References

• Abdullah, F., & Ward, R. (2016). Developing a general extended technology acceptance model for e-learning by analysing commonly used external factors. Computers in Human Behavior, 56, 238–256. https://doi.org/10.1016/j.chb.2015.11.036
   Google Scholar
• Agarwal, R., & Prasad, P. (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information Systems Research, 9(2), 204–215. https://doi.org/10.1287/isre.9.2.204
   Google Scholar
• Ahmad, A., Jamaludin, A., Zuraimi, N. S. M., & Valeri, M. (2021). Visit intention and destination image in post-Covid-19 crisis recovery. Current Issues in Tourism, 24(17), 2392–2397. https://doi.org/10.1080/13683500.2020.1842342
   Google Scholar
• Al-alak, B. A., & Alnawas, I. A. M. (2011). Measuring the acceptance and adoption of E-Learning by academic staff. Knowledge Management & E-Learning: An International Journal, 3(2), 201–221. https://doi.org/10.34105/j.kmel.2011.03.016
   Google Scholar
• Ali, E. H. M., & Ahmed, M. O. (2019). Sensory marketing and its effect on hotel market-share: Perception of hotel customers. Journal of Tourism and Hospitality Management, 7(1), 116–126. https://doi.org/10.15640/jthm.v7n1a12
   Google Scholar
• Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended Two-Step approach. Psychological Bulletin, 103(3), 411–423. https://doi.org/10.1037/0033-2909.103.3.411
   Google Scholar
• Assaker, G. (2020). Age and gender differences in online travel reviews and user-generated-content (UGC) adoption: Extending the technology acceptance model (TAM) with credibility theory. Journal of Hospitality Marketing & Management, 29(4), 428–449. https://doi.org/10.1080/19368623.2019.1653807
   Google Scholar
• Ayeh, J. K. (2015). Travellers’ acceptance of consumer-generated media: An integrated model of technology acceptance and source credibility theories. Computer Human Behaviour, 48, 173–180. https://doi.org/10.1016/j.chb.2014.12.049
   Google Scholar
• Bagozzi, R. P. (1981). Attitudes, intentions, and behavior: A test of some key hypotheses. Journal of Personality and Social Psychology, 41(4), 607–627. https://doi.org/10.1037/0022-3514.41.4.607
   Google Scholar
• Beldona, S., Schwartz, Z., & Zhang, X. (2018). Evaluating hotel guest technologies: Does home matter? International Journal of Contemporary Hospitality Management, 30(5), 2327–2342. https://doi.org/10.1108/IJCHM-03-2017-0148
   Google Scholar
• Bilgihan, A., Smith, S., Ricci, P., & Bujisic, M. (2016). Hotel guest preferences of in-room technology amenities. Journal of Hospitality and Tourism Technology, 7(2), 118–134. https://doi.org/10.1108/JHTT-02-2016-0008
   Google Scholar
• Binbasioglu, H., & Turk, M. (2020). Mobile technology acceptance among Turkish travelers. Digital marketing strategies for tourism, hospitality, and airline industries. IGI Global, Pennsylvania, 111–140. https://doi.org/10.4018/978-1-5225-9783-4.ch006
   Google Scholar
• Buhalis, D., & Foerste, M. (2015). SoCoMo marketing for travel and tourism: Empowering co-creation of value. Journal of Destination Marketing & Management, 4(3), 151–161. https://doi.org/10.1016/j.jdmm.2015.04.001
   Google Scholar
• Buhalis, D., & Sinarta, Y. (2019). Real-time co-creation and nowness service: Lessons from tourism and hospitality. Journal of Travel & Tourism Marketing, 36(5), 563–582. https://doi.org/10.1080/10548408.2019.1592059
   Google Scholar
• Byrne, B. M. (2013). Structural equation modeling with Mplus: Basic concepts, applications, and programming (3rd ed.). Routledge. https://doi.org/10.4324/9780203807644
   Google Scholar
