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Why On-line CustomersRemain with a ParticularE-retailer: An IntegrativeModel and Empirical

EvidenceHsien-Tung TsaiNational Taiwan University

Heng-Chiang Huang National Taiwan University

Yi-Long Jaw

National Taiwan University

Wen-Kuo ChenNational Taiwan University

ABSTRACT

This article formulates and empirically tests a conceptual frameworkthat considers the antecedents of switching barriers and overall sat-isfaction, and their roles as drivers of customer retention in on-linesettings. To test the proposed hypotheses, structural equation model-ing based on data obtained from a large on-line retailing store in Tai-wan is used. The results suggest that perceived switching costs andcommunity building exert the greatest impact on repurchase inten-tions through switching barriers and overall satisfaction. Further-more, relational orientations significantly moderate the link betweenswitching barriers and repurchase intentions. Finally, the theoreticaland practical implications of the findings are discussed. © 2006 WileyPeriodicals, Inc.

Psychology & Marketing, Vol. 23(5): 447–464 (May 2006)

Published online in Wiley InterScience (www.interscience.wiley.com)

© 2006 Wiley Periodicals, Inc. DOI: 10.1002/mar.20121

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Business-to-consumer (B2C) electronic commerce has proven to be apromising channel of choice for consumers (Devaraj, Fan, & Kohli, 2002).

According to Jupiter Research’s (2004) report, on-line retail sales reachedUS$65 billion in the United States last year, and are expected to growby a compound annual rate of 17% in the future. A recent MIC (Market

Intelligence Center, 2004) survey indicates that more than 78% of Inter-net users in Taiwan purchased products or services on-line in 2003, rel-ative to 51% in 2001. This trend indicates remarkable potential anddemonstrates that electronic commerce constitutes an alternative to tra-ditional brick-and-mortar shopping channels (Pavlou & Gefen, 2004).Even so, the Harris and Goode (2004) study of on-line buyer–seller rela-tionships established that attracting new on-line customers and retain-ing existing ones is not easy. Indeed, in recent years, both academiciansand practitioners have paid increased attention to the issue of on-line cus-tomer retention. This focus is essential, because not only is the cost of retaining existing customers less than that of acquiring new ones, but alsoexisting customers cost less to maintain than newly acquired ones (Lam,Shankar, Erramilli, & Murthy, 2004; Reichheld, 1996). Lam et al. (2004)even argue that “customer retention has a powerful impact on the per-formance of service firms and is considered by many service firms as animportant source of competitive advantage” (p. 293).

With respect to the determinants of customer retention, the literaturesuggests that customers are motivated to remain with a particularprovider by constraint-based drivers (because they need to) or desire-

based drivers (because they want to) (e.g., Bansal, Irving, & Taylor, 2004;Bendapudi & Berry, 1997; Burnham, Frels, & Mahajan, 2003; Jones,Mothersbaugh, & Beatty, 2000; Wathne, Biong, & Heide, 2001).Althoughthere is an abundance of related research in the brick-and-mortar con-text, the limited studies so far conducted in an on-line context have con-ceptualized on-line customer loyalty in terms of overall satisfaction andinvestigated the antecedents that lead to the creation of strategies.

In this study, we propose and empirically analyze a conceptual frame-work that considers switching barriers and overall satisfaction as the

drivers of customer retention and their antecedents in an online con-text. In particular, expected value sharing that focuses on future, ratherthan past, evaluations of a provider’s potential performance is incor-porated into the framework, and serves as one of the antecedents of switching barriers. Also examined is the role played by relational ori-entations in the customer-retention process. It is well recognized thatcustomer retention drivers serve different purposes for different cus-tomers, depending on whether they have high or low relational bondswith a particular provider (Garbarino & Johnson, 1999; Jackson, 1985).More specifically, given that building and maintaining retention driv-ers involves various kinds of investment, an understanding of the rolesthe two drivers play in the retention process is essential if providers areto make appropriate resource allocation decisions. In other words, if

TSAI, HUANG, JAW, AND CHEN

Psychology & Marketing DOI: 10.1002/mar

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the drivers for low and high relational orientation customers could bedifferentiated, service providers would be able to make better resourceallocation decisions.

