E-Satisfaction and Loyalty. a Contingency Framework

E-Satisfaction andE-Loyalty: A ContingencyFrameworkRolph E. Anderson and Srini S. SrinivasanDrexel University

ABSTRACT

The authors investigate the impact of satisfaction on loyalty in thecontext of electronic commerce. Findings of this research indicatethat although e-satisfaction has an impact on e-loyalty, thisrelationship is moderated by (a) consumers' individual level factorsand (b) firms' business level factors. Among consumer level factors,convenience motivation and purchase size were found to accentuatethe impact of e-satisfaction on e-loyalty, whereas inertia suppressesthe impact of e-satisfaction on e-loyalty. With respect to businesslevel factors, both trust and perceived value, as developed by thecompany, significantly accentuate the impact of e-satisfaction one-loyalty. © 2003 Wiley Periodicals, Inc.

The collapse of large numbers of dot-com companies has required man-agers, who felt that the Internet had changed everything, to relearn thatprofits indeed do matter (Rosenbloom, 2002) and that the traditionallaws of marketing were not rescinded with the arrival of the e-commerceera. Additionally, it has been reinforced that organizations not only needto attract new customers, but also must retain them to ensure profitablerepeat business. In several industries, the high cost of acquiring cus-tomers renders many customer relationships unprofitable during earlyyears. Even the individual stores of highly successful warehouse clubslike Sam's Club, Costco, and BJ's are typically not profitable until thesecond or third year after opening.

Psychology & Marketing, Vol. 20(2): 123-138 (February 2003)Published online in Wiley InterScience (www.interscience.wiley.com)© 2003 Wiley Periodicals, Inc. DOI: 10.1002/mar. 10063

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ANDERSON R., SRINIVASAN S.: "E-Satisfaction and E-Loyalty: A Contingency Framework" (Psychology and Marketing, February 2003, Vol.20, No.2, p:123-138)

Over their buying lifetimes, customers' loyal to a given seller may beworth up to 10 times as much as its average customer (Health, 1997-Newell, 1997). Without customer loyalty, even the best-designed e-busi-ness model will soon fall apart. In their quest to develop a loyal customerbase, most companies try their best to continually satisfy their custom-ers and develop long-run relationships with them. Although satisfactionmeasures seem to be an important barometer of how customers arelikely to behave in the future, there are two issues to consider:

1. Satisfaction measures are likely to be positively biased (Peterson& Wilson, 1992).

2. Establishing the relationship between satisfaction and repurchasebehavior has been elusive for many firms (Mittal & Kamakura,

The relationship between satisfaction and loyalty seems almost in-tuitive, and several researchers have attempted to confirm this in theirresearch (Cronin & Taylor, 1992; Newman & Werbel, 1973; WoodsideFrey, & Daley, 1989). Despite the intuitive appeal, however, theStrength of the relationship between satisfaction and loyalty has beenfound to vary significantly under different conditions. For exampleJones and Sasser (1995) discovered that the strength of the relationshipbetween satisfaction and loyalty depends upon the competitive struc-ture of the industry. In a more recent study, Oliver (1999) found thatsatisfaction leads to loyalty, but true loyalty can only be achieved whenother factors such as an embedded social network are present.

Competing businesses are only a mouse click away in e-commercesettings, so it is critical that companies understand how to build cus-tomer loyalty in online markets. The present study investigates the im-pact of individual and business level factors, which may either accen-tuate or reduce the impact of e-satisfaction on e-loyalty. Specifically thefocus is on three individual level variables (inertia, convenience moti-vation, and purchase size) and two firm specific variables (trust andperceived value offered by the firm).

