REUNIONES GRUPALES

The most significant attempts to define customer perceived switching costs in the extant literature are presented in Table 2-2. In searching for the best description of switching costs in the B2C context, perhaps the most helpful conceptualisation is provided by Patterson and Smith (2003). They viewed switching costs as “the perception of the magnitude of the additional costs required to terminate a relationship and secure an alternative one” (p. 108). Another way of explaining switching costs is as a “disutility that consumers would rather not incur” (Burnham et al. 2003, p. 115).

According to Fornell (1992), while satisfaction makes it harder for competitors to take away a firm’s customers, switching costs make it costly for customers to defect to competitors. Indeed, switching costs can be more

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critical an antecedent to customer retention than satisfaction because customers tend to attribute greater weight to them when making decisions (Dick and Basu 1994). As suggested in the theory of self-perception, losses always loom larger than benefits (Zauberman 2003). The presence of switching costs is one of the key factors explaining the imperfect correlation between satisfaction and loyalty (Balabanis et al. 2006; Gremler 1995). Switching costs are thus recognised as one of the core predictors of customer retention that can lead to more long-lasting and stable customer loyalty (Bendapudi and Berry 1997; Dick and Basu 1994; Oliver 1997; Polo and Sesé 2009).

Review of empirical studies of switching costs from marketing streams has produced mix findings of the role of switching costs in customer retention or loyalty formation (as shown in Table 2-1, p. 44). Torres and Martins (2009, p. 168) also concurred with this view, noting the presence of “conflicting results across empirical studies concerning the main effects as well as asymmetrical, moderating and interaction effects of switching costs between satisfaction and the loyalty relationship.”

Agreement among scholars on the direct influence (main effects) of switching costs in predicting switching behaviour in both B2C online and offline retailing is virtually unanimous (Balabanis et al. 2006; Bendapudi and

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Berry 1997; Burnham et al. 2003; Fornell 1992; Jones et al. 2000; Ranaweera and Prabhu 2003; Yang and Peterson 2004). There is empirical evidence that switching costs influence customer loyalty directly, both in the offline (Bell et al. 2005; Burnham et al. 2003; Patterson and Smith 2003; Ranaweera and Prabhu 2003) and online (Balabanis et al. 2006; Tsai and Huang 2007) service or retail environments. For example, Burnham et al.’s (2003) study on clients of credit card firms and long distance phone providers found switching costs to have a direct influence on customers’ repurchase intention. They also concluded that switching costs function as a better predictor of customer retention than satisfaction, explaining 16 per cent and 30 per cent of variance (on repurchase intention) respectively. However, Burnham et al. (2003) found only the main effect of switching costs on customer retention, not the moderating effect. Similarly, Tsai et al. (2006), surveying customers of one Taiwanese e-retailer, also found switching costs to have greater influence on repurchase intention. They concluded that switching costs explain 59 per cent of the variance of repurchase intention, far exceeding satisfaction, which explains just 36 per cent.

However, although most studies have found the direct effect between switching costs and loyalty formation, interestingly, there other studies that have found the absence or lack of main effects between switching costs and customer retention or loyalty (e.g., Jones et al. 2000; Lee, Kim and Moon

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2000; Methlie and Nysveen 1999; Yang and Peterson 2004). Although the main or direct effect of switching costs on repurchase intentions was not significant for Jones et al. (2000), their study on customers of banks and hair salons found that switching costs interact negatively with satisfaction to influence customer behavioural intentions. In other words, Jones et al. (2000) finds that while switching cost effects are evident; these effects only emerge as consumers become less satisfied with the core service offered, i.e., switching costs increase customer retention when satisfaction is low. This somewhat concurs with social exchange theory, which posits that in personal relationships, individuals start to perceive and/or experience switching costs when satisfaction with their current relationship begins to decrease. Jones et al. (2000) also noted that “the absence of main effects only serves to reinforce

[their] core thesis that a main effect approach is not sufficient to capture the complex processes underlying customer retention” (p. 268).

On the other hand, in the online settings, the interaction effects of switching costs have been found only under certain conditions. Balabanis et al. (2006) revealed that switching costs moderate the satisfaction and loyalty link only when satisfaction is perceived by online shoppers as below average. However, this contradicts the findings of Yang and Peterson (2004), namely, that switching costs only moderate the relationship between value and loyalty when value and/or satisfaction are/is perceived as higher than average

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by online shoppers. Balabanis et al.’s (2006) result somewhat concurs with Jones and colleagues’ (2000) offline study, which found that only when the level of satisfaction falls below a certain level does the customer feel the effect of switching costs on loyalty.

Interestingly, other research has also found the interaction effects of switching costs in their research models; however, these effects are positive

rather than negative. For example, Lam et al. (2004), in examining the linkages between satisfaction, perceived value, switching costs and client loyalty of a courier service provider (an offline service), found a positive interaction effect of switching costs and satisfaction on predicting loyalty.

Other studies have also suggested both direct and interaction effects of the switching costs construct in their models. For instance, Shin and Kim (2008), when predicting the switching behaviour of clients in the mobile phone service, concluded that switching costs positively affect intention to switch directly as well as indirectly, through their interactions with clients’ satisfaction. These results are comparable to another study (in a similar industry), where switching costs were found to have a positive, direct influence on retention through their interaction with customer satisfaction (Ranaweera and Prabhu 2003).

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These mixed results and the lack of a main effect of switching costs in terms of predicting customer retention or loyalty warrant further investigation. Such divergence in findings may actually stem from certain measurement issues relating to switching costs, the different way that switching costs are measured as well as the research contexts and research settings.

2.6.1.1Unidimensional versus Multidimensional Measure

Burnham et al. (2003) and Jones et al. (2002) mention that the customer switching cost literature is dominated by research conceptualising the construct as unidimensional, hence utilising a global measure to estimate switching costs. Again, referring to Table 2-1 (p. 44), most online studies using switching costs as an important construct typically either measure switching costs as a global construct or measure only selected switching costs. At a higher-level of abstraction in the customer’s cognitive structure, perceived switching costs are suggested by some scholars to be complex and difficult to measure (e.g., Fornell 1992). Due to this complexity and subjectivity, researchers have questioned the credibility of a single global measure of perceived switching costs. According to Bagozzi and Edwards (1998), multidimensional measurement is crucial to test complex constructs because

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a single global measure is not sufficient to capture the richness of perceived switching costs (Burnham 1998). As suggested by Torres and Martins (2009),

“...a more balanced set of [switching costs] measures is needed, allowing to reflect the multidimensionality of the construct which potentially increases its explanatory power.” (p. 169)

The following discussion synthesises the various types of customer perceived switching costs found in the literature.