How to avoid fake used cars in the online market: An empirical study with signaling theory

Abstract

It is known that information asymmetry between dealer and buyer in market for used cars leads to adverse selection. Prior works found evidences of adverse selection in used car market, however, they primarily focused on offline or auction market. A form of used car market is changing from offline to e-business and auction is not open to all people but only to dealers. In this paper, we investigated for online used car market where potential used car buyers generally look for the offerings. we found that there is fake used cars that are not, nor have ever been in dealer’s possession to lure buyers in online market. When buyers are lured by fake used cars and go to meet a fraudulent dealer, buyers cannot buy the used cars what they wanted to however, are forced to buy the used car with bad quality at high prices. As dealers communicate dealer and product quality to potential used car buyers through website signal, we used signaling theory to investigate for the relationship between signals and fake used cars. We collected unique data from one of the largest online market places for used cars in Korea and categorized collected data with a three-dimensional matrix. In this paper, we found that dealers with fake used cars provide fewer signals than did dealer with genuine used cars. Furthermore, dealer certification system by online intermediary weakened the negative correlation between the number of signals from dealer and the probability of fake used cars. These results have implications for online intermediary manager in charge of dealer certification and suggest the way for buyers to avoid fraudulent used car in online market.