E-Loyalty and E-Satisfaction

Early views of brand loyalty focused on repeat purchase behavior Forexample. Brown (1952) classified loyalty into four categories (a) undi-vided loyalty, (b) divided loyalty, (c) unstable loyalty, and (d) no loyalty,as revealed by the purchase patterns of consumers. Lipstein (1959) andKuehn (1962) measured loyalty by the probability of product repur-chase. Some researchers (Day, 1969; Jacoby & Chestnut, 1978) havesuggested that these behavioral-based definitions are not sufficient be-cause they do not distinguish between true loyalty and spurious loyaltydue to factors such as lack of consumer choice. For example, a consumer

ANDERSON AND SRINIVASAN

may appear to be loyal to a particular store or brand but, in reality, mayhave no other choice because he or she lacks convenient transportationto travel to another store and the preferred brand is not carried by thenearby store. In response to these criticisms, researchers have proposedmeasuring both the attitudinal component and the behavioral compo-nent.

Loyalty. Engel, KoUat, and Blackwell (1982) defined brand loyalty as"the preferential, attitudinal and behavioral response toward one ormore brands in a product category expressed over a period of time by aconsumer." Jacoby (1971) expressed the view that loyalty is a biasedbehavioral purchase process that results from a psychological process.Other researchers have defined loyalty as "a favorable attitude towarda brand resulting in consistent purchase of the brand over time" (Assael,1992; Keller, 1993). Keller suggested that loyalty is present when fa-vorable attitudes for the brand are manifested in repeat buying behav-ior. Gremler (1995) suggested that both attitudinal and behavioral di-mensions needed to be incorporated in measuring loyalty. Therefore, forpresent research purposes, e-loyalty is defined as the customer's favor-able attitude toward an electronic business resulting in repeat buyingbehavior.

Satisfaction. Satisfaction, according to Oliver (1997) is "the summarypsychological state resulting when the emotion surrounding discon-firmed expectations is coupled with a consumer's prior feelings aboutthe consumer experience." From his perspective, "satisfaction may bebest understood as an ongoing evaluation of the surprise inherent in aproduct acquisition and/or consumption experience." In this research,e-satisfaction is defined as the contentment of the customer with respectto his or her prior purchasing experience with a given electronic com-merce firm.

A dissatisfied customer is more likely to search for information onalternatives and more likely to yield to competitor overtures than is asatisfied customer. Also, a dissatisfied customer is more likely to resistattempts by his or her current retailer to develop a closer relationshipand more likely to take steps to reduce dependence on that retailer.Moreover, the dissatisfied member may wish to redefine the relation-ship. Because these variables are expected to apply in the electronicmarketplace as well, it is hypothesized that:

HI: The higher the level of e-satisfaction, the higher the level ofe-loyalty.

Moderating Role of Individual Level Variables

This research focuses on inertia, convenience motivation, and purchasesize as the individual customer moderating variables that tend to either

E-SATISFACTION AND E-LOYALTY 125

accentuate or reduce the impact of e-satisfaction on e-loyalty of custom-ers.

Moderating Role of Inertia. Campbell (1997) defines inertia as a con-dition where "repeat purchases occur on the basis of situational cuesrather than on strong partner commitment." According to Beatty andSmith (1987), around 40% to 60% of customers visit the same store forpurchasing out of habit. In a similar fashion, a considerable proportionof customers bookmark their favorite electronic commerce Web sites andare more likely to visit them than other sites. These customers visit thesites out of habit rather than by conscious determination on the basisof perceived benefits and costs offered by the e-business. When a cus-tomer has a high level of inertia the sensitivity of e-loyalty to e-satis-faction is likely to be lower. On the other hand, when the inertia of acustomer is low, the impact of e-satisfaction on e-loyalty is likely to behigher.

Moderating Role of Convenience Motivation. The motivations ofconsumers vary widely. Although some customers are driven by theneed to gather information and save money, others are driven more bythe need for convenience. Jarvenpaa and Todd (1997) found that con-venience was perceived as one of the major benefits of shopping over theInternet. Comparing Internet shoppers with non-Internet shoppers,Donthu and Garcia (1999) found that the former group was more con-venience seeking than the latter. According to Burke (1997), Internetshoppers appreciate the ability to conduct business with any firm at anytime while performing other activities such as exercising, cooking, ortaking care of children. A survey conducted by Visa showed that 60% ofInternet shoppers conducted their transactions in their pajamas (Ro-mani, 1999). Several writers have discussed the importance of conve-nience as a contributing factor to the growth of electronic commerce(Harrington & Reed, 1996; Romani, 1999; Rowley, 1996). Customersdriven by the need for convenience are less likely to inconvenience them-selves by repeatedly searching for new providers for their products andservices. Hence, they are more likely to exhibit higher levels of loyalty.

