C2C电子商务差异化折扣模型:基于在线购买历史聚合  

C2C E-commerce Differentiated Discount Model Based on Aggregated Online Purchase History

作　　者：李聪[1,2] 李雪琴[1] Gajanan G.Hegde 马丽[3] 

机构地区：[1]四川师范大学计算机科学学院,四川成都610068 [2]匹兹堡大学Katz商学院,宾夕法尼亚美国匹兹堡15213 [3]四川师范大学图书信息中心,四川成都610068

出　　处：《管理工程学报》2016年第2期64-75,共12页Journal of Industrial Engineering and Engineering Management

基　　金：国家自然科学基金资助项目(71202165)

摘　　要：基于C2C电子商务网站进行在线购物已成为人们的一种重要生活方式。根据买家信誉度向其提供购物折扣是有效的营销技术。但目前C2C网站使用的信誉评分累积模型过于简单,无法涵盖买家在线购买历史(online purchase history),因此不能准确反映买家信誉度和提供差异化折扣。针对上述问题,本文提出了一种面向C2C电子商务的差异化折扣模型。该模型包含能体现买家在线购买历史的交易、恶意评价惩罚、买家操作、退单、实名认证等五个指标,其中交易指标又包含交易金额、交易时间衰减因子、卖家评价等三个因子,买家操作指标又包含买家付款时间、买家确认收货时间等两个因子;然后基于线性加权方法,将C2C买家在线购买历史聚合为买家信誉度;进而通过min-max normalization方法对买家信誉度进行线性转换,并与C2C卖家给定的折扣区间结合,得到最终的差异化折扣,从而C2C卖家可以根据当前买家的信誉度实施更精准的一对一营销和动态定价策略。以淘宝网为背景的仿真实验结果证明了本文新模型的有效性。Online shopping on C2C（Consumer-to-Consumer） E-commerce websites has become an important way of life for consumers. C2 C E-commerce has many characteristics, including fierce marketing competition, serious homogeneity of products, incomplete credit mechanism, information asymmetry, and so on. Hence, a difficult problem was brought to sellers on C2 C platform： How to implement a more precise one-to-one marketing for an e-business in order to attract and retain more consumers than its competitors？One of highly effective methods is to provide differentiated discount services based on consumer＇s reputation. The services can increase the ＂stickiness＂ between consumers and sellers. Sellers can also receive support to distinguish and prevent malevolent buyers from making tricky deals. For instance, sellers can quote a higher price than market price, and buyers can ask sellers for more favorable services. Therefore, high-efficient reputation evaluation mechanisms can effectively reduce the negative influence of information asymmetry phenomenon, help buyers and sellers quickly establish trust and reduce transaction risk, restrict trick deals, encourage good faith transactions, and avoid moral hazard and adverse selection. However, the reputation rating sum model used in current C2 C websites is too simple. Consequently, it cannot reflect buyers＇ online purchase history, and is unable to provide accurate differentiated discount for consumers. To solve the above problem, a differentiated discount model for C2 C E-commerce is proposed. The basic idea behind this model is that an online purchase history list can reflect current buyer＇s trade characteristics such as consumption level, transaction time and credit. Thus, we can regard these characteristics as multi-dimensionality signals of buyer＇s reputation, and aggregate them into a comprehensive index, which will represent buyer＇s reputation. Those buyers with high reputation should obtain more shopping discount provided by sellers. The model integrates

关 键 词：C2C电子商务 差异化折扣 在线购买历史 

分 类 号：C931[经济管理—管理学]