• Chan, E. S. W., Okumus, F., & Chan, W. (2017). Application of environmental technologies in hotels. Journal of Hospitality Marketing & Management, 26(1), 23–47. https://doi.org/10.1080/19368623.2016.1176975
   Google Scholar
• Chen, Y. L. (2014). A study on student self-efficacy and technology acceptance model within an online task-based learning environment. Journal of Computers, 9(1), 34–43. https://doi.org/10.4304/jcp.9.1.34-43
   Google Scholar
• Chen, R. J. (2015). From sustainability to customer loyalty: A case of full service hotels’ guests. Journal of Retailing and Consumer Services, 22, 261–265. https://doi.org/10.1016/j.jretconser.2014.08.007
   Google Scholar
• Chen, N. H. (2019). Extending a TAM–TTF model with perceptions toward telematics adoption. Asia Pacific Journal of Marketing and Logistics, 31(1), 37–54. https://doi.org/10.1108/APJML-02-2018-0074
   Google Scholar
• Chen, C. F., & Chen, P. C. (2011). Applying the TAM to travelers’ usage intentions of GPS devices. Expert Systems with Applications, 38(5), 6217–6221. https://doi.org/10.1016/j.eswa.2010.11.047
   Google Scholar
• Chen, M. F., & Tung, P. J. (2014). Developing an extended theory of planned behaviour model to predict consumers’ intention to visit green hotels. International Journal of Hospitality Management, 36, 221–230. https://doi.org/10.1016/j.ijhm.2013.09.006
   Google Scholar
• Chen, S.-H., Tzeng, S. Y., Tham, A., & Chu, P, X. (2021). Hospitality services in the post COVID-19 era: Are we ready for high-tech and no touch service delivery in smart hotels? Journal of Hospitality Marketing & Management, 30(8), 905–928.https://doi.org/10.1080/19368623.2021.1916669
   Google Scholar
• Cheng, Y. M. (2014). Exploring the intention to use mobile learning: The moderating role of personal innovativeness. Journal of Systems and Information Technology, 16(1), 40–61. https://doi.org/10.1108/JSIT-05-2013-0012
   Google Scholar
• Chung, N., Han, H., & Joun, Y. (2015). Tourists’ intention to visit a destination: The role of augmented reality (AR) application for a heritage site. Computers in Human Behavior, 50, 588–599. https://doi.org/10.1016/j.chb.2015.02.068
   Google Scholar
• Ciftci, O., Berezina, K., & Kang, M. (2021). Effect of personal innovativeness on technology adoption in hospitality and tourism: Meta-analysis. In W. Wörndl, C. Koo, & J. L. Stienmetz (Eds.), Information and Communication Technologies in Tourism 2021 (pp. 162–174). Springer. https://doi.org/10.1007/978-3-030-65785-7_14
   Google Scholar
• Davis, F., Bagozzi, R., & Warshaw, P. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 8(8), 982–1003. https://doi.org/10.1287/mnsc.35.8.982
   Google Scholar
• De Kervenoael, R., Hasan, R., Schwob, A., & Goh, E. (2020). Leveraging human-robot interaction in hospitality services: Incorporating the role of perceived value, empathy, and information sharing into visitors’ intentions to use social robots. Tourism Management, 78, 104042. https://doi.org/10.1016/j.tourman.2019.104042
   Google Scholar
• De Smet, C., Bourgonjon, J., De Wever, B., Schellens, T., & Valcke, M. (2012). Researching instructional use and the technology acceptation of learning management systems by secondary school teachers. Computers & Education, 58(2), 688. https://doi.org/10.1016/j.compedu.2011.09.013
   Google Scholar
• DePinto, J. (2017, June 13). Occupancy sensing improves hospitality. Linkedin.https://www.linkedin.com/pulse/occupancy-sensing-improves-hospitality-jesse-depinto
   Google Scholar
• Dutilly, D. T., Browne, J., Ingeneri, N. P., & Monroe, S. R. (2015). System and method for using a touchscreen as an interface for music-based gameplay.https://patentimages.storage.googleapis.com/55/f8/42/5a1278a98dd7d3/US8961309.pdf
