Subido por razerstriker123

Information & Management Volume 41 issue 6 2004 [doi 10.1016 j.im.2003.08.006] Jyh-Shen Chiou -- The antecedents of consumers’ loyalty toward Internet Service Providers

Anuncio
Information & Management 41 (2004) 685–695
The antecedents of consumers’ loyalty
toward Internet Service Providers
Jyh-Shen Chiou*
Department of International Trade, College of Commerce, National Chengchi University, Mucha, Taipei, Taiwan, ROC
Received 25 June 2002; received in revised form 22 May 2003; accepted 13 August 2003
Available online 14 October 2003
Abstract
Internet popularity is growing at an impressive rate. Sooner or later, every consumer comes face to face with the decision of
choosing an Internet Service Provider (ISP). This study developed and empirically tested a model examining the antecedents of
consumer loyalty toward ISPs. It incorporated the concept of expected technology change into the model to examine its effects
on the formation of ISP loyalty intention. Confirmatory Factor Analysis (CFA) was performed to examine the reliability and
validity of the measurement model, and the structural equation modeling techniques were used to evaluate the casual model.
Based on an internet survey in Taiwan, this study showed that perceived value is very important in generating overall customer
satisfaction and loyalty intention toward an ISP, and that perceived trust of an ISP enhances perceived value, overall satisfaction,
and loyalty intention. However, the study demonstrated that future ISP technology expectancy exerted a negative influence on a
consumer’s overall satisfaction and loyalty intention toward their ISP.
# 2003 Elsevier B.V. All rights reserved.
Keywords: ISP; Trust; Value; Forthcoming technology expectancy; Loyalty
1. Introduction
Internet popularity is growing at an impressive rate
due to the many related services it provides: the ease
with which service can be created, the presence of a
single standard, and the global reach that makes
national boundaries invisible [47]. Sooner or later,
every consumer comes face to face with the decision
of choosing an Internet Service Provider (ISP)—the
companies that sell internet access in various packages.
Greenstein [28] proposed that they provide a good
example for illustrating the importance of technology
mediation in modern society. They provide access,
*
Tel.: þ886-2-2939-3091x81039; fax: þ886-2-2937-9071.
E-mail address: Jschiou@nccu.edu.tw (J.-S. Chiou).
maintain it for a fee, and develop related applications
as they see fit. ISPs customize internet technologies
to the unique needs of consumers and organizations,
solving problems as they arise, and tailoring general
solutions to idiosyncratic circumstances.
Because of this important role, the number of ISPs
maintaining national and regional networks increased
rapidly each year since 1994 in the Unites States and in
almost every part of the world. In the United States and
Canada, there were more than 4482 active ISPs in
2002 [35]. Due to this sudden increase, competition
is increasing, leading some to provide free internet
accesses to attract customers. This kind of competition leads to the demise of many ISPs in the market.
For example, more than 35 free ISPs went out of
business in the United States in the year 2000 [1].
0378-7206/$ – see front matter # 2003 Elsevier B.V. All rights reserved.
doi:10.1016/j.im.2003.08.006
686
J.-S. Chiou / Information & Management 41 (2004) 685–695
to the creation and maintenance of effective customer
retention programs [10], especially for the ISP industry. ISPs have to devise competitive program to retain
their customers. Therefore, it is important to examine
the factors that influence consumer loyalty intentions,
so that struggling companies might design more effective customer retention strategies.
First, we developed and empirically tested a model
for examining the antecedents of consumer loyalty
intentions toward an ISP. Second, we incorporated the
concept of expected forthcoming innovations into
the model and examined the effect on formation of
loyalty intention. If consumers expect a future technology improvement, their expectations will impact
their assessment of existing services [67].
In addition, according to a survey by messaging
consultancy, Outade.com, one third of UK ISPs will
go out of business over the next few years [17].
Therefore, it is important to understand the driving
forces of consumer loyalty, because strong loyalty
can help an ISP survive fierce competition.
Satisfaction has historically been identified as
the major driver for customer brand or company
loyalty, making high customer satisfaction a key goal.
Although this proposition is not totally disregarded by
marketers, it is challenge by several studies claiming
that more than half of the satisfied customers will
defect eventually [39]. Customer satisfaction may be
important, but it cannot explain all the variance of
customer loyalty. It may even become independent of
satisfaction, so that temporary reversals in satisfaction
may not influence long-term loyalty intention.
Since gaining new customers in the competitive
market is becoming difficult and the profit gained
from a loyal customer grows within the duration of
the business relationship, companies are shifting their
marketing focus from pure satisfaction generation to
loyalty cultivation [58]. Companies believe that customer loyalty is the key to long-term profitability, both
in the business-to-business and business-to-consumer
exchange relationship [57]. They are more committed
Future
ISP
Expectancy
2. Conceptual framework and hypotheses
Fig. 1 presents a model of a consumer’s loyalty
formation; attributive service satisfaction, perceived
trust toward the ISP, and future ISP expectancy are
modeled as exogenous variables, while construct
regarding perceived value and overall satisfaction
are modeled as the mediators between exogenous
variables and consumer loyalty intention toward
H9 (-)
H8(-)
H3(+)
Attributive
Service
Satisfaction
H1(+)
Perceived
Value
H2
(+)
Overall
Satisfaction
H5(+)
H4(+)
Perceived
Trust
Fig. 1. Proposed framework.
