An empirical study on the detection of phantom transaction in online auction

Although the Internet is useful for transferring information, Internet auction environments make fraud more attractive to offenders, because the chance of detection and punishment is decreased. One of these frauds is the phantom transaction, which is a colluding transaction by the buyer and seller to commit the illegal discounting of a credit card. They pretend to fulfill the transaction paid by credit card, without actually selling products, and the seller receives cash from the credit card corporations. Then the seller lends it out with quite a high interest rate to the buyer, whose credit rating is so poor that he cannot borrow money from anywhere else. The purpose of this study is to empirically investigate the factors necessary to detect phantom transactions in an online action. Based upon studies that have explored the behaviors of buyers and sellers in online auctions, the following have been suggested as independent variables: bidding numbers, bid increments, sellers' credit, auction lengths, and starting bids. In this study, we developed Internet-based data collection software and collected data on transactions of notebook computers, each of which had a winning bid of over &Wstrok; one million. Data analysis with a logistic regression model revealed that starting bids, sellers' credit, and auction length were significant in detecting the phantom transactions.