A meta-regression on the effect of online ratings on hotel room rates. Issue 12 (9th December 2019)

• Record Type: Journal Article
• Authors: Hu, Xingbao (Simon); Yang, Yang; Park, Sangwon
• Is Part Of: International journal of contemporary hospitality management. Volume 31:Issue 12(2019)
• Page Start: 4438
• Page End: 4461
• Publication Date: 2019-12-09
• Subjects: Hedonic pricing -- Hotel pricing -- Meta-regression -- Online ratings; Hospitality industry -- Management -- Periodicals; 647.94068
• DOI: 10.1108/IJCHM-10-2018-0835
• Languages: English
• ISSNs: 0959-6119

Abstract

Abstract : Purpose: Online ratings (review valence) have been found to exert a strong influence on hotel room prices. This study aims to systematically synthesize research estimating the impact of online ratings on room rates using a meta-analytical method. Design/methodology/approach: From major academic databases, a total of 163 estimates of the effects of online ratings on room rates were coded from 22 studies across different countries through a systematic review of relevant literature. All estimates were converted into elasticity-type effect sizes, and a hierarchical linear meta-regression was used to investigate factors explaining variations in the effect sizes. Findings: The median elasticity of online ratings on hotel room rates was estimated to be 0.851. Meta-regression results highlighted four categories of factors moderating the size of this elasticity: data characteristics, research settings, variable measures and publication outlet. Among sub-ratings, results revealed value rating and room rating to exert the largest impact on room rates, whereas staff and cleanliness ratings demonstrated non-significant impacts. Practical implications: This study provides practical implications on the relative importance of different types of online ratings for online reputation and revenue management. Originality/value: This study represents the first research effort to understand factors moderating the effects of online ratings on hotel room rates based on a quantitative review of the literature. Moreover, this study provides beneficial insights into the specification of empirical hedonic pricing models and data-collection strategies, such as the selection of price variables and choices of model functional forms.