Have a personal or library account? Click to login

From negative feedback to actionable insights: a computational analysis of service robot adoption challenges in Chinese hotels

Open Access
|Oct 2025

References

  1. Bandura, A. (1986). Social Foundations of Thought and Action: A Social-Cognitive View. The Academy of Management Review, 12(1).
  2. Barnes, S. B. (2006). A privacy paradox: Social networking in the United States. First Monday, 11(9). doi: 10.5210/fm.v11i9.1394
  3. Belanche, D., Casaló, L. V., & Flavián, C. (2020). Frontline robots in tourism and hospitality: Service enhancement or cost reduction? Electronic Markets, 31(3), 477-492. doi: 10.1007/s12525-020-00432-5
  4. BenMessaoud, C., Kharrazi, H., & MacDorman, K. F. (2011). Facilitators and barriers to adopting robotic-assisted surgery: Contextualizing the Unified Theory of Acceptance and Use of Technology. PLoS ONE, 6(1), e16395. doi: 10.1371/journal.pone.0016395
  5. Blei, D. M. (2012). Probabilistic topic models. Communications of the ACM, 55(4), 77-84. doi: 10.1145/2133806.2133826
  6. Bowen, J., & Morosan, C. (2018). Beware hospitality industry: The robots are coming. Worldwide Hospitality and Tourism Themes, 10(6), 726-733. doi: 10.1108/WHATT-07-2018-0045
  7. Brandstötter, M., Komenda, T., Breitenhuber, G., Rathmair, M., Steiner, M., Laflamme, C., Müller, A., & Hofbaur, M. (2022). A method to enhance the flexibility of collaborative human-robot workspaces through an extended safety perspective. Procedia CIRP, 112, 197-202. doi: 10.1016/j.procir.2022.09.072
  8. Buerkle, A., Eaton, W., Al-Yacoub, A., Zimmer, M., Kinnell, P., Henshaw, M., Coombes, M., Chen, W. H., & Lohse, N. (2023). Towards industrial robots as a service (IRaaS): Flexibility, usability, safety and business models. Robotics and Computer-Integrated Manufacturing, 81, 102484. doi: 10.1016/j.rcim.2022.102484
  9. Çalişkan, G., & Sevim, B. (2023). Use of service robots in hospitality: An observational study in terms of technology acceptance model. Tourism and Hospitality Research, 25(2), 167-179. doi: 10.1177/14673584231198438
  10. Cao, K., Yin, H., & Wang, J. (2025). Introducing robot or not? Decisions of competing hotels. International Journal of Hospitality Management, 126, 104034. doi: 10.1016/j.ijhm.2024.104034
  11. Cao, X., Xu, Y., Yao, Y., & Zhi, C. (2023). An improved hybrid A* algorithm of path planning for hotel service robot. International Journal of Advanced Computer Science and Applications, 14(10). doi: 10.14569/IJACSA.2023.0141091
  12. Ceccarelli, M. (2011). Problems and issues for service robots in new applications. International Journal of Social Robotics, 3(3), 299-312. doi: 10.1007/s12369-011-0097-8
  13. Ceglowski, J., & Golub, S. S. (2012). Does China still have a labor cost advantage? Global Economy Journal, 12(3), 1850270. doi: 10.1515/1524-5861.1874
  14. Chang, C., Shao, B., Li, Y., & Zhang, Y. (2022). Factors influencing consumers’ willingness to accept service robots: Based on online reviews of Chinese hotels. Frontiers in Psychology, 13. doi: 10.3389/fpsyg.2022.1016579
  15. Chen, J., Zhang, Y., & Wang, L. (2025). The impact of service robot communication style on consumers’ continued willingness to use. Collabra: Psychology, 11(1). doi: 10.1525/collabra.128020
  16. Chiang, A.-H., & Trimi, S. (2020). Impacts of service robots on service quality. Service Business, 14(4). doi: 10.1007/s11628-020-00423-8
