E-satisfaction and e-loyalty: A contingency framework

Abstract

This study investigates the impact of satisfaction on loyalty in the context of electronic commerce. Findings of this research indicate that although e-satisfaction has an impact on e-loyalty, this relationship is moderated by 1. consumers' individual level factors, and 2. firms' business level factors. Among consumer level factors, convenience motivation and purchase size were found to accentuate the impact of e-satisfaction on e-loyalty, whereas inertia suppresses the impact of e-satisfaction on e-loyalty. With respect to business level factors, both trust and perceived value, as developed by the company, significantly accentuate the impact of e-satisfaction on e-loyalty.

Headnote

ABSTRACT

The authors investigate the impact of satisfaction on loyalty in the context of electronic commerce. Findings of this research indicate that although e-satisfaction has an impact on e-loyalty, this relationship is moderated by (a) consumers' individual level factors and (b) firms' business level factors. Among consumer level factors, convenience motivation and purchase size were found to accentuate the impact of e-satisfaction on e-loyalty, whereas inertia suppresses the impact of e-satisfaction on e-loyalty. With respect to business level factors, both trust and perceived value, as developed by the company, significantly accentuate the impact of e-satisfaction on e-loyalty. (c) 2003 Wiley Periodicals, Inc.

The collapse of large numbers of dot-com companies has required managers, who felt that the Internet had changed everything, to relearn that profits indeed do matter (Rosenbloom, 2002) and that the traditional laws of marketing were not rescinded with the arrival of the e-commerce era. Additionally, it has been reinforced that organizations not only need to attract new customers, but also must retain them to ensure profitable repeat business. In several industries, the high cost of acquiring customers renders many customer relationships unprofitable during early years. Even the individual stores of highly successful warehouse clubs like Sam's Club, Costco, and BJ's are typically not profitable until the second or third year after opening.

Over their buying lifetimes, customers' loyal to a given seller may be worth up to 10 times as much as its average customer (Health, 1997; Newell, 1997). Without customer loyalty, even the best-designed e-business model will soon fall apart. In their quest to develop a loyal customer base, most companies try their best to continually satisfy their customers and develop long-run relationships with them. Although satisfaction measures seem to be an important barometer of how customers are likely 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 repurchase behavior has been elusive for many firms (Mittal &Kamakura, 2001).

The relationship between satisfaction and loyalty seems almost intuitive, and several researchers have attempted to confirm this in their research (Cronin &Taylor, 1992; Newman &Werbel, 1973; Woodside, Frey, &Daley, 1989). Despite the intuitive appeal, however, the strength of the relationship between satisfaction and loyalty has been found to vary significantly under different conditions. For example, Jones and Sasser (1995) discovered that the strength of the relationship between satisfaction and loyalty depends upon the competitive structure of the industry. In a more recent study, Oliver (1999) found that satisfaction leads to loyalty, but true loyalty can only be achieved when other factors such as an embedded social networkare present.

Competing businesses are only a mouse clickaway in e-commerce settings, so it is critical that companies understand how to build customer loyalty in online markets. The present study investigates the impact of individual and business level factors, which may either accentuate or reduce the impact of e-satisfaction on e-loyalty. Speci.cally, the focus is on three individual level variables (inertia, convenience motivation, and purchase size) and two firm speci.c variables (trust and perceived value offered by the firm).

E-Loyalty and E-Satisfaction

Early views of brand loyalty focused on repeat purchase behavior. For example, Brown (1952) classi.ed loyalty into four categories, (a) undivided loyalty, (b) divided loyalty, (c) unstable loyalty, and (d) no loyalty, as revealed by the purchase patterns of consumers. Lipstein (1959) and Kuehn (1962) measured loyalty by the probability of product repurchase. Some researchers (Day, 1969; Jacoby &Chestnut, 1978) have suggested that these behavioral-based de.nitions are not suf.cient because they do not distinguish between true loyalty and spurious loyalty, due to factors such as lackof consumer choice. For example, a consumer may appear to be loyal to a particular store or brand but, in reality, may have no other choice because he or she lacks convenient transportation to travel to another store and the preferred brand is not carried by the nearby store. In response to these criticisms, researchers have proposed measuring both the attitudinal component and the behavioral component.

