Signaling, Bidding and the Final Price in the Online Auction Platform Almost Without Information Asymmetry: An Empirical Study on China's Largest B2C Marketplace

Abstract

Business-to-customer (B2C) online auctions differ from customer-to-customer (C2C) online auctions by having much less sellers who have established their reputations. Thus, B2C online auctions face much lower levels of information asymmetry and relies more on seller’s signaling and buyers’ bidding to determine the final price. This paper uses the second-hand product auction data from Jingdong, the largest B2C electronic market in China, to understand the determinants of the final price in B2C online auctions. We find that the signaling from the single seller and the bidding from the buyers can almost fully explain the final price, where the signaling is much more important than the demand side’s bidding, and posting the price of new product selling in the online market is the most effective signaling. These findings are robust after controlling the endogeneity of the number of bidders. Results from Quantile IV Regression further show that the valuation-reference role of the seller’s signaling such as posting the price of new product and the newness levels of the product decreases with the value of product price while the role of bidding behaviors such as the number and the heterogeneity of bidders increases with that value.

Keywords: second-hand product; B2C; online auction; final price; quantile regression