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出 处:《北京邮电大学学报(社会科学版)》2014年第2期30-36,共7页Journal of Beijing University of Posts and Telecommunications(Social Sciences Edition)
基 金:国家自然科学基金项目(70972122)
摘 要:现有电子商务的信用评价体系单一维度的特点使得评级体系难以准确衡量、比较店铺在各维度之间的差异及其变化。为了提高C2C电子商务信用评级体系的信息揭示作用,本文试图从多维度指标分析店铺的诚信行为模式及其动态性。本文对淘宝7大行业不同信用等级的卖家的诚信指标数据进行聚类分析表明,店铺在动态评分、信用等级、好评率上分别具有六类不同的静态组合特征,信用积分在解释店铺诚信状态上弱于动态评分和好评率指标。动态模式分析表明,店铺的好评率、动态评分指标及其与同业行业比值会呈现出三个不同的组合变化趋势。最后本文提出对现有的评价体系改进,以体现店铺之间在模式上的差异,从而真实展现卖家的诚信水平。Existing credit evaluation system of e-commerce is difficult to accurately measure and compare the differences and the changes in multi-dimension credit indexes, because of the characteristics of single dimension. In order to promote the revealing function of current credit rating system in C2C market, online shops' behavioral patterns and its dynamic mode from multi-dimensional index is analyzed through clustering methods by collecting integrity indicators data of Taobao in seven industries of different credit rating sellers. Static mode a- nalysis shows that online shops have six types of characteristics combining dynamic rating, credit rating and positive ratio, and indicates that credit score is weaker than dynamic rating and positive ratio when individually revealing credit performance of online shops. Dynamics mode analysis shows that there are three types of combined changes. Finally, suggestions are proposed to make improvements to the existing evaluation system, so that it can show the real integrity level of different types of sellers.
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