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论文编号：	4470
作者编号：	2120102226
上传时间：	2012/6/10 17:30:26
中文题目：	极端负面在线评论有用性影响因素研究——基于京东商城数码产品的实证分析
英文题目：	The Helpfulness of Extreme Negative Online Review:Digital Products Data from 360buy.com
指导老师：	严建援
中文关键字：	负面在线评论，有用性，内容分析，电子商务
英文关键字：	Negative Online Review, Helpfulness, Content Analysis, e-Commerce
中文摘要：	伴随着互联网的普及，电子商务发展日趋成熟，网络购物逐渐被越来越多的人接受。在线评论作为网络口碑的一种重要形式，能够降低消费者网络购物的风险和不确定性，进而有助于其购买决策的制定，同时对电子商务网络零售商产品的销量也会产生影响。由于网络“信息过载”，在线评论数量巨大，电子商务网络零售商面临着如何从海量的在线评论中迅速识别有用评论并将其提供给消费者以便实现自身销售额增加这一难题。 虽然负面在线评论数量极少，但是其对消费者购买决策的影响比正面评论更大，如果电子商务网络零售商不能正确处理负面在线评论，其产品的销量将会受到严重影响。之前很少有学者专门就负面在线评论相关问题进行研究，网络零售商不清楚到底怎样的负面在线评论对消费者的影响更大，对如何处理负面评论也无所适从。 在焦点小组访谈和文献分析的基础上，本文从负面评论内容、评论表达、评论来源和评论时间四个维度出发，建立负面在线评论有用性影响因素模型，并以我国大型B2C电子商务网站京东商城上数码产品得分为1分的极端负面在线评论真实数据为研究对象，对定量变量进行数据处理、同时利用内容分析法实现定性变量的量化，进而通过实证研究的方法对模型进行检验。研究发现负面评论的客观性、具体性和负面情感强度、评论可读性以及发布天数与其有用性正相关，评论回复数与其有用性负相关，评论长度和评论者级别与其有用性不相关。在此结论的基础上，本文为我国电子商务网络零售商如何判别新发布的负面在线评论的有用性、怎样减少其负面影响等提供借鉴。
英文摘要：	Along with the popularity of the Internet, the development of E-commerce is more mature, making online shopping universally accepted. As an important format of eWOM (short for Electronic Word of Mouth), online review can reduce online shopping risk and uncertainty of customers, therefore making it easy to make purchase decision and influencing sales of E-commerce online retailers. For the consideration of Information Overload, the amount of online review is huge and E-commerce online retailers are facing the problem of how to identify helpful online reviews from mass information quickly after they’re posted and put them to customers to increase sales. Compared with positive online reviews, there are only few negative online reviews, but they do have a stronger effect on the purchase decision of customers. For this reason, if E-commerce online retailers couldn’t treat them seriously, product sales will be hurt badly. Few researches have been done specializing on negative online reviews, so E-commerce online retailers are not sure about what kind of negative online reviews have a stronger influence on customers and how to deal with them. In this research, a model of the helpfulness of extreme negative online review which is based on focus group research and literature analysis is established from the dimension of review content, review expression, review source and released days. Based on digital products’ real 1-point review data from 360buy.com which is the biggest B2C website in China, we test this model by the method of data analysis and content analysis. Results show that review objectivity, review sufficiency, review intensity, review readability and released days are positively related to the helpfulness of review; number of replies is negatively related; while review length and reviewers’ rank are not related to the helpfulness of review. On such basis, several management implications of how to judge the helpfulness of a new posted review and how to reduce its negative effect are put forward.
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