In addition to contributing directly to customer loyalty, convenienceorientation is also expected to indirectly affect the relationship betweencustomer satisfaction and customer loyalty. For customers who are mo-tivated somewhat by convenience, but more so by other factors such asprice seeking or information seeking, satisfaction will not have as muchof an impact on loyalty because they are constantly exploring alterna-tive service providers. However, the relationship between e-satisfactionand e-loyalty is expected to be stronger for customers with a high con-venience orientation relative to customers with low convenience orien-tation.

126 ANDERSON AND SRINIVASAN

Moderating Role of Purchase Size. Past researchers have found apositive relationship between purchase size (dollar amount spent by thecustomer) and loyalty. Kuehn (1962) and Day (1969) found heavy pur-chasers of a product to be more brand loyal than light purchasers. Be-cause the consequences for consumers who spend less is smaller, theytend to be less loyal and more likely to shop around among vendors thanthose consumers who spend more. Therefore, it is expected that e-sat-isfaction will have a stronger impact on e-loyalty for heavy spendersthan for light spenders. Higher-spending customers are expected alsoto be more emotionally involved with their purchasing decisions (due tothe increased financial and social risk of making a wrong decision) thanlow-spending customers. As noted by Kim, Scott, and Crompton (1997),there is a positive relationship between involvement and loyalty. Be-cause high-spending customers are likely to be more personally involvedin their decision making, the relationship between e-satisfaction ande-loyalty is expected to be stronger for consumers who are heavy spend-ers. Conversely, because low spenders are likely to be less involved, theimpact of e-satisfaction on e-loyalty is expected to be lower for themthan for high-spending customers.

Hence it is posited that

H2: The impact of customer e-satisfaction on e-loyalty is moderatedby (a) inertia, (b) convenience motivation, and (c) purchase size.

Moderating Role of Business Level Variables

In addition to the above-cited individual level variables, the impact ofe-satisfaction on e-loyalty is also likely to be affected by business levelvariables such as trust and perceived value offered by the e-business.

Moderating Role of Trust. Morgan and Hunt (1994) define trust asthe "confidence in the exchange partner's reliability and integrity." In asimilar vein, Doney and Cannon (1997) defined trust as "the perceivedcredibility and benevolence of a target." One of the main reasons for theimportance of trust or confidence in an online business is the perceivedlevel of risk associated with online purchasing. According to Medintz(1998), customer concerns about security, privacy, and protectionagainst business scams are very high and have created a market forrating agencies and seals. Providing credit card information to an onlinebusiness that has no physical location increases the perception of riskfor certain customers (Shannon, 1998). Many electronic commerce cus-tomers do not trust the online businesses they are dealing with to keeptheir purchase data confidential (Wang, Lee, & Wang, 1998). Accordingto Singh and Sirdeshmukh (2000) "trust is a crucial variable that de-


termines outcomes at different points in the process and serves as aglue that holds the relationship together." In the electronic commercecontext, customers who do not trust an e-business will not he loyal to iteven though they are generally satisfied with the e-husiness. Therefore,it seems apparent that e-satisfaction is likely to result in strongere-loyalty when customers have a higher level of̂ trust in the e-business.

Moderating Role of Perceived Value. Zeithaml (1988) defines valueas "the consumer's overall assessment of the utility of a product basedon perceptions of what is received and what is given." The importanceof perceived value in electronic commerce stems from the fact that it iseasy to compare product features as well as prices online. According toBakos (1991), the search costs in electronic marketplaces are lower, re-sulting in more competitive prices to the consumer. The reduction insearch costs not only increases the likelihood that customers will com-pare prices, but also enables the customers to compare the array of ben-efits that they will derive from the products and services that they buy.According to Parasuraman and Grewal (2000), perceived value is a func-tion of "a 'get' component—i.e., the benefits a buyer derives from aseller's offering—and a 'give' component—i.e., the buyer's monetaryand nonmonetary costs in acquiring the offering." A number of research-ers have concluded that a significant number of electronic commercecustomers are motivated by low prices (Goldberg, 1998; McCune, 1999;Tanaka, 1999).