CONCEPTUAL FRAMEWORK AND HYPOTHESISDEVELOPMENT

Based on relationship marketing and consumer behavior research, thisstudy developed the conceptual framework shown in Figure 1. According to the literature, customers are motivated to remain with a particularservice provider by constraint-based determinants (switching barriers)and desire-based determinants (overall satisfaction) (Bansal et al., 2004;Benapudi & Berry, 1997; Burnham et al., 2003; Jones et al., 2000). Giventhe possibility that the strength of the links between the drivers andcustomers’ repurchase intentions may be influenced by customer rela-tional orientations (Garbarino & Johnson, 1999), this study follows pre-

vious research by identifying two types of relational orientation and ana-lyzing their effects. The next section focuses on the antecedents of switching barriers and overall satisfaction, and elucidates the roles theyplay in predicting the future intentions of on-line customers to remainwith a particular e-retailer.

WHY ONLINE CUSTOMERS REMAIN


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Figure 1. Conceptual framework.

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Antecedents of the Two Drivers

Expected Value Sharing. Expected value sharing is defined as theextent to which customers perceive that tangible economic benefits willbe shared by a service provider in the future. The more positive cus-tomers’ expectations of future value sharing, the more they are psycho-

logically locked in to the relationship with the provider. This future ori-entation recognizes that customer behavior is driven by anticipatedfuture outcomes. When a customer expects future value-sharing oppor-tunities, there is an interest in maintaining a sound long-term relation-ship with a particular service provider. Essentially, expected value shar-ing is a way for providers to use sharing patterns as a sign of good faith.By establishing such incentives, providers offer tangible evidence thatthey are willing to lower their profits to benefit customers (Heide &Miner, 1992; Lemon, White, & Winer, 2002). Also, by remaining with an

e-retailer, customers become claimants of benefits and are therefore enti-tled to reap accumulated value in the future. Thus, the following hypoth-esis is proposed:

H1: Expected value sharing has a positive influence on switching barriers.

Perceived Switching Costs. According to Porter (1980), switching costsare one-off costs involved in changing from one service provider to another.

As perceived switching costs increase, consumers are more likely to feel thatit is difficult to switch from a current provider to a new one. In the on-lineshopping environment,perceived switching costs include setup costs, learn-ing costs, and highly personalized services (Chen & Hitt, 2002). For exam-ple, e-retailers are increasingly able to adapt their customer interface andservices to specific needs through personalized services so that customersmay be psychologically committed to an e-retailer. Moreover, setup costsinclude the time and effort associated with the process of initiating a rela-tionship with a new e-retailer, such as customers providing personal infor-mation on-line when they first use the service (Burnham, Frels, & Maha-

jan, 2003). Based on organizational behavior literature, Bansal, Irving,and Taylor (2004) argue that “continuance commitment” (similar to switch-ing barriers in this study) is associated with the perceived switching costs.Therefore, the following hypothesis is advanced:

H2: Perceived switching costs have a positive influence on switching barriers.

Community Building. A community is comprised of its participants

and the relationships among them (McAlexander, Schouten, & Koening,2002). More recently, researchers (e.g., McAlexander et al., 2002; Muniz& O’Guinn, 2001) have developed a commercial concept of communitieswhose primary bases of identification are either brands or consumption



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activities. In other words, the communities represent a form of associa-tion within a consumption context positioned around one product or serv-ice. This article uses a general concept that includes both a face-to-facecommunity and an on-line community, situated within a consumptioncontext and positioned around the same e-retailer. Through these mar-

ketplace communities, customers can share meaningful consumptionexperiences that enhance mutual appreciation of the on-line serviceprovider (McAlexander et al., 2002). More important, communities allowand encourage communication between all those involved, that is, on-line customers, suppliers, and other parties interested in a particularcommunity. In other words, community building enhances mutual sat-isfaction, because members of a community can share their experiencesand their expectations.

Furthermore, in the study of customer relationship management,Muniz and O’Guinn (2001) suggested that businesses in both on-line andoff-line environments can build a community that makes it more difficultfor a customer to leave the “family” of people who purchase from thecompany. At the same time, they found that by sharing interests andexpertise within a consumption context, participants feel more securein their awareness that there are many like-minded others out there,which increases the uncertainty and “cost of thinking” associated withswitching providers. From another point of view, frequent interactions ina community could lead to the development of consumption-focused inter-personal bonds (McAlexander et al., 2002). It is assumed that these

embedded relationship properties create “exit barriers” as customersrealize that valued interpersonal relationships would be lost if they wereto switch to alternative providers (Wathne, Biong, & Heide, 2001). There-fore, the following hypotheses are proposed:

H3(a): Community building has a positive influence on switching bar-riers.

