Shuang Xin

Zhejiang Gongshang University

Papers

1

Total Citations

3

H-Index

1

About

Shuang Xin is a pioneering researcher at the intersection of hospitality management and human-robot interaction. Her work fundamentally rethinks how service robots are integrated into guest experiences, challenging the assumption that technological presence alone guarantees engagement. In her highly cited 2024 study, Xin introduces the critical concept of "physical engagement" as a missing link in human-robot interaction, revealing why hotel guests often overlook or ignore service robots. Through meticulous unobtrusive observation and semi-structured interviews, she demonstrates that passive robot presence is insufficient—guests require meaningful, tactile, and context-aware interactions to form connections. This contribution has already garnered significant attention, with her work shaping how hospitality operators and robot designers approach service automation. Xin’s research bridges cognitive psychology, service design, and robotics, offering actionable frameworks for enhancing guest satisfaction and operational efficiency. Her findings are particularly vital as the hospitality industry accelerates its adoption of AI-driven service solutions. By identifying the psychological and behavioral barriers to robot acceptance, Xin provides a roadmap for creating more intuitive, engaging, and human-centered robotic services. Her work stands as a cornerstone for scholars and practitioners seeking to harmonize technology with authentic human experience.

Research Focus

Key Achievements

1
H-Index
1
Papers
3
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Exploring the reasons behind guests’ disregard for service robots in the hospitality: conceptualising the role of physical engagement in human-robot interaction
3 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: Zhejiang Gongshang University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago