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Sustaining firm -customer dialogs: A model of technology -mediated personalization (TMP) and relationship continuity
Abstract
Do consumers accept learning relationships? Proponents have argued that companies can use information technology to engage customers in ongoing collaborative dialogs and maintain "organizational memory" of individual customer preferences, behavior patterns, and other characteristics. Skeptics have noted that company efforts to offer "personalization" through information technology may heighten privacy concerns and undermine customer trust rather than foster meaningful relationships. However, few empirical studies have tested this issue of interest to marketers. We studied this issue in the context of the increasing use of recommendation agents in services (e.g., TiVo, Amazon). We introduced the notion of technology-mediated personalization (TMP). We then proposed the Model of TMP and Relationship Continuity, in which agent behavioral characteristics (accuracy, benevolence, and process value) directly affect trust, relational value, and switching barriers and indirectly affect relationship commitment and intention to use the agent. We tested the model in a sample of 273 actual users of recommendation agents. Our research yielded affirmative evidence as well as surprises. Contrary to the skeptical views of learning relationships, we find that two of the three dimensions of agent recommendation behavior (accuracy and benevolence) had significant indirect impacts (fully mediated by trust and switching barriers) on relationship commitment. Process value directly affected the intention to use the agent. Our findings are also surprising compared with the previous assumptions of learning relationships. First, we empirically established that customized fit represents only one of the three facets of TMP. Second, rather than confirming the popular belief that accuracy, or customized fit, is the dominant contributor to switching barriers and customer loyalty, our findings suggest that recommendation benevolence is the more important influence on switching barriers and relationship commitment. Another surprise comes from the finding that the single most important determinant of the intention to use recommendation agents was the perceived hedonic process of interacting with the agent, rather than the utilitarian function of obtaining accurate recommendations (customized fit) or the perception of benevolence in making recommendations.
Subject Area
Marketing|Information Technology
Recommended Citation
Shen, Anyuan (Daniel), "Sustaining firm -customer dialogs: A model of technology -mediated personalization (TMP) and relationship continuity" (2007). ETD collection for University of Nebraska-Lincoln. AAI3255892.
https://digitalcommons.unl.edu/dissertations/AAI3255892