PhD Seminar Series: The Social Process of Reputation Convergence: Unpacking How Reputational Communities Produce Collective Assessments

The Social Process of Reputation Convergence: Unpacking How Reputational Communities Produce Collective Assessments

Speaker: Yang Jiang

Abstract: This research challenges the dominant “online review aggregator” perspective, which assumes that an organization’s online reputation results from aggregating independent, isolated evaluations. Instead, this research argues that online reputation is socially constructed, as reviewers attend to and are influenced by prior evaluations in an environment of uncertainty. Building on this view, it is conceptualized that online rating platforms comprise multiple reputational communities, in which evaluations of the same organization become increasingly aligned. Drawing on social influence theory and the visibility of social cues on rating platforms, this research proposes community size, evaluators' similarity in evaluation preferences, and the number of high-status evaluators as three community structural characteristics. It contends that the first two factors contribute to evaluation convergence. Further, the greater influence of high-status evaluators moderates the convergence effect in different ways; it strengthens the positive effect of evaluator similarity on evaluation convergence while weakening that of community size. Using Yelp data on U.S. restaurants, this research finds supportive evidence for the arguments. By theorizing online reputation formation as a community-level, socially influenced process, this study advances research on online organizational reputation and provides new insights into how reputational dynamics unfold in online review environments.