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首页> 外文期刊>Sensor Letters: A Journal Dedicated to all Aspects of Sensors in Science, Engineering, and Medicine >Psychometric Analysis of Validity of Trust Evaluating Indicators in C2C Online Markets: A Case Study of Taobao
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Psychometric Analysis of Validity of Trust Evaluating Indicators in C2C Online Markets: A Case Study of Taobao

机译：C2C在线市场信任评估指标有效性的心理计量分析：以淘宝网为例

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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).
机译：目的：“卖家声誉得分”和“卖家声誉等级”是淘宝网和其他在线零售市场上两种主要的信任评估指标，本文旨在验证这两种信任评估指标的有效性。方法：本文数据是从在淘宝上经营至少一年的34家女士/女士精品店中随机获得的，并使用相关和一元线性回归方法进行数据处理。结果：发现，对于两个信任评估指标与某些信任评价指标之间的相关性，“卖方声誉得分”和“卖方声誉等级”都不能很好地预测消费者可能面临的风险或消费者所享受的服务。评估标准（包括总体好评率。过去六个月的好评率，过去一个月的好评率，过去一周的好评率，消费者保护服务的状态以及服务质量）非常低甚至为负（从-0.476到0.163）。而且还发现，“卖家的声誉得分”和“卖家的声誉等级”实际上都是商店开业以来时间长度的良好预测指标（它们之间的相关系数分别为0.568和0.637）。结论：“卖方信誉点”和“卖方信誉等级”对于帮助消费者抵御风险均无济于事，但有助于C2C在线市场和商店吸引更多企业。因此，提出了一些新的想法来改善现有的C2C信誉系统，即用新的二维模型（已知/未知和肯定/否定）替换现有的一维模型。

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