The Relative Effect of the Convergence of Product Recommendations from Various Online Sources

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Author(s)

Detail(s)

Original languageEnglish
Pages (from-to)788-819
Journal / PublicationJournal of Management Information Systems
Volume37
Issue number3
Online published18 Nov 2020
Publication statusPublished - 2020

Abstract

Most previous studies about online product recommendation sources (recommendation agents [RAs], consumers, and experts) have been limited to the evaluation by a single source on a website. Thus, the relative influence of convergent recommendations from different sources on consumers’ acceptance of the advice remains largely unknown. We draw upon and extend the product uncertainty model to theorize how the convergence of recommendations from various sources differentially influences customers’ acceptance of recommendations. Our experiments show that the recommendation convergence between RAs and experts leads to the greater recommendation acceptance of the jointly recommended products than the convergence between experts and consumers or convergence between RAs and consumers. The rationale is that RAs best reduce fit uncertainty, and experts best reduce description and performance uncertainties. Experts and RAs complement each other by reducing all three dimensions of product uncertainty. Online merchants are advised to incorporate multiple sources into their websites, including sources (i.e., RAs and experts) that play complementary roles in reducing product uncertainty.

Research Area(s)

  • Online product uncertainty, description uncertainty, fit uncertainty, performance uncertainty, recommendation sources, online recommenders, convergent recommendations