Scores vs. stars: A regression discontinuity study of online consumer reviews

With the rising popularity of consumer reviews, the design of the review system becomes increasingly crucial for e-commerce platforms and online retailers in their business decision-makings. Though the relationship between consumer reviews and sales has been extensively studied, only few studies have been conducted on the effects of different review designs. In this paper, we collect detailed review data from Meituan.com, a popular Chinese shopping website, to examine the effects of numerical presentation of consumer reviews (detailed to one decimal place) and graphical presentation of consumer reviews (in half-stars) on sales. By using a regression discontinuity design, we find that while consumer review scores may affect sales positively, the star presentation can create negative, rather than positive, jumps at cutoffs. Consumers restrict their attention to a star category; therefore, the “best” sellers in a lower star category are better off than the “worst” sellers in a higher star category. The incentive for review manipulation is strongly reduced, which in the long run will create trust and confidence for the review system as well as the sellers. For those sellers that are just below the cutoffs, simply crossing over the cutoffs would not lead to higher sales. Instead, they will have to substantially improve their service quality to attract consumers.