  17. Choi, Y., Choi, M., Oh, M., & Kim, S. (2019). Service robots in hotels: Understanding the service quality perceptions of human-robot interaction. Journal of Hospitality Marketing & Management, 29(6), 1-23. doi: 10.1080/19368623.2020.1703871
  18. Choi, Y., Oh, M., Choi, M., & Kim, S. (2020). Exploring the influence of culture on tourist experiences with robots in service delivery environment. Current Issues in Tourism, 24(5), 1-17. doi: 10.1080/13683500.2020.1735318
  19. Chung, M. J., & Cakmak, M. (2018,). “How was your stay?”: Exploring the use of robots for gathering customer feedback in the hospitality industry. In 2018 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN) (pp. 947-954). Nanjing, China: IEE. doi: 10.1109/ROMAN.2018.8525604
  20. Cohen, J. (1960). A coefficient of agreement for nominal scales. Educational and Psychological Measurement, 20(1), 37-46. doi: 10.1177/001316446002000104
  21. Collins, G. R. (2020). Improving human-robot interactions in hospitality settings. International Hospitality Review, 34(1), 61-79. doi: 10.1108/IHR-09-2019-0019
  22. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. Journal of Risk and Uncertainty, 18(3), 321-325. doi: 10.1023/A:1011156710779
  23. Ding, P., Chong, K. M., Tan, T. H., Zhang, W., Gao, J., & Zhang, Q. (2023). Investigating behavioural intention toward adopting artificial intelligence service robots technology in hospitality in China. Environment-Behaviour Proceedings Journal, 8(26), 389-397. doi: 10.21834/e-bpj.v8i26.4990
  24. Fang, X., & Zhan, J. (2015). Sentiment analysis using product review data. Journal of Big Data, 2(1). doi: 10.1186/s40537-015-0015-2
  25. Ganesh, S. R. (1980). Institution building for social and organizational change: An appreciation. Organization Studies, 1(3), 209-227. doi: 10.1177/017084068000100301
  26. Garcia, S., Strüber, D., Brugali, D., Di Fava, A., Pelliccione, P., & Berger, T. (2022). Software variability in service robotics. Empirical Software Engineering, 28(2). doi: 10.1007/s10664-022-10231-5
  27. García, S., Strüber, D., Brugali, D., Di Fava, A., Pelliccione, P., & Berger, T. (2023). Software variability in service robots (Summary). Proceedings of the 27th ACM International Systems and Software Product Line Conference - Volume A, 268-268. doi: 10.1145/3579027.3608999
  28. Goel, P., Kaushik, N., Sivathanu, B., Pillai, R., & Vikas, J. (2022). Consumers’ adoption of artificial intelligence and robotics in hospitality and tourism sector: Literature review and future research agenda. Tourism Review, 77(4), 1081-1096. doi: 10.1108/TR-03-2021-0138
  29. Guo, L., Gong, L., Xu, Z., Wang, W., & Chen, M.-H. (2024). The role of service robots in enhancing customer satisfaction in embarrassing contexts. Journal of Hospitality and Tourism Management, 59, 116-126. doi: 10.1016/j.jhtm.2024.04.008
  30. Guo, Y., Barnes, S. J., & Jia, Q. (2017). Mining meaning from online ratings and reviews: Tourist satisfaction analysis using latent Dirichlet allocation. Tourism Management, 59, 467-483. doi: 10.1016/j.tourman.2016.09.009
  31. Gupta, S., Mishra, R. S., Singal, G., Badal, T., & Garg, D. (2020). Corridor segmentation for automatic robot navigation in indoor environment using edge devices. Computer Networks, 178, 107374. doi: 10.1016/j.comnet.2020.107374
  32. Gutsche, K., Genovese, J., Serstjuk, P., & Altindis, S. (2025). User-centered design of professional social service robots. AHFE International, 160. doi: 10.54941/ahfe1005806
  33. Hagen, L. (2018). Content analysis of e-petitions with topic modeling: How to train and evaluate LDA models? Information Processing & Management, 54(6), 1292-1307. doi: 10.1016/j.ipm.2018.05.006
