Understanding the Effect of Customer Relationship Management Efforts on Customer Retention and Customer Share Development free essay sample

The results show that affective commitment and loyalty programs that provide economic incentives positively affect both customer retention and customer share development, whereas direct mailings influence customer share development. However, the effect of these variables is rather small. The results also indicate that firms can use the same strategies to affect both customer retention and customer share development. ustomer relationships have been increasingly studied in the academic marketing literature (Berry 1995; Dwyer, Schurr, and Oh 1987; Morgan and Hunt 1994; Sheth and Parvatiyar 1995). An intense interest in customer relationships is also apparent in marketing practice and is most evident in firms’ significant investments in customer relationship management (CRM) systems (Kerstetter 2001; Reinartz and Kumar 2002; Winer 2001). Customer retention rates and customer share are important metrics in CRM (Hoekstra, Leeflang, and Wittink 1999; Reichheld 1996). Customer share is defined as the ratio of a customer’s purchases of a particular category of products or services from supplier X to the customer’s total purchases of that category of products or services from all suppliers (Peppers and Rogers 1999). To maximize these metrics, firms use relationship marketing instruments (RMIs), such as loyalty programs and direct mailings (Hart et al. 1999; Roberts and Berger 1999). Firms also aim to build close relationships with customers to enhance customers’ relationship perceptions (CRPs). Although the impact of these tactics on customer retention has been reported (e. g. , Bolton 1998; Bolton, Kannan, and Bramlett 2000), there is skepticism about whether such tac- C Peter C. Verhoef is Assistant Professor of Marketing, Department of Marketing and Organization, Rotterdam School of Economics, Erasmus University, Rotterdam. The author gratefully acknowledges the financial and data support of a Dutch financial services company. The author thanks Bas Donkers, Fred Langerak, Peter Leeflang, Loren Lemon, Peeter Verlegh, Dick Wittink, and the four anonymous JM reviewers for their helpful suggestions. The author also acknowledges the comments of research seminar participants at the University of Groningen, Yale School of Management, Tilburg University, and the University of Maryland. Finally, he acknowledges his two dissertation advisers, Philip Hans Franses and Janny Hoekstra, for their enduring support. tics can succeed in developing customer share in consumer markets (Dowling 2002; Dowling and Uncles 1997). Several studies have considered the impact of CRP on either customer retention or customer share, but not on both (e. g. , Anderson and Sullivan 1993; Bolton 1998; Bowman and Narayandas 2001; De Wulf, Odekerken-Schroder, and Iacobucci 2001). A few studies have considered the effect of RMIs on customer retention (e. . , Bolton, Kannan, and Bramlett 2000). In contrast, the effect of RMIs on customer share has been overlooked. Furthermore, most studies focus on customer share in a particular product category (e. g. , Bowman and Narayandas 2001). Higher sales of more of the same product or brand can increase this share; however, firms that sell multiple products or services achieve share increases by cross-selling other products. Moreover, no study has consider ed the effect of CRPs and RMIs on both customer retention and customer share. It is often assumed in the literature that the same strategies used for maximizing customer share can be used to retain customers; however, recent studies indicate that increasing customer share might require different strategies than retaining customers (Blattberg, Getz, and Thomas 2001; Bolton, Lemon, and Verhoef 2002; Reinartz and Kumar 2003). Prior studies have used self-reported, cross-sectional data that describe both CRPs and customer share (e. g. , De Wulf, Odekerken-Schroder, and Iacobucci 2001). The use of such data may have led to overestimation of the considered associations because of methodological problems such as carryover and backfire effects and common method variance (Bickart 1993). Such data cannot establish a causal relationship; indeed, the argument could be made that causality works the other way (i. e. , I am loyal, therefore I like the company) (Ehrenberg 1997). Longitudinal data rather than cross-sectional data should be used to establish the causal relationship between customer share and its antecedents. Journal of Marketing Vol. 7 (October 2003), 30–45 30 / Journal of Marketing, October 2003 I have the following research objectives: First, I aim to understand the effect of CRPs and RMIs on customer retention and customer share development over time. Second, I examine whether the effect of CRPs and RMIs on customer retention and customer share development is different. My study analyzes questionnaire data on CRPs, operational data on the applied RMIs, and longitudinal data on customer retention and customer share of a (multiservice) financial service provider. Literature Review CRPs and Customer Behavior Table 1 provides an overview of studies that report the effect of CRPs on customer behavior, and it describes the dependent variables, the design and context of the study, the CRPs studied, and