Navigating change: a qualitative exploration of chatbot adoption in recruitment

References

• Abulibdeh, A., Zaidan, E., & Abulibdeh, R. (2024). Navigating the confluence of artificial intelligence and education for sustainable development in the era of industry 4.0: Challenges, opportunities, and ethical dimensions. Journal of Cleaner Production, 437(December 2023), 1. https://doi.org/10.1016/j.jclepro.2023.140527
   Google Scholar
• Alam, M. S., Khan, T.-U.-Z., Dhar, S. S., & Munira, K. S. (2020). HR professionals’ intention to adopt and use of artificial intelligence in recruiting talents. Business Perspective Review, 2(2), 15–18. https://doi.org/10.38157/business-perspective-review.v2i2.122
   Google Scholar
• Alhassan, K. (2022). Tacit knowledge sharing in software development projects of mobile applications domain [Doctoral dissertation]. Northcentral University.
   Google Scholar
• Bani Ahmad, A. Y. A. (2024). Ethical implications of artificial intelligence in accounting: A framework for responsible ai adoption in multinational corporations in Jordan. International Journal of Data and Network Science, 8(1), 401–414. https://doi.org/10.5267/j.ijdns.2023.9.014
   Google Scholar
• Black, J. S., & van Esch, P. (2020). AI-enabled recruiting: What is it and how should a manager use it? Business Horizons, 63(2), 215–226. https://doi.org/10.1016/j.bushor.2019.12.001
   Web of Science ®Google Scholar
• Bukar, U. A., Sayeed, M. S., Razak, S. F. A., Yogarayan, S., Amodu, O. A., & Mahmood, R. A. R. (2023). A method for analyzing text using VOSviewer. MethodsX, 11(May), 102339. https://doi.org/10.1016/j.mex.2023.102339
   PubMedGoogle Scholar
• Carmigniani, J., Furht, B., Anisetti, M., Ceravolo, P., Damiani, E., & Ivkovic, M. (2011). Augmented reality technologies, systems and applications. Multimedia Tools and Applications, 51(1), 341–377. https://doi.org/10.1007/s11042-010-0660-6
   Web of Science ®Google Scholar
• Chatterjee, S., Chaudhuri, R., & Vrontis, D. (2023). Acceptance of social robot and its challenges: From privacy calculus perspectives. Technological Forecasting and Social Change, 196(December 2022), 122862. https://doi.org/10.1016/j.techfore.2023.122862
   Google Scholar
• Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319. https://doi.org/10.2307/249008
   Web of Science ®Google Scholar
• de Andrés-Sánchez, J., & Gené-Albesa, J. (2023). Explaining policyholders’ Chatbot acceptance with an unified technology acceptance and use of technology-based model. Journal of Theoretical and Applied Electronic Commerce Research, 18(3), 1217–1237. https://doi.org/10.3390/jtaer18030062
   Web of Science ®Google Scholar
• Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., Galanos, V., Ilavarasan, P. V., Janssen, M., Jones, P., Kar, A. K., Kizgin, H., Kronemann, B., Lal, B., Lucini, B., … Williams, M. D. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57(August 2019), 101994. https://doi.org/10.1016/j.ijinfomgt.2019.08.002
   Google Scholar
• Ferrario, A., Loi, M., & Viganò, E. (2020). In AI we trust incrementally: A multi-layer model of trust to analyse human–artificial intelligence interactions. Philosophy & Technology, 33(3), 523–539. https://doi.org/10.1007/s13347-019-00378-3
   Google Scholar
• Hakimi, M. (2022). From artificial intelligence to artificial human interaction: Understand consumer acceptance of smart objects via mental representations of future interactions. De l ‘ Intelligence Artificielle à.
   Google Scholar
• Hancock, J. T., Naaman, M., & Levy, K. (2020). AI-mediated communication: Definition, research agenda, and ethical considerations. Journal of Computer-Mediated Communication, 25(1), 89–100. https://doi.org/10.1093/jcmc/zmz022
   Web of Science ®Google Scholar
• Hartnell, C. A., Ou, A. Y., & Kinicki, A. (2011). Organisational culture and organisational effectiveness: A meta-analytic investigation of the competing values framework’s theoretical suppositions. The Journal of Applied Psychology, 96(4), 677–694. https://doi.org/10.1037/a0021987
   PubMed Web of Science ®Google Scholar
• Hengstler, M.,Enkel, E., &Duelli, S. (2016). Applied artificial intelligence and trust—The case of autonomous vehicles and medical assistance devices. Technological Forecasting and Social Change, 105, 105–120. https://doi.org/10.1016/j.techfore.2015.12.014
   Web of Science ®Google Scholar
• Javed, A., & Brishti, J. K. (2020). The viability of AI-based recruitment process. Umea University, 1(1), 1–39.