  34. Han, H., Kim, S. I., Lee, J.-S., & Jung, I. (2024). Understanding the drivers of consumers’ acceptance and use of service robots in the hotel industry. International Journal of Contemporary Hospitality Management, 37(2), 541-559. doi: 10.1108/IJCHM-02-2024-0163
  35. Heuer, T., Schiering, I., & Gerndt, R. (2019). Privacy-centered design for social robots. Interaction Studies, 20(3), 509-529. doi: 10.1075/is.18063.heu
  36. Hong, H., Jung, H., Park, K., & Ha, S. (2018). SeMo: Service-oriented and model-based software framework for cooperating robots. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 37(11), 2952-2963. doi: 10.1109/TCAD.2018.2857339
  37. Huang, D., Chen, Q., Huang, J., Kong, S., & Li, Z. (2021). Customer-robot interactions: Understanding customer experience with service robot. International Journal of Hospitality Management, 99, 103078. doi: 10.1016/j.ijhm.2021.103078
  38. Ivanov, S., Seyitoğlu, F., & Markova, M. (2020). Hotel managers’ perceptions towards the use of robots: A mixed-methods approach. Information Technology & Tourism, 22(4), 505-535. doi: 10.1007/s40558-020-00187-x
  39. Jeong, H., Lee, H., Kim, C., & Shin, S. (2024). A survey of robot intelligence with large language models. Applied Sciences, 14(19), 8868. doi: 10.3390/app14198868
  40. Jia, S. J., Chi, O. H., & Lu, L. (2024). Social robot privacy concern (SRPC): Rethinking privacy concerns within the hospitality domain. International Journal of Hospitality Management, 122, 103853. doi: 10.1016/j.ijhm.2024.103853
  41. Kapur, P., & Williams, J. D. (2025). Balancing efficiency and human touch: The role of AI and robotics in hospitality. Artificial Intelligence, Machine Learning, & Robotics in Business, 1(1), 49-51. doi: 10.32473/aimlrb.1.1.138286
  42. Kim, S., Kim, J., Badu-Baiden, F., Giroux, M., & Choi, Y. (2021). Preference for robot service or human service in hotels? Impacts of the COVID-19 pandemic. International Journal of Hospitality Management, 93, 102795. doi: 10.1016/j.ijhm.2020.102795
  43. Lajante, M., & Dohm, N. C. (2024). Customer’s social cognition in service recovery satisfaction with human vs robot agent. International Journal of Quality and Service Sciences, 16(4), 498-518. doi: 10.1108/IJQSS-07-2024-0098
  44. Lee, H., Ma, H., & Xiao, G. (2023). Ready for robot assistance? Exploring gender influences on service robot adoption in luxury vs. economy hotels. Journal of Marketing Development and Competitiveness, 17(4). doi: 10.33423/jmdc.v17i4.6663
  45. Lei, C., Hossain, M. S., & Wong, E. (2023). Determinants of repurchase intentions of hospitality services delivered by artificially intelligent (AI) service robots. Sustainability, 15(6), 4914. doi: 10.3390/su15064914
  46. Lestari, N. S., Rosman, D., Chan, S., Nawangsari, L. C., Natalina, H. D., & Triono, F. (2022). Impact of robots, artificial intelligence, service automation (RAISA) acceptance, self-efficacy, and relationship quality on job performance. In 2022 4th International Conference on Cybernetics and Intelligent System (ICORIS) (pp. 1-6). Medan, Indonesia: IEEE. doi: 10.1109/ICORIS56080.2022.10031336
  47. Leung, X. Y., Zhang, H., Lyu, J., & Bai, B. (2023). Why do hotel frontline employees use service robots in the workplace? A technology affordance theory perspective. International Journal of Hospitality Management, 108, 103380. doi: 10.1016/j.ijhm.2022.103380