the effect of CRPs on behavioral customer loyalty measures (which can be self-reported or actual observed loyalty measures). Table 1 shows that the results of studies that relate CRPs to actual customer behavior are mixed. RMIs and Customer Behavior Table 2 provides an overview of the limited number of academic studies that consider the effect of RMIs. The majority of the studies have focused on loyalty or preferential treatment programs, and the results show mixed effects of these programs on customer loyalty. Despite the intensive use of direct mailings in practice, their effect on customer loyalty has almost been ignored. More important, the effect of RMIs on customer share development over time has not been investigated. tomer relationship largely depends on the applied RMIs (Bhattacharya and Bolton 2000; Christy, Oliver, and Penn 1996; De Wulf, Odekerken-Schroder, and Iacobucci 2001). Moreover, because of the increasing popularity of CRM among businesses, an increasing number of firms are using RMIs. In the model, I also include customers’ past behavior in the relationship as control variables, which might capture inertia effects that are considered important determinants of customer loyalty in business-to-consumer markets (Dowling and Uncles 1997; Rust, Zeithaml, and Lemon 2000). Past customer behavioral variables (e. g. , relationship age, prior customer share) can also be indicators of past behavioral loyalty, which often translates into future loyalty. Prior research suggests that the type of product purchased in the past is an indicator of future cross-selling potential (e. g. , Kamakura, Ramaswami, and Srivastava 1991). Hypotheses CRPs Relationship marketing theory and customer equity theory posit that customers’ perceptions of the intrinsic quality of the relationship (i. e. , strength of the relationship) and customers’ evaluations of a supplier’s offerings shape customers’ behavior in the relationship (Garbarino and Johnson 1999; Rust, Zeithaml, and Lemon 2000; Woodruff 1997). The most prominent perception representing the strength of the relationship is (affective) commitment (Moorman, Zaltman, and Desphande 1992; Morgan and Hunt 1994). Because satisfaction and payment equity are important constructs with respect to the evaluation of a supplier’s offerings (Bolton and Lemon 1999), I included these three constructs in the model. The two categories of constructs differ in terms of both content and time orientation: Affective commitment is forward looking, whereas satisfaction and payment equity are retrospective evaluations. In the customer equity and relationship marketing literature, other CRPs that are not included in my model are often studied. Trust and brand perceptions are the most prominent of these variables (Morgan and Hunt 1994; Rust, Zeithaml, and Lemon 2000). I did not include brand perceptions because the focus is on current customers. My contention is that the brand is especially significant in attracting new customers. During the relationship, the brand probably influences affective commitment (Bolton, Lemon, and Verhoef 2002). I did not include trust, because trust should be considered merely an antecedent of satisfaction and commitment (Geyskens, Steenkamp, and Kumar 1998). No direct effect on customer behavior should be expected. Affective Commitment Commitment is usually defined as the extent to which an exchange partner desires to continue a valued relationship (Moorman, Zaltman, and Desphande 1992). I focus on the affective component of commitment, that is, the psychological attachment, based on loyalty and affiliation, of one exchange partner to the other (Bhattacharya, Rao, and Glynn 1995; Gundlach, Achrol, and Mentzer 1995). Customer Relationship Management Efforts / 31 Conceptual Model Figure 1 shows the conceptual model. In this model, I consider customer retention and customer share development between two periods (T1 and T0) as the dependent variables, which are affected by CRPs and RMIs. Because I consider customer retention and customer share development as two separate processes, relationship maintenance and relationship development, the underlying hypotheses of the model explicitly predict that different constructs of CRPs, and different RMIs influence customer retention and customer share development. The rationale for this distinction is that a customer’s decision to stay in a relationship with a firm may be different from his or her incremental decision to add or drop existing products. Consistent with this notion, Blattberg, Getz, and Thomas (2001) argue that customer retention is not the same as customer share, because two firms could retain the same customer. Reinartz and Kumar (2003) suggest that relationship duration and customer share should be considered as two separate dimensions of the customer relationship. Bolton, Lemon, and Verhoef (2002) propose that the antecedents of customer retention might be different from the antecedents of cross-buying behavior. I explicitly address these differences in the hypotheses. The inclusion of CRPs as antecedents of retention and customer share development is based on relationship marketing theory, which suggests that CRPs affect behavioral customer loyalty. I included RMIs because a successful cus- TABLE 1 Overview of Studies on Effect of CRPs on Behavioral Loyalty Examples of Studies