Reputation inflation detection in a Chinese C2C market
Electronic Commerce Research and ApplicationsPublished 26 June 2011
Weijia You, Lu Liu, Mu Xia, Chenggong Lv
Citations38
SJR quartileQ1
SJR score1.41
SNIP1.70
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TL;DR
A conceptual framework to identify the characteristics of collusive transactions based on the homo economicus assumption is presented and it is hypothesized 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 traders.
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.
Keywords
PsychologyComputer ScienceDecision Sciences
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