Consumer Evaluation of Hotel Service Robots

Conference paper


In light of the trend in integrating artificial intelligence and robotics into tourism and hospitality operations, it is important to understand consumer responses to hotel service robots. Two studies were conducted to achieve this objective: an online survey and a laboratory experiment using measurements of automatic emotional reactions via biosensors. Responses to two types of robots, NAO for check-in and Relay for room delivery, were tested. Study 1 demonstrates that consumer intention to adopt hotel service robots is influenced by human-robot interaction dimensions of anthropomorphism, perceived intelligence, and perceived security. Differences were found between NAO and Relay: NAO’s adoption depends on anthropomorphism and perceived security, while Relay’s on perceived intelligence and importance of service operation in hotel experiences. Study 2 revealed support for the importance of anthropomorphism and perceived security in NAO, as reflected in Galvanic Skin Response (GSR) peaks during sequences of interactions and fixation on NAO’s face. Support for perceived intelligence in Relay was also identified. Implications for the hospitality industry are provided.


Service robot Human-robot interaction Godspeed scale Hotel management Emotional response Biometric research 


  1. Aggarwal, P., McGill, A.L.: Is that car smiling at me? Schema congruity as a basis for evaluating anthropomorphized products. J. Consum. Res. 34(4), 468–479 (2007)CrossRefGoogle Scholar
  2. Bartneck, C., Kanda, T., Mubin, O., Mahmud, A.A.: Does the design of a robot influence its animacy and perceived intelligence? Int. J. Soc. Rob. 1, 195–204 (2009a)CrossRefGoogle Scholar
  3. Bartneck, C., Kulic, D., Croft, E., Zoghbi, S.: Measurement instruments for the anthropomorphism, animacy, likeability, perceived intelligence, and perceived safety of robots. Int. J. Soc. Rob. 1, 71–81 (2009b)CrossRefGoogle Scholar
  4. Borsenik, F.: Hospitality technology in the 21st century. Hospitality Res. J. 17(1), 259–269 (1993)CrossRefGoogle Scholar
  5. Brave, S., Nass, C.: Emotion in human-computer interaction. In: Human-Computer Interaction Handbook. pp. 81–96. L. Erlbaum Associates Inc., Hillsdale (2003)Google Scholar
  6. Collier, D.A.: The service sector revolution: the automation of services. Long Range Plan. 16(6), 10–20 (1983)CrossRefGoogle Scholar
  7. Crook, J.: Starwood introduces robotic butlers at Aloft Hotel in Cupertino. (2014)
  8. Duffy, B.R.: Anthropomorphism and the social robot. Rob. Auton. Syst. 42, 177–190 (2003)CrossRefGoogle Scholar
  9. Duncan, T., Moriarty, S.E.: A communication-based marketing model for managing relationships. J. Mark. 62(2), 1–13 (1998)CrossRefGoogle Scholar
  10. EARS: EARS—application scenario—NAO in a hotel lobby—March 2015. (2015)
  11. Engadget: Aloft Hotel’s robot butler. (2014)
  12. Guardian, The: Japan’s robot hotel: a dinosaur at reception, a machine for room service. (2015)
  13. Hair, J.F., Ringle, C.M., Sarstedt, M.: PLS-SEM: indeed a silver bullet. J. Mark. Theory Pract. 19(2), 139–152 (2011)CrossRefGoogle Scholar
  14. Hilton: Hilton and IBM pilot “Connie,” the world’s first Watson-enabled hotel concierge. (2016)
  15. Ivanov, S., Webster, C., Berezina, K.: Adoption of robots and service automation by tourism and hospitality companies. Paper presented at the INVTUR conference, Aveiro, Portugal, 17–19 May 2017 (2017)Google Scholar
  16. Lee, K.M., Peng, W., Jing, S.-A., Yan, C.: Can robots manifest personality? An empirical test of personality recognition, social responses, and social presence in human-robot interaction. J. Commun. 56, 754–772 (2006)CrossRefGoogle Scholar
  17. McDuff, D., Amr, M., Mahmoud, A., Turcot, J., Mavadati, M., el Kaliouby, R.: AFFDEX SDK: a cross-platform real-time multi-face expression recognition toolkit. In: Proceedings of CHI 2016. ACM, San Jose (2016)Google Scholar
  18. Morewedge, C.K., Preston, J., Wegner, D.M.: Timescale bias in the attribution of mind. J. Pers. Soc. Psychol. 93(1), 1–11 (2007)CrossRefGoogle Scholar
  19. Murphy, J., Hofacker, C., Gretzel, U.: Dawning of the age of robots in hospitality and tourism: Challenges for teaching and research. Eur. J. Tourism Res. 15, 104–111 (2017)Google Scholar
  20. Osawa, H., Akiya, N., Koyama, T., Ema, A., Kanzaki, N., Ichise, R., Hattori, H., Kubo, A.: What is real risk and benefit on work with robots? From the analysis of a robot hotel. In: HRI2017 Companion. ACM, Vienna (2017)Google Scholar
  21. Russell, J.: A circumplex model of affect. J. Pers. Soc. Psychol. 39, 1161–1178 (1980)CrossRefGoogle Scholar
  22. Russell, J., Feldman Barrett, L.: Core affect, prototypical emotional episodes, and other things called emotion: dissecting the elephant. J. Pers. Soc. Psychol. 76, 805–819 (1999)CrossRefGoogle Scholar
  23. Salem, M., Lakatos, G., Amirabollahian, F., Dautenhahn, K.: Would you trust a (faulty) robot? Effects of error, task type and personality on human-robot cooperation and trust. HRI2015. ACM, Portland (2015)Google Scholar
  24. Scholl, B., Tremoulet, P.D.: Perceptual causality and animacy. Trends Cogn. Sci. 4(8), 299–309 (2000)CrossRefGoogle Scholar
  25. Stubbs, K., Hinds, P.J., Wettergreen, D.: Autonomy and common ground in human-robot interaction: a field study. IEEE Intell. Syst. 22(2), 42–50 (2007)CrossRefGoogle Scholar
  26. Thrun, S.: Toward a framework for human-robot interaction. Hum. Comput. Interact. 19(1–2), 9–24 (2004)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.School of Hospitality and Tourism ManagementUniversity of SurreyGuildfordUK
  2. 2.School of Hotel and Tourism ManagementThe Hong Kong Polytechnic UniversityKowloonHong Kong

Personalised recommendations