Information revelation and customer decision-making process of repeat-bidding name-your-own-price auction

Abstract

Information revelation has become increasingly popular among name-your-own-price (NYOP) providers as a strategy to influence buyers' behavior and facilitate the transaction success rate in industrial practice. However, the mechanism underlying how disclosed information affects a bidder's decision-making process, as well as the consequent bidding results, remains unknown. In this study, we adopted an adapted dynamic choice model to simulate the bidders' decision process, which led to our proposal of a novel mechanism to explain how specific price information affects bidders' willingness to pay, expectation on threshold price and haggling willingness. The relationship model was then tested using real transaction data from the Shanghai Steel Transaction Center, one of the biggest steel spot transaction platforms in China that employs the NYOP pricing system. Our empirical results showed that a bidder's haggling behavior can be influenced by both personal transaction experience and revealed environmental information; therefore, sellers who intend to hinder haggling behavior can choose to reveal list price information that is more consistent with their bidders' internal reference price. Interestingly, we also found that haggling behavior may not always be harmful because it can enhance the bidders' net utility under certain conditions. Analysis of the combined effects on customer behavior—when more than one kind of relevant price information is disclosed—showed that additional market condition information (i.e., market price fluctuation) has a moderating effect on how current revealed list price information influences a bidder's decision. Thus, by very slightly increasing threshold price, sellers can facilitate haggling in order to increase customer utility in a volatile market. In summary, our study investigated an approach to understand a customer's behavior under different price information environments in the NYOP context. The results indicate that platform providers can implement various information revelation strategies to facilitate dynamic adjustment in the threshold price by sellers to maximize their profits.