eWOM Information Richness and Online User Review Behavior: Evidence from TripAdvisor

Abstract

The growing number of online users commenting on review platforms has fueled the development of electronic word–of–mouth (eWOM). At the same time, merchants have improved their requirements for the length and frequency of online reviews. However, few studies have examined the updating mechanism of online reviews length and frequency from the perspective of businesses. This study explores the relationship between online commenting platform users and eWOM and examines how eWOM information richness affects online user review behavior. We used media richness theory (MRT) to quantify the information richness of eWOM content (linguistic, textual, and photographical) to build an empirical framework. For the research data, we used advanced big data analytics to retrieve and analyze TripAdvisor data on restaurant services in nine major tourist destinations, the United States, Mexico, and mainland Europe (including UK, Spain, Netherlands, etc.), over a long period of time. Based on >10 million eWOM, this study used multiple regression to examine the impact of eWOM information richness on online user review behavior, considering the moderating effect of information ambiguity. Our research results show that content information richness positively affects online user review behavior, increasing their frequency and length. Information ambiguity play a moderating role that strengthens this relationship. This supports our theoretical hypothesis. Finally, for greater applicability and reliability, we conducted a comparative study on the degree of differences in the relationship between eWOM and users based on different cultural backgrounds across countries.