11

Prog
Satisfaction

.75

PL2_1

.82



.64

.61
S T 4_1

.77
S T 3_1

.56
S T 2_1



.41 
S T 1_1

e 13









 



e 12







e 11

e7

e 15

.70

.79

SL4_1

.63
.49

SL3_1





e 10
























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

Figure 2. Structural Model

e6

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Gadjah Mada International Journal of Business, September - December 2007, Vol. 9, No. 3



Omar, Muhamad & Musa—Program Perceived Value and Program Satisfaction Influences on Store Loyalty

The pool of items was further refined using confirmatory factor analysis (via AMOS 6.0 and the maximum
likelihood estimation technique). To
test the Hypothesized links among the
constructs in the framework, Structural Equation Modeling was used and
subsequently analyzes the mediating
effect of program card loyalty in the
satisfaction-store loyalty chain. Table
1 presents the correlation matrix, descriptive statistics, Cronbach’s alpha,
reliability coefficients, composite reliability, square multiple correlation (R2),
AVE for the measures and sources of
items. Figure 2 depicts the structural
model.

Reliability and Validity of
Measures
Reliability and validity test are
important to standardize the measurement scales, and to demonstrate
whether they truly measure what they
are supposed to measure. In Structural
Equation Modeling (SEM), there are
some statistical outputs which can be
used to measure the construct reliability. They include square multiple correlations R2 for each measurement item,
composite reliability, and variance
extracted for each factor. As a rule of
thumb measurement variables are reliable when the square multiple correlation R2 of each one is greater than 0.5
(Byrne 2001). Cronbach alpha coefficient, composite reliability and variance extracted were calculated to measure the reliability of each factor, as
represented in Table 1. Composite reliability should be greater than 0.7 and

variance extracted (AVE) > 0.5 to indicate reliable factors (Hair et al. 1998).
The composite reliability and variance
extracted were calculated using Fornell
and Larker’s (1981) formula. The composite reliability, variance extracted,
and Cronbach alpha coefficient values
for all critical factors, greatly exceeded
the minimum acceptable values. This
indicated that the measures were free
from error and therefore yielded very
consistent results (Zikmund 2003).
Given that the factor structure remained stable, we proceed to perform
a confirmatory factor analysis (CFA)
using AMOS 6.0 to test the 6 hypothesized relationships among the constructs. Accordingly, the assessment
of the model fit in this paper was based
on multiple criteria; the normed X2 or
X2/df ratio, the Root Mean Square Error of Approximation (RMSEA), the
Comparative Fit Index (CFI), TuckerLewis Index (TLI), Normed Fit Index
(NFI), Incremental Fit Index (IFI), and
the Relative Fit Index (RFI) (Hair et al.
1998; Byrne 2001). Table 2 shows the
acceptable fit criteria and the model fit
indices values. All of the statistical
values of the final measurement model
indicated that the model fitted well in
representing the data. Ultimately, results for the hypothesized structural
paths are reported in Table 3. Standardized coefficient is preferable as it
is generally used in multiple regression (de Vaus 2002). Other reasons for
using standard coefficients are the variables are on the same scale on measurement, are more easily interpreted
and can be easily be converted back to
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Gadjah Mada International Journal of Business, September - December 2007, Vol. 9, No. 3

Table 1. Correlation Matrix
Construct

Mean SD

Program
Perceived Value (X1)

3.47

Std
Critical
Composite AVE
Regression Ratio
R 2 Reliability
(Loadings) (t-values)

0.64

1. worth the money
(PV2)

0.69

8.27

2. getting a good deal
(PV3)

0.85

10.22

3. economical (PV4)

0.77

9.28

4. reasonable (PV5)

0.75

—

Program Satisfaction
(X2)

3.46

0.62

1. very satisfied (ST1)

0.64

—

2. right decision (ST2)

0.75

7.72

3. pleased experience
(ST3)

0.88

8.60

4. satisfies my needs
(ST4)

0.78

8.00

Program Card Loyalty
3.39
(X3)
1. like the program (PL 1)

0.65
0.82

8.46

2. strong preference (PL2)