H6 (+)
H7
(+)
Loyalty
Intention
J.-S. Chiou / Information & Management 41 (2004) 685–695
the ISP. The framework is based on Bagozzi’s [4]
appraisal ! emotional response ! coping framework. In the research model, there are two types of
satisfaction.
The first, attributive service satisfaction, refers to
a customer’s cognitive satisfaction regarding individual attributes and services of the providers [26,40].
Westbrook proposed that attributive service satisfaction is an accumulation of separate satisfactions
with salespeople, store environment, products, and
other factors [70]. ISPs provide different kinds of
services, such as internet access, email accounts, and
technical support. Consumers will form their attributive service satisfaction toward an ISP based on their
cumulative satisfaction with the individual services
they receive.
The second type, overall satisfaction, stems from a
customer’s perception of the transaction experience
as a whole [53]. Overall satisfaction is defined as
‘‘pleasurable fulfillment’’ and an affective response
in Oliver’s loyalty framework [50]. Therefore, overall
satisfaction of an ISP is defined as an affective
construct, whereas attributive service satisfaction is
defined as a cognitive construct.
2.1. Attributive satisfaction, perceived value,
overall satisfaction and loyalty intention
As defined by Zeithaml et al. [71], perceived value
is a consumers’ overall assessment of the utility of a
product or service based on perceptions of what is
received and what is given. It is the trade-off between
received benefit and cost. Based on the means-end
chain, value is assumed to be a higher-level abstraction. It is more personal and individualistic than
attributive service satisfaction. Similar to the studies
regarding the positive effect of service quality on
perceived value [62,68], favorable attributive service
satisfaction of an ISP can enhance a consumer’s
perception of what is received. In other words, customers who received better ISP services will have
more positive perception towards it. These positive
perceptions in turn improve the perceived value
toward the ISP. Thus:
H1. Attributive satisfaction with an ISP’s service
will positively affect a consumers’ perceived value
of the ISP.
687
Past research has shown that perceived value is an
important antecedent for overall satisfaction and
future purchase intention. For example, in efforts to
conceptualize the effects of quality, satisfaction, and
value on consumer behavioral intentions, Cronin et al.
[18] found that perceived value had direct and positive
impacts on overall satisfaction and behavioral intention. Similarly, Patterson and Spreng [52] found that
perceived value directly affects overall satisfaction.
As emphasized by Sirdeshmukh et al. [61], value, a
superordinate consumer goal, regulates consumer
actions at the level of loyalty intention. Consumers
are expected to regulate their actions towards achievement of this goal; they will indicate loyalty intentions
toward a service provider as long as the transaction
provides superior value. Similarly, Bolton and Drew
[9] found that value is an important determinant of
consumers’ loyalty intention toward telephone services. Chang and Wildt [13] also found that value
drives loyalty in the context of personal computers and
apartments. Therefore, it is believed that perceived
value toward an ISP will directly affects overall
satisfaction toward the ISP.
H2. Perceived value of an ISP’s service will positively affect consumers’ overall satisfaction with the
ISP.
H3. Perceived value of an ISP’s service will positively
affect consumers’ loyalty intention toward the ISP.
2.2. Perceived trust, overall satisfaction,
and loyalty intention
Rao [56] proposed that system integrity is one
of the most important factors for an ISP. It must
have integrity against breaches of security and
failure of hardware and software. Trustworthiness is
also an important factor for E-commerce success
[22,42,66,69]. As claimed by Kirmani and Rao
[41], trust-related issues cannot be fully resolved after
purchase when violations of quality claims cannot
be unambiguously recognized after usage. Internetrelated business involves many ambiguous aspects of
services. Thus, the management of customer trust is
especially important.
Similar to Morgan and Hunt [45], our study proposed that trust is an important factor in consumer
688
J.-S. Chiou / Information & Management 41 (2004) 685–695
outcome evaluation; i.e. consumers’ perceived trust
for an ISP influences their overall satisfaction with it.
The framework proposed by Singh and Sirdeshmukh
[60] supports this assertion by distinguishing between
trust before initiation of an exchange (pre-trust) and
after an exchange (post-trust). Based on social
exchange theories, they propose that customers’
pre-trust will have direct influence on their post-purchase satisfaction. Therefore, it can be argued that
accumulated trust perceptions will affect accumulated
overall satisfaction. Furthermore, Gwinner et al. [29]
also found that customers in long-term relationships
with service firms experienced three primary benefits:
confidence, social, and special treatment benefits.
