Indian Journal of Industrial Relations: Economics & Social Dev.

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Adoption of Artificial Intelligence in Human Resource Management: A Conceptual Model


Affiliations
1 HR Leader, IBM India & Research Scholar, IILM University, Gurugram 122011, India
2 IT& Systems Specialist, State Bank of India, Digital & Transaction Banking Unit Thiruvananthapuram 695012., India
3 Associate Professor, IILM University 122011, India
     

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The advent of Artificial Intelligence Technologies (AIT) has a transformational impact on HRM domain. This research proposes an integrated model related to factors that impact the adoption of Artificial Intelligence in the HR function. The study deploys a framework of the Technology-Organization-Environment model enhanced by Technology-Adoption-Model. The proposed model provides key insights to support researchers to enhance assimilation, and forge ahead in the research on the organizational perspective of the adoption of AIT in HRM. The model is appropriately linked to the decision- makers and HR professionals. The research provides a foundation for detailed empirical studies related to the factors impacting the adoption of AIT.
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  • Ajibade, P. (2018), “Technology Acceptance Model Limitations and Criticisms: Exploring the Practical Applications and Use in Technology-related Studies, Mixedmethod, and Qualitative Researches”, Library Philosophy & Practice, e-journal, Summer 2018,1941

  • Ajzen, I. (1991), “The Theory of Planned Behavior”, Organizational Behavior and Human Decision Processes, 50(2): 179-211.

  • Alam, M.G.R., Masum, A.K.M., Beh, L.S. & Hong, C.S. (2016), “Critical Factors Influencing Decision to Adopt Human Resource Information System (HRIS) in Hospital”, Public Library of Science One, 11(8): 1-22.

  • Armenteros, M., Liaw, S. S., Fernández, M., Díaz, R. F., & Sánchez, R. A. (2013). “Surveying FIFA Instructors’ Behavioral Intention Toward the Multimedia Teaching Materials”. Computers & Education, 61:91-104.

  • Bondarouk, T, Parry, E. & Furtmueller, E. (2017), “Electronic HRM: Four Decades of Research on Adoption and Consequences”, International Journal of Human Resource Management, 28 (1): 98-131, doi: 10.1080/ 09585192.2016.1245672.

  • Calisir, F., Gumussoy, C. A. & Bayram, A. (2009), “Predicting the Behavioral Intention to Use Enterprise Resource Planning Systems”, Management Research News, 32(7): 597.

  • Chau, P. & Hu, P. (2001), “Information Technology Acceptance by Individual Professionals: A Model of Comparison Approach”, Decision Sciences, 32(4): 699–719.

  • Cooper, R. B. & Zmud, R. W. (1990), “Information Technology Implementation Research: A Technological Diffusion Approach”, Management Science, 36 (2): 123–39.

  • doi:10.1287/mnsc.36.2.123.

  • Davis, F. (1989), “Perceived Usefulness, Ease of Use and User Acceptance of Information Technology”, MIS Quarterly, 13 (3): 31940, Retrieved from http://www.lstor.org/ stable/249008

  • Dedrick, J. & West, J. (2003), “Why Firms Adopt Open Source Platforms: a Grounded Theory of Innovation and Standards Adoption”, MISQ Special Issue Workshop: Standard Making: A Critical Research Frontier for Information Systems, Seattle, WA: 236257.

  • Fishbein, M. & Ajzen, I. (1975), Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research, Addison-Wesley, Reading, MA.

  • Gangwar, H., Date, H. & Ramaswamy, R. (2015), “Understanding Determinants of Cloud Computing Adoption Using an Integrated TAM-TOE Model”, Journal of Enterprise Information Management, 28(1): 107-130.

  • Ghobakhloo, M., Hong, T. S., Sabouri, M. S. & Zulkifli, N. (2012), “Strategies for Successful Information Technology Adoption in Small and Medium-sized Enterprises”, Information, 3(1): 36-67.

  • Gulliford, F. & Dixon, A., (2019), “AI: the HR Revolution”, Strategic HR Review, https:// doi.org/10.1108/ SHR-12-2018-0104

  • Hossain, M.A. & Quaddus, M. (2011), “The Adoption and Continued Usage Intention of RFID: an Integrated Framework”, Information Technology & People, 24 (3): 236-56.

  • Khasawneh, A.M. (2008), “Concepts and Measurements of Innovativeness: The Case of Information and Communication Technologies”, International Journal of Arab Culture, Management and Sustainable Development, 1(1): 23-33.

  • King, W. R. & He, J. (2006), “A Meta-analysis of the Technology Acceptance Model”, Information & Management, 43(6): 740-55.

  • Lee, J.N., Miranda, S.M. & Kim, Y.M. (2004), “IT Outsourcing Strategies: Universalistic, Contingency, and Configurational Explanations of Success”, Information Systems Research, 15 (2):10-31.

  • Legris, P., Ingham, J. & Collerette, P. (2003), “Why Do People Use Information Technology? A Critical Review of the Technology Acceptance Model”, Information & Management, 40 (3): 191-204.

  • Low, C., Chen, Y. & Wu, M. (2011), “Understanding the Determinants of Cloud Computing Adoption”, Industrial Management & Data Systems, 111(7): 1006-23.

