How do robots reshape restaurant service attributes? – Evidence from online reviews

Purpose This study aims to compare key restaurant service attributes before and after robot implementation to examine how customer expectations shift in response to technological integration. Design/methodology/approach A total of 38,736 Yelp reviews for 76 outlets of a restaurant chain across the US were collected as of June 2025. After conducting sentiment analysis and semantic clustering of reviews, this study applied the Kano model and importance-performance analysis (IPA) to illustrate the transition in key service attributes following the restaurant’s implementation of service robots. Findings Kano classification shows that robots, along with location and service system, emerge as excitement attributes. Service quality transforms from a basic attribute to a performance attribute after the robot is implemented. Meanwhile, wait time and perceived value transform from excitement attributes to performance and basic attributes, respectively. The IPA results identify food and service quality as top priorities for service improvement, both before and after robot implementation. Robots become a high-priority service attribute after implementation, while the importance of value and service system declines. Practical implications By classifying key service attributes into various distinct categories, this study reveals what customers value in their dining experiences following the implementation of new technologies. The findings provide practical insights for restaurant operators by clarifying how customer expectations have shifted and identifying which service attributes deserve greater managerial attention when integrating robots into restaurant operations. Originality/value Building on multi-attribute utility theory, to the best of the authors’ knowledge, this research is among the first to examine the evolution of key service attributes that shape the customer dining experience in robot-integrated restaurants.