H3(b): Community building has a positive influence on overall satis-

faction.

Perceived Service Quality. Service quality is often seen as one of thekey determinants of on-line retailers’ success (Devaraj et al., 2002; Har-ris & Goode, 2004; Parasuraman, Zeithaml, & Malhotra, 2005). Recently,a number of researchers have attempted to identify the key service-qual-ity attributes that best conform to the on-line business environment. Forexample, Parasuraman et al. (2005) developed E-S-QUAL to measureoverall on-line service quality. In studying on-line consumer loyalty, Har-

ris and Goode (2004) measured service quality as a unidimensional con-cept. Meanwhile, they argued that perceptions of service quality could pos-itively influence overall customer satisfaction.As Oliver (1999) suggests,perceived service quality is cognitive and precedes overall satisfaction,



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which is an affective response. Devaraj et al. (2002) found that perceivedservice quality in on-line environments has a significant impact on over-all satisfaction similar to that in conventional off-line contexts.This find-ing is consistent with the argument (e.g., Chiou, Droge, & Hanvanich,2002) that overall satisfaction is an emotional response, whereas per-

ceived service quality is an appraisal construct, and appraisal generallycomes before emotional response. The above discussion leads to the nexthypothesis.

H4: Perceived service quality has a positive influence on overall satis-faction.

Perceived Trust. Trust has been conceptualized by previous researchersin a variety of ways, both theoretically and operationally (Gefen, Kara-hanna, & Straub, 2003). Singh and Sirdeshmukh (2000) distinguishedbetween trust before initiation of an exchange episode (pretrust) andafter an exchange (post-trust). This study focuses on pre-trust in orderto be consistent with the concept of trust. Schurr and Ozanne (1985)define trust as “the belief that a party’s word or promise is reliable andthat the party will fulfill his/her obligations in an exchange relation-ship” (p. 940). Researchers (e.g., Chiou, 2004; Harris & Goode, 2004)working in the area of on-line buyer–seller relationships have foundthat perceived trust significantly affects overall satisfaction. This find-ing is consistent with the Singh and Sirdeshmukh (2000) argument that

“consumers’ trust evaluations before a specific exchange episode willhave a direct influence on their post purchase satisfaction” (p. 159). Sim-ilarly, Chiou (2004) also found that on-line customers prefer to do busi-ness with service providers they believe they can trust. More impor-tant, trust in one’s exchange partner mitigates or removes the hazardsof opportunistic behavior, and thus increases exchange satisfaction.Hence, the following hypothesis is posited:

H5: Perceived trust has a positive influence on overall satisfaction.

The Two Main Drivers of Customer Retention

Switching Barriers. Switching barriers are defined as the degree towhich customers experience a sense of being locked into a relationshipbased on the economic, social, or psychological costs associated with leav-ing a particular service provider (Allen & Meyer, 1990; Bendapudi &Berry, 1997). Similarly, Bansal, Irving, & Taylor (2004) use the term “con-tinuance commitment”as a measure of the extent to which a buyer is psy-chologically bonded to a seller. Switching barriers help service providersprevent switching if there is a negative situation, such as a temporarydecline in service quality. The barriers allow time for the provider torebuild the higher satisfaction levels before the incident (Burnham et



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al., 2003). Furthermore, Wathne et al. (2001) indicate that customersmay derive utility from the customer-service provider relationship, whichserves as a switching barrier. Thus, switching to an alternative serviceprovider means sacrificing utility from the existing relationship (Wathneet al., 2001). In other words, switching barriers act as disincentives that

customers would rather not incur (Burnham et al., 2003), even if a newpotential service provider offers more favorable prices or other benefits.On the basis of the above arguments and evidence, the following hypoth-esis is proposed:

H6: Switching barriers have a positive influence on repurchase inten-tions.