Loyalty. Engel, Kollat, and Blackwell (1982) de.ned brand loyalty as "the preferential, attitudinal and behavioral response toward one or more brands in a product category expressed over a period of time by a consumer." Jacoby (1971) expressed the view that loyalty is a biased behavioral purchase process that results from a psychological process. Other researchers have de.ned loyalty as "a favorable attitude toward a brand resulting in consistent purchase of the brand over time" (Assael, 1992; Keller, 1993). Keller suggested that loyalty is present when favorable attitudes for the brand are manifested in repeat buying behavior. Gremler (1995) suggested that both attitudinal and behavioral dimensions needed to be incorporated in measuring loyalty. Therefore, for present research purposes, e-loyalty is de.ned as the customer's favorable attitude toward an electronic business resulting in repeat buying behavior.

Satisfaction. Satisfaction, according to Oliver (1997) is "the summary psychological state resulting when the emotion surrounding disconfirmed expectations is coupled with a consumer's prior feelings about the consumer experience." From his perspective, "satisfaction may be best understood as an ongoing evaluation of the surprise inherent in a product acquisition and/or consumption experience." In this research, e-satisfaction is de.ned as the contentment of the customer with respect to his or her prior purchasing experience with a given electronic commerce firm.

A dissatis.ed customer is more likely to search for information on alternatives and more likely to yield to competitor overtures than is a satis.ed customer. Also, a dissatis.ed customer is more likely to resist attempts by his or her current retailer to develop a closer relationship and more likely to take steps to reduce dependence on that retailer. Moreover, the dissatis.ed member may wish to rede.ne the relationship. Because these variables are expected to apply in the electronic marketplace as well, it is hypothesized that:

H1: The higher the level of e-satisfaction, the higher the level of e-loyalty.

Moderating Role of Individual Level Variables

This research focuses on inertia, convenience motivation, and purchase size as the individual customer moderating variables that tend to either accentuate or reduce the impact of e-satisfaction on e-loyalty of customers.

Moderating Role of Inertia. Campbell (1997) de.nes inertia as a condition where "repeat purchases occur on the basis of situational cues rather than on strong partner commitment." According to Beatty and Smith (1987), around 40% to 60% of customers visit the same store for purchasing out of habit. In a similar fashion, a considerable proportion of customers bookmark their favorite electronic commerce Web sites and are more likely to visit them than other sites. These customers visit the sites out of habit rather than by conscious determination on the basis of perceived benefits and costs offered by the e-business. When a customer has a high level of inertia the sensitivity of e-loyalty to e-satisfaction is likely to be lower. On the other hand, when the inertia of a customer is low, the impact of e-satisfaction on e-loyalty is likely to be higher.

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

In addition to contributing directly to customer loyalty, convenience orientation is also expected to indirectly affect the relationship between customer satisfaction and customer loyalty. For customers who are motivated somewhat by convenience, but more so by other factors such as price seeking or information seeking, satisfaction will not have as much of an impact on loyalty because they are constantly exploring alternative service providers. However, the relationship between e-satisfaction and e-loyalty is expected to be stronger for customers with a high convenience orientation relative to customers with low convenience orientation.

Moderating Role of Purchase Size. Past researchers have found a positive relationship between purchase size (dollar amount spent by the customer) and loyalty. Kuehn (1962) and Day (1969) found heavy purchasers of a product to be more brand loyal than light purchasers. Because the consequences for consumers who spend less is smaller, they tend to be less loyal and more likely to shop around among vendors than those consumers who spend more. Therefore, it is expected that e-satisfaction will have a stronger impact on e-loyalty for heavy spenders than for light spenders. Higher-spending customers are expected also to be more emotionally involved with their purchasing decisions (due to the increased financial and social riskof making a wrong decision) than low-spending customers. As noted by Kim, Scott, and Crompton (1997), there is a positive relationship between involvement and loyalty. Because high-spending customers are likely to be more personally involved in their decision making, the relationship between e-satisfaction and e-loyalty is expected to be stronger for consumers who are heavy spenders. Conversely, because low spenders are likely to be less involved, the impact of e-satisfaction on e-loyalty is expected to be lower for them than for high-spending customers.

