Abstract
In consumer-to-consumer (C2C) markets, sellers can manipulate their reputation by employing a large number of puppet buyers who offer positive feedback on fake transactions. We present a conceptual framework to identify the characteristics of collusive transactions based on the homo economicus assumption. We hypothesize that transaction-related indicators including price, frequency, comment, and connectedness to the transaction network, and individual-related indicators including reputation and age can be used to identify collusive transactions. The model is empirically tested using a dataset from Taobao, the largest C2C market in China. The results show that the proposed indicators are effective in identifying collusive traders.
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