Among the three, confidence (which is similar to trust
for the ISP in our study) was found to be the most
important across several categories of services. Confidence benefits include a sense of reduced anxiety,
faith in the provider, reduced perceptions of anxiety
and risk, and knowing what to expect. Thus:
Finally, research in customer satisfaction found
that satisfied customers are more likely to purchase
the same product/service repeatedly, to resist competitive offers from competitors, and to generate
positive word of mouth [3,8,11,19,72]. Research in
the American Customer Satisfaction Index provides
additional empirical support for positive customer
loyalty responses as the major consequence of
customer satisfaction [24]. Research in the ISP industry also found similar results. Therefore, it is reasonable to predict that consumers who are satisfied
with an ISP have a higher loyalty intention toward
an ISP.
H4. Customers’ trust in an ISP provider will positively affect their overall satisfaction.
Product performance can affect customers’ satisfaction and loyalty to a high degree [6,12]. However, if
consumers expect a future technology improvement,
this expectation will impact their assessment of existing and future technologies. This is particularly critical when products with intermediate levels of
technology are introduced while the market waits
for future technology introduction. Consumers have
learned to anticipate improvements in technology
and reduction in prices for these kinds of products.
As argued by Furedi [23] and Glassner [27], avoiding
risk has become a dominant cultural theme, and
technology is equated with risk. Therefore, it is very
important to incorporate consumers’ future expectations in modeling their satisfaction and loyalty
intentions. As proposed by Lemon et al. [43], consumers not only consider current and past evaluations
of the supplier’s performance (e.g. service satisfaction, perceived value, overall satisfaction) but also
incorporate future considerations of what the service
will be. The satisfaction formation model can be
enhanced by incorporating these future considerations. Similarly, Holak et al. find that when considering the purchase of high technology products,
consumers incorporate their expectations of the
timing of the next-generation technology into their
purchase decision [32].
Following Chaudhuri and Holbrook [14], it is proposed that commitment in the form of loyalty intention
is a result of trust. Trust seems implicit in customer
intention [65]. Trust is the perception of confidence in
the exchange partners’reliability and integrity, and it is a
necessary ingredient for long-term orientation because
it shifts the focus to future conditions [21,25]. Thus:
H5. Customers’ trust in the ISP will positively affect
their loyalty intention.
Trust not only affects loyalty intention directly, it
also affects it indirectly through perceived value.
Consumers are thought to consummate exchanges
with providers that offer maximum value. Perceived
trust of the service provider can create value by
providing relational benefits derived from interacting
with a service provider and reducing the exchange
uncertainty. Therefore, if customers have higher perceived trust toward an ISP, they will have higher
perceived value toward using it. Thus:
H6. Perceived trust of an ISP will positively affect
consumers’ perceived values toward the ISP.
H7. Consumers’ overall satisfaction with an ISP will
positively affect their loyalty intention toward the
ISP.
2.3. Effect of expected technology change on
overall satisfaction and loyalty intention
J.-S. Chiou / Information & Management 41 (2004) 685–695
Providers have not offered a standardized menu of
services, which is indicative of the lack of consensus
about the optimal business model. Firms have to face
technical, commercial, and structural challenges that
force them to adapt their operation and business
processes. Therefore, consumers are forced to modify
facilities (software and hardware) frequently, making
consumers’ future considerations an important part
of models dealing with this market. Chen et al.
[15] found that compatibility of an innovation with
existing services is very important for its adoption.
Therefore, when consumers feel that current service
will not be compatible with the future technology,
they will have lower loyalty intention toward their
service.
It is therefore proposed that if consumers expect
that a new ISP service will provide better technology
and services in the near future, they will not have high
satisfaction and strong loyalty intention toward
their current ISP. On the other hand, if consumers
expect that their ISP services are going to be the best
available in the market for a long time, they will have
strong satisfaction and loyalty intention toward it.
Therefore:
H8. High future technology expectancy for ISPs will
negatively affect customer overall satisfaction toward
their current ISPs.
H9. High future technology expectancy for ISPs will
negatively affect customer loyalty intention toward
their current ISPs.
3. Method
3.1. Study object and sample
Over the past 30 years, the Taiwanese economy
evolved through three stages: from underdeveloped, to
developing, to being a leading producer of high technology goods. Taiwanese IT firms have specialized as
the electronic world’s OEM partners and Taiwan has
grown to be the largest OEM country for personal
computing products. In 2000, its production value of
IT hardware exceeded 48 billion US dollars, placing it
at number four among major IT producing countries in
the world [36]. Driven by encouraging state policies
689
and advances in Internet access technology, the ISP
industry has shown impressive development over the
past five years, with more than 50 ISPs competing
for this emerging market. In 2001, there were around
8 million internet users, which represents 35% penetration rate in the whole island. Among these users
about 62% access internet through commercial ISPs,
while the rest get their internet access from school’s or
company’s ISPs [34]. Although this internet penetration rate is not as high as that of the United States,
this figure puts Taiwan as one of the most internet
connected societies in Asia Pacific.
Since this study explored the loyalty of household
users toward commercial ISPs, only household users
of commercial ISPs were included. To effectively
reach these users of ISPs in Taiwan, an internet-based
survey was employed to gather information (see [54]
for an explanation of benefits of an internet-based
survey). With the assistance of a marketing research
firm in Taiwan, a total of 10,000 surveys were emailed
randomly to individuals within the company’s database. Before the formal study, a pretest involved
exploratory interviews with users of ISPs was conducted to make sure the questionnaire was relevant
and clear to the respondents.