Overall Satisfaction. Overall satisfaction can be defined as a positiveaffective state resulting from a global evaluation of performance basedon overall previous purchasing and consumption experiences with a par-ticular product or service over time (E. W. Anderson & Fornell, 1994;Lam et al., 2004). Longitudinal and cross-sectional studies have demon-strated that satisfied customers are more likely to continue patronizing a particular service provider than dissatisfied ones (e.g., Crosby &Stephens, 1987; Gilly & Gelb, 1982; Oliver, Rust, & Varki, 1997; Szy-manski & Henard, 2001). Similarly, in the case of online e-retailing serv-ices, researchers (e.g., Chiou, 2004; Devaraj et al., 2002; Szymanski &Hise, 2000) have found that the overall satisfaction experienced by on-

line customers reduces the perceived benefits of switching serviceproviders, and thus yields stronger repurchase intentions. A large bodyof evidence from e-commerce contexts supports the notion that higher lev-els of overall customer satisfaction generate higher levels of loyalty (e.g.,R. E. Anderson & Srinivasan 2003; Chiou, 2004; Devaraj et al., 2002).Thus, the following hypothesis is proposed:

H7: Overall satisfaction has a positive influence on repurchase inten-tions.

Moderating Effects of Relational Orientations

A substantial body of marketing research emphasizes the importance of a transaction/relational continuum (Garbarino & Johnson,1999; Jackson,1985). High relational orientation customers focus on creating a seriesof sequential, rather than individual, purchases and on establishing long-term interactive relationships with the seller (Garbarino & Johnson,1999). On-line customers with a high relational orientation tend to have

values that focus on the future. Because such customers anticipate thata relationship will continue, they invest time and money in a variety of product types, features, and functions only offered by their particularservice provider. In other words, they lock themselves into the relation-



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ship. Hence, there is sometimes an obligation for high relational orien-tation customers to continue with a particular provider. In contrast, cus-tomers with a low relational orientation focus on creating individualtransactions. Macneil (1980) suggested that transactional exchanges arediscrete buyer–seller exchanges of a commodity or performance for money,

and involve limited communication, nonuniqueness in personal terms,andno anticipation of future exchanges. In other words, transactional-typecustomers base their decisions solely on rational economic and practicalcriteria; therefore, they have low levels of specific commitment and do notfeel locked in. These arguments suggest the following hypotheses:

H8(a): The effect of switching barriers on repurchase intentions isstronger for high relational orientation customers than for lowrelational orientation customers.

H8(b): The effect of overall satisfaction on repurchase intentions isstronger for high relational orientation customers than for lowrelational orientation customers.

RESEARCH METHOD

Sampling and Data Collection Procedures

Data were collected from a survey of on-line customers of ETMall, a well

known e-retailer in Taiwan. A Web-based survey was used for this study,which is more effective for qualifying potential participants as appro-priate subjects (Szymanski & Hise,2000).The on-line version of the ques-tionnaire was set up on a survey portal provided by Chunghwa Telecomand introduced to 1,750 on-line customers selected randomly fromETMall’s mailing list. A total of 526 respondents participated in the sur-

vey, with 21 incomplete responses, yielding a usable response rate of 29%. The usable surveys were obtained in roughly equal proportionsfrom men and women, and the respondents were well educated, with

about 93% holding a college degree or higher.The customer base was divided into four relational orientation groupsaccording to their relational orientation composite scores. Following Gar-barino and Johnson (1999), the customer base was segmented according to the length of time between purchases by each respondent. Customerswho bought from ETMall three times per month on average were con-sidered high frequency, and those who purchased only once every 3months were considered low frequency. Two additional questions were alsodeveloped: “Have you ever bought insurance through ETMall?” and “Howmany times have you bought from the other channels of Eastern Multi-media Group?” The responses to these additional questions yielded use-ful information about the level of commitment to ETMall. The relationalorientation composite score of each customer was calculated and used



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to differentiate customers. In this analysis, customers with higher scoresare regarded as relational customers (n ϭ 118), and those with lowerscores as transactional customers (n ϭ 117).

Variable Measurement

All the focal constructs of the model were measured using multiple itemsbased on validated scales obtained from the literature, and all the itemswere assessed via a 7-point interval scale ranging from strongly disagree

to strongly agree. As suggested by Heide and Miner (1992) and Lemon etal. (2002), expected value-sharing represents the provider’s use of “profitsharing” to establish future incentives. Thus, an adaptation of the three-item scale of expected value sharing of Lemon et al. (2002) was adopted.The switching-cost scale employed was based on the switching-cost meas-ure of Burnham et al. (2003). Community building was measured by four-item measures adapted from McAlexander et al. (2002).