Hence it is posited that

H2: The impact of customer e-satisfaction on e-loyalty is moderated by (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 of e-satisfaction on e-loyalty is also likely to be affected by business level variables such as trust and perceived value offered by the e-business.

Moderating Role of Trust. Morgan and Hunt (1994) de.ne trust as the "confidence in the exchange partner's reliability and integrity." In a similar vein, Doney and Cannon (1997) de.ned trust as "the perceived credibility and benevolence of a target." One of the main reasons for the importance of trust or confidence in an online business is the perceived level of riskassociated with online purchasing. According to Medintz (1998), customer concerns about security, privacy, and protection against business scams are very high and have created a market for rating agencies and seals. Providing credit card information to an online business that has no physical location increases the perception of risk for certain customers (Shannon, 1998). Many electronic commerce customers do not trust the online businesses they are dealing with to keep their purchase data confidential (Wang, Lee, &Wang, 1998). According to Singh and Sirdeshmukh (2000) "trust is a crucial variable that determines outcomes at different points in the process and serves as a glue that holds the relationship together." In the electronic commerce context, customers who do not trust an e-business will not be loyal to it even though they are generally satis.ed with the e-business. Therefore, it seems apparent that e-satisfaction is likely to result in stronger e-loyalty when customers have a higher level of trust in the e-business.

Moderating Role of Perceived Value. Zeithaml (1988) de.nes value as "the consumer's overall assessment of the utility of a product based on perceptions of what is received and what is given." The importance of perceived value in electronic commerce stems from the fact that it is easy to compare product features as well as prices online. According to Bakos (1991), the search costs in electronic marketplaces are lower, resulting in more competitive prices to the consumer. The reduction in search costs not only increases the likelihood that customers will compare prices, but also enables the customers to compare the array of benefits that they will derive from the products and services that they buy. According to Parasuraman and Grewal (2000), perceived value is a function of "a 'get' component-i.e., the benefits a buyer derives from a seller's offering-and a 'give' component-i.e., the buyer's monetary and nonmonetary costs in acquiring the offering." A number of researchers have concluded that a significant number of electronic commerce customers are motivated by low prices (Goldberg, 1998; McCune, 1999; Tanaka, 1999).

Researchers have also established a positive relationship between perceived value and intention to purchase/repurchase (Dodds, Monroe, &Grewal, 1991; Parasuraman &Grewal, 2000). Perceived value contributes to the loyalty of an electronic business by reducing an individual's need to seekalternative service providers. When the perceived value is low, customers will be more inclined to switch to competing businesses in order to increase perceived value, thus contributing to a decline in loyalty. Even satis.ed customers are unlikely to patronize an e-business, if they feel that they are not getting the best value for their money. Instead, they will seekout other sellers in an ongoing effort to find a better value. The relationship between e-satisfaction and e-loyalty appears strongest when the customers feel that their current e-business vendor provides higher overall value than that offered by competitors.

Hence, it is posited that

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

METHODOLOGY

An instrument with multiple scaled items for the constructs of interest was developed and pretested. Then a random sample of 5000 consumers was drawn from a large list of e-retailing customers maintained by an online marketing research firm. An e-mail invitation was sent to each of the 5000 potential respondents, containing an embedded URL linkto the site hosting the survey and informing them that those who completed the questionnaire would be automatically entered in a drawing for a $500 prize. A summary of survey results was also offered for those respondents who chose to request it. This e-mail campaign produced 1211 complete and usable responses, an overall effective response rate of 24%. The respondents, representative of online customers across numerous e-retailers, were requested to respond to the questionnaire based upon their latest online purchase. To assess the representativeness of the sample, demographic data about the respondents, similar to that which was reported in a national study conducted by Green.eld Online, were also collected. Results show the demographic characteristics of the sample closely resemble those of the Green.eld Online study.

