在线评论有用性影响因素与组态分析——基于负二项回归和fsQCA方法

Analysis of the influencing factors and configuration of the usefulness of online reviews--Based on negative binomial regression and fsQCA method

在线评论有用性作为电商领域的研究热点,从整体视角出发对其进行影响因素与组态分析,将有利于形成相对统一的研究脉络和理论框架。基于信息采纳模型,构建在线评论有用性影响因素模型,采集亚马逊中国网站评论数据,结合负二项回归和fsQCA方法进行分析。结果表明:评论长度、标题信息量、时效性、图片、评论者等级、权威性均正向影响在线评论有用性;而评论星级、商品类型、评论者经验则对在线评论有用性起负向作用。组态分析结果表明存在6条在不同商品类型及正/负面评论情境下的影响高在线评论有用性的实现路径。

The usefulness of online reviews became a hot topic in the field of e-commerce. From an overall perspective,the analysis of its influencing factors and configuration effects would help to form a relatively unified research context and theoretical framework. Based on the information adoption model,this paper constructed a model of factors influencing online review usefulness,and analyzed the model by capturing the review data of amazon. cn website,combining with negative binomial regression and fsQCA method. The results showed that review length,title information,timeliness,pictures,reviewers’ rating,reviewers’ authority all positively affected the usefulness of online reviews;review rating,product type,and reviewers’ experience negatively affected the usefulness of online reviews. The results of configuration analysis showed that there were six realization paths for high online review usefulness under different commodity types and positive/negative review contexts.