Researchers have also established a positive relationship betweenperceived value and intention to purchase/repurchase (Dodds, Monroe,& Grewal, 1991; Parasuraman & Grewal, 2000). Perceived value con-tributes to the loyalty of an electronic business by reducing an individ-ual's need to seek alternative service providers. When the perceivedvalue is low, customers will be more inclined to switch to competingbusinesses in order to increase perceived value, thus contributing to adecline in loyalty. Even satisfied customers are unlikely to patronize ane-business, if they feel that they are not getting the best value for theirmoney. Instead, they will seek out other sellers in an ongoing effort tofind a better value. The relationship between e-satisfaction and e-loyaltyappears strongest when the customers feel that their current e-businessvendor provides higher overall value than that offered by competitors.

Hence, it is posited that

H3: The relationship between e-satisfaction and e-loyalty is moder-ated by (a) trust and (b) perceived value.

METHODOLOGY

An instrument with multiple scaled items for the constructs of interestwas developed and pretested. Then a random sample of 5000 consumers


was drawn from a large list of e-retailing customers maintained by anonline marketing research firm. An e-mail invitation was sent to eachof the 5000 potential respondents, containing an embedded URL link tothe site hosting the survey and informing them that those who com-pleted the questionnaire would be automatically entered in a drawingfor a $500 prize. A summary of survey results was also offered for thoserespondents who chose to request it. This e-mail campaign produced1211 complete and usable responses, an overall effective response rateof 24%. The respondents, representative of online customers across nu-merous e-retailers, were requested to respond to the questionnairebased upon their latest online purchase. To assess the representative-ness of the sample, demographic data about the respondents, similar tothat which was reported in a national study conducted by GreenfieldOnline, were also collected. Results show the demographic character-istics of the sample closely resemble those of the Greenfield Onlinestudy.

To measure the various constructs, validated items used by other re-searchers^ were adapted. E-satisfaction was assessed by adapting thescale developed by Oliver (1980). Trust was measured with the use of a4-point scale, and perceived value was determined by scale itemsadapted from Dodds et al. (1991) and Sirohi, McLaughlin, and Wittink(1998). Purchase size was calculated as the amount of money the cus-tomer spent on the particular e-business in the previous 6 months. Theconcept of inertia was evaluated on a 3-point scale adapted from Grem-ler (1995). Convenience motivation was gauged by a five-item scaleadapted from Moorman (1998). Lastly, e-loyalty was evaluated by usingscale items adapted from Gremler (1995) and Zeithaml, Berry, and Par-asuraman (1996). The conceptual model for the study is presented inFigure 1.

Analysis and Results

To avoid the bias from using the same set of responses for refining andtesting the scale items, then evaluating the hypotheses, the responses(total sample size of 1211) were split into two separate data sets (a) anexploratory data set of 360 observations and (b) the model estimationdata set of 851 observations. The exploratory data set was used to es-tablish the reliability and unidimensionality of the scale items. Initially,an exploratory factor analysis and internal consistency estimates wereconducted on the exploratory data set. Scale items loaded as expectedand were found to have high internal consistency estimates. The hy-potheses were tested with the set of responses used for refining/testingthe scale items excluded. To estimate the model, the model estimationdata set was used, the results of which are reported in the following

'Items used in the final instrument are given in Appendix A.


Business Level Factors• Trust• Perceived Value

Individual Level Factors• Purchase Size• Inertia• Convenience Motivation

E-Satisfaction\z

E-Loyalty

Figure 1. Moderated effect of e-satisfaction on e-loyalty.

section. Table 1 reports the coefficient alphas, means, and standard de-viations for the various constructs calculated based upon the model es-timation data set. All the reliability estimates are greater than the sug-gested cutoff point of 0.70 (Nunnally, 1978).

