Muzi Xie

Papers

Total Citations

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About

Dr. Muzi Xie is a leading researcher at the intersection of human-robot interaction, service innovation, and tourism technology. Her most cited work, "User Acceptance of Hotel Service Robots Using the Quantitative Kano Model" (2022, 24 citations), provides a groundbreaking framework for understanding how guests perceive and accept robotic services in hospitality settings. By applying the quantitative Kano model—a sophisticated method for categorizing customer preferences—Xie moves beyond simple acceptance metrics to reveal which robot features truly delight users versus those that merely satisfy basic expectations. This contribution is pivotal as hotels worldwide accelerate their adoption of artificial intelligence and service robots, offering developers and managers clear guidance on prioritizing design investments. Xie’s research uniquely bridges engineering and consumer psychology, demonstrating that successful service robots must not only function reliably but also align with nuanced human emotional and experiential needs. Her work has immediate practical implications for the tourism industry, where balancing technological efficiency with guest satisfaction is paramount. As service robotics continues to reshape hospitality, Dr. Xie’s insights remain essential reading for researchers, hoteliers, and technology developers seeking to create robots that people genuinely welcome.