Perceived service quality was measured based on eight items adapted fromHarris and Goode (2004).The items reflect the degree to which customersperceive that e-commerce facilitates efficient and effective shopping, pur-chasing, and delivery. Perceived trust was measured by adapting the cus-tomer trust scale of Chiou (2004), representing honesty, responsibility,understanding/knowledge of consumers, and professionalism.The switch-ing-barrier scale was constructed to estimate the extent to whichon-line cus-tomers experience a sense of being locked in.A four-item switching barrier

was measured by adapting the continuance commitment scale of Bansal etal. (2004). Based on measures developed by various researchers (e.g., Har-ris & Goode, 2004; Szymanski & Hise, 2000), overall customer satisfactionwas measured by a four-item scale,which assessed respondents’ general sat-isfaction, confirmation of expectations, and divergence of the actual pur-chase from the hypothetically ideal product or service. A three-item scaleused by Burnham et al. (2003) and Bansal et al. (2004) was adapted toassess customers’ intentions to remain with their current service providers.

To ensure that the English and Chinese versions were consistent in

meaning, all the scales used in this study were examined by experts to verify that the items were comprehensible and unambivalent to Chineserespondents. The items used in the questionnaire are shown in Table 1.

RESULTS

The LISREL 8.54 program was used to test the theoretical model shownin Figure 1. Following the J. C. Anderson and Gerbing (1988) two-stageapproach, confirmatory factor analysis (CFA) was conducted to assess con-struct validity, and then structural equation analysis was performed totest the research hypotheses. With respect to the quality of the measure-ment model for the full sample, the constructs display satisfactory levels



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Table 1. Measurement Items and Reliabilities.

StandardizedItem Composite

Construct/Item Loading t Value Reliability

Repurchase intentions .95(Y1) If I were to repurchase again, I would .93 _a

choose ETMall.(Y2) I consider myself a loyal patron of ETMall. .94 39.19(Y3) I will do more business with ETMall in the .90 33.87

future.

Switching barriers .78(Y4) It would be very difficult for me to leave .73 —

ETMall right now, even if I wanted to.(Y5) I would lose too much utility if I decided .52 11.25

I wanted to leave ETMall now.

(Y6) I feel that I am more familiar with the online .78 17.04shopping environment of ETMall than withother providers.

(Y7) I feel that I would have too few options to .69 14.95consider if I were to leave ETMall.

Overall satisfaction .92(Y8) In general, the products/services of ETMall .84 —

meet my expectations.(Y9) In general, I am satisfied with the services .87 24.90

or products that ETMall provides.

(Y10) My choice to purchase from ETMall was a .91 26.85wise one.

(Y11) I am happy with my decision to purchase .88 25.46from ETMall.

Expected value sharing .85(X1) I anticipate that I will benefit from the .82 —

service provider.(X2) I expect that in the future, I will use the .85 20.52

award points that I accumulate.(X3) I think that I will gain some benefits from .76 18.12

doing business with this service provider.

Perceived switching costs .88(X4) It would take a lot of effort to switch from .78 —

ETMall to another online store.(X5) It takes time to go through the steps of .86 20.73

switching to a new online store.(X6) Switching to a new service provider would .89 21.34

mean losing or replacing reward points andother benefits that I have accumulated withETMall.

Community building .93(X7) Making purchases at ETMall is fun. .84 —(X8) I feel a sense of kinship with other ETMall .88 25.15

shoppers.(continued)

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of reliability, as indicated by the composite reliabilities ranging from 0.78to 0.95 and shared variances ranging from 0.66 to 0.93.To assess the con-

vergent validity of the measures (Bollen, 1989), factor loadings of 0.60

(Bagozzi & Yi, 1988) and squared multiple correlations values above 0.40(Taylor & Todd, 1995) were used as the criteria. All multi-item constructsmeet these criteria, with each factor loading being significantly associatedwith its underlying factor, which confirms the validity. More robust evidenceof discriminant validity was found through the chi-square difference testsin which the correlations between all possible pairs of constructs were firstfreely estimated,and then set to be equal.All chi-square differences for con-structs were significant at the .05 level, suggesting that the constructsunder analysis were distinct and discriminately valid.

