Power of agglomeration on electronic word–of–mouth in the restaurant industry: Exploring the moderation role of review quality difference

Abstract

This study evaluates the impact of electronic word–of–mouth (eWOM) based on an extended research model, bridging the information value concept from agglomeration theory with transparency theory. Particularly, it aims to understand how various agglomeration theory aspects, such as store density, product type concentration, and store quality, interact with online reviews’ quality to influence eWOM volume. The study employs a Tobit model to estimate the agglomeration effects on eWOM volume. For nine years (2010–2018), data was collected from 11,234 monthly users at 4004 restaurants in the Phoenix area. This study explores the nuanced effects of store and quality agglomeration on eWOM within the restaurant industry, demonstrating that increased agglomeration positively impacts eWOM by lowering competition and search costs, while ambiguous quality among establishments dampens eWOM. Notably, it reveals that review quality's influence on eWOM varies with agglomeration type, being minimal for store agglomeration, reducing positive impacts in product agglomeration, yet significantly boosting the benefits of quality agglomeration. By integrating agglomeration and transparency theories and breaking down agglomeration into detailed components, this research highlights the pivotal role of high-quality reviews in mitigating the negative effects of geographical proximity, thus providing fresh insights into eWOM dynamics in the restaurant sector.