Study Design Study Context Included Perceptions (Effect) Additional Results/Comments Behavioral Loyalty Measurement Self-Reported Purchase intentions Anderson and Sullivan (1993) Morgan and Hunt (1994) Cross-sectional Cross-sectional Cross-sectional Longitudinal Cross-sectional Cross-sectional Retailing Retailing Car market Theater visitors Satisfaction (+), commitment (–) Satisfaction (+) Commitment (+) Relationship quality (+) Satisfaction (+) Various industries Channels Benefits (+), commitment (+) Service quality (+) Experiment Various industries Satisfaction (+) 32 / Journal of Marketing, October 2003 Zeithaml, Berry, and Parasuraman (1996) Garbarino and Johnson (1999) Mittal, Kumar, and Tsiros (1999) Macintosch and Lockshin (1997) De Wulf, OdekerkenSchroder, and Iacobucci (2001) Bowman and Narayandas (2001) Cross-sectional Grocery brands Gruen, Summers, and Acito (2000) Bolton (1998) Longitudinal Longitudinal Longitudinal Cross-sectional Professional association Telecommunications Credit card Car market Commitment (0) Satisfaction (+) Satisfaction (+), payment equity (+) Satisfaction (+) Bolton, Kannan, and Bramlett (2000) Mittal and Kamakura (2001) Lemon, White, and Winer (2002) Longitudinal Entertainment Satisfaction (0) Longitudinal Longitudinal Longitudinal Telecommunications, entertainment Credit card Financial services Satisfaction (+) Bolton and Lemon (1999) Bolton, Kannan, and Bramlett (2000) Verhoef, Franses, and Hoekstra (2001) Satisfaction (+), payment equity (+) Satisfaction (0), payment equity (0) Effect depends on relationship orientation of customer Customer share Quadratic effect of satisfaction Observed Customer retention and/or relationship duration Service usage Cross-buying Effect of satisfaction enhanced by relationship age Performance differences with other firms are important Effect of satisfaction moderated by consumer characteristics Effect of satisfaction mediated by future expected service usage Payment equity positively affects satisfaction Performance differences with other firms are important Effect of satisfaction and payment equity enhanced by relationship age Effect on customer retention. Given the previous definition of affective commitment, it might be expected that this type of commitment affects customer retention positively. In line with this, researchers who relate commitment to selfreported behavior, such as purchase intentions, usually find that commitment positively affects customer loyalty (e. g. , Garbarino and Johnson 1999; Morgan and Hunt 1994). However, the appearance of such an effect has recently been questioned (Gruen, Summers, and Acito 2000; MacKenzie, Podsakoff, and Ahearne 1998). Despite this, I hypothesize the following: H1: Affective commitment positively affects customer retention. from a particular supplier (Oliver and Winer 1987). This depends on, among other things, the customer’s satisfaction level. As a consequence, customers who are more satisfied are more likely to remain customers. Thus: H3: Satisfaction positively affects customer retention. Effect on customer share development. Relationship marketing theory posits that because affectively committed customers believe they are connected to the firm, they display positive behavior toward the firm. As a consequence, affectively committed customers are less likely to patronize other firms (Dick and Basu 1994; Morgan and Hunt 1994; Sheth and Parvatiyar 1995). In other words, committed customers are more (less) likely to increase (decrease) their customer share for the focal supplier over a period of time. H2: Affective commitment positively affects customer share development over time. Effect on customer share development. Although a positive relationship between satisfaction and customer share has been demonstrated in a single product category (Bowman and Narayandas 2001), this does not necessarily imply that satisfaction also positively affects customer share development for a multiservice provider. A theoretical explanation for the absence of such an effect could be that positive evaluations of currently consumed products or services do not necessarily transfer to other offered products or services. In other words, satisfied customers are not necessarily more likely to purchase additional products or services (Verhoef, Franses, and Hoekstra 2001). Another explanation is that though customer retention relates to the focal supplier alone, customer share development also involves competing suppliers. As a result, development of a customer’s share might be affected more by the actions of competing suppliers than by the focal firm’s prior performance. Thus, I do not expect satisfaction to have a positive effect on customer share development. Payment Equity Payment equity is defined as a customer’s perceived fairness of the price paid for the firm’s products or services (Bolton and Lemon 1999, p. 73) and is closely related to the customer’s price perceptions. Payment equity is mainly affected by the firm’s pricing policy. As a result of its grounding in fairness, a firm’s payment equity also depends on competitors’ pricing polici es and the relative quality of the offered services or products. Effect on customer retention. Higher payment equity (i. e. , price perceptions) leads to greater perceived utility of the purchased products or services (Bolton and Lemon 