Because we did not know whether the respondents
used a commercial ISP or not in advance, this sampling frame included those who use other portals to
access the internet. One question on the first page was
used to screen qualified responses. For those who used
a company or school portal, only a few internet and
background related questions were administrated.
Once the questionnaire was completed, the responses
were automatically sent to the database. The respondents were guaranteed that all answers were anonymous. A reminder letter was emailed approximately
one week after the questionnaire. The return questionnaires were initially screened for usability and
reliability.
Overall, 408 completed responses were received.
Among them, 199 used company or school portals.
Therefore, only 209 responses were usable for further
analyses. The response rate is slightly lower than
ordinary mail surveys in Taiwan (averaging 5–10%).
However, considering the length of the questionnaire,
the response rate is acceptable. More importantly,
our sampling method was successful in soliciting
respondents with varied personal characteristics, and
690
J.-S. Chiou / Information & Management 41 (2004) 685–695
the background proportion was consistent with surveys
of typical internet users in Taiwan. Respondents were
young and well educated. They varied in sex (female,
43%; male, 57%), age (<20 years of age, 43%; 21–25
years of age, 42%; 26–30 years of age, 9%, >30 years
of age, 5%), and education (high school diploma,
5%; some college, 10%; university or higher 85%).
3.2. Measure development
Self-administered questionnaires were used for
all measures. Where possible, established measures
were used to measure the latent constructs. The measures tapped consumers’ perceptions of their relationship with the ISP that they used most frequently.
All measures used are shown in Table 1. A pre-test
on 20 ISP users was conducted to solicit the most
important attributive services of their ISPs. The
results showed that connection speed, email services,
online service assistance, and technical support and
consulting were most important to consumers. Attributive service satisfaction was operationalized by
asking ‘‘Please rate your satisfaction on the following
service attributes of the XYZ ISP,’’ 5-point scales
anchored from ‘‘Very satisfied’’ to ‘‘Very unsatisfied’’
were used.
Perceived trust was measured by five-item measures
adapted from Smith, representing honest, responsible,
understand consumers, professional, and care about
customers [63]. Overall satisfaction was assessed by
Table 1
Measurement model
Constructs
Item-construct loading
Standardized
t-valued
Cronbach’s
alpha
Attributive service satisfaction
Connection speed
Email services
On-line services (e.g. applications, registration, searching, amendment)
Technical support and consulting
0.60
0.64
0.72
0.52
–a
6.75
7.24
5.83
0.70
Perceived value
The service of the ISP is good value for money
The ISP is a good buy
The price of the ISP is economical
The service of the ISP is worthwhile
0.61
0.79
0.54
0.82
–
8.68
6.54
8.89
0.77
Perceived trust
I feel that the
I feel that the
I feel that the
I feel that the
I feel that the
0.71
0.86
0.81
0.57
0.73
–
11.4
10.8
7.70
9.79
0.85
Future ISP expectancy
There are possibilities that I will leave the current ISP because a new ISP
I expect that a more valuable ISP is coming to be established
I am afraid that a new ISP with better services to be established in the near future
0.73
0.91
0.83
–
11.6
11.3
0.86
Overall satisfaction
I am happy about my decision to choose this ISP
I believe that I did the right thing when I chose this ISP
Overall, I am satisfied with this ISP
0.89
0.94
0.85
–
21.1
16.8
0.92
Loyal intention
If I have to do it over again, I would choose XYZ brand
I try to use XYZ brand because it is the best choice for me
I consider myself to be a loyal patron of XYZ brand
0.87
0.91
0.80
–
17.6
14.3
0.89
a
ISP
ISP
ISP
ISP
ISP
is honest
is responsible
understands consumers
is very professional
cares about me
The loading was fixed.
J.-S. Chiou / Information & Management 41 (2004) 685–695
three item measures taken from measures of satisfaction developed by Oliver [49]. Perceived value of an
ISP was assessed by four item measures adapted from
Dodds et al. [20]. Future ISP expectancy was assessed
by asking respondents (1) the possibility that they will
leave the current ISP for a new ISP, (2) whether they
expect that a more valuable ISP would be established,
and (3) whether they are afraid that a new ISP with
better services was likely to be established in the near
future. Loyalty intention was assessed by the measures
developed by Muncy [46] and Selin et al. [59]. These
measures were used by Pritchard et al. [55] and were
rated on a 5-point scale from strongly agree to strongly
disagree.
3.3. Data analysis
Following Anderson and Gerbing’s [2] work, the
models were tested using a two-stage structural equation model. First, we performed Confirmatory Factor
Analysis (CFA) to evaluate construct validity regarding convergent and discriminant validity. In the second, we performed structural equation analysis to test
the research hypotheses empirically.
691
indicator loadings indicated that all were significant.
An inspection of the Cronbach’s alpha coefficients
reveals that, among the six alpha coefficients, all constructs are greater than 0.70, which indicates acceptable
reliability [48]. These results provided supports for the
unidimensionality of the scales.
