From negative feedback to actionable insights: a computational analysis of service robot adoption challenges in Chinese hotels

With the rapid rise in labour costs in China’s hotel industry, service robots have emerged as a potential solution to enhance service efficiency and reduce operational expenses. However, their adoption rate in Chinese hotels remains low. While prior studies have primarily explored technical performance and costs from a managerial perspective, there is a lack of systematic methodologies examining adoption barriers from the lens of guests’ negative emotions. This study employs web-crawling technology to collect 20,900 low-rated reviews from six major Chinese online travel platforms. Using Latent Dirichlet Allocation (LDA) topic modelling combined with computational grounded theory, the authors identified ten key barriers to the adoption of service robots in hotels. Notably, this study introduces “Cultural Misfit”, “Frequent Malfunctions”, and “Inconvenient Operation” as distinct barriers. It also reveals a cascading effect involving service quality, functional utility, and expectation alignment, highlighting that multidimensional interactions drive technology acceptance. These findings provide theoretical and practical insights for optimising service robot deployment, offering new perspectives to improve service efficiency and user acceptance in China’s hotel industry.