   Google Scholar
• Dykins, R. (2020). Globetrender. https://globetrender.com/2020/08/24/leyeju-smart-hotels-touch-free-stays-china/EHL
   Google Scholar
• Faiers, A., Neame, C., & Cook, M. (2007). The adoption of domestic solar-power systems: Do consumers assess product attributes in a stepwise process? Energy Policy, 35(6), 3418–3423. https://doi.org/10.1016/j.enpol.2006.10.029
   Google Scholar
• Gefen, D., Karahanna, E., & Straub, D. (2003). Inexperience and experience with online stores: The importance of TAM and trust. IEEE Transactions on Engineering Management, 50(3), 307–321. https://doi.org/10.1109/TEM.2003.817277
   Google Scholar
• Gössling, S., Scott, D., & Hall, C. M. (2021). Pandemics, tourism and global change: A rapid assessment of COVID-19. Journal of Sustainable Tourism, 29(1), 1–20. https://doi.org/10.1080/09669582.2020.1758708
   Google Scholar
• Han, H., Hsu, L., & Sheu, C. (2010). Application of the theory of planned behaviour to green hotel choice: testing the effect of environment friendly activities. Tourism Management, 31(3), 325–334.
   Google Scholar
• Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. Guilford Publications.
   Google Scholar
• Jaremen, D., Jędrasiak, M., & Rapacz, A. (2016). The concept of smart hotels as an innovation on the hospitality industry market-case study of Puro Hotel in Wrocław. Economic Problems of Tourism, 36(4), 65–75. https://doi.org/10.18276/ept.2016.4.36-06
   Google Scholar
• Joe, S., Kim, J., & Zemke, D. M. V. (2022). Effects of social influence and perceived enjoyment on Kiosk acceptance: A moderating role of gender. International Journal of Hospitality and Tourism Administration, 23(2), 289–316. https://doi.org/10.1080/15256480.2020.1746217
   Google Scholar
• John, D. R., Scott, C. A., & Bettman, J. R. (1986). Sampling data for covariation assessment: The effect of prior beliefs on search patterns. Journal of Consumer Research, 13(1), 38–47. https://doi.org/10.1086/209046
   Google Scholar
• Kamboj, S., & Gupta, S. (2020). Use of smart phone apps in co-creative hotel service innovation: An evidence from India. Current Issues in Tourism, 23(3), 323–344. https://doi.org/10.1080/13683500.2018.1513459
   Google Scholar
• Kang, J. W., & Namkung, Y. (2019). The role of personalization on continuance intention in food service mobile apps. International Journal of Contemporary Hospitality Management, 31(2), 734–752. https://doi.org/10.1108/IJCHM-12-2017-0783
   Google Scholar
• Kaushik, A. K., Agrawal, A. K., & Rahman, Z. (2015). Tourist behaviour towards self-service hotel technology adoption: Trust and subjective norm as key antecedents. Tourism Management Perspectives, 16, 278–289. https://doi.org/10.1016/j.tmp.2015.09.002
   Google Scholar
• Kim, J., & Han, H. (2020). Hotel of the future: Exploring the attributes of a smart hotel adopting a mixed-methods approach. Journal of Travel & Tourism Marketing, 37(7), 804–822. https://doi.org/10.1080/10548408.2020.1835788
   Google Scholar
• Kim, W. G., Li, J., Han, J. S., & Kim, Y. (2017). The influence of recent hotel amenities and green practices on guests’ price premium and revisit intention. Tourism Economics, 23(3), 577–593. https://doi.org/10.5367/te.2015.0531
   Google Scholar
• Kim, M., & Qu, H. (2014). Travelers’ behavioral intention toward hotel self-service kiosks usage. International Journal of Contemporary Hospitality Management, 26(2), 225–245. https://doi.org/10.1108/IJCHM-09-2012-0165
   Google Scholar
