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Say Aye to AI: Customer Acceptance and Intention to Use Service Robots in the Hospitality Industry

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International Conference on Information Systems and Intelligent Applications (ICISIA 2022)

Abstract

As industrial revolution 4.0 is introduced, many turn into the use of technology and artificial intelligence (AI) in creating a new competitive advantage to business as well as create an automation that ease the operations and increases profitability. With the important contributions of the tourism and hospitality industry, the advantages of using AI can be benefited. Consequently, it is vital for business to understand customers perception towards the use of AI and services robots. Thus, this study aims to investigate the relationship of eight items under three elements of the service robot acceptance model with the acceptance and intention to use service robots. The results of the study show that the perceived usefulness, trust and rapport are significantly related to acceptance of service robots, which in turn, positively related to intention to use them. Implications of the research findings are discussed to support the notion should the industry Say Aye to AI.

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References

  1. Bulchand-Gidumal J (2020) Impact of artificial intelligence in travel, tourism, and hospitality. In: Handbook of e-Tourism. Springer International, Cham, pp 1–20

    Google Scholar 

  2. Li JJ, Bonn MA, Ye BH (2019) Hotel employee’s artificial intelligence and robotics awareness and its impact on turnover intention: The moderating roles of perceived organizational support and competitive psychological climate. Tour Manag 73:172–181

    Article  Google Scholar 

  3. Samala N, Katkam BS, Bellamkonda RS, Rodriguez RV (2020) Impact of AI and robotics in the tourism sector: a critical insight. J Tour Futures 8:73–87

    Article  Google Scholar 

  4. World Travel & Tourism Council, Economic Impact Reports, https://wttc.org/Research/Economic-Impact. Accessed 2 May 2022

  5. Travel Channel, 10 hotels that have robot employees, https://www.travelchannel.com/interests/gear-and-gadgets/photos/10-hotels-that-are-using-robots. Accessed 2 May 2022

  6. Mahomed S (2020) COVID-19: The role of artificial intelligence in empowering the healthcare sector and enhancing social distancing measures during a pandemic. S Afr Med J 110(7):610–613

    Google Scholar 

  7. Haseeb M, Mihardjo LW, Gill AR, Jermsittiparsert K (2019) Economic impact of artificial intelligence: New look for the macroeconomic assessment in Asia-pacific region. Int J Comput Intell Syst 12(2):1295

    Article  Google Scholar 

  8. Helble M, Fink A (2020) Reviving tourism amid the COVID-19 pandemic. ADB Briefs 1(150):1–13

    Google Scholar 

  9. Sharma GD, Thomas A, Paul J (2021) Reviving tourism industry post-COVID-19: a resilience-based framework. Tour Manag Persp 37:100786

    Google Scholar 

  10. Mukherjee S, Baral MM, Venkataiah C, Pal SK, Nagariya R (2021) Service robots are an option for contactless services due to the COVID-19 pandemic in the hotels. Decision 48(4):445–460

    Article  Google Scholar 

  11. Seyitoğlu F, Ivanov S (2021) Service robots as a tool for physical distancing in tourism. Curr Issue Tour 24(12):1631–1634

    Article  Google Scholar 

  12. The Star: ‘Robots don't sneeze’: Hotels, hospitals, offices turning to delivery bots during coronavirus pandemic. https://www.thestar.com.my/tech/tech-news/2020/10/12/robots-dont-sneeze-hotels-hospitals-offices-turning-to-delivery-bots-during-coronavirus-pandemic. Accessed 18 Febr 2022

  13. Wirtz J, Patterson PG, Kunz WH, Gruber T, Lu VN, Paluch S, Martins A (2018) Brave new world: service robots in the frontline. J Serv Manag 29(5):907–931

    Article  Google Scholar 

  14. Belanche D, Casaló LV, Flavián C (2021) Frontline robots in tourism and hospitality: service enhancement or cost reduction? Electr Mark 31(3):477–492

    Google Scholar 

  15. Fernandes T, Oliveira E (2021) Understanding consumers’ acceptance of automated technologies in service encounters: drivers of digital voice assistants adoption. J Bus Res 122:180–191

    Article  Google Scholar 

  16. Gursoy D, Chi OH, Lu L, Nunkoo R (2019) Consumers acceptance of artificially intelligent (AI) device use in service delivery. Int J Inf Manage 49:157–169

    Article  Google Scholar 

  17. Park S (2020) Multifaceted trust in tourism service robots. Ann Tour Res 81:1–33

    Article  Google Scholar 

  18. Malay Mail: EcoWorld to unveil Malaysia's first robot hotel. https://www.malaymail.com/news/money/2019/02/17/ecoworld-to-unveil-malaysias-first-robot-hotel/1723905. Accessed 2 Sept 2022

