WangLe / School of Economics and Finance, Xi 'an Jiaotong University
Cuixueying / School of Economics and Finance, Xi 'an Jiaotong University
The direct consequences of review manipulation have been well documented in literature, while its spillover effect received surprisingly little attention in academia. On the one hand, competitors might suffer from a focal firm’s review manipulation due to the market diverting effect, refers to the fact that the focal firm will wrest consumers and market shares from its competitors and the negative contagion effect caused by the fact that individual wrongdoings being extrapolated to the whole seller group. On the other hand, competitors might benefit from a focal firm’s review manipulation as consumers, once identified firm’s review manipulation, may shift from that firm to its competitors, leading the positive competitive effect. Platform-based business forms a dual structure of the reputation system including an individual reputation of the seller and a collective reputation of the seller group. Integrating social cognitive theory and the accessibility–diagnosticity framework, we theorize that the interplay between seller’s collective and individual reputation will activates one of the three paths, leading to heterogeneous spillover effects of seller’s review manipulation. Analyses of more than one million observations from two leading online reservation platforms in China show that: (1) for high collective reputation sellers, review manipulation activates the market diverting effect and impedes the sales of both their direct and in-direct competitors; (2) for sellers with low collective reputation but high individual reputation, review manipulation activates the negative contagion effect and impedes the sales of their direct competitors, but fuels the sales of their in-direct competitors; (3) for sellers with low collective and individual reputation, review manipulation activates the positive competitive effect and fuels the sales of both their direct and indirect competitors. These findings survive a myriad of robust examinations, including the use of a set of subsample analyses, alternative measures of independent and depedent variables, alternative causal identification techniques, and alternative observation time windows. The findings have design implications for marketers and platform managers and contribute to our understanding of how seller’s manipulation of online reviews, depending on the interplay between seller’s individual and collective reputation, can either benefit or hurt its competitors.