Author List: Mudambi, Susan M.; Schuff, David;
MIS Quarterly, 2010, Volume 34, Issue 1, Page 185-200.
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.
Keywords: consumer behavior; diagnosticity; electronic commerce; information economics; product reviews
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#199 0.435 reviews product online review products wom consumers consumer ratings sales word-of-mouth impact reviewers word using effect marketing helpfulness electronic commerce
#0 0.099 information types different type sources analysis develop used behavior specific conditions consider improve using alternative understanding data available main target
#173 0.086 effect impact affect results positive effects direct findings influence important positively model data suggest test factors negative affects significant relationship
#46 0.076 perceived transparency control design enjoyment experience study diagnosticity improve features develop consequences showing user experiential providing antecedents interface effects economy
#217 0.075 search information display engine results engines displays retrieval effectiveness relevant process ranking depth searching economics create functions incorporate low terms