  48. Liu, W., Ni, S., & Tuo, Y. (2019). Usability testing and requirements analysis of service robot. In 2019 11th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC) (pp. 225-228). Hangzhou, China. doi: 10.1109/IHMSC.2019.00059
  49. Mayer, R. C., Davis, J. H., & Schoorman, F. D. (1995). An integrative model of organizational trust. Academy of Management Review, 20(3), 709-734. doi: 10.5465/amr.1995.9508080335
  50. McCartney, G., & McCartney, A. (2020). Rise of the machines: Towards a conceptual service-robot research framework for the hospitality and tourism industry. International Journal of Contemporary Hospitality Management, 32(12), 3835-3851. doi: 10.1108/IJCHM-05-2020-0451
  51. Milohnić, I., & Kapeš, J. (2024). Exploring the barriers and prospects for service robot adoption in the hotel industry: A management perspective. European Journal of Tourism Research, 38, 3805. doi: 10.54055/ejtr.v38i.3387
  52. Nikolenko, S. I., Koltcov, S., & Koltsova, O. (2016). Topic modelling for qualitative studies. Journal of Information Science, 43(1), 88-102. doi: 10.1177/0165551515617393
  53. Qi, H., Han, Z., & Feng, X. (2024). Research on hotel service robot management system based on artificial intelligence. In 2024 3rd International Conference on Artificial Intelligence and Autonomous Robot Systems (AIARS) (pp. 265-269). Bristol, United Kingdom: IEEE. doi: 10.1109/AIARS63200.2024.00055
  54. Ranieri, C. M., & Romero, R. A. F. (2016). An emotionbased interaction strategy to improve human-robot interaction. In 2016 XIII Latin American Robotics Symposium and IV Brazilian Robotics Symposium (LARS/SBR) (pp. 31-36). Recife, Brazil: IEEE. doi: 10.1109/LARS-SBR.2016.13
  55. Rasheed, H. M. W., He, Y., Khizar, H. M. U., & Abbas, H. S. M. (2023). Exploring consumer-robot interaction in the hospitality sector: Unpacking the reasons for adoption (or resistance) to artificial intelligence. Technological Forecasting and Social Change, 192, 122555. doi: 10.1016/j.techfore.2023.122555
  56. Rasmussen, M. K., Schneider-Kamp, A., Hyrup, T., & Godono, A. (2024). New colleague or gimmick hurdle? A user-centric scoping review of the barriers and facilitators of robots in hospitals. PLOS Digital Health, 3(11), e0000660. doi: 10.1371/journal.pdig.0000660
  57. Ren, Q., Hou, Y., Botteldooren, D., & Belpaeme, T. (2024). No more mumbles: Enhancing robot intelligibility through speech adaptation. IEEE Robotics and Automation Letters, 9(7), 6162-6169. doi: 10.1109/LRA.2024.3401117
  58. Richard, L. J., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159-174. doi: 10.2307/2529310
  59. Romero-Gonzalez, C., Martinez-Gomez, J., & Garcia-Varea, I. (2020). Spoken language understanding for social robotics. In 2020 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC) (pp. 152-157). Ponta Delgada, Portugal: IEEE. doi: 10.1109/ICARSC49921.2020.9096175
  60. Rosete, A., Soares, B., Salvadorinho, J., Reis, J., & Amorim, M. (2020). Service robots in the hospitality industry: An exploratory literature review. Exploring Service Science, 377, 174-186. doi: 10.1007/978-3-030-38724-2_13
  61. Sadangharn, P. (2022). Acceptance of robots as co-workers: Hotel employees’ perspective. International Journal of Engineering Business Management, 14. doi: 10.1177/18479790221113621
  62. Saeki, W., & Ueda, Y. (2024). Sequential model based on human cognitive processing to robot acceptance. Frontiers in Robotics and AI, 11. doi: 10.3389/frobt.2024.1362044
