What Makes a Helpful Online Review? A Study of Customer Reviews on Amazon.Com1

亚马逊雨林 业务 计算机科学 知识管理 数据科学 工程类 生态学 生物
作者
Susan M. Mudambi,David Schuff
出处
期刊:Management Information Systems Quarterly [MIS Quarterly]
卷期号:34 (1): 185-200 被引量:2459
标识
DOI:10.2307/20721420
摘要

Customer reviews are increasingly available online for a wide range of products and services. They supplement other information provided by electronic storefronts such as product descriptions, reviews from experts, and personalized advice generated by automated recommendation systems. While researchers have demonstrated the benefits of the presence of customer reviews to an online retailer, a largely uninvestigated issue is what makes customer reviews helpful to a consumer in the process of making a purchase decision. Drawing on the paradigm of search and experience goods from information economics, we develop and test a model of customer review helpfulness. An analysis of 1,587 reviews from Amazon.Com across six products indicated that review extremity, review depth, and product type affect the perceived helpfulness of the review. Product type moderates the effect of review extremity on the helpfulness of the review. For experience goods, reviews with extreme ratings are less helpful than reviews with moderate ratings. For both product types, review depth has a positive effect on the helpfulness of the review, but the product type moderates the effect of review depth on the helpfulness of the review. Review depth has a greater positive effect on the helpfulness of the review for search goods than for experience goods. We discuss the implications of our findings for both theory and practice.
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