IDEAS home Printed from https://ideas.repec.org/a/spt/admaec/v14y2024i5f14_5_7.html
   My bibliography  Save this article

Unpacking the Reasons Shaping Employee Acceptance and Attitudes towards AI Assistant Services in the Hotel Industry: A Behavioral Reasoning Perspective

Author

Listed:
  • Tarikul Islam
  • Erhua Zhou

Abstract

This study investigated organizational employees' opinions and acceptance of AI-based service assistants using the Behavioral Reasoning Theory (BRT). The behavioural reasoning theory-based study included 50 hotel industry executives, HR leaders, and employees. Themes were identified by thematic analysis of observations, focus groups, and participant interviews. This study used comparative thematic analysis and MAXQDA automated content analysis. It examines "reasons for" and "reasons against" adoption from a least developing nation's perspective. The reasons are personalisation, interactivity, perceived intelligence, anthropomorphism, language difficulties, technology phobia, service failure recovery, and inadequate infrastructure. "Reasons for" positively affect mindset and adoption intention, whereas "reasons against" negatively affect them. Financial risks, technological infrastructure issues, data security issues, and a lack of an organisational strategy are also seen in Bangladesh's AI deployment. The study provides practical insights for hotel industry practitioners, managers, and employees, as well as system designers and developers of AI-driven service solutions, on AI assistant adoption. Behavioural reasoning theory is used for the first time to examine hotel employees' attitudes and intentions to use AI-based service assistants. This study is a cross-sectional investigation that is carried out within certain, limited industrial sectors. Longitudinal studies can be conducted to generalize the outcome of this study. Â JEL classification numbers: M21, M30, 010.

Suggested Citation

  • Tarikul Islam & Erhua Zhou, 2024. "Unpacking the Reasons Shaping Employee Acceptance and Attitudes towards AI Assistant Services in the Hotel Industry: A Behavioral Reasoning Perspective," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 14(5), pages 1-7.
    • Handle: RePEc:spt:admaec:v:14:y:2024:i:5:f:14_5_7
    as