  63. Said, N., Ben Mansour, K., Bahri-Ammari, N., Yousaf, A., & Mishra, A. (2024). Customer acceptance of humanoid service robots in hotels: moderating effects of service voluntariness and culture. International Journal of Contemporary Hospitality Management, 36(6), 1844-1867. doi: 10.1108/IJCHM-12-2022-1523
  64. Schmiedel, T., Müller, O., & vom Brocke, J. (2018). Topic modeling as a strategy of inquiry in organizational research. Organizational Research Methods, 22(4). doi: 10.1177/1094428118773858
  65. Senthamarai, M., Kishore, R. K., Vikram, U. & Kathir, R. (2024). The role and progression of serving robots in hospitality and service industries. International Journal for Multidisciplinary Research, 6(5). doi: 10.36948/ijfmr.2024.v06i05.27961
  66. Stavropoulou, P., Spiliotopoulos, D., & Κουρουπέτρογλου, Γ. (2020). Voice user interfaces for service robots: Design principles and methodology. Lecture Notes in Computer Science, 489-505. doi: 10.1007/978-3-030-49282-3_35
  67. Stirpe, M., Brugnoli, B., Donelli, G., Francolini, I., & Vuotto, C. (2020). Poloxamer 338 affects cell adhesion and biofilm formation in Escherichia coli: Potential applications in the management of catheter-associated urinary tract infections. Pathogens, 9(11), 885. doi: 10.3390/pathogens9110885
  68. Taecharungroj, V., & Mathayomchan, B. (2019). Analysing TripAdvisor reviews of tourist attractions in Phuket, Thailand. Tourism Management, 75, 550-568. doi: 10.1016/j.tourman.2019.06.020
  69. Tractinsky, N., Katz, A. S., & Ikar, D. (2000). What is beautiful is usable. Interacting with Computers, 13(2), 127-145. doi: 10.1016/S0953-5438(00)00031-X
  70. Tsushima, Y., Yamamoto, S., Ravankar, A. A., Luces, J. V. S., & Hirata, Y. (2025). Task planning for a factory robot using large language model. IEEE Robotics and Automation Letters, 10(3), 2383-2390. doi: 10.1109/LRA.2025.3531153
  71. Tung, V. W. S., & Au, N. (2018). Exploring customer experiences with robotics in hospitality. International Journal of Contemporary Hospitality Management, 30(7), 2680-2697. doi: 10.1108/IJCHM-06-2017-0322
  72. Tuomi, A., Tussyadiah, I. P., & Stienmetz, J. (2020). Applications and implications of service robots in hospitality. Cornell Hospitality Quarterly, 62(2). doi: 10.1177/1938965520923961
  73. Tussyadiah, I. P., & Park, S. (2018). Consumer evaluation of hotel service robots. Information and Communication Technologies in Tourism 2018, 308-320. doi: 10.1007/978-3-319-72923-7_24
  74. Vallverdú, J., & Trovato, G. (2016). Emotional affordances for human-robot interaction. Adaptive Behavior, 24(5), 320-334. doi: 10.1177/1059712316668238
  75. Wang, R., Hao, J.-X., Law, R., & Wang, J. (2019). Examining destination images from travel blogs: A big data analytical approach using latent Dirichlet allocation. Asia Pacific Journal of Tourism Research, 24(11), 1092-1107. doi: 10.1080/10941665.2019.1665558
  76. Wang, X., Zhang, Z., Huang, D., & Li, Z. (2023). Consumer resistance to service robots at the hotel front desk: A mixed-methods research. Tourism Management Perspectives, 46, 101074. doi: 10.1016/j.tmp.2023.101074
  77. Wang, Z., Huang, J., Xiong, N., Zhou, X., Lin, X., & Ward, T. L. (2020). A robust vehicle detection scheme for intelligent traffic surveillance systems in smart cities. IEEE Access, 8, 139299-139312. doi: 10.1109/ACCESS.2020.3012995
  78. Wu, X., & Huo, Y. (2023). Impact of the introduction of service robots on consumer satisfaction: Empirical evidence from hotels. Technological Forecasting and Social Change, 194, 122718. doi: 10.1016/j.techfore.2023.122718