Turning to the structural model itself, Table 2 presents the overall fitof the model and the tests of each research hypothesis. The overall modelfit is good, 2(505, N ϭ 505) ϭ 1476.27, p Ͻ .001, CFI ϭ 0.99, NNFI ϭ 0.99,RMSEA ϭ 0.062. Although the overall chi-square is significant, whichmight reflect its sensitivity to sample size (Bagozzi & Yi, 1988), the ratio



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Table 1. (continued).

StandardizedItem Composite

Construct/Item Loading t Value Reliability

(X9) I am interested in a club for ETMall shoppers .90 26.32

and the service provider.(X10) I have met really nice people through ETMall. .91 26.73

Service quality .92(X11) The products/services I ordered were delivered .77 —

within the time promised by ETMall.(X12) The quantity and quality of the products/ .77 18.30

services I received were exactly as I had ordered.(X13) The organization and structure of online .79 18.94

catalogs were logical and easy to follow.(X14) I felt secure in providing personal information .82 19.91

to ETMall for my online purchases.

(X15) All the terms and conditions (e.g., payment, .85 20.77warranty, and return policies) were easy toread/understand.

(X16) If I wanted to, I could easily contact a .73 17.12customer service representative by telephone.

(X17) ETMall responds to my inquiries promptly. .75 17.83(X18) ETMall website reacted quickly to my .69 16.12

requests for information.

Perceived trust .93(X19) I feel that ETMall is honest. .89 —(X20) I feel that ETMall is responsible. .86 27.48(X21) I feel that ETMall understands its customers. .90 30.63(X22) I feel that ETMall cares about me. .78 23.08(X23) I feel that ETMall is very professional. .81 24.36

1-7 scale, 1 ϭ strongly disagree; 7 ϭ strongly agree.

aThe loading was fixed.

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of chi-square to degrees of freedom (2.9, less than 3) indicates a satis-factory fit (Carmines & McIver, 1981). These fit indices show that a sub-stantial amount of variance is accounted for by the model.Thus, the pro-posed model is a reasonably accurate representation of the data.

H1 suggests that expected value sharing is positively and directlylinked to switching barriers. From the structural modeling results andstandardized ␥ coefficients of 0.16 ( p Ͻ .01), this contention is stronglysupported. The results also show that perceived switching costs influ-ence switching barriers positively (␥ ϭ 0.40, p Ͻ .01), providing some sup-port for H2. Structural equation modeling also broadly supports H3(a)and H3(b), producing significant parameter estimates with standardized␥ coefficients of 0.44 ( p Ͻ .01) and 0.24 ( p Ͻ .01), respectively. H4 pro-poses a positive and direct relationship between service quality andoverall satisfaction. The result also strongly supports this view (␥ ϭ

.33, p Ͻ .01). As expected, perceived trust appears to affect overall sat-isfaction positively (␥ ϭ .35, p Ͻ .01). In this regard, H5 is supported.Similarly, H6 and H7 are supported, as the paths from switching bar-riers and overall satisfaction to repurchase intentions are positive and

significant, with standardized ␥ coefficients of .59 ( p Ͻ .01) and .36 ( pϽ .01), respectively.

Finally, the groups with the highest and lowest relational orientationscores were selected, and multigroup analysis was run to estimate theparameters. It was found that the results of the high relational orienta-tion group are identical to the general results; that is, switching barri-ers (␥ high

barrier ϭ 0.72, p Ͻ .01) and overall satisfaction (␥ highsat ϭ 0.30, p Ͻ

.01) both significantly affect repurchase intentions. For the low relationalorientation group, the results also show that switching barriers (␥ low

barrier

ϭ 0.40, p Ͻ .01) and overall satisfaction (␥lowsat ϭ 0.40, p Ͻ .01) significantlyimpact on repurchase intentions.A chi-square difference test shows that

there is a significant degradation in fit when ␥ is constrained to be equalacross the two groups (⌬2 ϭ 6.43, ⌬df ϭ 1, p Ͻ .05), indicating that the



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Table 2. Structural Parameter Estimates and Goodness-of-fit Indices.