The most common test of discriminant validity is
that the confidence interval around the correlation
between any two latent constructs does not include
one [64]. None of the correlations between latent
constructs for both CFA models reached one. A more
conservative test of discriminant validity involves
comparing the values of models that either free or
constrain (to a value of one) the phi value and testing
whether the constraint causes a significant decrease
in fit [5]. Again in all cases, the overall fit of the
models was significantly diminished by constraining
the correlation to one. Therefore, it is concluded that
discriminant validity is adequate for the measurement
model.
Having satisfied the measurement requirements, we
subsequently tested the structural relationship using
structural equation procedure.
4.2. Overall model fit
4. Results
4.1. Measurement model
CFAs were used to test the adequacy of the measurement model. We estimated the proposed measurement model using LISREL 8.20. The adequacy of the
measurement models was evaluated on the criteria of
overall fit with the data, convergent validity, discriminant validity, and reliability.
The results indicate reasonable overall fits between
the model and the observed data. The overall fit of
measurement model were w2ð194Þ ¼ 389:6, P ¼ 0:000,
CFI ¼ 0:93, NNFI ¼ 0:92, RMSEA ¼ 0:07. Both
NNFI and CFI exceed the recommended 0.90 threshold levels [7,33,37]. In addition, RMSEA is lower than
0.08 as recommended by Hair et al. [30].
According to Anderson and Gerbing, convergent
validity can be assessed by determining whether
each indicator’s estimated pattern coefficient on its
proposed underlying construct is significant (greater
than twice its standard error). An examination of the
Table 2 presents the overall model fit and the tests
of each research hypotheses. As shown, the results of
the full model (structural and measurement models)
indicated an adequate fit: w2ð197Þ ¼ 391:5, P ¼ 0:000,
CFI ¼ 0:93, NNFI ¼ 0:92, RMSEA ¼ 0:07. The
degree of freedom of the full model increased by
three, however, w2 only increases by 1.93. This demonstrates that the structural model fits the data very
well and there is little room for improvement in the
structural equation.
4.3. Hypothesis testing
The effect of attributive service satisfaction on
perceived value of an ISP was significant (g ¼ 0:53,
P < 0:05). Therefore, H1 was supported by the data.
The effects of perceived value on overall satisfaction
and loyalty intention were also significant (g ¼ 0:67
and 0.31, P < 0:05). These results showed that perceived value of an ISP is very important for consumers’ overall satisfaction and loyalty intention toward
an ISP. Therefore, H2 and H3 were supported.
692
J.-S. Chiou / Information & Management 41 (2004) 685–695
Table 2
Results of the proposed model
Causal path
Hypothesis
Expected
sign
Standardized structural
coefficient
t-value
Assessment
(P 0.05)
Attributive service satisfaction ! perceived value
Perceived value ! overall satisfaction
Perceived value ! loyalty intention
Perceived trust ! perceived value
Perceived trust ! overall satisfaction
Perceived trust ! loyalty intention
Overall satisfaction ! loyalty intention
Future ISP expectancy ! overall satisfaction
Future ISP expectancy ! loyalty intention
H1
H2
H3
H4
H5
H6
H7
H8
H9
þ
þ
þ
þ
þ
þ
þ
0.53
0.67
0.31
0.29
0.28
0.27
0.37
0.11
0.06
4.35
7.19
2.55
3.05
4.12
3.79
2.84
2.45
1.33
Significant
Significant
Significant
Significant
Significant
Significant
Significant
Significant
P ¼ 0.09
Note. w2ð197Þ ¼ 391:5, P ¼ 0:00; CFI ¼ 0:93; NNFI ¼ 0:92, RMSEA ¼ 0:07.
Perceived trust of an ISP was found to influence
perceived value, overall satisfaction, and loyalty intention positively (g ¼ 0:29, 0.28, and 0.27, P < 0:05).
These results provided evidence that perceived trust of
an ISP exerts an important role in enhancing consumers’ perceived value, overall satisfaction, and loyalty
intention. Therefore, H4, H5, and H6 were supported.
Finally, as expected, overall satisfaction appeared to
affect loyalty intention positively (g ¼ 0:37, P < 0:05).
Therefore, H7 was supported.
Future ISP expectancy appears to negatively influence overall satisfaction toward the ISP (g ¼ 0:11,
P < 0:05). However, the result showed that future
ISP expectancy only influenced loyalty intention at
a marginally significant level (g ¼ 0:06, P ¼ 0:09).
Therefore, H8 was supported, while H9 was only
marginally supported.
5. Discussions and implications
The results of this study confirm the mediating role
of perceived value in the relationships of attributive
service satisfaction, perceived trust, overall satisfaction, and loyalty intention in the ISP industry (H1, H2,
H3, and H7). These results may explain why free
internet access services are so popular in the market,
regardless of their low service quality. Although free
internet access companies may not provide the same
service level as ISPs with fees, the pricing scheme
improves perceived values. Therefore, it is very
important that an ISP should evaluate consumers’
perceived utility of its services frequently to know
whether their charges are reasonable and acceptable.