1999). As a result of this greater perceived utility, customers should be more likely to remain with the firm. Consequently, payment equity should have a positive effect on customer retention. This is consistent with empirical studies that show that payment equity positively affects customer retention (Bolton, Kannan, and Bramlett 2000; Varuki and Colgate 2001). Thus: H4: Payment equity positively affects customer retention. Satisfaction I define satisfaction in this study as the emotional state that occurs as a result of a customer’s interactions with the firm over time (Anderson, Fornell, and Lehmann 1994; Crosby, Evans, and Cowles 1990). Szymanski and Henard’s (2001) meta-analysis shows that satisfaction has a positive impact on self-reported customer loyalty. Despite such positive results in the literature, the link between satisfaction and actual customer loyalty has been questioned (e. . , Jones and Sasser 1995). Researchers have searched for a better understanding of this link and have proposed a nonlinear relationship between satisfaction and customer behavior (e. g. , Anderson and Mittal 2000; Bowman and Narayandas 2001). Other studies have shown tha t relationship age, product usage, variety seeking, switching costs, consumer knowledge, and sociodemographics (e. g. , age, income, gender) moderate the link between satisfaction and customer loyalty (Bolton 1998; Bowman and Narayandas 2001; Capraro, Broniarczyck, and Srivastava 2003; Homburg and Giering 2001; Jones, Mothersbaugh, and Beatty 2001; Mittal and Kamakura 2001). Finally, dynamics during the relationship may also affect this link. Customers update their satisfaction levels using information gathered during new interaction experiences with the firm, and this new information may diminish the effect of prior satisfaction levels (Mazursky and Geva 1989; Mittal, Kumar, and Tsiros 1999). Effect on customer retention. Despite the apparent absence of an empirical link between satisfaction and behavioral customer loyalty, several studies show that satisfaction affects customer retention (Bolton 1998; Bolton, Kannan, and Bramlett 2000). The underlying rationale is that customers aim to maximize the subjective utility they obtain Effect on customer share development. Although I expect payment equity to have a positive effect on customer retention, I do not necessarily expect this to be true for customer share development. There are two reasons payment equity may have no effect on customer share development. First, literature on price perceptions suggests that customers with higher price perceptions are more likely to search for better prices (Lichtenstein, Ridgway, and Netemeyer 1993). Intuitively, the suggestion that such customers are less loyal makes sense. For example, customers of discounters (with high scores on price perceptions) are known to visit the greatest number of stores in their search for the best bargain. Customer Relationship Management Efforts / 33 TABLE 2 Studies on Effect of RMIs on Behavioral Loyalty Study Aggregated purchase shares Customer share Cross-sectional survey, perceptions on direct mail use — Aggregated panel data Panel design Loyalty Measure Study Design Study Context Grocery brands Retailing Results Short-term positive effect on purchase rates No effect 34 / Journal of Marketing, October 2003 No empirical data Aggregated penetration, average purchase frequency, customer share, sole buyers Purchase intentions — Retailing — Cross-sectional survey data, perceptions on loyalty program use Longitudinal Cross-sectional survey data, perceptions on preferential treatment programs Airlines Positive effect Customer retention, service usage Customer share Credit card Retailing No effect RMI Direct mail Bawa and Shoemaker (1987) De Wulf, Odekerken-Schroder, and Iacobucci (2001) Loyalty programs Dowling and Uncles (1997) Sharp and Sharp (1997) No convincing effect of loyalty programs Rust, Zeithaml, and Lemon (2000) Bolton, Kannan, and Bramlett (2000) Positive effect on retention and service usage De Wulf, Odekerken-Schroder, and Iacobucci (2001) FIGURE 1 Conceptual Model CRPs Satisfaction H3 H4 Payment equity H1 H2 Affective commitment ? Customer share T 1 T0 Customer retention T 1 T0 H6a H6b H5 Loyalty program RMIs Direct mailings Control Variables Customer share T0 Relationship age T0 Type of service purchased T0 According to this reasoning, customers with better price perceptions are more likely to decrease customer share over time. Second, as is satisfaction, a customer’s payment equity is based on the customer’s awareness of the prices of services or products purchased from the focal firm in the past (Bolton, Lemon, and Verhoef 2002). However, the prices of additional services or products from the focal supplier might be different from the currently purchased services or products. Therefore, a high payment equity score may not indicate that the customer will purchase other products or services from the same supplier. As a consequence, I do not expect payment equity to affect customer share development. RMIs Bhattacharya and Bolton (2000) suggest that RMIs are a subset of other marketing instruments that are specifically aimed at facilitating the relationship, and they distinguish between loyalty or reward programs and tailored promotions. In addition, RMIs can be classified according to Berry’s (1995) first two levels of relationship marketing. At the first level (Type I), firms use economic incentives, such as rewards and pricing discounts, to develop the relationship. At the second level (Type II), instruments include more social attributes. By using Type II instruments, firms attempt to give the customer relationship a personal touch. In this study, I focus on two specific Type I RMIs: direct mailings and loyalty programs. Direct mailings usually are personally customized offers on products or services that the customer currently does not purchase. In most cases, price discounts or other sales promotions (e. g. , gadgets) are used to entice the customer to buy. I focus on direct mailings that are a â€Å"call to action† rather than only a reinforcing mechanism for the relationship (e. g. , thank-you letters). The loyalty program I include in the study is a reward program that provides price discounts based on the number of products or services purchased and the length of the relationship. Direct Mailings Direct mailings have some unique characteristics: enablement of personalized offers, no direct competition for the attention of the customer from other advertisements, and a capacity to involve the respondent (Roberts and Berger 1999). Because direct mailings focus on creating additional sales, I do not expect them to influence customer retention. Moreover, the data do not enable me to relate direct mailings to customer retention. Effect on customer share development. There are several theoretical reasons direct mailings should positively influence customer share development. First, direct mailings can create interest in a (new) service and thereby lead to a final purchase (Roberts and Berger 1999). Second, the personalization afforded by direct mailings may increase perceived relationship quality, because customers are approached with individualized communications that appeal to their specific needs and desired manner of fulfilling them (De Wulf, Odekerken-Schroder, and Iacobucci 2001; Hoekstra, Leeflang, and Wittink 1999). Third, according to the sales promotions literature, the short-term rewards (i. e. , price discounts) offered by direct mailings may motivate customers to purchase additional services and thus increase customer share. In support of this claim, Bawa and Shoemaker (1987) report short-term gains in redemption rates of direct mail coupons. I hypothesize the following: H5: Direct mailings positively affect customer share development over time. Loyalty Programs Effect on customer retention and customer share development. There are several theoretical reasons the rewardbased loyalty program being studied should positively affect both customer retention and customer share development. First, psychological investigations show that rewards can be highly motivating (Latham and Locke 1991). Research also shows that people possess a strong drive to behave in whatCustomer Relationship Management Efforts / 35 ever manner necessary to achieve future rewards (Nicholls 1989). According to Roehm, Pullins, and Roehm (2002, p. 203), it is reasonable to assume that during participation in a loyalty program, a customer might be motivated by program incentives to purchase the program sponsor’s brand repeatedly. Second, because the program’s reward structure usually depends on prior customer behavior, loyalty programs can provide barriers to customers’ switching to another supplier. For example, when the reward structure depends on the length of the relationship, customers are less likely to switch (because of a time lag before the same level of rewards can be received from another supplier). It is well known that switching costs are an important antecedent of customer loyalty (Dick and Basu 1994; Klemperer 1995). Despite the theoretical arguments in favor of the positive effect of loyalty programs on customer retention and customer share development, several researchers have questioned this effect (e. g. , Dowling and Uncles 1997; Sharp and Sharp 1997). In contrast, Bolton, Kannan, and Bramlett (2000) and Rust, Zeithaml, and Lemon (2000) show that loyalty programs have a significant, positive effect on customer retention and/or service usage. In this study, I build on the theoretical argument in favor of the positive effect that loyalty programs have on customer retention and customer share development. H6: Loyalty program membership positively affects (a) customer retention and (b) customer share development. products, and customer characteristics. In the second (T1) survey, I collected data on customer ownership of various insurance products. Although the company whose data I used offers other products, such as loans, I limited the study to the category of insurance products. The rationale for this limitation is that customers usually buy each type of insurance product from a single insurance carrier (i. e. insurance type X [life insurance] from insurance carrier Y [i. e. , Allianz Life Company]), but this does not necessarily hold for other financial products or services. For example, it is well known that many customers have savings accounts at several financial institutions. Moreover, the insurance market is the most important market for this company in terms of the number of customers and customer turnover (approximately 90%). As a result of this choice, the sample