To measure the various constructs, validated items used by other researchers1 were adapted. E-satisfaction was assessed by adapting the scale developed by Oliver (1980). Trust was measured with the use of a 4-point scale, and perceived value was determined by scale items adapted from Dodds et al. (1991) and Sirohi, McLaughlin, and Wittink (1998). Purchase size was calculated as the amount of money the customer spent on the particular e-business in the previous 6 months. The concept of inertia was evaluated on a 3-point scale adapted from Gremler (1995). Convenience motivation was gauged by a five-item scale adapted from Moorman (1998). Lastly, e-loyalty was evaluated by using scale items adapted from Gremler (1995) and Zeithaml, Berry, and Parasuraman (1996). The conceptual model for the study is presented in Figure 1.

Analysis and Results

To avoid the bias from using the same set of responses for re.ning and testing the scale items, then evaluating the hypotheses, the responses (total sample size of 1211) were split into two separate data sets (a) an exploratory data set of 360 observations and (b) the model estimation data set of 851 observations. The exploratory data set was used to establish the reliability and unidimensionality of the scale items. Initially, an exploratory factor analysis and internal consistency estimates were conducted on the exploratory data set. Scale items loaded as expected and were found to have high internal consistency estimates. The hypotheses were tested with the set of responses used for re.ning/testing the scale items excluded. To estimate the model, the model estimation data set was used, the results of which are reported in the following section. Table 1 reports the coef.cient alphas, means, and standard deviations for the various constructs calculated based upon the model estimation data set. All the reliability estimates are greater than the suggested cutoff point of 0.70 (Nunnally, 1978).

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

LT - - - - SA - - TR - - PV - - PS - - IN - -CM - -SA TR * 0 1 2 3 3 4 5 - - SA PV - - SA PS - - SA IN - - SA CM - - (1)

where

LT - e-loyalty

SA - e-satisfaction

TR - trust in the e-business

PV - perceived value

PS - purchase size

IN - inertia

CM - convenience orientation

The overall model was found to be significant (p - . 05) with an adjusted R2 of 0.5856. Regression results of Eq. (1) are provided in Table 2.

H1 posits that e-satisfaction is positively related to e-loyalty. As the impact of satisfaction on loyalty is moderated by a number of individual level and business level factors, the positive and significant parameter estimate for -1 alone does not fully support this hypothesis. To evaluate the impact of satisfaction on loyalty Eq. (1) is partially differentiated with respect to satisfaction.

-LT - - - - TR - - PV - - PS - - IN - - CM (2)

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

H2(a) posits that at lower levels of inertia increasing customer satisfaction will lead to an increased e-loyalty. In other words, -LT/ -SA will be higher for lower levels of inertia than for higher levels of inertia. Partially differentiating Eq. (1) with respect to satisfaction gives2

-LT/-SA - - - - IN (3)

Because -9 is expected to be negative, e-satisfaction will have a higher impact on e-loyalty at lower values of inertia than at higher values of inertia. Consistent with expectations, the main effect of inertia is positive and significant and the interaction effect of inertia with satisfaction is negative (-0.0864) and significant (p - .05). H2(b) predicts that the impact of e-satisfaction on e-loyalty is moderated by convenience motivation. The parameter estimate for the main effect of convenience motivation on e-loyalty is insignificant, but the parameter estimate for the interaction term (e-satisfaction with convenience motivation) is 0.0575 (p - .05). This confirms the hypothesis that convenience motivation indeed positively moderates the impact of e-satisfaction on e-loyalty. H2(c) posits that purchase size moderates the impact of e-satisfaction on e-loyalty. Parameter estimates of both the main effect of purchase size and the interaction of purchase size with e-satisfaction are significant, supporting this hypothesis.

