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An empirical investigation of online review helpfulness: A big data perspective
Decision Support Systems ( IF 7.5 ) Pub Date : 2020-09-20 , DOI: 10.1016/j.dss.2020.113403
Hoon S. Choi , Steven Leon

This study investigates the determinants of online review helpfulness, adopting various predictors from three dimensions of the online review management: source factors, review factors, and context factors. Based on a large, comprehensive dataset that includes 14,051,211 online reviews in 24 product categories from an ecommerce retailer, Amazon.com, this study provides empirical evidence on the effect of source and reviews factors on perceived review helpfulness, which the extant literature has reached inconsistent conclusions. In addition, this study considers the effects on review helpfulness created by context factors: product satisfaction, product popularity, product intangibility, and product variety. These factors are scarcely discussed in the existing literature. The major findings include (1) review extremity, review depth, and reviewer expertise have a positive effect on review helpfulness; (2) review inconsistency, product intangibility, product satisfaction, product popularity, product variety, and reviewer experience have negative effects; and (3) product intangibility moderates the effect of review extremity and depth on review helpfulness.



中文翻译:

在线评论帮助的实证研究:大数据视角

这项研究调查了在线评论有用性的决定因素,并从在线评论管理的三个维度采用了各种预测因素:来源因素,评论因素和情境因素。基于大型综合数据集,其中包括来自电子商务零售商Amazon.com的24个产品类别中的14,051,211条在线评论,该研究提供了有关证据来源和评论因素对感知评论有用性的影响的经验证据,现有文献对此并不一致结论。此外,本研究还考虑了以下环境因素对评论有用性的影响:产品满意度,产品受欢迎程度,产品无形性和产品种类。这些因素在现有文献中很少讨论。主要发现包括(1)肢体末端,深度,审稿人的专业知识对审稿有用性产生积极影响;(2)评论不一致,产品无形,产品满意度,产品知名度,产品种类和审阅者经验有负面影响;(3)产品的无形性会缓和评论肢体和深度对评论有用性的影响。

更新日期:2020-11-06
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