  19. Oh C, Lee T, Kim Y, Park SH, Kwon S, Suh B (2017) Us vs. them: understanding artificial intelligence technophobia over the Google DeepMind Challenge Match. In: Conference on Human Factors in Computing Systems—Proceedings, pp 2523–2534

    Google Scholar 

  20. Cham TH, Low SC, Lim CS, Aye AK, Ling RL (2018) Bin: preliminary study on consumer attitude towards fintech products and services in Malaysia. Int J Eng Technol 7(2):166–169

    Google Scholar 

  21. Godoe P, Johansen TS (2012) Understanding adoption of new technologies: technology readiness and technology acceptance as an integrated concept. J Eur Psychol Stud 3:38

    Article  Google Scholar 

  22. Al-Emran M, Granić A (2021) Is it still valid or outdated? A bibliometric analysis of the technology acceptance model and its applications from 2010 to 2020. In: Recent advances in technology acceptance models and theories. Springer, Cham

    Google Scholar 

  23. Stock RM, Merkle M (2017) A service robot acceptance model: user acceptance of humanoid robots during service encounters. In: 2017 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops, pp 339–344

    Google Scholar 

  24. Stock RM, Merkle M (2018) Can humanoid service robots perform better than service employees? A comparison of innovative behavior cues. In: Proceedings of the Annual Hawaii International Conference on System Sciences, 2018-January(February), pp 1056–1065

    Google Scholar 

  25. Venkatesh V, Davis FD (2000) Theoretical extension of the technology acceptance model: four longitudinal field studies. Manag Sci 46(2):186–204

    Article  Google Scholar 

  26. Tinwell A, Grimshaw M, Williams A (2011) The uncanny wall. Int J Arts Technol 4(3):326–341

    Article  Google Scholar 

  27. Heerink M, Krose B, Evers V, Wielinga B (2008) The influence of social presence on acceptance of a companion robot by older people. J Phys Agents 2(2):33–40

    Google Scholar 

  28. Siau K, Wang W (2018) Building trust in artificial intelligence, machine learning, and robotics. Cutter Bus Techno J 31(2):47–53

    Google Scholar 

  29. Gremler DD, Gwinner KP (2000) Customer-employee rapport in service relationships. J Serv Res 3(1):82–104

    Article  Google Scholar 

  30. Schmidt DM, Brüderle P, Mörtl M (2016) Focusing aspects of customer acceptance for planning product-service systems—A case study from construction machines industry. Procedia CIRP 50:372–377

    Article  Google Scholar 

  31. Abdul Rahim F, Goh PJ, Cheah LF (2019) Malaysian coffee culture: attributes considered to purchase coffee beverages. J Mark Adv Pract 1(1):50–62

    Google Scholar 

  32. Cham TH, Ng CKY, Lim YM, Cheng BL (2018) Factors influencing clothing interest and purchase intention: a study of Generation Y consumers in Malaysia*. Int Rev Retail Distrib Cons Res 28(2):174–189

    Google Scholar 

  33. Abdul Rahim F, Zulfakar ZA, Rusli KA (2021) Halalan Toyyiban: the mediating effect of attitude on Muslim’s purchase intention towards imported Halal food in Malaysia. J Mark Adv Pract 3(2):60–75

    Google Scholar 

  34. McLean G, Osei-Frimpong K (2019) Hey Alexa … examine the variables influencing the use of artificial intelligent in-home voice assistants. Comput Hum Behav 99:28–37

    Article  Google Scholar 

  35. Heerink M, Krose B, Evers V, Wielinga B (2010) Assessing acceptance of assistive social agent technology by older adults: The Almere model. Int J Soc Robot 2(4):361–375

    Article  Google Scholar 

  36. 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. Tour Manag 78:104042

    Article  Google Scholar 

  37. Lu L, Cai R, Gursoy D (2019) Developing and validating a service robot integration willingness scale. Int J Hosp Manag 80:36–51

    Article  Google Scholar 

  38. Hair JF, Risher JJ, Sarstedt M, Ringle CM (2019) When to use and how to report the results of PLS-SEM. Eur Bus Rev 31(1):2–24

    Article  Google Scholar 

  39. Huang MH, Rust RT (2018) Artificial intelligence in service. J Serv Res 21(2):155–172

    Article  Google Scholar 

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Correspondence to Zufara Arneeda Zulfakar .

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Zulfakar, Z.A., Rahim, F.A., Yat, D.N.C., Mun, L.H., Cham, TH. (2023). Say Aye to AI: Customer Acceptance and Intention to Use Service Robots in the Hospitality Industry. In: Al-Emran, M., Al-Sharafi, M.A., Shaalan, K. (eds) International Conference on Information Systems and Intelligent Applications. ICISIA 2022. Lecture Notes in Networks and Systems, vol 550. Springer, Cham. https://doi.org/10.1007/978-3-031-16865-9_7

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