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Psychometric Analysis of Validity of Trust Evaluating Indicators in C2C Online Markets: A Case Study of Taobao

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Objective: "Sellers' Reputation Points" and "Sellers' Reputation Grades" are the two main types of trust evaluating indicators in Taobao and other online retail market, and the purpose of this paper is to verify the validity of these two trust evaluating indicators. Methods: The data in this paper are obtained randomly from 34 Women/Madam Boutique shops operating at least one year on Taobao, and the Correlation and Unary Linear Regression methods are used for data processing. Results: It is found that neither "Sellers' Reputation Points" nor "Sellers' Reputation Grades" is a good predictor of the risks that consumers may encounter or the services that consumers may enjoy, for the correlation between the two trust evaluating indicators and some criterions (including the overall praise rate. The praise rates of past six months, the praise rates of past one months, the praise rates of past one weeks, the status of consumer protection services and the qualities of services) are very low or even negative (from −0.476 to 0.163). And it is also found that both "Sellers' Reputation Points" and "Sellers' Reputation Grades" actually are good predictors of the length of time since the shop opened (the correlation coefficients between them are 0.568 and 0.637, respectively). Conclusions: Both "Sellers' Reputation Points" and "Sellers' Reputation Grades" are useless in helping the consumers to resist the risks, but useful in helping the C2C online markets and shops to attract more businesses. Therefore some new ideas are proposed to improve the existing C2C reputation systems, that is, replacing the existing single-dimensional model with a new two-dimensional model (Known/Unknown and Positive/Negative).
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Document Type: Research Article

Publication date: 2012-01-01

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