Analyzing the Impact of Public Buyer–Seller Engagement During Online Auctions - Tripathi, Arvind K.; Lee, Young-Jin; Basu, Amit (Information Systems Research, 2022)
Information asymmetry between sellers and buyers is inherent in online markets where transactions often occur between strangers. Trust-building mechanisms such as seller feedback ratings have reduced these problems because a seller’s feedback ratings build buyers’ trust in the seller before they engage in a transaction. However, these ratings are retrospective, that is, they generate information about a transaction after it is completed, rather than during the transaction itself. Additionally, they are based on other users’ experiences, possibly in different contexts, not based on any direct interaction between the prospective buyer and the seller. To address this problem, we study public buyer–seller engagement via question and answer during online auctions and find that seller engagement (responding to buyers’ questions) can affect buyer behavior, including those who do not ask any questions. Our analysis shows that the impact of the seller’s engagement on buyer behavior varies with product type and seller reputation (feedback ratings). A key insight is that sellers with higher reputation reap greater benefits from this engagement than other sellers. We also find that the cost of an additional negative feedback rating outweighs the benefit of a positive one.