    Download full text from publisher

    File URL: http://www.scienpress.com/Upload/AMAE%2fVol%2014_5_7.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Loureiro, Sandra Maria Correia & Guerreiro, João & Tussyadiah, Iis, 2021. "Artificial intelligence in business: State of the art and future research agenda," Journal of Business Research, Elsevier, vol. 129(C), pages 911-926.
    2. Michael Antioco & Mirella Kleijnen, 2010. "Consumer adoption of technological innovations : Effects of psychological and functional barriers in a lack of content versus a presence of content situation," Post-Print hal-02312561, HAL.
    3. Prentice, Catherine & Nguyen, Mai, 2020. "Engaging and retaining customers with AI and employee service," Journal of Retailing and Consumer Services, Elsevier, vol. 56(C).
    4. Verma, Vivek Kumar & Chandra, Bibhas & Kumar, Sumit, 2019. "Values and ascribed responsibility to predict consumers' attitude and concern towards green hotel visit intention," Journal of Business Research, Elsevier, vol. 96(C), pages 206-216.
    5. Sahu, Aditya Kumar & Padhy, R.K. & Dhir, Amandeep, 2020. "Envisioning the future of behavioral decision-making: A systematic literature review of behavioral reasoning theory," Australasian marketing journal, Elsevier, vol. 28(4), pages 145-159.
    6. Yogesh Bhatt & Karminder Ghuman, 2022. "Managerial cognition and environmental behavioral intentions: A behavioral reasoning theory perspective," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 29(5), pages 1315-1329, September.
    7. M. Antioco & M. Kleijnen, 2010. "Consumer adoption of technological innovations Effects of psychological and functional barriers in a lack of content versus a presence of content situation," Post-Print hal-00387308, HAL.
    8. Arpan Kumar Kar & Amit Kumar Kushwaha, 2023. "Facilitators and Barriers of Artificial Intelligence Adoption in Business – Insights from Opinions Using Big Data Analytics," Information Systems Frontiers, Springer, vol. 25(4), pages 1351-1374, August.
    9. Bonsón Ponte, Enrique & Carvajal-Trujillo, Elena & Escobar-Rodríguez, Tomás, 2015. "Influence of trust and perceived value on the intention to purchase travel online: Integrating the effects of assurance on trust antecedents," Tourism Management, Elsevier, vol. 47(C), pages 286-302.
    10. Chen, Peng-Ting & Kuo, Shu-Chen, 2017. "Innovation resistance and strategic implications of enterprise social media websites in Taiwan through knowledge sharing perspective," Technological Forecasting and Social Change, Elsevier, vol. 118(C), pages 55-69.
    11. Westaby, James D., 2005. "Behavioral reasoning theory: Identifying new linkages underlying intentions and behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 98(2), pages 97-120, November.
    12. Brachten, Florian & Kissmer, Tobias & Stieglitz, Stefan, 2021. "The acceptance of chatbots in an enterprise context – A survey study," International Journal of Information Management, Elsevier, vol. 60(C).
    13. Kichan Nam & Christopher S. Dutt & Prakash Chathoth & Abdelkader Daghfous & M. Sajid Khan, 2021. "The adoption of artificial intelligence and robotics in the hotel industry: prospects and challenges," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(3), pages 553-574, September.
    14. Daniel Belanche & Luis V. Casaló & Carlos Flavián & Jeroen Schepers, 2020. "Service robot implementation: a theoretical framework and research agenda," The Service Industries Journal, Taylor & Francis Journals, vol. 40(3-4), pages 203-225, March.
    15. Thomas P. Novak & Donna L. Hoffman, 2019. "Relationship journeys in the internet of things: a new framework for understanding interactions between consumers and smart objects," Journal of the Academy of Marketing Science, Springer, vol. 47(2), pages 216-237, March.
    16. Elizabeth Kempen & Rejoice Jealous Tobias-Mamina, 2022. "Applying behavioral reasoning theory to South African female consumers’ emerging apparel-shopping behavior during COVID-19," Journal of Global Fashion Marketing, Taylor & Francis Journals, vol. 13(3), pages 221-237, July.
    17. Gupta, Anil & Arora, Neelika, 2017. "Understanding determinants and barriers of mobile shopping adoption using behavioral reasoning theory," Journal of Retailing and Consumer Services, Elsevier, vol. 36(C), pages 1-7.
    18. Milad Mirbabaie & Felix Brünker & Nicholas R. J. Möllmann Frick & Stefan Stieglitz, 2022. "The rise of artificial intelligence – understanding the AI identity threat at the workplace," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(1), pages 73-99, March.
    19. Tenzer, Helene & Pudelko, Markus & Zellmer-Bruhn, Mary, 2021. "The impact of language barriers on knowledge processing in multinational teams," Journal of World Business, Elsevier, vol. 56(2).
    20. Feng, Shengjia & Buxmann, Peter, 2020. "My Virtual Colleague: A State-of-the-Art Analysis of Conversational Agents for the Workplace," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 118817, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    21. Shivani Inder & Kiran Sood & Simon Grima, 2022. "Antecedents of Behavioural Intention to Adopt Internet Banking Using Structural Equation Modelling," JRFM, MDPI, vol. 15(4), pages 1-18, March.
    22. Gupta, Somya & Ghardallou, Wafa & Pandey, Dharen Kumar & Sahu, Ganesh P., 2022. "Artificial intelligence adoption in the insurance industry: Evidence using the technology–organization–environment framework," Research in International Business and Finance, Elsevier, vol. 63(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Talwar, Shalini & Talwar, Manish & Kaur, Puneet & Dhir, Amandeep, 2020. "Consumers’ resistance to digital innovations: A systematic review and framework development," Australasian marketing journal, Elsevier, vol. 28(4), pages 286-299.