   Google Scholar
• Jiang, X., Goh, T. T., & Liu, M. (2022). On students’ willingness to use online learning: A privacy calculus theory ­approach. Frontiers in Psychology, 13(March 2020), 880261. https://doi.org/10.3389/fpsyg.2022.880261
   PubMedGoogle Scholar
• Jonas, M., Samuel, K., Kala, P., & Jean, K. (n.d.). Contribution of analytics on firm performance: The moderating effect of the organizational culture. A research in progress. 1–9.
   Google Scholar
• Kafi, M. A., & Adnan, T. (2022). Empowering organizations through IT and IoT in the pursuit of business process reengineering: The scenario from the USA and Bangladesh. Asian Business Review, 12(3), 67–80. https://doi.org/10.18034/abr.v12i3.658
   Google Scholar
• Koivunen, S., Ala-Luopa, S., Olsson, T., & Haapakorpi, A. (2022). The March of Chatbots into recruitment: Recruiters’ experiences, expectations, and design opportunities. Computer Supported Cooperative Work (CSCW), 31(3), 487–516. https://doi.org/10.1007/s10606-022-09429-4
   Web of Science ®Google Scholar
• Kong, Y., Xie, C., Wang, J., Jones, H., & Ding, H. (2021). AI-assisted recruiting technologies: Tools, challenges, and opportunities. Proceedings of the 39th ACM International Conference on the Design of Communication: Building Coalitions. Worldwide, SIGDOC 2021, pp. 359–361. https://doi.org/10.1145/3472714.3473697
   Google Scholar
• Lin, W. Y. (2023). Prototyping a Chatbot for site managers using building information modeling (BIM) and natural language understanding (NLU) techniques. Sensors (Basel, Switzerland), 23(6), 2942. https://doi.org/10.3390/s23062942
   PubMed Web of Science ®Google Scholar
• Lockey, S., Gillespie, N., Holm, D., & Someh, I. A. (2021). A review of trust in artificial intelligence: Challenges, vulnerabilities and future directions. Proceedings of the Annual Hawaii International Conference on System Sciences, pp. 5463–5472. https://doi.org/10.24251/HICSS.2021.664
   Google Scholar
• Lucci, S., & Kopec, D. (2015). Artificial intelligence in the 21st century. Stylus Publishing, LLC.
   Google Scholar
• Ma, Q., & Liu, L. (2011). The technology acceptance model. Advanced Topics in End User Computing, 4, 17. https://doi.org/10.4018/9781591404743.ch006.ch000
   Google Scholar
• McKinsey & Company. (2022). The state of AU in 2022-and half a decade in review. Retrieved February 5, 2023, from, https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-in-2022-and-a-half-decade-in-review.
   Google Scholar
• Nanayakkara, K., & Wilkinson, S. (2021). Organizational culture theories: Dimensions of organizational culture and office layouts. In A handbook of theories on designing alignment between people and the office environment (pp. 132–147). Routledge. https://doi.org/10.1201/9781003128830-12
   Google Scholar
• Omrani, N., Rivieccio, G., Fiore, U., Schiavone, F., & Agreda, S. G. (2022). To trust or not to trust? An assessment of trust in AI-based systems: Concerns, ethics and contexts. Technological Forecasting and Social Change, 181(December 2021), 121763. https://doi.org/10.1016/j.techfore.2022.121763
   Google Scholar
• Ore, O., & Sposato, M. (2022). Opportunities and risks of artificial intelligence in recruitment and selection. International Journal of Organizational Analysis, 30(6), 1771–1782. https://doi.org/10.1108/IJOA-07-2020-2291
   Web of Science ®Google Scholar
• Oswal, N., Khaleeli, M., & Alarmoti, A. (2020). Recruitment in the era of Industry 4.0.  Use of Artificial, 17(8), 39–47.