To test the hypotheses, the following regression model was run:

= 7o + 7iSA + raTR ++ 77SA * PV +

+* PS +

+ 74IN +* IN +

+ 7SA * TR* CM + e (1)

where

LT = e-loyaltySA = e-satisfactionTR = trust in the e-businessPV = perceived valuePS = purchase sizeIN = inertiaCM = convenience orientation

Table 1. Reliability and Dimensionality of Variables Used in Analysis

Variables

E-satisfactionE-loyaltyTrustPerceived valueInertiaConvenience motivationPurchase size

Number ofItems

6744341

Alpha

0.89470.91440.95460.95490.83880.9534

NA

Mean

6.19494.82144.33625.87563.63096.3965307.0

StandardDeviation

1.12141.48580.82301.12501.77160.9399969.6


The overall model was found to be significant (p < . 05) with anadjusted R^ of 0.5856. Regression results of Eq. (1) are provided inTable 2.

HI posits that e-satisfaction is positively related to e-loyalty. As theimpact of satisfaction on loyalty is moderated by a number of individuallevel and business level factors, the positive and significant parameterestimate for ji alone does not fully support this hypothesis. To evaluatethe impact of satisfaction on loyalty Eq. (1) is partially differentiatedwith respect to satisfaction.

= 7i + 76* TR + 77 * PV + 78 * PS + 79 * IN + 7io * CM (2)

As seen by the preceding equation, the impact of satisfaction on loyaltyis a function of trust, perceived value, inertia, convenience motivation,and purchase size. The main effect of satisfaction on loyalty (for an av-erage firm) can be evaluated from Eq. (2) by using the average valuesof trust, perceived value, inertia, convenience motivation, and purchasesize. Substituting the parameter estimates from Table 2, and the av-erage values from Table 1, results in 6LT/5SA - 1.03, thus supportingHypothesis 1.

H2(a) posits that at lower levels of inertia increasing customer sat-isfaction will lead to an increased e-loyalty. In other words, SLT/5SA

Table 2. Results of Regression Analysis Examining tbe Moderators of tbeRelationsbip Between E-Satisfaction and E-Loyalty

Variables

ConstantSatisfaction (SA)Trust (TR)Perceived value (PV)Purchase Size (PS)Inertia (IN)Convenience motivation (CM)SA*TRSA*PVSA*PSSA*INSA*CM

*A1I the results are significant at p

ParameterEstimate

4.72720.28040.41490.33458.3745e-50.3732

-0.00540.07640.05728.6301e-5

-0.08640.0575

< .05.

Standard Error

0.03970.05450.07160.04273.737e-50.02050.04470.03910.02524.112e-50.02250.0309

rvalue*119.152

5.1435.7957.8262.241

18.1770.121"=1.9552.2682.099

-3.8441.857


will be bigher for lower levels of inertia tban for bigber levels of inertia.Partially differentiating Eq. (1) witb respect to satisfaction gives^

aLT/aSA - 7i + 79IN (3)

Because yg is expected to be negative, e-satisfaction will bave a bigberimpact on e-loyalty at lower values of inertia tban at bigber values ofinertia. Consistent witb expectations, tbe main effect of inertia is posi-tive and significant and tbe interaction effect of inertia witb satisfactionis negative (-0.0864) and significant (p < .05). H2(b) predicts tbat tbeimpact of e-satisfaction on e-loyalty is moderated by convenience moti-vation. Tbe parameter estimate for tbe main effect of convenience mo-tivation on e-loyalty is insignificant, but tbe parameter estimate for tbeinteraction term (e-satisfaction witb convenience motivation) is 0.0575(p < .05). Tbis confirms tbe bypotbesis tbat convenience motivation in-deed positively moderates tbe impact of e-satisfaction on e-loyalty. H2(c)posits tbat purcbase size moderates tbe impact of e-satisfaction one-loyalty. Parameter estimates of botb tbe main effect of purcbase sizeand tbe interaction of purcbase size witb e-satisfaction are significant,supporting tbis bypotbesis.

