Exploring motivational drivers of AI chatbot adoption in emerging markets: insights from the stimulus-organism-response model for service automation

Purpose This study aims to investigate the adoption of artificial intelligence (AI) chatbots in the hospitality sector of an emerging market to identify the key technological, social and cognitive factors that influence customer trust and attitudes. It further explores how both trust and attitude significantly shape customers’ intentions to adopt chatbot technologies in service interactions. Design/methodology/approach This study uses the stimulus-organism-response model to analyze customer behaviors toward chatbot use in hotels. Data were collected from 426 hotel customers and analyzed using partial least squares structural equation modeling to assess the relationships between utilitarian and hedonic incentives, perceived intelligence, social influence, innovativeness and anthropomorphism in relation to trust and customer attitudes toward chatbot adoption. Findings The results indicate that customer attitudes and trust in chatbots significantly impact their intention to adopt this technology. Hedonic and utilitarian incentives, perceived intelligence and social influence positively influenced attitudes, although innovativeness and anthropomorphism showed no significant effect. Trust is similarly shaped by hedonic and utilitarian incentives, perceived intelligence and anthropomorphism, whereas innovativeness and social influence do not contribute significantly. Practical implications This study provides valuable insights for hotel managers and system designers in emerging markets, outlining how AI chatbots can be implemented to enhance customer service while aligning with broader goals, such as cost efficiency and operational optimization. Recommendations are offered for designing chatbots with user-friendly and human-like features to meet customer expectations and facilitate smoother adoption. Originality/value This study pioneers empirical research on AI chatbot adoption in hospitality in emerging markets, offering theoretical insights by integrating technological and behavioral perspectives. It identifies the key factors for successful implementation and proposes a scalable framework to guide digital transformation and sustainable innovation, aiding stakeholders in advancing AI-driven service automation in competitive and developing economies.