Exploring the Attractiveness of Service Robots in the Hospitality Industry: Analysis of Online Reviews

As the hospitality industry has begun adopting service robots to replace frontline human services, service robots' attractiveness becomes a salient factor in their design and implementation. However, it is unclear what consist of service robots' attractiveness and how they affect customer responses. This study examines the effects of multiple dimensions of service robots' attractiveness on customers' emotions using a text mining approach. For the data analysis, we collected 50,629 online reviews on 59 hotels and restaurants using service robots from the largest social commerce platform in China. Using the Linguistic Inquiry and Word Count (LIWC) method, we analyzed 7570 online reviews that are directly related to service robots. With the LIWC outcomes, the relationships between the attractiveness dimensions and customer emotions were investigated. Based on our findings, finally, we provide propositions for understanding the attractiveness of service robots. The theoretical and practical implications of the findings are discussed.