The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Antecedents of customers’ acceptance of artificially intelligent robotic device use in hospitality services
Abstract
This study examines the antecedents of customers’ willingness and objection to use artificially intelligent robotic devices in hospitality services (full-service and limited-service hotels). Drawing on the Artificially Intelligent Device Use Acceptance (AIDUA) theory, this study validates and extends the AIDUA framework in the hospitality service setting. The results point to the applicability of the AIDUA framework, suggesting that hospitality customers’ intention to the use of artificially intelligent devices are influenced by social influence, hedonic motivation, anthropomorphism, performance and effort expectancy, and emotions toward the artificially intelligent devices. Findings further suggest that compared to limited-service hotel customers, full-service hotel customers rely less on their social groups when evaluating artificially intelligent robotic devices; their emotions toward the use of artificially intelligent devices are less likely to be influenced by effort expectancy; and their emotions cause less impact on their objection to the use. Theoretical contributions and managerial implications of this study are discussed. Limitations and future study recommendations are provided.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003) · Journal of Applied Psychology · doi:10.1037/0021-9010.88.5.879 · Cited by 82,194
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012) · MIS Quarterly · doi:10.2307/41410412 · Cited by 15,756
Work and/or Fun: Measuring Hedonic and Utilitarian Shopping Value
Babin, B. J., Darden, W. R., & Griffin, M. (1994) · Journal of Consumer Research · doi:10.1086/209376 · Cited by 6,020
Exploratory and confirmatory factor analysis: Understanding concepts and applications.
Thompson, B. (2004) · doi:10.1037/10694-000 · Cited by 3,469
The Elaboration Likelihood Model of Persuasion
Petty, R. E., & Cacioppo, J. T. (1986) · Communication and Persuasion · doi:10.1007/978-1-4612-4964-1_1 · Cited by 3,202
Consumers acceptance of artificially intelligent (AI) device use in service delivery
Gursoy, D., Chi, O. H., Lu, L., & Nunkoo, R. (2019) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2019.03.008 · Cited by 1,437
Self-citationDeveloping and validating a service robot integration willingness scale
Lu, L., Cai, R., & Gursoy, D. (2019) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2019.01.005 · Cited by 1,013 · cited 3×
“Also, Lu et al. (2019) suggested that customers ’ long-term willingness to use AI robots depends on customers ’ perception of service robots ’ performance e ffi cacy, customers ’ intrinsic motivations, anthropomorphism, social in fl uences, customers ’ emotions and facilitating condition.”
BackgroundResultWu, Y.-H., Wrobel, J., Cornuet, M., Kerhervé, H., Damnée, S., & Rigaud, A.-S. (2014) · Clinical Interventions in Aging · doi:10.2147/cia.s56435 · Cited by 261
The Hedonic Value of Hospitality Consumption: Evidence From Spring Break Experiences
Miao, L., Lehto, X., & Wei, W. (2014) · Journal of Hospitality Marketing & Management · doi:10.1080/19368623.2013.766582 · Cited by 87
Research works printed but not linked: 43
- Ackerman, E. (2016). Study: Nobody wants social robots that look like humans because they threaten our identity. IEEE Spectrum. Retrieved from: https://spectrum.ieee.org/automaton/robotics/humanoids/study-nobody-wants-social-robots-that-look-like-humans
- 10.3233/AIS-150315 · DOI
- 10.4468/2016.2.03bellini.convert · doi:10.4468/2016.2.03bellini.convert
- 10.1080/00036810600603377 · DOI · Paper page
- Cacioppo J. T., 1984, Advances in Consumer Research, 11, 673
- 10.1287/mnsc.35.8.982 · DOI · Paper page
- 10.1145/3029610.3029623 · doi:10.1145/3029610.3029623
- 10.1080/19368623.2019.1639095 · DOI · Paper page
- 10.1016/j.chb.2017.09.028 · DOI
- 10.1177/002224378101800104 · DOI · Paper page
- 10.1016/j.chb.2017.05.045 · DOI · Paper page
- 10.1016/j.jdmm.2017.02.004 · DOI
- Hair J. F., 2014, A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM)
- 10.2753/MTP1069-6679190202 · DOI · Paper page
- 10.1080/10705519909540118 · DOI · Paper page
- 10.1108/JHTT-08-2018-0087 · DOI · Paper page
- Ivanov S. H., 2017, Revista Turismo & Desenvolvimento, 27, 1501
- 10.1080/19368623.2017.1367346 · DOI
- 10.1093/jcr/ucy006 · DOI
- Kline, R. B. (2005). Principles and practice of structural equation modeling (2nd ed.). New York, NY, US: Guilford Press.
