Effects of service attributes and competition on electronic word of mouth: an elaboration likelihood perspective

Abstract

The management of electronic word of mouth (eWOM) is critical in e-commerce. In this study, on the basis of the elaboration likelihood model (ELM), we constructed a model of factors influencing eWOM by dividing merchants’ attributes into the central and peripheral routes, which correspond to consumers’ systematic and heuristic cognitive modes respectively. We then tested the developed model by using a cross-sectional data set. The results of this study indicate that the degree of competition faced by merchants has a significant negative association with eWOM. Moreover, price level and location moderate the relationship between competition and eWOM. The services of reservation and group buying have positive associations with eWOM. This research has three main contributions. First, we explored the effect of competition on eWOM. Second, we validated the feasibility of applying the ELM to the catering industry by dividing merchant attributes into the central and peripheral routes; this approach is consistent with systematic and heuristic cognitive theories. Finally, this research provides practical suggestions for eWOM management in the catering industry.

Spatial differences and underlying mechanisms in electronic word of mouth in the foodservice industry: A case of Sanya, China

“…The results show that price, market popularity, restaurant ratings, transportation conditions, and commercial development all positively influence eWOM in the foodservice industry. The availability public services does not have a significant influence, which is consistent with previous findings [ 46 – 50 ]. Population has a negative influence, as high concentrations of tourists may lead to problems such as long wait times, noisy dining environments, and traffic congestion [ 49 ].…”

“…with previous findings [46][47][48][49][50]. Population has a negative influence, as high concentrations of tourists may lead to problems such as long wait times, noisy dining environments, and traffic congestion [49].…”

“…Areas with high population density will have a greater demand for restaurants, but excessive tourism will lead to queuing, a noisy dining environment, damage to the environment and other problems. (2) Price [ 46 ], was measured as per capita consumption. The per capita food and beverage consumption is measured by a variety of factors and reflects the overall level of service, but excessive consumption will negatively affect tourists’ dining experience.…”