• Kucukusta, D. (2017). Chinese travellers’ preferences for hotel amenities. International Journal of Contemporary Hospitality Management, 29(7), 1956–1976. https://doi.org/10.1108/IJCHM-09-2016-0511
   Google Scholar
• Kuo, Y. F., & Yen, S. N. (2009). Towards an understanding of the behavioral intention to use 3G mobile value-added services. Computers in Human Behavior, 25(1), 103–110. https://doi.org/10.1016/j.chb.2008.07.007
   Google Scholar
• Lai, W. C., & Hung, W. H. (2018). A framework of cloud and AI based intelligent hotel. In E. Y. Li & F. K. Chang (Eds.), Proceedings of the 18th international conference on electronic business ICEB’18 (pp. 36–43). http://iceb.johogo.com/proceedings/2018/ICEB2018_paper_81_full.pdf
   Google Scholar
• Law, R., Chan, I., & Wang, L. (2018). A comprehensive review of mobile technology use in hospitality and tourism. Journal of Hospitality Marketing & Management, 27(6), 626–648. https://doi.org/10.1080/19368623.2018.1423251
   Google Scholar
• Lee, Y., Hsieh, Y., & Chen, Y. (2013). An investigation of employees’ use of e-learning systems: Applying the technology acceptance model. Behaviour and Information Technology, 32(2), 173–189. https://doi.org/10.1080/0144929X.2011.577190
   Google Scholar
• Lee, Y. K., Park, J. H., Chung, N., & Blakeney, A. (2012). A unified perspective on the factors influencing usage intention toward mobile financial services. Journal of Business Research, 65(11), 1590–1599. https://doi.org/10.1016/j.jbusres.2011.02.044
   Google Scholar
• Leung, R. (2019). Smart hospitality: Taiwan hotel stakeholder perspectives. Tourism Review, 74(1), 50–62. https://doi.org/10.1108/TR-09-2017-0149
   Google Scholar
• Liébana-Cabanillas, F., Sánchez-Fernández, J., & Muñoz-Leiva, F. (2014). Antecedents of the adoption of the new mobile payment systems: The moderating effect of age. Computers in Human Behavior, 35, 464–478. https://doi.org/10.1016/j.chb.2014.03.022
   Google Scholar
• Liljander, V., Gillberg, F., Gummerus, J., & Van Riel, A. (2006). Technology readiness and the evaluation and adoption of self-service technologies. Journal of Retailing and Consumer Services, 13(3), 177–191. https://doi.org/10.1016/j.jretconser.2005.08.004
   Google Scholar
• Lin, J., Chang, H., & Fisk, R. P. (2011). The role of technology readiness in self-service technology acceptance. Managing Service Quality, 21(4), 424–444. https://doi.org/10.1108/09604521111146289
   Google Scholar
• Lin, H., Chi, O. H., & Gursoy, D. (2020). Antecedents of customers’ acceptance of artificially intelligent robotic device use in hospitality services. Journal of Hospitality Marketing & Management, 29(5), 530–549. https://doi.org/10.1080/19368623.2020.1685053
   Google Scholar
• Lin, C., Shih, H., & Sher, P. J. (2007). Integrating technology readiness into technology acceptance: The TRAM model. Psychology and Marketing, 24(7), 641–657. https://doi.org/10.1002/mar.20177
   Google Scholar
• Liu, C., Hung, K., Wang, D., & Wang, S. (2020). Determinants of self-service technology adoption and implementation in hotels: The case of China. Journal of Hospitality Marketing Management, 29(6), 636–661. https://doi.org/10.1080/19368623.2020.1689216
   Google Scholar
• Ma, Y., Hardy, A., & Ooi, C. S. (2019). Researching Chinese tourists on the move. Journal of China Tourism Research, 16(2), 214–229. https://doi.org/10.1080/19388160.2019.1607794
   Google Scholar
• Makmor, N., Aziz, A., & Alam, S. S. (2019). Social commerce an extended technology acceptance model: The mediating effect of perceived ease of use and perceived usefulness. Malaysian Journal of Consumer and Family Economics, 22, 119–136.