- 10.1108/IJCHM-08-2015-0414 · DOI · Paper page
- 10.4301/S1807-17752017000100002 · DOI · Paper page
- 10.1037/0003-066X.46.4.352 · DOI · Paper page
- 10.1080/02642060802287189 · DOI
- 10.1016/j.tourman.2015.09.005 · DOI
- Mori M., 1970, Energy, 7, 33
- Murphy, J., Gretzel, U. & Hofacker, C. (2017). Service robots in hospitality and tourism: investigating anthropomorphism.15th APacCHRIE conference, Bali, Indonesia · DOI · Paper page
- 10.1145/3029798.3038333 · DOI
- 10.3727/108354209789116501 · doi:10.3727/108354209789116501
- 10.1258/jhsrp.2010.010001 · DOI
- 10.1145/3029798.3038312 · DOI
- 10.1007/s12369-015-0320-0 · DOI
- 10.1080/19368623.2019.1645073 · DOI · Paper page
- 10.1080/10963758.2016.1163497 · DOI
- 10.1177/1938965509344294 · DOI
- Stock, R. & Merkle, M. (2017). A service robot acceptance model: User acceptance of humanoid robots during service encounters. 2017 IEEE International Conference onPervasive Computing and Communications Workshops(PerCom Workshops), Kona, HI, USA, 2017, 339-344. · DOI
- Tussyadiah, I. P. & Park, S. (2018).Consumer evaluation of hotel service robots. In: Stangl B., Pesonen J. (eds). Information and Communication Technologies in Tourism 2018 (pp.308-320). Cham, Switzerland: Springer. · DOI · Paper page
- 10.2307/25148660 · DOI · Paper page
- 10.1016/j.robot.2013.09.014 · DOI
- Wan J., 2015, Strong brands, strong relationships, 119, 10.4324/9781315767079-20 · DOI
- 10.1080/19368623.2019.1592733 · DOI · Paper page
- 10.1007/978-3-319-03653-3_1 · DOI
- 10.1016/j.chb.2016.11.069 · DOI · Paper page
Cited by
Cao, G., Duan, Y., Edwards, J. S., & Dwivedi, Y. K. (2021) · Technovation · doi:10.1016/j.technovation.2021.102312 · Cited by 571
“…empirically that performance expectancy and effort expectancy are key antecedents to customers ’ will-ingness to accept AI device use, while Lin et al. (2020) further showed that compared with limited-service hotel customers, full-service hotel customers ’ emotions toward the use of AI…”
BackgroundAdoption of artificial intelligence (AI) for talent acquisition in IT/ITeS organizations
Pillai, R., & Sivathanu, B. (2020) · Benchmarking: An International Journal · doi:10.1108/bij-04-2020-0186 · Cited by 422
Chi, O. H., Denton, G., & Gursoy, D. (2020) · Journal of Hospitality Marketing & Management · doi:10.1080/19368623.2020.1721394 · Cited by 334
Self-citationCheng, B., Lin, H., & Kong, Y. (2023) · Journal of Business Research · doi:10.1016/j.jbusres.2023.113987 · Cited by 272
Self-citationHotel managers’ perceptions towards the use of robots: A mixed-methods approach
Ivanov, S., Seyitoğlu, F., & Markova, M. (2020) · Information Technology & Tourism · doi:10.1007/s40558-020-00187-x · Cited by 243
Metadata
- Authors
- Lin, H., Chi, O. H., & Gursoy, D.
- Venue
- Journal of Hospitality Marketing & Management
- Publisher
- Informa UK Limited
- Published
- 2019-11-12
- Volume
- 29
- Issue
- 5
- Pages
- 530-549
- ISSN
- 1936-8623 (ISSN-L)
- 1936-8631
- OpenAlex
- W2987092822
- Cited by
- 387
- References
- 9
- FWCI
- 12.20
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
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.