In order to continue its fee policy, an ISP should
upgrade its service quality frequently to give customers the feeling that they are receiving more value
than their cost. To lessen the fierce competition from
key ISP players and free ISP companies, secondary
ISP companies can seek to establish competitive
position in niche markets. For example, they may
try to aim at specific industries and provide better
service for their specific needs.
This study also found that perceived trust of an ISP
exerts a pivotal role in enhancing consumers’ perceived value, overall satisfaction, and loyalty intention
(H4, H5, and H6). These results again demonstrate the
consumers’ trust in a supplier is very important for an
internet-related business. The case of Genuity in the
United States represents the important of trust of an
ISP [51]. Many of their customers received letters
saying that their contracts were being abandoned
when the company suddenly declared bankruptcy.
Some customers re-negotiated, some did not, and
some were not even given the opportunity to renegotiate. Customers gradually found that the trustworthy of an ISP was very important. Sudden changes
of ISP services may cause non-trivial switching cost.
Therefore, an ISP should try to establish a trustworthy
image through visible policy and consistent image
activities to reduce perceived risk and increase perceived trust.
Finally, this study demonstrated that better technology expectancy is very important in influencing
a consumer’s overall satisfaction and loyalty intention (H8 and H9). Future innovation expectation can
J.-S. Chiou / Information & Management 41 (2004) 685–695
influence a consumer’s current purchasing behavior.
There are several ways that an ISP can reduce the
effects of future technology expectation. First, they
should ease the anxiety of future technology expectation by stating that the company has a dedicated team
to watch technology development and that it will try to
make sure that there is compatibility between forthcoming technology and the current system. Second,
they should direct customers’ attention toward service
quality instead of technology. Third, ISPs should try to
establish on-line community support. Communitiesoriented service strategy can both enhance the community service and let customers feel that they are not
alone. Finally, ISP companies should try to keep up
with mainstream technology. Although an established
ISP does not necessarily have to be the technology
leader in the industry, it cannot lag behind too much.
There are several limitations of this study. The first
is the cross-sectional design employed. To provide
stronger inference, the model developed and tested
could benefit from being tested in a longitudinal
design. Second, the model was empirically tested in
a Taiwanese sample. Past research has found that
culture plays a significant role in consumer behaviors
[16,31,44]. The strength and relative importance of the
proposed constructs in our study may differ by culture.
For example, Jarvenpaa et al. [38] argue that national
culture has an impact on trust.
Acknowledgements
The author gratefully acknowledges the editor and
reviewers’ constructive comments on an earlier of
the paper. The study was funded by National Science
Council, Taiwan.
References
[1] L.C. Allardice, Free ISPs, Link-up 18 (2), 2001, pp. 20.
[2] J.C. Anderson, D.W. Gerbing, Structural equation modeling
in practice: a review and recommended two-step approach,
Psychological Bulletin 103, 1988, pp. 411.
[3] E.W. Anderson, M.W. Sullivan, The antecedents and consequences of customer satisfaction for firms, Marketing
Science 12, 1993, pp. 125–143.
[4] R.P. Bagozzi, The self-regulation of attitudes intentions, and
behavior, Social Psychology Quarterly 55, 1992, pp. 178–193.
693
[5] R.P. Bagozzi, Y. Yi, L.W. Phillips, Assessing construct
validity in organizational research, Administrative Science
Quarterly 36, 1992, pp. 421–458.
[6] M.J. Bitner, Evaluating service encounters: the effects of
physical surroundings and employee responses, Journal of
Marketing 54, 1990, pp. 69–82.
[7] K.A. Bollen, Structural Equations with Latent Variables,
Wiley, New York, 1989.
[8] R.N. Bolton, A dynamic model of the duration of the
customer’s relationship with a continuous service provider:
the role of satisfaction, Marketing Science 17, 1998, pp. 45–
65.
[9] R.N. Bolton, J.H. Drew, A multistage model of customers’
assessments of service quality and value, Journal of
Consumer Research 17 (4), 1991, pp. 875–884.
[10] R.N. Bolton, P.K. Kannan, M.D. Bramlett, Implications of
loyalty program membership and service experiences for
customer retention and value, Journal of Academy of
Marketing Science 28 (1), 2000, pp. 95–108.
[11] R.N. Bolton, K.N. Lemon, A dynamic model of customers’
usage of services: usage as an antecedent and consequence of
satisfaction, Journal of Marketing Research 36, 1999, pp.
171–186.
[12] C.S. Carver, M.F. Scheier, Origins and functions of positive
and negative affect: a control-process view, Psychological
Review 97, 1990, pp. 19.
[13] T.Z. Chang, A.R. Wildt, Price, product information, and
purchase intention: an empirical study, Journal of the
Academy of Marketing Science 22, 1994, pp. 16–27.
[14] A. Chaudhuri, M.B. Holbrook, The chain of effects from
brand trust and brand affect to brand performance: the role of
brand loyalty, Journal of Marketing 65, 2001, pp. 83–93.
[15] L. Chen, M.L. Gillenson, D.L. Sherrell, Enticing online
consumers: an extended technology acceptance perspective,
Information & Management 39, 2002, pp. 705–719.
