Research Note–Online Users' Switching Costs: Their Nature and Formation

Research Note–Online Users' Switching Costs: Their Nature and Formation

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Article ID: iaor20123008
Volume: 23
Issue: 1
Start Page Number: 197
End Page Number: 213
Publication Date: Mar 2012
Journal: Information Systems Research
Authors: , ,
Keywords: retailing, statistics: inference, statistics: empirical, statistics: multivariate, statistics: regression
Abstract:

The highly competitive and rapidly changing market for online services is becoming increasingly effective at locking users in through the coercive effects of switching costs. Although the information systems field increasingly recognizes that switching costs plays a big part in enforcing loyalty, little is known about what factors users regard as switching costs or why they perceive these costs. Consequently, it is hard for online services to know what lock‐in strategies to use and when to apply them. We address this problem by first developing a theory‐driven structure of online users' perceived switching costs that distinguishes between vendor‐related and user‐related factors. We then propose that important antecedent influences on switching costs from economic value, technical self‐efficacy, and past investments are more complex and intertwined than previously thought. We empirically validated the proposed model using data collected from home users of Internet service providers. Our findings demonstrate that an online service's economic value more heavily influences users' perceptions of vendor‐related switching costs than does technical self‐efficacy. However, users' technical abilities outweigh economic value in influencing user‐related switching costs. Furthermore, although we confirmed the commonly held notion that deeply invested users are generally more vulnerable to lock‐in, we also found that this relationship is contingent on users' technical abilities. Finally, we found that our multidimensional measure of switching costs is a valid predictor of user loyalty and is more powerful than previous global measures. Overall, this study uncovered a finer network of switching‐cost production than had been previously established and suggests a new approach to modeling and exploiting online users' perceived switching costs.

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