Author List: Ray, Soumya; Kim, Sung S.; Morris, James G.;
Information Systems Research, 2012, Volume 23, Issue 1, Page 197-213.
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 lockin, 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.
Keywords: online consumer behavior; partial least squares; structural equation modeling; survey data; switching costs
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#151 0.209 costs cost switching reduce transaction increase benefits time economic production transactions savings reduction impact services reduced affect expected optimal associated
#130 0.169 online users active paper using increasingly informational user data internet overall little various understanding empirical despite lead cascades help availability
#134 0.098 users end use professionals user organizations applications needs packages findings perform specialists technical computing direct future selection ability help software
#26 0.058 business large organizations using work changing rapidly make today's available designed need increasingly recent manage years activity important allow achieve
#108 0.053 model research data results study using theoretical influence findings theory support implications test collected tested based empirical empirically context paper
#112 0.053 services service network effects optimal online pricing strategies model provider provide externalities providing base providers fee complementary demand offer derive