   Google Scholar
• Perdana, R. C.,Agustino, M. R.,Hartawan, D.,Suyoso, Y. A., &Sari, R. (2020). Adaptasi dan Kebiasaan Baru Human Resource Department di Masa Pandemik Covid-19. Business Innovation and Entrepreneurship Journal, 2(3), 201–204. https://doi.org/10.35899/biej.v2i3.138
   Google Scholar
• Phuong Dung, P. T., Minh An, H., Huy, P. Q., & Dinh Quy, N. L. (2023). Understanding the startup’s intention of digital marketing’s learners: An application of the theory of planned behavior (TPB) and technology acceptance method (TAM). Cogent Business & Management, 10(2), 2219415. https://doi.org/10.1080/23311975.2023.2219415
   Web of Science ®Google Scholar
• Piderit, S. K. (2000). Rethinking resistance and recognizing ambivalence: A multidimensional view of attitudes toward an organizational change. The Academy of Management Review, 25(4), 783–794. https://doi.org/10.2307/259206
   Web of Science ®Google Scholar
• Ployhart, R. E. (2006). Staffing in the 21st century: New challenges and strategic opportunities. Journal of Management, 32(6), 868–897. https://doi.org/10.1177/0149206306293625
   Web of Science ®Google Scholar
• Rapp, A., Curti, L., & Boldi, A. (2021). The human side of human–Chatbot interaction: A systematic literature review of ten years of research on text-based chatbots. International Journal of Human-Computer Studies, 151(January), 102630. https://doi.org/10.1016/j.ijhcs.2021.102630
   Google Scholar
• Raveendra, P. V., Satish, Y. M., & Singh, P. (2020). Changing landscape of recruitment industry: A study on the impact of Artificial Intelligence on eliminating hiring bias from recruitment and selection process. Journal of Computational and Theoretical Nanoscience, 17(9), 4404–4407. https://doi.org/10.1166/jctn.2020.9086
   Google Scholar
• Rizzuto, T. E.,Schwarz, A., &Schwarz, C. (2014). Toward a deeper understanding of IT adoption: A multilevel analysis. Information & Management, 51(4), 479–487. https://doi.org/10.1016/j.im.2014.02.005
   Web of Science ®Google Scholar
• Sahay, P. (2014). Design thinking in talent acquisition: a practitioner’s perspective. Strategic HR Review, 13(4/5), 170–180. https://doi.org/10.1108/SHR-04-2014-0027
   Google Scholar
• Scholz, T. M. (2017). Big Data in organizations and the role of human resource management: A complex systems theory-based conceptualization. Peter Lang International Academic Publishers.
   Google Scholar
• Sekhri, A., & Cheema, J. (2019). The new era of HRM: AI reinventing HRM functions. International Journal of Scientific Research and Review, 7(3), 3073–3077.
   Google Scholar
• Sołek-Borowska, C., & Wilczewska, M. (2018). New technologies in the recruitment process. Economics and Culture, 15(2), 25–33. https://doi.org/10.2478/jec-2018-0017
   Google Scholar
• Srnicek, N. (2017). Platform Capitalism. John Wiley and Sons.
   Google Scholar
• Statisica. (2022). Retrieved March 17, 2023, from https://www.statista.com/statistics/941137/aiinvestment-and-funding-worldwide/.
   Google Scholar
• Sullivan, Y. W., &Fosso Wamba, S. (2022). Moral Judgments in the Age of Artificial Intelligence. Journal of Business Ethics, 178(4), 917–943. https://doi.org/10.1007/s10551-022-05053-w
   Web of Science ®Google Scholar
• Votto, A. M., Valecha, R., Najafirad, P., & Rao, H. R. (2021). Artificial Intelligence in tactical human resource management: A systematic literature review. International Journal of Information Management Data Insights, 1(2), 100047. https://doi.org/10.1016/j.jjimei.2021.100047
   Google Scholar
• Xie, L., & Lei, S. (2022). The nonlinear effect of service robot anthropomorphism on customers’ usage intention: A privacy calculus perspective. International Journal of Hospitality Management, 107(July), 103312. https://doi.org/10.1016/j.ijhm.2022.103312
   Google Scholar
• Yang, J., Blount, Y., & Amrollahi, A. (2024). Artificial intelligence adoption in a professional service industry: A multiple case study. Technological Forecasting and Social Change, 201(February), 123251. https://doi.org/10.1016/j.techfore.2024.123251
   Google Scholar
• Yi, P. K., Ray, N. D., & Segall, N. (2023). A novel use of an artificially intelligent Chatbot and a live, synchronous virtual question-and answer session for fellowship recruitment. BMC Medical Education, 23(1), 152. https://doi.org/10.1186/s12909-022-03872-z
   PubMed Web of Science ®Google Scholar
• Zhang, J. J. Y., Følstad, A., & Bjørkli, C. A. (2023). Organizational factors affecting successful implementation of Chatbots for customer service. Journal of Internet Commerce, 22(1), 122–156. https://doi.org/10.1080/15332861.2021.1966723
   Web of Science ®Google Scholar