Standardized

Paths Hypothesis Coefficient t value Conclusion

Expected value sharing ➔ switching barriers H1 .16 3.05* Support

Perceived switching costs ➔ switching barriers H2 .40 7.65** Support

Community building ➔ switching barriers H3a .44 7.84** SupportCommunity building ➔ overall satisfaction H3b .24 5.33** Support

Service quality ➔ overall satisfaction H4 .33 4.74** Support

Perceived trust ➔ overall satisfaction H5 .35 4.73** Support

Switching barriers ➔ repurchase intentions H6 .59 11.78** Support

Overall satisfaction ➔ repurchase intentions H7 .36 8.37** Support

Note. 2 (505, N ϭ 505) ϭ 1476.27, p Ͻ .001. Comparative fit index (CFI) ϭ .99, normed fit index (NFI) ϭ

.98, goodness of fit index (GFI) ϭ .85, adjusted goodness of fit index (AGFI) ϭ .83, root-mean-square error of

approximation (RMSEA) ϭ .062.* p Ͻ .01. ** p Ͻ .001.

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effect of switching barriers on repurchase intentions is stronger in thehigh relational orientation group than in the low group. This finding supports H8(a). However, there is no significant difference between thetwo groups (⌬2 ϭ 0.77, ⌬df ϭ 1, p Ͼ .1) when ␥sat is constrained to beequal across two groups. Thus, H8(b) is not supported.

DISCUSSION AND MANAGERIAL IMPLICATIONS

The Antecedents of Switching Barriers and OverallSatisfaction

The present study suggests that on-line customers’ switching barriers maybe strengthened by raising customers’ perceptions of future value shar-ing and switching costs, and by community building. Furthermore, on-

line customers’ overall satisfaction may be increased by improving serv-ice quality, enhancing perceptions of trust, and community building. Oneway to strengthen value sharing perceptions is to provide tangible evi-dence that the e-retailers are willing to lower their own profits in orderto benefit the customer, for example, with award points programs, spe-cial discounts, or benefits that can be accumulated. E-retailers attempt-ing to strengthen perceptions of switching costs should incorporate serv-ice heterogeneity (i.e., personalized services), the breadth and scope of thecustomer’s relationship with the provider, and setup costs (i.e., register-ing personal information by on-line customers for initial use) into theircustomer retention programs. For example, the service heterogeneityprovided by an e-retailer may increase the economic risks (and associatedpotential costs) and evaluation costs associated with switching from ane-retailer who is perceived as different or nonsubstitutable in a market(Burnham et al., 2003). Obviously, such bonds are broken when switch-ing to an alternative service provider (Chen & Hitt, 2002).

With regard to the total effects of antecedents on repurchase intentions(not reported in the tables), community building has the greatest influ-ence on repurchase intentions. The results suggest that a customer-

focused form of community, both on-line and off-line, provides an oppor-tunity for long-term relationship maintenance. As Muniz and O’Guinn(2001) argue, community building facilitates the buying and selling process, and, in particular, participants interact intensively with oneanother within a consumption context positioned around a particular e-retailer. McAlexander et al. (2002) suggest that service providers cancultivate a community through programs like strategically designedbrandfests. Moreover, through community building, consumers can com-municate directly with other participants, and thereby obtain informa-

tion and solicit opinions.With respect to the various antecedents of customer satisfaction, per-

ceived service quality and trust have the greatest effects on overall sat-isfaction with direct effects of 0.33 ( p Ͻ .01) and 0.35 ( p Ͻ .01), respec-



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tively. In other words, appropriate deployment of marketing resourcesaimed at improving service quality and increasing trust significantlyenhances on-line customer satisfaction. The results also indicate that e-retailers seeking to improve on-line customers’ perceptions of servicequality should consider other significant factors, such as ease of navi-

gation of the on-line store (Parasuraman et al., 2005). More important,providers’ claims should be matched by physical distribution performanceand product return policies to enhance overall satisfaction and furtherincrease loyalty. Thus, it is arguable that the integration of on-line andconventional off-line channels may well prove to be a productive andcomplementary approach (Harris & Goode, 2004).

The present findings not only confirm the claims of Gefen et al. (2003)that the importance of trust on-line appears to be intensified by theabsence of face-to-face communication; they also provide some empiricalsupport for the Bendapudi and Berry (1997) proposition that “customers’trust in a service provider will lead to greater dedication in maintaining the relationship” (p. 21). On-line retailing practitioners should developpolicies and systems to create on-line customer trust, because virtualreality might be an obstacle to the widespread adoption of a service orproduct that the e-retailers provide. When relationships are character-ized by trust, outcomes can be reliably predicted, which makes on-line cus-tomers feel secure in their interactions.

