Competition and restaurant online review manipulations: A dynamic panel data analysis

Abstract

It is important to understand business online review manipulations, through which consumers can make better choice and platforms’ reputations can be maintained. Based on monthly panel data of 970 restaurants across 14 years in a metropolitan city in the US, this study investigates the impact of competition on both restaurant positive and negative online review manipulations. This study constructed a new competition index reflecting competitors’ quantity, quality, and negative influence of distance on the intensity of competition using the Gaussian kernel function, and the empirical results show: (1) both positive and negative review manipulations are positively influenced by competition; (2) the influence of the same cuisine competitors on the focal restaurant’s review manipulations are stronger than their counterpart competitors; and (3) the competition’s influence on positive review manipulation is stronger for high-priced than low-priced restaurants, but no difference exists regarding restaurant review demotion received. This study enriches the online review manipulation literature.