   Google Scholar
• Massey, A. P., Khatri, V., & Montoya-Weiss, M. M. (2007). Usability of online services: The role of technology readiness and context. Decision Sciences, 38(2), 227–308. https://doi.org/10.1111/j.1540-5915.2007.00159.x
   Google Scholar
• Molina, M. Á. R., Frías-Jamilena, D., & Castañeda-García, J. A. (2013). The moderating role of past experience in the formation of a tourist destination’s image and in tourists’ behavioural intentions. Current Issues in Tourism, 16(2), 107–127. https://doi.org/10.1080/13683500.2012.665045
   Google Scholar
• Monzavi, T., Zarei, B., & Hossein Ghapanchi, A. (2013). Investigating the impacts of external factors on user beliefs in adopting software. International Technology Management Review, 3(3), 160–174. https://doi.org/10.2991/itmr.2013.3.3.2
   Google Scholar
• Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192–222. https://doi.org/10.1287/isre.2.3.192
   Google Scholar
• Morosan, C. (2012). Theoretical and empirical considerations of guests’ perceptions of biometric systems in hotels: Extending the technology acceptance model. Journal of Hospitality and Tourism Research, 36(1), 52–84. https://doi.org/10.1177/1096348010380601
   Google Scholar
• Moslehpour, M., Pham, V. K., Wong, W. K., & Bilgiçli, I. (2018). E-purchase intention of Taiwanese consumers: Sustainable mediation of perceived usefulness and perceived ease of use. Sustainability (Switzerland), 10(1), 234. https://doi.org/10.3390/su10010234
   Google Scholar
• O’Cass, A., & Fenech, T. (2003). Web retailing adoption: Exploring the nature of internet users Web retailing behavior. Journal of Retailing and Consumer Services, 10(2), 81–94. https://doi.org/10.1016/S0969-6989(02)00004-8
   Google Scholar
• Park, S. Y. (2009). An analysis of the technology acceptance Model in understanding university behavioral intention to use e-learning. Educational Technology and Society, 12(3), 150–162.
   Google Scholar
• Ramayah, T., Ignatius, J., & Aafaqi, B. (2005). PC usage among students in a private institution of higher learning: The moderating role of prior experience. Asia Pacific Journal of Educators and Education, 20, 131–152. http://eprints.usm.my/34321/1/JPP09Ramayah(131-152)B.pdf
   Google Scholar
• Roberts, D., Hughes, M., & Kertbo, K. (2014). Exploring consumers’ motivations to engage in innovation through co-creation activities. European Journal of Marketing, 48(1/2), 147–169. https://doi.org/10.1108/EJM-12-2010-0637
   Google Scholar
• Rogers, E. (2002). Diffusion of Preventive Innovations. Addictive Behaviors, 27(6), 989–993. https://doi.org/10.1016/S0306-4603(02)00300-3
   Google Scholar
• Rosenbaum, M. S., & Wong, I. A. (2015). If you install it, will they use it? Understanding why hospitality customers take technological pauses from self-service technology. Journal of Business Research, 68(9), 1862–1868. https://doi.org/10.1016/j.jbusres.2015.01.014
   Google Scholar
• Santos, V., Ramos, P., Sousa, B., Almeida, N., & Valeri, M. (2021). Factors influencing touristic consumer behaviour. Journal of Organizational Change Management. Advance online publication. https://doi.org/10.1108/JOCM-02-2021-0032
   Google Scholar
• Sbounias, J. (2019, July 30). 5 smart hotels around the world that highlight this new global trend. Hotelier Academy. https://www.hotelieracademy.org/5-smart-hotels-that-confirm-the-potentials-of-this-new-hotel-trend/
   Google Scholar
• Shashou, A. (2019). Hotels’ Digital Divide. ALICE. https://www.aliceplatform.com/hubfs/ALICE-Hotels-Digital-Divide.pdf
   Google Scholar
• Shen, S., Sotiriadis, M., & Zhang, Y. (2020). The influence of smart technologies on customer journey in tourist attractions within the smart tourism management framework. Sustainability, 12(10), 1–18. https://doi.org/10.3390/su12104157
   Google Scholar
• Shin, H. H., & Jeong, M. Redefining luxury service with technology implementation: The impact of technology on guest satisfaction and loyalty in a luxury hotel. (2022). International Journal of Contemporary Hospitality Management 34(4), 1491–1514. Advance online publication. https://doi.org/10.1108/IJCHM-06-2021-0798
   Google Scholar
• Shoenfeld, N. A. (2019). Pass-through convenience cabinet for hotel or similar public accommodation. Patent Application Publication (U. S. Patent). https://patentimages.storage.googleapis.com/cb/41/72/65a2625d39f4e4/US20190082829A1.pdf
   Google Scholar
• Sinaiko, H. W., & Brislin, R. W. (1973). Evaluating language translations: Experiments on three assessment methods. Journal of Applied Psychology, 57(3), 328–334.