The Focal Drivers of Customer Retention

The results confirm that switching barriers and satisfaction drive on-line customers’ repurchase intentions. The findings have implicationsfor both the theory and practice of e-commerce. Most important, theresults suggest the need to extend existing theories of on-line customerretention to incorporate constraint-based drivers, such as switching bar-riers. Furthermore, consistent with the study of Burnham et al. (2003),the effect of customer satisfaction on repurchase intentions was againfound to be much weaker than that of switching barriers, with total

effects of 0.36 ( p Ͻ .01) and 0.59 ( p Ͻ .01), respectively. In other words,potential monetary benefits (from the current provider) and costs (of switching to a new provider) appear to be more significant disincentivesto switching providers than customer satisfaction. This finding showsthat managing customer perceptions of switching barriers to ensure con-tinued customer patronage represents a powerful tactical element in on-line customer retention programs.

The Moderating Role of Relational Orientations

In this study, the moderating effect of relational orientations is of con-siderable importance in Internet-based settings. Given that on-line cus-tomers have easy access to information about products or services that



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competitors provide, as most on-line information is “just a click away”(Chen & Hitt, 2002), e-retailers’ marketing resources may be allocatedinappropriately if the roles of the two drivers are not properly under-stood in terms of high- and low-orientation customers. The results indi-cate that the drivers have very different effects on the intentions of these

two types of customer. First, a higher relational orientation strengthensthe relationship between switching barriers and repurchase intentions.This result suggests that e-retailers should make a concerted effort to fac-tor switching barriers into customer retention programs to retain on-line customers with a high relational orientation. No evidence is foundto support that a higher relational orientation strengthens the rela-tionship between overall satisfaction and repurchase intentions. A pos-sible explanation is that customers in both groups attach considerablesignificance to previously accumulated satisfaction when deciding whether to continue the relationship with a particular service provider(E. W. Anderson & Fornell, 1994).

CONCLUSION AND FUTURE RESEARCH

This study makes three major contributions to e-commerce research.First, it provides researchers with a comprehensive theoretical frameworkof the antecedents that drive customer motivation to remain with a par-ticular e-retailer. It is found that expected value sharing, perceived switch-

ing costs, and community building significantly impact on switching bar-riers. Moreover, it is also found that community building, perceived servicequality, and perceived trust significantly influence overall satisfaction.These findings extend previous research (e.g., Chen & Hitt, 2002; Chiou,2004; Harris & Goode, 2004; Pavlou & Gefen, 2004), and provide e-com-merce practitioners with guidelines for effectively managing on-line cus-tomer retention.

Second, the results suggest the need to extend existing theories of on-line customer retention to incorporate anticipation-based drivers, such

as expected value sharing. The findings demonstrate that the effect of expected value sharing on switching barriers is highly significant. Inconsidering such future-oriented drivers, the results may partially explain,for example, why dissatisfied customers remain with a certain e-retailer,even when no specific physical asset investments or commitments areinvolved. Thus, an e-retailer’s retention program should include expected

value sharing as a basic element.Third, this study augments the research on customer retention (e.g.,

Burnham et al., 2003; Garbarino & Johnson, 1999) by establishing thesignificant moderating effect of relational orientations on the linksbetween customer retention drivers and repurchase intentions.This sug-gests that on-line customers with a high relational orientation attachconsiderable significance to constraint-based factors when deciding



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whether to repatronize a particular e-retailer. An e-retailer should exer-cise caution when incorporating switching barriers in its retention pro-gram, because there are potential dangers associated with an overlyaggressive use of switching barriers.

One potential limitation of this study is the applicability of the results

to other contexts. Future research using this model in other buyer–sellersettings should enhance the generalizability of these results. Furthermore,distinguishing between positive and negative switching barriers, as theyrelate to different relational orientation groups, would extend the man-agerial applications of these drivers. Finally, other variables, such ascustomer involvement, may also have a moderating effect on the linksbetween drivers and repurchase intentions. Highly involved customersmay be retained more effectively by desire-based drivers, because theyrapidly and accurately evaluate options and gain additional product- orservice-related information. Thus, service providers who rely on switch-ing barriers to retain customers may not achieve their goal. This impor-tant issue is challenging and merits further investigation.

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Correspondence regarding this article should be sent to: Heng-Chiang Huang,Department of International Business, National Taiwan University, 50, Lane 144,Section 4, Kee-Lung Road, Taipei 10617, Taiwan ([email protected]).


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