Understanding the drivers of consumers’ acceptance and use of service robots in the hotel industry

Abstract

Purpose: This study aims to discover factors and configurations that influence customers’ acceptance behaviors to investigate the current hospitality industry using service robots. Design/methodology/approach: A mix of symmetrical and asymmetrical modeling methods was used for the data analysis. The symmetrical modeling was used to find the net effects, whereas asymmetrical modeling was adopted to find the combined configurations for hotel guests’ robot service acceptance behaviors. Findings: The results revealed the significant effect of innovativeness, willingness to be a lighthouse customer, personal norms and concern about service robot performance on acceptance behaviors. In addition, the complex solution models using characteristics of tech-forward consumers, norms and attitude and uncertainty and concern were found. Practical implications: The study shows directions to hotel marketers, to help them make customers adopt service robots. Originality/value: The study explored customer service robot acceptance behaviors based on comprehensive theoretical backgrounds, including the technology acceptance model, theory of planned behavior, norm activation model and service robot acceptance model.