  79. Xie, M., & Kim, H. (2022). User acceptance of hotel service robots using the quantitative Kano model. Sustainability, 14(7), 3988. doi: 10.3390/su14073988
  80. Xu, J., Hsiao, A., Reid, S., & Ma, E. (2023). Working with service robots? A systematic literature review of hospitality employees’ perspectives. International Journal of Hospitality Management, 113, 103523. doi: 10.1016/j.ijhm.2023.103523
  81. Yang, J., & Chew, E. (2020). A systematic review for service humanoid robotics model in hospitality. International Journal of Social Robotics. International Journal of Social Robotics, 13(6), 1397-1410. doi: 10.1007/s12369-020-00724-y
  82. Ye, H., Sun, S., & Law, R. (2022). A review of robotic applications in hospitality and tourism research. Sustainability, 14(17), 10827. doi: 10.3390/su141710827
  83. Ying, S., Chan, J. H., & Qi, X. (2020). Why are Chinese and North American guests satisfied or dissatisfied with hotels? An application of big data analysis. International Journal of Contemporary Hospitality Management, 32(10), 3249-3269. doi: 10.1108/IJCHM-02-2020-0129
  84. Yörük, T., Akar, N., & Özmen, N. V. (2023). Research trends on guest experience with service robots in the hospitality industry: A bibliometric analysis. European Journal of Innovation Management, 27(6), 2015-2041. doi: 10.1108/EJIM-09-2022-0530
  85. Zahedifar, R., Baghshah, M. S., & Taheri, A. (2025). LLMcontroller: Dynamic robot control adaptation using large language models. Robotics and Autonomous Systems, 186, 104913. doi: 10.1016/j.robot.2024.104913
  86. Zhang, Y., Ran, X., Luo, C., Gao, Y., Zhao, Y., & Shuai, Q. (2022). “Only visible for three days”: Mining microblogs to understand reasons for using the Time Limit setting on WeChat Moments. Computers in Human Behavior, 134, 107316. doi: 10.1016/j.chb.2022.107316
  87. Zhang, Y., Wang, X., Wu, X., Zhang, W., Jiang, M., & Al-Khassaweneh, M. (2019). Intelligent hotel ROSbased service robot. In 2019 IEEE International Conference on Electro Information Technology (EIT) (pp. 399-403). Brookings, USA: IEEE. doi: 10.1109/EIT.2019.8834040
  88. Zheng, T., Wu, F., Law, R., Qiu, Q., & Wu, R. (2021). Identifying unreliable online hospitality reviews with biased user-given ratings: A deep learning forecasting approach. International Journal of Hospitality Management, 92, 102658. doi: 10.1016/j.ijhm.2020.102658
  89. Zhong, L., Verma, R., Wei, W., Morrison, A. M., & Yang, L. (2022). Multi-stakeholder perspectives on the impacts of service robots in urban hotel rooms. Technology in Society, 68, 101846. doi: 10.1016/j.techsoc.2021.101846
  90. Zia, A., & Alotaibi, A. (2024). Navigating the Customer Experience Landscape: Unraveling the Dynamics of AI-driven Chatbot Services for FMCG Retailers. Journal of Comprehensive Business Administration Research, 1(3), 113-123. doi: 10.47852/bonviewJCBAR42023726
  91. Zuo, S. (2023). How can hospitality industry improve customer satisfaction by determining the relevant degree of robot staff implementation? Journal of Research in Social Science and Humanities, 2(4), 49-68. doi: 10.56397/JRSSH.2023.04.06
DOI: https://doi.org/10.2478/emj-2025-0017 | Journal eISSN: 2543-912X | Journal ISSN: 2543-6597
Language: English
Page range: 1 - 26
Submitted on: Apr 27, 2025
Accepted on: Jul 30, 2025
Published on: Oct 8, 2025
Published by: Bialystok University of Technology
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2025 Xiaocong Jiang, Tianyang Luo, published by Bialystok University of Technology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.