[16] J. Chiou, Antecedents and moderators of behavioral intention:
differences between the United States and Taiwanese students,
Genetic, Social, and General Psychology Monographs 126 (1),
2000, pp. 105–124.
[17] ISPs believes 30 per cent ‘‘will fail’’, Credit Control 22 (2)
(2001) 23.
[18] J.J. Cronin, M.K. Brady, G.T.M. Hult, Assessing the effects
of quality, value, and customer satisfaction on consumer
behavioral intentions in service environments, Journal of
Retailing 76, 2000, pp. 193–218.
[19] J.J. Cronin, S.A. Taylor, Measuring service quality: a reexamination and extension, Journal of Marketing 56, 1992,
pp. 55–68.
[20] W.B. Dodds, K.B. Monroe, D. Drewal, Effects of prices,
brand, and store information on buyers’ product evaluations,
Journal of Marketing Research 46, 1991, pp. 121–132.
[21] P.M. Doney, J.P. Cannon, An examination of the nature of
trust in buyer-seller relationships, Journal of Marketing 61,
1997, pp. 35–51.
[22] S. Elliot, S. Fowell, Expectations versus reality: a snapshot of
consumer experiences with Internet retailing, International
Journal of Information Management 20, 2000, pp. 323–336.
694
J.-S. Chiou / Information & Management 41 (2004) 685–695
[23] F. Furedi, Culture of Fear: Risk-Taking and the Morality of
Low Expectation, Cassell, London, 1997.
[24] C. Fornell, M.D. Johnson, E.W. Anderson, J. Cha, B.E.
Bryant, The American customer satisfaction index: nature,
purpose, and findings, Journal of Marketing 60, 1996,
pp. 7–18.
[25] S. Ganesan, Determinants of long-term orientation in buyerseller relationships, Journal of Marketing 58, 1994, pp. 1–19.
[26] E. Garbarino, M.S. Johnson, The different roles of satisfaction, trust and commitment in customer relationship, Journal
of Marketing 63, 1999, pp. 70–87.
[27] B. Glassner, The Culture of Fear: Why Americans are Afraid
of the Wrong Things, Basic Books, New York, 1999.
[28] S. Greenstein, Technological mediation and commercial
development in the early internet access market, California
Management Review 43 (2), 2001, pp. 75–94.
[29] K.P. Gwinner, D. Gremier, M.J. Bitner, Relational benefits in
service industries: the customer’s perspective, Journal of the
Academy of Marketing Science 26 (2), 1998, pp. 101–114.
[30] J.F. Hair, R.E. Anderson, R.L. Tatham, W.C. Black, Multivariate Data Analysis, 5th ed., Prentice-Hall, New Jersey,
1998.
[31] G. Hofstede, The culture relativity of organizational practices
and theories, Journal of International Business Studies 14,
1983, pp. 75–89.
[32] S. Holak, D. Lehmann, F. Sultan, The role of expectations
in the adoption of innovative consumer durables: some
preliminary evidence, Journal of Retailing 3, 1987, pp. 243–
259.
[33] R.H. Hoyle, A.T. Panter, Writing about structural equation
modeling, in: R.H. Hoyle (Ed.), Structural Equation Modeling, Sage Publications, Thousand Oaks, CA, 1995, pp. 158–
176.
[34] http://www.find.org.tw/.
[35] http://www.findanisp.com/.
[36] http://www.itis.org.tw/.
[37] L.T. Hu, P.M. Bentler, Evaluating model fit, in: Rick H.
Hoyle (Ed.), Structural Equation Modeling, Sage Publications, Thousand Oaks, CA, 1995, pp. 76–99.
[38] S.L. Jarvenpaa, N. Tractinsky, M. Vitale, Consumer trust in
an internet store, Information Technology and Management 1,
1999, pp. 45–72.
[39] T.O. Jones, W.E. Sasser Jr., Why satisfied customers defect,
Harvard Business Review 73 (6), 1995, pp. 88–99.
[40] M.A. Jones, J. Suh, Transaction-specific satisfaction and
overall satisfaction: an empirical analysis, Journal of Services
Marketing 14 (2), 2000, pp. 147–159.
[41] A. Kirmani, A.R. Rao, No pain, no gain: a critical review of
the literature on signaling unobservable product quality,
Journal of Marketing 64, 2000, pp. 66–79.
[42] M.K.O. Lee, E. Turban, A trust model for consumer internet
shopping, International Journal of Electronic Commerce 6
(1), 2001, pp. 75–91.
[43] K.N. Lemon, T.B. White, R.S. Winer, Dynamic customer
relationship management: incorporating future considerations
into the service retention decision, Journal of Marketing 66,
2002, pp. 1–14.
[44] Z. Liao, M.T. Cheung, Internet-based e-shopping and
consumer attitudes: an empirical study, Information &
Management 38, 2001, pp. 299–306.
[45] R.M. Morgan, S. Hunt, The commitment-trust theory of
relationship marketing, Journal of Marketing 58, 1994,
pp. 20–38.
[46] J.D. Muncy, An Investigation of Two-Dimensional Conceptualization of Brand Loyalty, Ph.D. Dissertation, Texas Tech
University, Lubbock, TX, 1983.