    2. Chakraborty, Debarun & Singu, Hari Babu & Patre, Smruti, 2022. "Fitness Apps's purchase behaviour: Amalgamation of Stimulus-Organism-Behaviour-Consequence framework (S–O–B–C) and the innovation resistance theory (IRT)," Journal of Retailing and Consumer Services, Elsevier, vol. 67(C).
    3. Mahmud, Hasan & Islam, A.K.M. Najmul & Mitra, Ranjan Kumar, 2023. "What drives managers towards algorithm aversion and how to overcome it? Mitigating the impact of innovation resistance through technology readiness," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    4. Lalicic, Lidija & Weismayer, Christian, 2021. "Consumers’ reasons and perceived value co-creation of using artificial intelligence-enabled travel service agents," Journal of Business Research, Elsevier, vol. 129(C), pages 891-901.
    5. Jan, Ihsan Ullah & Ji, Seonggoo & Kim, Changju, 2023. "What (de) motivates customers to use AI-powered conversational agents for shopping? The extended behavioral reasoning perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
    6. Xingjun, Huang & Mao, Zhouhui & Lin, Yun & Shi, Qiuju & Liu, Feng & Zhou, Fuli, 2024. "Sharing or privacy for private electric vehicle charging piles? Evidence from Chongqing," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    7. Hajiheydari, Nastaran & Delgosha, Mohammad Soltani & Olya, Hossein, 2021. "Scepticism and resistance to IoMT in healthcare: Application of behavioural reasoning theory with configurational perspective," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    8. Zafar, Abaid Ullah & Shahzad, Mohsin & Shahzad, Khuram & Appolloni, Andrea & Elgammal, Islam, 2024. "Gamification and sustainable development: Role of gamified learning in sustainable purchasing," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    9. Muhammad Zeeshan Zafar & Adnan Maqbool & Lucian-Ionel Cioca & Syed Ghulam Meran Shah & Shahjahan Masud, 2021. "Accentuating the Interrelation between Consumer Intention and Healthy Packaged Food Selection during COVID-19: A Case Study of Pakistan," IJERPH, MDPI, vol. 18(6), pages 1-14, March.
    10. Delgosha, Mohammad Soltani & Hajiheydari, Nastaran, 2020. "On-demand service platforms pro/anti adoption cognition: Examining the context-specific reasons," Journal of Business Research, Elsevier, vol. 121(C), pages 180-194.
    11. Rakshit, Sandip & Islam, Nazrul & Mondal, Sandeep & Paul, Tripti, 2022. "An integrated social network marketing metric for business-to-business SMEs," Journal of Business Research, Elsevier, vol. 150(C), pages 73-88.
    12. Huang, Dan & Jin, Xin & Coghlan, Alexandra, 2021. "Advances in consumer innovation resistance research: A review and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    13. Kaur, Puneet & Dhir, Amandeep & Singh, Naveen & Sahu, Ganesh & Almotairi, Mohammad, 2020. "An innovation resistance theory perspective on mobile payment solutions," Journal of Retailing and Consumer Services, Elsevier, vol. 55(C).
    14. Nguyen-Phuoc, Duy Quy & Nguyen, Nguyen An Ngoc & Tran, Phuong Thi Kim & Pham, Huong-Giang & Oviedo-Trespalacios, Oscar, 2023. "The influence of environmental concerns and psychosocial factors on electric motorbike switching intention in the global south," Journal of Transport Geography, Elsevier, vol. 113(C).
    15. Friedman, Nicola & Ormiston, Jarrod, 2022. "Blockchain as a sustainability-oriented innovation?: Opportunities for and resistance to Blockchain technology as a driver of sustainability in global food supply chains," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    16. Sarah Zafar & Saeed Badghish & Rana Muhammad Shahid Yaqub & Muhammad Zafar Yaqub, 2023. "The Agency of Consumer Value and Behavioral Reasoning Patterns in Shaping Webrooming Behaviors in Omnichannel Retail Environments," Sustainability, MDPI, vol. 15(20), pages 1-21, October.
    17. Chawla, Umesh & Verma, Balraj & Mittal, Amit, 2024. "Resistance to O2O technology platform adoption among small retailers: The influence of visibility and discoverability," Technology in Society, Elsevier, vol. 76(C).
    18. Ruparel, Namita & Bhardwaj, Seema & Seth, Himanshu & Choubisa, Rajneesh, 2023. "Systematic literature review of professional social media platforms: Development of a behavior adoption career development framework," Journal of Business Research, Elsevier, vol. 156(C).
    19. de Bellis, Emanuel & Venkataramani Johar, Gita, 2020. "Autonomous Shopping Systems: Identifying and Overcoming Barriers to Consumer Adoption," Journal of Retailing, Elsevier, vol. 96(1), pages 74-87.
    20. Jayaswal, Pragya & Parida, Biswajita, 2023. "The role of augmented reality in redefining e-tailing: A review and research agenda," Journal of Business Research, Elsevier, vol. 160(C).

    More about this item

    Keywords

    AI service assistant; Employee adoption; Behavioral reasoning theory; Hotel industry.;
    All these keywords.

    JEL classification:

    • M21 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - Business Economics
    • M30 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spt:admaec:v:14:y:2024:i:5:f:14_5_7. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Eleftherios Spyromitros-Xioufis (email available below). General contact details of provider: http://www.scienpress.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.