Emotional expression by artificial intelligence chatbots to improve customer satisfaction: Underlying mechanism and boundary conditions

Artificial intelligence chatbots have invaded the tourism industry owing to their low cost and high efficiency. However, the influence of emotional expressions of chatbots on service outcomes has not received much attention from researchers. Drawing upon expectancy violations theory, we explored how emotional expressions of chatbots affect customer satisfaction using three experiments in the context of tourist attraction recommendations. Chatbots' expressions of concern for customers can improve customer satisfaction by reducing expectancy violations. In particular, customer's goal orientation, the human-likeness of chatbot's avatars, and the relationship type between customers and chatbots can moderate the negative relationship between emotional expression and expectancy violation. These findings advance research on the emotional expressions of chatbots and provide critical insights for deploying chatbots in customer service in the tourism industry.