H3(a) posits tbat tbe impact of e-satisfaction on e-loyalty is moderatedby trust. Tbe parameter estimate of tbe main effect of trust on e-loyaltyis 0.4149 (p < .05) and tbe parameter for tbe interaction effect is 0.0764(p < .05). H3(b) predicts tbat tbe level of perceived value will moderatethe impact of e-satisfaction on e-loyalty. The parameter estimate for themain effect of perceived value on e-loyalty is 0.3345 (p < .05) and tbeparameter estimate for tbe interaction effect is 0.0572 (p < .05). Tbisresult sbows tbat tbe perceived value of a Web site moderates tbe im-pact of e-satisfaction on e-loyalty, supporting Hypotbesis 3(b).

Managerial Implications

In tbe face of severe competition and continually rising customer ex-pectations, e-commerce companies bave necessarily become increas-ingly interested in identif5dng, understanding, nurturing, and keepingtbeir profitable existing customers. In particular, tbere is a strong andgrowing interest in pusbing beyond tbe tecbnological factors of con-ducting an online business to a better understanding of tbe bebavioraldimensions. Typically, e-satisfaction bas been assumed to be a naturalantecedent to e-loyalty. Tbis researcb reveals tbat tbe impact of e-sat-isfaction on e-loyalty can be significantly moderated by individual levelvariables (inertia, convenience motivation, and purcbase size) and com-

the sake of simplicity, trust, perceived value, purchase size, and convenience motivation areheld at a theoretical zero value.


pany level variables (trust and perceived value). Companies can provideloyalty discounts and incentives to influence purchase size over thesbort run. But individual customer variables, sucb as inertia or conve-nience motivation, and tbe resultant customer switcbing bebavior arelargely beyond tbe control of company management. However, trust andperceived value may be somewbat controllable by management. Per-ceived value is believed to be calculated eitber consciously or subcon-sciously by customers eacb time tbey consider a purcbase transaction.Apparently, many customers compare tbe array of benefits to be ob-tained from a particular transaction versus tbe perceived costs of tbattransaction to arrive at an overall perceived value. Over tbe longer run,customers may also look at tbe perceived value of continuing a businessrelationsbip witb tbeir current vendor versus tbe perceived benefits andcosts of switcbing to anotber seller. Tbus, to remain competitive, a com-pany must continuously work at enbancing perceived value for custom-ers to discourage tbeir switcbing to competitors. Customer expectationscontinue to rise and, in fact, may be virtually infinitely elastic, so nocompany can rest on its laurels for long in offering tbe bigbest perceivedvalue to customers.

Building trusting relationsbips is an even more difficult cballengetbat may require e-commerce companies to go beyond bottom-line profittbinking to differentiate tbemselves from competitors. Two companieswbo bave been leaders in developing trusting relationsbips witb tbeircustomers, resulting in retention rates of over 90%, are tbe VanguardGroup and USAA—botb giants in tbeir respective fields of financialservices and insurance. Vanguard Group, tbe second largest mutual-fund seller in tbe world, does no selling wbatsoever on its Web site. Tbesite is devoted solely to continually educating botb current and potentialinvestors and informing tbem about sucb tbings as tax laws and finan-cial planning. For example. Vanguard warns its customers about up-coming dividend and capital gains distribution dates so tbat tbey do notinnocently "buy tbe dividend," tbat is, purcbase a mutual fund just be-fore tbis date and tbereby wind up seeing tbeir fund value reduced bytbe distribution amount and baving to pay taxes on tbe dividend, too.

USAA also went beyond profit before tbe Persian Gulf War wben itsent notifications to its mostly active and reserve military customers toadvise tbem tbat tbey could increase tbe amount of tbeir life insurancepolicies on sbort notice if tbey wisbed. It also suggested to its customerstbat tbey migbt want to review tbeir automobile insurance policies iftbeir cars would be driven fewer miles or not at all during tbe nextseveral montbs, belping tbem to reduce expenses. In contrast to tbesetwo beyond tbe bottom line notifications made by USAA, many otberinsurance company policies retained clauses stating tbat tbere wouldbe no payoff if an insured was killed in war. Few, if any, otber companiestold tbeir customers to review tbeir automobile policies to see wbetbertbey migbt qualify for a lower rate. Tbese kinds of actions sbow savvy.


long-run orientation to customer relationsbips tbat most companies talkabout but few actually practice. Demonstrating to customers tbat youcare about tbem and want to assist tbem irrespective of tbe sbort-runprofit consequences belps to create and/or strengtben tbe kind of trust-ing relationsbip tbat garners customer loyalty.

Limitations

Tbere are a few limitations of tbis researcb tbat sbould be consideredwben interpreting its findings. In tbis researcb, not all of tbe diversebusiness level and individual level factors tbat may drive e-loyalty wereincluded. In addition, a more comprebensive model of e-loyalty migbtbe developed. Replication of tbis researcb in different business and prod-uct settings in botb cross-sectional and longitudinal studies could alsobelp extend the validity of these findings. Learning more about tbe crit-ical relationsbip between e-satisfaction and e-loyalty sbould be a toppriority for scbolars and practitioners as domestic and world competi-tion for loyal customers and profits increase in relatively slow growtbmarkets.

APPENDIX A—SCALE ITEMSScale Items

Satisfaction The items in this scale use a 7-point Likert-type measure.(a) I am satisfied with my decision to purchase from this Web

site.(b) If I had to purchase again, I would feel differently about

buying from this Web site."(c) My choice to purchase from this Web site was a wise one.(d) I feel badly regarding my decision to buy from this Web

site."(e) I think I did the right thing by buying from this Web site.(f) I am unhappy that I purchased from this Web site."

(Based on Oliver, 1980)

E-Loyalty The items in this scale also use a 7-point Likert-type measure.(a) I seldom consider switching to another Web site.(b) As long as the present service continues, I doubt that I

would switch Web sites.(c) I try to use the Web site whenever I need to make a pur-

chase.(d) When I need to make a purchase, this Web site is my first

choice.(e) I like using this Web site.(f) To me this site is the best retail Web site to do business

with.(g) I believe that this is my favorite retail Web site.

(Based on Gremler, 1995; Zeithaml, Berry, & Parasuraman, 1996)Continued on following page


APPENDIX A—Continued

Scale Items

Inertia The items in this scale use a 7-point Likert-type measure.(a) Unless I became very dissatisfied with this Web site, chang-

ing to a new one would be a bother.(b) I would find it difficult to stop using this Web site.(c) For me the cost in time, money, and effort to change Web

sites is high.(Based on Gremler, 1995)

Perceived The items in this scale use a 7-poiiit semantic differential mea-Value sure.

(a) Products purchased at this Web site are:"Very poor value for money Very good value for money

(b) Products purchased at this Web site are considered to be agood buy.^

Strongly disagree Strongly agree(c) You get what you pay for at this Web site:

Strongly disagree Strongly agree(d) Products purchased at this Web site are worth the money

paid:Strongly disagree Strongly agree(Based on Dodds et al., 1991)

Trust The items in this scale use a 5-point Likert-type measure.(a) The performance of this web-site meets my expectations.(b) This Web site can be counted on to successfully complete

the transaction.(c) I can trust the performance of this Web site to be good.(d) This Web site is reliable for online shopping.

Convenience The items in this scale use a 7-point Likert-type measure.Motivation (a) I want the convenience that online shopping offers.

(b) I enjoy the flexibility of shopping online.(c) I am interested in taking advantage of the ease of online

shopping.(d) I would like to shop at my own pace while shopping online.

(Based on Moorman, 1998)

"Scale items are reverse coded.

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Correspondence regarding this article should be sent to: Rolph E. Anderson,Department of Marketing, LeBow College of Business, Drexel University, Phil-adelphia, PA 19104 ([email protected])


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E-Satisfaction and Loyalty. a Contingency Framework