What makes a helpful online review? A meta-analysis of review characteristics

Yani Wang (), Jun Wang () and Tang Yao ()
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Yani Wang: Beihang University
Jun Wang: Beihang University
Tang Yao: Beihang University

Electronic Commerce Research, 2019, vol. 19, issue 2, No 1, 257-284

Abstract: Abstract In this study, we aim to clarify the determinants of online review helpfulness concerning review depth, extremity and timeliness. Based on a meta-analysis, we examine the effects of important characteristics of reviews employing 53 empirical studies yielding 191 effect sizes. Findings reveal that review depth has a greater impact on helpfulness than review extremity and timeliness with the exception of its sub-metric of review volume, which exerts the negative influence on review helpfulness. Specifically, readability is the most important factor in evaluating review helpfulness. Furthermore, we discuss important moderators of the relationships and find interesting insights regarding website and culture background. In accordance with the results, we propose several implications for researchers and E-business firms. Our study provides a much needed quantitative synthesis of this burgeoning stream of research.

Keywords: Customer reviews; Online review helpfulness; Review depth; Review extremity; Timeliness; Meta-analysis (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (16)

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DOI: 10.1007/s10660-018-9310-2

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