0.70

7.61

3. recommend the
program (PL3)

0.72

—

Store Loyalty (X4)

3.45

0.60

1. recommend the store
(SL3)

0.79

6.37

2. strong store preference
(SL4)

0.70

—

368



Sources of
items of the
Constructs

—

0.90

0.70

0.85 Bolton and
Drew (1991);
Feng (2004)

0.60

0.91

0.72

0.84 Crosby and
Stephens
(1987)

0.53

0.87

0.62

0.79 Yi and Jeon
(2003)

0.48

0.85

0.73

0.72 Zeithamal
et al. (1996)

Omar, Muhamad & Musa—Program Perceived Value and Program Satisfaction Influences on Store Loyalty

Table 2. Goodness of Fit Indices for Model
Goodness of fit indices

Fit Criteria

Model

=3
=0.08
=0.9
=0.9
=0.9
=0.9
=0.9

73.754
59
0.094
1.25
0.041
0.984
0.979
0.926
0.984
0.902

X2
df
p
2
X /df
RMSEA
CFI
TLI
NFI
IFI
RFI

Adapted from Hair et al. (1998) and Byrne (2001)

Table 3. Results of the Hypotheses Tested
Hypothesised Path

Standardized
Coefficient

Critical Ratio
(t-value)

Results

H1 Program Perceived Value
Program Satisfaction

0.772

6.579 ****

Supported

H2 Program Perceived Value
Program Card Loyalty

0.605

3.819 ****

Supported

H3 Program Perceived Value
Store Loyalty

-0.109

-0.563

Not Supported

H4 Program Satisfaction
Program Card Loyalty

0.153

1.062

Not Supported

H5 Program Satisfaction
Store Loyalty

0.614

3.378 ****

H6 Program Card Loyalty
Store Loyalty

0.234

1.526

Supported
Not Supported

Note: **** Significant at p< 0.001 (t>  3.29)

* Significant at p< 0.10 (t>  1.65)

*** Significant at p< 0.01 (t> 2.57)
a
Non-significant

** Significant at p< 0.05 (t> 1.96)

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Gadjah Mada International Journal of Business, September - December 2007, Vol. 9, No. 3

the raw scale metric (Schumacker and
Lomax 2004).

Discussion
It is worthwhile to highlight that
in this study program perceived value
and program satisfaction were incorporated in the model. This allowed the
authors to examine, test and ultimately
generate knowledge on the effects of
these constructs on the formation of
loyalty toward the program and loyalty toward the store. As highlighted in
Table 3, the current study has found
strong empirical support (of the hypothesized path of perceived value and
program satisfaction as well as program satisfaction and store loyalty. In
essence, this findings offer empirical
evidence the cardholders that found
the program valuable are likely to be
satisfied with the program and engaged
in behaviors targeted in enhancing the
relationship such as loyal to the store.
These findings clearly in line with prior
studies (e.g. Ball et al. 2006; Grace and
O’Cass 2005) that revealed, perceived
value is positively related to satisfaction. In fact, recent findings in the
tourism and hospitality research, revealed that satisfaction as a consequence of perceived value (Spiteri and
Dion 2004).
However, it is important to note
that the new linkage which was hypothesized in the present study, program perceived value–store loyalty was
found to be insignificant. This finding
sharply contradicts with the empirical
evidence provided by Lin and Wang

370

(2006) and Harris and Goode (2004)
that perceived value and loyalty are
positively related. It is reasonable to
speculate that the proposed link was
not significant because in the current
study program perceived value was
conceptualized solely from the economic and rational view. Hence, it
would be more fruitful for future research to capture the concept of value
from the multidimensional elements
specifically from the loyalty program
context. Besides that, upon examination of the descriptive findings of respondents’ membership duration, it
was unveiled that the majority of respondents
were
experienced
cardholders. As noted by prior scholars such as Day (2002), that the perceptions of value sometime change
over time largely because of greater
experience with the category or brand.
Therefore, this implies that economic
value is not always an important element for cardholders when evaluating
loyalty towards the program, particularly, for experienced cardholders.
Hence, more research is needed to capture the influence of membership duration towards the evaluation of program perceived value.
Besides that, it is also important to
note that in this study two relationship
outcomes, ‘program card loyalty’ and
‘store loyalty’ were introduced and
examined in the loyalty program context as suggested by few researchers
(see Magi 2003; Yi and Jeon 2003).
This allowed the authors to examine,
test and ultimately generate knowl-

