The DOI matches its Crossref record; 45 of the 45 references it cites were found in a registry or an index.
Service robots in hotels: understanding the service quality perceptions of human-robot interaction
Abstract
Hotel industry started to adopt service robots, which are considered a future workforce. However, no attempt was conducted to examine the dimensionality of service quality of service robots. This paper aims to understand the influence of human–robot interaction from the viewpoint of hoteliers and guests. Two studies are conducted in this respect. Study 1 organizes focus-group interviews with hotel managers from various departments to elicit themes related to guest–robot interaction and robot-delivered services. Based on the findings in Study 1, Study 2 conducts an experiment to examine and compare hotel guests’ perceptions about the quality of services provided by human staff and service robots, as well as their joint services. Human staff services are perceived higher than the services of service robots in terms of interaction quality and physical service environment. However, no significant difference in outcome quality is noted.
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Cites
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Measuring Service Quality: A Reexamination and Extension
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“Similarly, Epley, Waytz, and Cacioppo (2007) also observed that robots exhibit important attributes that make them seem like human beings: mobility, crush, intelligence, and safety.”
BackgroundSome New Thoughts on Conceptualizing Perceived Service Quality: A Hierarchical Approach
Brady, M. K., & Cronin, J. J. (2001) · Journal of Marketing · doi:10.1509/jmkg.65.3.34.18334 · Cited by 3,530
Bartneck, C., Kulić, D., Croft, E., & Zoghbi, S. (2009) · International Journal of Social Robotics · doi:10.1007/s12369-008-0001-3 · Cited by 3,193
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Brave new world: service robots in the frontline
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Focus-group interview and data analysis
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Cited by
Preference for robot service or human service in hotels? Impacts of the COVID-19 pandemic
Kim, S. (., Kim, J., Badu-Baiden, F., Giroux, M., & Choi, Y. (2021) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2020.102795 · Cited by 567
Self-citationMan Tang, P., Koopman, J., McClean, S. T., Zhang, J. H., Li, C. H., De Cremer, D., Lu, Y., & Ng, C. T. S. (2022) · Academy of Management Journal · doi:10.5465/amj.2020.1516 · Cited by 370
Kim, J. H., Kim, J., Kim, C., & Kim, S. (. (2023) · Journal of Travel & Tourism Marketing · doi:10.1080/10548408.2023.2293006 · Cited by 144
Self-citationXie, L., & Lei, S. (2022) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2022.103312 · Cited by 123
When Robot (Vs. Human) Employees Say “Sorry” Following Service Failure
Wang, X., Hwang, Y., & Guchait, P. (2023) · International Journal of Hospitality & Tourism Administration · doi:10.1080/15256480.2021.2017812 · Cited by 60
Metadata
- Authors
- Choi, Y., Choi, M., Oh, M. (., & Kim, S. (.
- Venue
- Journal of Hospitality Marketing & Management
- Publisher
- Informa UK Limited
- Published
- 2019-12-25
- Volume
- 29
- Issue
- 6
- Pages
- 613-635
- ISSN
- 1936-8623 (ISSN-L)
- 1936-8631
- OpenAlex
- W2997061806
- Cited by
- 522
- References
- 45
- FWCI
- 16.81
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