H3(a) posits that the impact of e-satisfaction on e-loyalty is moderated by trust. The parameter estimate of the main effect of trust on e-loyalty is 0.4149 (p - .05) and the parameter for the interaction effect is 0.0764 (p - .05). H3(b) predicts that the level of perceived value will moderate the impact of e-satisfaction on e-loyalty. The parameter estimate for the main effect of perceived value on e-loyalty is 0.3345 (p - .05) and the parameter estimate for the interaction effect is 0.0572 (p - .05). This result shows that the perceived value of a Web site moderates the impact of e-satisfaction on e-loyalty, supporting Hypothesis 3(b).

Managerial Implications

In the face of severe competition and continually rising customer expectations, e-commerce companies have necessarily become increasingly interested in identifying, understanding, nurturing, and keeping their profitable existing customers. In particular, there is a strong and growing interest in pushing beyond the technological factors of conducting an online business to a better understanding of the behavioral dimensions. Typically, e-satisfaction has been assumed to be a natural antecedent to e-loyalty. This research reveals that the impact of e-satisfaction on e-loyalty can be significantly moderated by individual level variables (inertia, convenience motivation, and purchase size) and company level variables (trust and perceived value). Companies can provide loyalty discounts and incentives to influence purchase size over the short run. But individual customer variables, such as inertia or convenience motivation, and the resultant customer switching behavior are largely beyond the control of company management. However, trust and perceived value may be somewhat controllable by management. Perceived value is believed to be calculated either consciously or subconsciously by customers each time they consider a purchase transaction. Apparently, many customers compare the array of benefits to be obtained from a particular transaction versus the perceived costs of that transaction to arrive at an overall perceived value. Over the longer run, customers may also lookat the perceived value of continuing a business relationship with their current vendor versus the perceived benefits and costs of switching to another seller. Thus, to remain competitive, a company must continuously workat enhancing perceived value for customers to discourage their switching to competitors. Customer expectations continue to rise and, in fact, may be virtually infinitely elastic, so no company can rest on its laurels for long in offering the highest perceived value to customers.

Building trusting relationships is an even more dif.cult challenge that may require e-commerce companies to go beyond bottom-line profit thinking to differentiate themselves from competitors. Two companies who have been leaders in developing trusting relationships with their customers, resulting in retention rates of over 90%, are the Vanguard Group and USAA-both giants in their respective fields of financial services and insurance. Vanguard Group, the second largest mutualfund seller in the world, does no selling whatsoever on its Web site. The site is devoted solely to continually educating both current and potential investors and informing them about such things as tax laws and financial planning. For example, Vanguard warns its customers about upcoming dividend and capital gains distribution dates so that they do not innocently "buy the dividend," that is, purchase a mutual fund just before this date and thereby wind up seeing their fund value reduced by the distribution amount and having to pay taxes on the dividend, too.

USAA also went beyond profit before the Persian Gulf War when it sent noti.cations to its mostly active and reserve military customers to advise them that they could increase the amount of their life insurance policies on short notice if they wished. It also suggested to its customers that they might want to review their automobile insurance policies if their cars would be driven fewer miles or not at all during the next several months, helping them to reduce expenses. In contrast to these two beyond the bottom line noti.cations made by USAA, many other insurance company policies retained clauses stating that there would be no payoff if an insured was killed in war. Few, if any, other companies told their customers to review their automobile policies to see whether they might qualify for a lower rate. These kinds of actions show savvy, long-run orientation to customer relationships that most companies talk about but few actually practice. Demonstrating to customers that you care about them and want to assist them irrespective of the short-run profit consequences helps to create and/or strengthen the kind of trusting relationship that garners customer loyalty.

Limitations

There are a few limitations of this research that should be considered when interpreting its findings. In this research, not all of the diverse business level and individual level factors that may drive e-loyalty were included. In addition, a more comprehensive model of e-loyalty might be developed. Replication of this research in different business and product settings in both cross-sectional and longitudinal studies could also help extend the validity of these findings. Learning more about the critical relationship between e-satisfaction and e-loyalty should be a top priority for scholars and practitioners as domestic and world competition for loyal customers and profits increase in relatively slow growth markets.

Footnote

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

Footnote

2 For the sake of simplicity, trust, perceived value, purchase size, and convenience motivation are held at a theoretical zero value.

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