   Google Scholar
• Skavronskaya, L., Moyle, B., Scott, N., & Schaffer, V. (2020). Collecting memorable tourism experiences: How do ‘wechat’? Journal of China Tourism Research, 16(3), 424–446. https://doi.org/10.1080/19388160.2019.1656131
   Google Scholar
• Song, H., Ma, E., & Cheng, M. (2021). Dining with distance during the pandemic: An enquiry from the theory of proxemics and social exchange. Current Issues in Tourism. Advance online publication. https://doi.org/10.1080/13683500.2021.1940108
   Google Scholar
• Sun, S., Lee, P., & Law, R. (2020). Impact of cultural values on technology acceptance and technology readiness. International Journal of Hospitality Management, 77, 89–96. https://doi.org/10.1016/j.ijhm.2018.06.017
   Google Scholar
• Tan, G. W. H., Ooi, K. B., Leong, L. Y., & Lin, B. (2014). Predicting the drivers of behavioral intention to use mobile learning: A hybrid SEM-Neural Networks approach. Computers in Human Behavior, 36, 198–213. https://doi.org/10.1016/j.chb.2014.03.052
   Google Scholar
• Tavitiyaman, P., Zhang, X., & Tsang, W. Y. (2020). How tourists perceive the usefulness of technology adoption in hotels: Interaction effect of past experience and education level. Journal of China Tourism Research. 18(1). https://doi.org/10.1080/19388160.2020.1801546
   Google Scholar
• Taylor, S., & Todd, P. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144–176. https://doi.org/10.1287/isre.6.2.144
   Google Scholar
• Thakur, R., & Srivastava, M. (2014). Adoption readiness, personal innovativeness, perceived risk and usage intention across customer groups for mobile payment services in India. Internet Research, 24(3), 369–392. https://doi.org/10.1108/IntR-12-2012-0244
   Google Scholar
• Tom Dieck, M. C., & Jung, T. (2018). A theoretical model of mobile augmented reality acceptance in urban heritage tourism. Current Issues in Tourism, 21(2), 154–174. https://doi.org/10.1080/13683500.2015.1070801
   Google Scholar
• Tom Dieck, M. C., Jung, T. H., Kim, W. G., & Moon, Y. (2017). Hotel guests’ social media acceptance in luxury hotels. International Journal of Contemporary Hospitality Management, 29(1), 530–550. https://doi.org/10.1108/IJCHM-10-2015-0552
   Google Scholar
• Tung, V. W. S., & Au, N. (2018). Exploring customer experiences with robotics in hospitality. International Journal of Contemporary Hospitality Management, 30(7), 2680–2697. https://doi.org/10.1108/IJCHM-06-2017-0322
   Google Scholar
• Valenti, C., & Riviere, J. (2008). Marketing dissertation The concept of Sensory Marketing. Högskolan i Halmstad. https://www.diva-portal.org/smash/get/diva2:238806/FULLTEXT01.pdf
   Google Scholar
• Valeri, M. (2021). Organizational studies: implications for the strategic management. Springer Nature.