is restricted to those customers who purchase insurance products only from the company. This resulted in a usable sample size of 1677 customers for the first measurement (T0) and 918 for the second measurement (T1). Contents of the Company Customer Database The company’s customer database provided data on the past behavior of individual customers and the company RMIs directed at individual customers. The past customer behavior data cover two periods. The first period starts at the beginning of a relationship between the company and the customer and ends at T0 (this period differs among customers). The data on past customer behavior included variables such as number of insurance policies purchased, type of insurance policies purchased, and relationship length. The second period covers the interval between T0 and T1. For this period, the database provided data about which customers left the company and the number of company insurance policies a customer owned at T1. The company’s customer database contains the following information on RMIs: loyalty program membership at T0 and the number of direct mailings sent between T0 and T1. Every customer who purchases one or more financial Research Methodology Research Design I combined survey data from customers of a Dutch financial services company with data from that company’s customer database. I used a panel design, displayed in Figure 2, to collect the data. I collected the survey data at two points in time: T0 and T1. I used the first (T0) survey to measure CRPs of the company, customer ownership of various insurance FIGURE 2 Panel Design Data from Customer Database Start of Relationship T 0 (Survey 1 Among Customers) T 1 (Survey 2 Among Customers Interviewed in Survey 1) 6 / Journal of Marketing, October 2003 services from the company can become a member of the loyalty program (an opt-in program). At the end of each year, the program gives customers a monetary reward based on the num ber of services purchased and the age of the relationship. Because the company uses regression-type models to select the customers with the highest probability of responding to direct mailings, the number of direct mailings sent differs among customers. Customer Survey Data Collection At T0, customer survey data were collected by telephone from a random sample of 6525 customers of the company. A quota sampling approach was used to obtain a representative sample. I received data from 2300 customers (35% response rate). After those responses with too many missing values were deleted, a sample size of 1986 customers remained. At T1, I again collected data from those customers, except for those who left the company between T0 and T1. In the second data collection effort, 1128 customers were willing to cooperate (65% response rate). To assess nonresponse bias at T1, I tested whether respondents and nonrespondents differed significantly with respect to customer share at T0. A ttest does not reveal a significant difference (p = . 36). Thus, I conclude that there is no nonresponse bias. Measurement of CRPs For the measurement of CRPs (i. e. affective commitment, satisfaction, and payment equity), I adapted existing scales to fit the context of financial services. For the affective commitment scale, I adapted items from the studies of Anderson and Weitz (1992), Garbarino and Johnson (1999), and Kumar, Scheer, and Steenkamp (1995). To measure satisfac tion, I adapted Singh’s (1990) scale and added four new items. Finally, I based the payment equity scale on items adapted from Bolton and Lemon’s (1999) and Singh’s (1990) studies. To assess construct validity and clarify wording, the original scales were tested by a group of 12 marketing academics and 3 marketing practitioners familiar with customer relationships. Subsequently, the scales were tested by a random sample of 200 customers of the company. On the basis of interitem correlations, item-to-total correlations, coefficient alpha, and exploratory and confirmatory factor analysis, I reduced the set of items in each scale. 1 1I follow Steenkamp and van Trijp’s (1991) proposed method, using exploratory factor analysis and then confirmatory factor analysis to validate marketing constructs. Validation of CRPs The final measures are reported in the Appendix. The scales for commitment and satisfaction have reasonable coefficient alphas. For payment equity, I report a correlation coefficient of . 49, which is not considerably high. 2 However, note that the reported composite reliabilities of all scales are sufficient (Bagozzi and Yi 1988). I applied confirmatory factor analysis in Lisrel 83 to further assess the quality of the measures (Joreskog and Sorbom 1993), and I achieved the following model fit: ? 2 = 217. 4 (degrees of freedom [d. f. ]) = 51, p . 10; ? = . 03, p gt; . 10; customer share development: ? = . 01, p gt; . 10; ? = –. 01, p gt; . 10). In addition, I reestimated both models, leaving out satisfaction and payment equity. The parameter estimates for commitment were significant in both models (customer retention: ? = . 17, p lt; . 05; customer share development: ? = . 02, p lt; . 01). Finally, I estimated a regression model in which I related satisfaction and payment equity to commitment. The parameters of both satisfaction and payment equity were positive and significant (? = . 61, p lt; . 01; ? = . 09, p