Helpfulness of Online Product Reviews as Seen by Consumers: Source and Content Features

Abstract

Online product reviews are important determinants of consumers' purchase decision. Although prior research has articulated various benefits of online product reviews, there are few investigations into whether or not they are perceived as helpful by consumers. Product review helpfulness is conceptualized as a second-order formative construct, which is manifested by perceived source credibility, perceived content diagnosticity, and perceived vicarious expression of the product review. In this study, we conduct a laboratory experiment to investigate product review helpfulness as well as its corresponding antecedents from the product review feature perspective (i.e., source-and content-based review features). Findings from the study are threefold. First, the results of the data analysis support the theoretical conceptualization of product review helpfulness as a formative construct. Second, the results support the notion that the source-and content-based review features have direct impact on product review helpfulness. Consumers perceive customer-written product reviews as more helpful than those written by experts; they also perceive a concrete review as more helpful than an abstract review. Third, we find an interaction effect of the source-and content-based features of product reviews on review helpfulness. A customer-written product review with a low level of content abstractness yields the highest perceived review helpfulness.

Which One to Read? Factors Influencing the Usefulness of Online Reviews for RE

“…4) Content: Reviews that are concrete are found to be more helpful than abstract ones [37]. The argumentation included to support the opinion presented in the review, both in terms of density and diversity, was also found to be a significant predictor of review helpfulness [34].…”

“…For all papers that were published prior to 2016, we only included those that had a number of citations that is above a certain threshold. The older the publication date the higher the threshold we Parallel with the majority average rating [24] Neutral polarity in text & Sentiment [28] Emotions [36] Content Concrete [37] Argumentation [34] Mixture of objective and subjective elements [21] Explained actions [38] Explained reactions [38] Proportion of product-descriptive statements [26] Proportion of reviewer-descriptive statements [26] Reviewer Reputation and rank [27][24] [23] Helpfulness of previous reviews [21][29] Identity information disclosure [27][39] Number of followers [31] Positive historical record [20] Level of expertise [31] Customer vs expert [37][34] Expressed innovativeness [32] set (3 citations for 2015, 7 citations for 2014, 15 citations for 2013, etc.). For 2016, we considered all the papers that were published when we did the search (early June) without restrictions on the number of citations.…”

“…Cheng and Ho [31] found that the level of expertise had a positive impact on usefulness, while Willemsen et al [34] found that when the expertise level is based on self claims, the influence on helpfulness was weak. Li et al [37] also found that customers consider customerwritten reviews to be more useful than the reviews written by experts although these are usually in-depth and unbiased. In the context of tourism, Fang et al [20] found that reviews that are written by reviewers who have a positive historical record of reviewers are likely to be more useful.…”

Customer Perception Towards Online Reviews of Movies – A Study with Special Reference to Chennai

“…Li, M., Huang, L., Tan, C. & Wei, K. (2013) in their article named 'Helpfulness of online product reviews as seen by consumers: source and content features' found that product review is one of the most important indicators that reflects the extent to which consumers perceive the review in facilitating judgment or purchase decisions. A helpful product review significantly influences consumer purchase decisions.…”

How buyers perceive the credibility of advisors in online marketplace: review balance, review count and misattribution

“…A recent business survey reported that 92% of online consumers read advisors' reviews before they make purchase decisions [1]. Literature also suggests that advisors' reviews significantly influence consumers' attitudes towards the products or sellers, which ultimately influence sales [2,3].…”