  • Matsa, P. & Gullamajji, K. (2019), “To Study Impact of Artificial Intelligence on Human Resource Management”, International Research Journal of Engineering and Technology, 6(8): 1229-38.

  • Nankervis, A.,Connell, J.,Cameron,R., Montague, A. & Prikshat, V. (2019), “Are we there yet? Australian HR Professionals and the Fourth Industrial Revolution”, Asia Pacific Journal of Human Resources.

  • doi:10.1111/1744-7941.12245 Niehueser, W. & Boak, G. (2020), “Introducing Artificial Intelligence into a Human Resources Function”, Industrial and Commercial Training, 52(2): 121-30.

  • Pillai, R. & Sivathanu, B. (2020), “Adoption of Artificial Intelligence (AI) for Talent Acquisition in IT/ITeS Organ izat io ns ”, Benchmarking: An International Journal, 27(9) Riyadh, A.N., Akter, Md. S. & Islam, N. (2009), “The Adoption of e-banking in Developing Countries: a Theoretical Model for SMEs”, International Review of Business Research Papers, 5(6): 212-30.

  • Rogers, E.M. (1995), Diffusion of Innovation, Free Press, New York, NY.

  • Rogers, E.M. (2003), Diffusion of Innovations, 5th ed., Free Press., New York, NY.

  • Salwani, M.I., Marthandan, G., Norzaidi, M.D. & Chong, S.C. (2009), “E-commerce Usage and Business Performance in the Malaysian Tourism Sector: Empirical Analysis”, Information Management & Computer Security, 17 (2):166-85.

  • Schillewaert, N., Ahearne, M.J., Frambach, R.T. & Moenaert, R.K. (2005), “The Adoption of Information Technology in the Sales Force”, Industrial Marketing Management, 34 (4): 323-36.

  • Sonnenwald, D.H., Maglaughlin, K.L. & Whitton, M.C. (2001), “Using Innovation Diffusion Theory to Guide Collaboration Technology Evaluation”, Work in Progress. IEEE 10th International Workshop on Enabling Technologies: Infrastructure for Collaborative Enterprises, Massachusetts Institute of Technology, Cambridge, MA,USA

  • Tan, J., Tyler, K. & Manica, A. (2007), “Businessto-business Adoption of e-Commerce in China”, Information & Management, 44(3): 332–51.

  • Tornatzky, L.G. & Fleischer, M. (1990) The Processes of Technological Innovation, Lexington Books, Lexington, MA.

  • Upadhyay, A. K. & Khandelwal, K. (2018), “Applying Artificial Intelligence: Implications for Recruitment”, Strategic HR Review, 17 (5): 255-58.

  • Venkatesh, V., Morris, M.G., Davis, G.B. & Davis, F. (2003), “User Acceptance of Information Technology: Toward a Unified View”, MIS Quarterly, 27 (3): 425-78.

  • Wang, Y., Wang, Y. & Yang, Y. (2010), “Understanding the Determinants of RFID Adoption in the Manufacturing Industry”, Technological Forecasting & Social Change, 77(5): 803–15.

  • Yabanci, O. (2019), “From Human Resource Management to Intelligent Human Resource Management: a Conceptual Perspective”, Human-Intelligent Systems Integration, 1(2):101-09.

  • Zehir C., Karaboða, T. & Baþar, D. (2020), “The Transformation of Human Resource Management and Its Impact on Overall Business Performance: Big Data Analytics and AI Technologies in Strategic HRM”, in Digital Business Strategies in Blockchain Ecosystems, Springer, Cham.

  • Zhao, A.L., Koenig-Lewis, N., Hanmer-Lloyd, S. & Ward, P. (2010), “Adoption of Internet Banking Services in China: Is It All About Trust?”, International Journal of Bank Marketing, 28 (1): 7-26.

  • Zhu, K., Dong, S., Xu, S.X. & Kraemer, K.L. (2006), “Innovation Diffusion in Global Contexts: Determinants of Post-adoption Digital Transformation of European Companies”, European Journal of Information Systems,15 (6): 601-16.

  • Zhu, K., Kraemer, K.L., Xu, S. & Dedrick, J. (2004), “The Complementarity of Information Technology Infrastructure and e-Commerce Capability Are Source-based Assessment of Their Business Value”, Journal of Management Information Systems, 21(1): 167-202.


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  • Adoption of Artificial Intelligence in Human Resource Management: A Conceptual Model

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Authors

Mandeep Kaur
HR Leader, IBM India & Research Scholar, IILM University, Gurugram 122011, India
Rekha A G
IT& Systems Specialist, State Bank of India, Digital & Transaction Banking Unit Thiruvananthapuram 695012., India
Sona Vikas
Associate Professor, IILM University 122011, India

Abstract


The advent of Artificial Intelligence Technologies (AIT) has a transformational impact on HRM domain. This research proposes an integrated model related to factors that impact the adoption of Artificial Intelligence in the HR function. The study deploys a framework of the Technology-Organization-Environment model enhanced by Technology-Adoption-Model. The proposed model provides key insights to support researchers to enhance assimilation, and forge ahead in the research on the organizational perspective of the adoption of AIT in HRM. The model is appropriately linked to the decision- makers and HR professionals. The research provides a foundation for detailed empirical studies related to the factors impacting the adoption of AIT.

References