[47] E.W.T. Ngai, F.K.T. Wat, A literature review and classification of electronic commerce research, Information &
Management 39, 2002, pp. 415–429.
[48] J.C. Nunnally, Psychometric Theory, 2nd ed., McGraw-Hill,
New York, 1978.
[49] R.L. Oliver, A cognitive model of the antecedents and
consequences of satisfaction decisions, Journal of Marketing
Research 17, 1980, pp. 460–469.
[50] R.L. Oliver, Whence consumer loyalty, Journal of Marketing
63, 1999, pp. 33–44.
[51] D. Pappalardo, ISP dumps 500 user contracts, Network World
20 (18), 2003, pp. 1–56.
[52] P.G. Patterson, R.A. Spreng, Modeling the relationship
between perceived value, satisfaction and repurchase intentions in a business-to-business, services context: an empirical
examination, The International Journal of Service Industry
Management 8 (5), 1997, pp. 415–432.
[53] A. Parasuraman, V. Zeithaml, L. Berry, Reassessment of
expectations as a comparison standard in measuring service
quality: implications for further research, Journal of Marketing 58, 1994, pp. 111–124.
[54] J.E. Pitkow, M.M. Recker, Using the web as a survey tool:
results from the second WWW user survey, Journal of
Computer Networks ISDN System 27 (6) 1995, pp. 809–822.
[55] M.P. Pritchard, M.E. Havitz, D.R. Howard, Analyzing the
commitment-loyalty link in service contexts, Journal of the
Academy of Marketing Science 27 (3), 1999, pp. 333–348.
[56] S.S. Rao, Internet service providers: an Indian scenario,
Online Information Review 24 (4), 2000, pp. 322–328.
[57] F. Reichheld, The Loyalty Effect, Harvard Business School
Press, Boston, MA, 1996.
[58] F. Reichheld, Lead for loyalty, Harvard Business Review 79
(7) (2001) 76–84.
[59] S. Selin, D.R. Howard, E. Udd, T. Cable, An analysis of
consumer loyalty to municipal recreation programs, Leisure
Science 10, 1988, pp. 210–223.
[60] J. Singh, D. Sirdeshmukh, Agency and trust mechanisms in
consumer satisfaction and loyalty judgments, Journal of the
Academy of Marketing Science 28 (1), 2000, pp. 150–167.
[61] D. Sirdeshmukh, J. Singh, B. Sabol, Consumer trust, value,
and loyalty in relational exchanges, Journal of Marketing 66,
2002, pp. 15–37.
[62] N. Sirohi, E.W. McLaughlin, D.R. Wittink, A model of
consumer perceptions and store loyalty intentions for a
supermarket retailer, Journal of Retailing 74 (2), 1998, pp.
223–245.
[63] J.B. Smith, Selling alliances: issues and insights, Industrial
Marketing Management 26 (2), 1997, pp. 146–161.
J.-S. Chiou / Information & Management 41 (2004) 685–695
[64] J.B. Smith, D.W. Barclay, The effects of organizational
differences and trust on the effectiveness of selling partner
relationships, Journal of Marketing 61, 1997, pp. 3–21.
[65] R.F. Spekman, Perceptions of strategic vulnerability among
industrial buyers and its effect on information search and
supplier evaluation, Journal of Business Research 23, 1988,
pp. 313–326.
[66] J.R. Sullivan, K.A. Walstron, Consumer perspectives on
service quality of electronic commerce web sites, Journal of
Computer Information Systems 41 (3), 2001, pp. 8–21.
[67] F. Sultan, Consumer preferences for forthcoming innovations:
the case of high definition television, The Journal of
Consumer Marketing 16 (1), 1999, pp. 24–41.
[68] J.C. Sweeney, G.N. Soutar, L.W. Johnson, The role of
perceived risk in the quality-value relationship: a study in retail
environment, Journal of Retailing 75 (1), 1999, pp. 77–105.
[69] D.M. Szymanski, R.T. Hise, e-Satisfaction: an initial
examination, Journal of Retailing 76 (3), 2000, pp. 309–322.
[70] R.A. Westbrook, Sources of consumer satisfaction with retail
outlets, Journal of Retailing 57, 1981, pp. 68–85.
695
[71] V.A. Zeithaml, Consumer perceptions of price, quality, and
value: a means-end model and synthesis of evidence, Journal
of Marketing 52, 1988, pp. 2–22.
[72] V.A. Zeithaml, L.L. Berry, A. Parasuraman, The behavioral
consequences of service quality, Journal of Marketing 60,
1996, pp. 31–46.
Jyh-Shen Chiou (PhD in Marketing,
Michigan State), is professor of Marketing, College of Commerce, National
Chengchi University, Taiwan. His research focuses on consumer loyalty, and
strategic marketing. His work has been
published in Psychology & Marketing,
Journal of Interactive Marketing, Journal
of Service Research, International Journal of Advertising, European Journal of
Marketing, Journal of Business Logistics,
Journal of Social Psychology, Genetic, Social, and General
Psychology Monographs, Journal of Global Marketing, etc.
Descargar