Omar, Muhamad & Musa—Program Perceived Value and Program Satisfaction Influences on Store Loyalty

edge on the formation of store loyalty
among program members. Interestingly, the research findings demonstrate that program satisfaction is the
strongest driver of store loyalty (see
Table 3). Apparently, the research results indicate that program perceived
value and program card loyalty are not
significantly related to store loyalty.
Thus, the results elucidate that program satisfaction is the sole determinant of store loyalty.
Clearly, this finding lends support
to the notion that loyalty program that
is valuable can consistently produce
positive outcomes to cardholder such
as satisfaction towards the program
which indirectly link to store loyalty.
Ignoring perceived value in a loyalty
program experience may cause lowered satisfaction and reduced loyalty.
This is consistent with the views of
several other researchers (Chiu et al.
2005; Gallarza and Saura 2006) that
satisfaction is the behavioral consequence of perceived value, loyalty attitude being the final outcome. Consequently, this implies that program perceived value is not a predictor of store
loyalty however, program satisfaction
help to mediate the link between program perceived value and store loyalty. These findings seem plausible
both in a research and managerial context: managers might assume that the
level of cardholder’s loyalty towards
the store comes from a higher level of
program satisfaction.

Research Limitation and
Future Directions
This study has several limitations
that should be considered in an interpretation of the results. A major criticism of the study concerned external
validity, as the respondents were not
selected randomly, and may not be an
accurate representation of the population of loyalty program members. However, it should be noted that the profiles of the respondents’ (gender and
age) are consistent with the existing
literature (see Harmon and Hill 2003).
On this basis, the results and interpretations may be generalizzeable, specifically with regard to retail loyalty
program context in Malaysia and other
South-East Asian countries. A second
pertinent weakness concerns the crosssectional research design employed.
Certainly, longitudinal research is required to fully capture the dynamic
nature of customer post-consumption
evaluation. Obviously, efforts to test
the present model through sagacious
longitudinal research would require an
enormous amount of sustained cooperation by consumers serving as key
informants over time. Next in the current research, reflective-indicators
measurement model were used for all
the research constructs. To some extent, however, this choice is seem appropriate since the reflective view are
widely utilized in the psychological
and management science, while the

371

Gadjah Mada International Journal of Business, September - December 2007, Vol. 9, No. 3

formative view is common in economics and sociology (Coltman, Devinney,
Midgley and Venaik 2008). However,
future studies may utilize formative
measurement model to investigate how
these different views of flow construct
could lead to different parameter estimates and conclusions of the same
research question with the same data
set.
Another weakness concerns with
the number of limited aspects is included in the study. Hence, it is suggested to include other aspects to be
explored and investigated as well. For
example, it may be fruitful for future
research to assess whether the type of
involvement (high and low involvement) or perception of fairness may
have different impact in the proposed
model. It may be fruitful for future
research to replicate and validate all
parts of the current model, in order to
determine the robustness of the findings. This research direction appears
to be potentially fertile as loyalty program is considered as an important
retention strategy and mechanism for
retailers to increase revenue growth. In
addition, the current model might be

extended usefully in future research
work through the inclusion of the multidimensional elements of value specifically from the loyalty program context.

Conclusion
In conclusion, the findings of this
study enable us to clarify the structural
relationships among core constructs as
postulated in the relationship marketing literature. Importantly, the major
findings of this study enhance the understanding of the interrelationship
among the constructs which were incorporated in the hypothesized model.
It is believed that the new findings
drawn by the current study will be
relevant to the advancement of relationship marketing theory particularly
in the customers’ retention strategy
namely the retail loyalty program. In
essence, this study has advanced the
understanding of the relationship between program perceived value and
relationship outcomes such as store
loyalty among loyalty program members.

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