Understanding Online Consumer Textual Reviews and Rating: Review Length With Moderated Multiple Regression Analysis Approach

Abstract

This research endeavors to fill the research cavity in the domain of online consumer reviews (OCRs) through investigating the relationship between review length and rating. Moderated multiple regression (MMR) analysis was used to investigate the moderation interactions of some critical factors, including the product price, brand, product type, and delivery systems. Through data curation, 10,547 sets of cross-sectional product data containing 200,169 sets of reviews refined from the original 12,009 products collected from jd.com in China were used. Research through econometric analysis reveals that review length improves rating. Through interactions, this study found that the price has negative interaction, whereas brand familiarity has a positive interaction with review length and rating. Domestic brands, search goods, and third-party delivery systems have more positive interactions on review length and rating than the overseas brand, experience goods, and platform’s self-delivery systems, respectively. This paper renders insight for managers, especially merchants, who should encourage consumers to write meaningful lengthy reviews to improve their reputation.