   Google Scholar
• Valeri, M., & Baggio, R. (2020). Social network analysis: Organizational implications in tourism management. International Journal of Organizational Analysis, 29(2), 342–353. https://doi.org/10.1108/IJOA-12-2019-1971
   Google Scholar
• Valeri, M., & Baggio, R. (2021a). Increasing the efficiency of knowledge transfer in Italian tourism system: A network approach. Current Issues in Tourism, 1–16. Advance online publication. https://doi.org/10.1080/13683500.2021.1937960
   Google Scholar
• Valeri, M., & Baggio, R. (2021b). Italian tourism intermediaries: A social network analysis exploration. Current Issues in Tourism, 24(9), 1270–1283. https://doi.org/10.1080/13683500.2020.1777950
   Google Scholar
• Vankatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204.
   Google Scholar
• Verma, V., & Baltoo, M. (2020). The influence of technological amenities in relation to hotel guest overall satisfaction. UGC Care Journal, 31(4), 87–105. https://doi.org/10.1080/1528008X.2011.541842
   Google Scholar
• Wang, C., & Jeong, M. (2018). What makes you choose Airbnb again? An examination of users’ perceptions toward the website and their stay. International Journal of Hospitality Management, 74, 162–170. https://doi.org/10.1016/j.ijhm.2018.04.006
   Google Scholar
• Wang, Y., Wang, S., Wang, J., Wei, J., & Wang, C. (2020). An empirical study of consumers’ intention to use ride‑sharing services: Using an extended technology acceptance model. Transportation, 47(1), 397–415. https://doi.org/10.1007/s11116-018-9893-4
   Google Scholar
• Webster, C., & Ivanov, S. (2020). Robots in travel, tourism and hospitality: Key findings from a global study. Zangador, Varna. https://ssrn.com/abstract=3542208
   Google Scholar
• Wolfe, A. (2020, March 24). Cali group expands use of facial recognition Tech. Hospitality Technology.https://hospitalitytech.com/cali-group-expands-use-facial-recognition-tech
   Google Scholar
• Wu, H. C., & Cheng, C. C. (2018). Relationships between technology attachment, experiential relationship quality, experiential risk and experiential sharing intentions in a smart hotel. Journal of Hospitality and Tourism Management, 37, 42–58. https://doi.org/10.1016/j.jhtm.2018.09.003
   Google Scholar
• Xu, X. (2018). Research on the construction and development of smart hotel from the perspective of serving customers. Proceedings of the 2018 2nd international conference on education science and economic management (ICESEM 2018), Xiamen, China. https://doi.org/10.2991/icesem-18.2018.228
   Google Scholar
• Yang, F. X. (2017). Effects of restaurant satisfaction and knowledge sharing motivation on eWOM intentions: The moderating role of technology acceptance factors. Journal of Hospitality and Tourism Research, 41(1), 93–127. https://doi.org/10.1177/1096348013515918
   Google Scholar
• Yang, H., Song, H., Cheung, C., & Guan, J. (2021). How to enhance hotel guests’ acceptance and experience of smart hotel technology: An examination of visiting intentions. International Journal of Hospitality Management, 97, 103000. https://doi.org/10.1016/j.ijhm.2021.103000
   Google Scholar
• Yoh, E., Damhorst, M. L., Sapp, S., & Laczniak, R. (2003). Consumer adoption of the internet: The case of apparel shopping. Psychology and Marketing, 20(12), 1095–1118. https://doi.org/10.1002/mar.10110
   Google Scholar
• Yu, C. S. (2011). Sensory marketing. Managing Service Quality: An International Journal, 21(5), 568–570. https://doi.org/10.1108/09604521111159834
   Google Scholar
• Zeng, Z., Chen, P. J., & Lew, A. A. (2020). From high-touch to high-tech: COVID-19 drives robotics adoption. Tourism Geographies, 22(3), 724–734. https://doi.org/10.1080/14616688.2020.1762118
   Google Scholar