• Abstract

    With the advancement of Technology, it has become imperative for H.R. and recruitment strategies to adapt. This paper will highlight the emerging trends in H.R. and Recruitment driven by Technology. One prominent trend in H.R. Technology is the increasing prevalence of artificial intelligence (A.I.). A.I. is already utilized to streamline and automate H.R. processes like resume screening, interview scheduling, and performance reviews. Looking ahead, A.I. is anticipating a significant impact on H.R. by aiding organizations in making better hiring decisions, designing personalized training programs, and fostering more engaging employee experiences. Another notable trend in H.R. Technology revolves around the transition towards cloud-based platforms. These platforms offer advantages over on-premises systems, including scalability, flexibility, and cost-effectiveness. As a result of the various benefits brought by Technology, we would bring about the critical themes in the form of the strategies that the organizations should adopt to enhance their productivity in Recruitment and selection with the help of bibliometric analysis, thematic analysis, ISM (interpretive structuring model) and MICMAC analysis.

  • References

    1. Abraham, S. (2011). Acquisition and allocation of human, financial, and physical resources in the health care system. Health Care Manager, 30(1), 38–44. https://doi.org/10.1097/HCM.0b013e3182078b1d
    2. Ada, N., Ilic, D., &Sagnak, M. (2021). A framework for new workforce skills in the era of Industry 4.0. International Journal of Mathematical, Engineering and Management Sciences, 6(3), 111–186. Retrieved from https://www-scopus-com-presiuniv.knimbus.com/inward/record.uri?eid=2s2.05107437651&partnerID=40&md5=c9b18fd53e4309049257c4c5be6b7acc
    3. Adubor, N. V., Adeniji, A. A., Salau, O. P., Olajugba, O. J., &Onibudo, G. O. (2022). Exploring green human resource adoption and corporate sustainability in Nigerian manufacturing industry. Sustainability (Switzerland), 14(19). https://doi.org/10.3390/su141912635
    4. Ahmad, N., &Qahmash, A. (2021). SmartISM: Implementation and assessment of interpretive structural modeling. Sustainability, 13(16), 8801. https://doi.org/10.3390/su13168801
    5. Akram, S., Tofighi, S., Yamani, N., & Changiz, T. (2020). Clinical instructors' recruitment challenges: Interpretive structural modeling approach. Journal of Education and Health Promotion. https://doi.org/10.4103/JEHP.JEHP_722_19
    6. Alizadeh, M., Baoosh, M., & Rahimi, A. (2022). One hundred years of human resource management progress at three levels in the world. International Journal of Human Capital in Urban Management, 7(1), 125–142. https://doi.org/10.22034/IJHCUM.2022.01.10
    7. Alsharif, N. Z., Schwartz, A. H., Malone, P. M., Jensen, G., Chapman, T., & Winters, A. (2006). Educational mentor program in a web-based doctor of pharmacy degree pathway. American Journal of Pharmaceutical Education, 70(2). https://doi.org/10.5688/aj700231
    8. Ananthakumar, U., & Nerurkar, A. N. (2011). Factors perceived to influence the selection of information technology jobs. International Journal of Business Performance and Supply Chain Modelling, 3(1), 86–98. https://doi.org/10.1504/IJBPSCM.2011.039975
    9. Andrew, J. B., Fugard, H. W. W., & Potts, H. (2015). Supporting thinking on sample sizes for thematic analyses: A quantitative tool. International Journal of Social Research Methodology. https://doi.org/10.1080/13645579.2015.1005453
    10. Ardichvili, A., &Gasparishvili, A. (2001). Human resource development in an industry in transition: The case of the Russian banking sector. Human Resource Development International, 4(1), 47–63. https://doi.org/10.1080/13678860122157
    11. Aspridis, G., Kazantzi, V., & Kyriakou, D. (2013). Social networking websites and their effect in contemporary human resource management - A research approach. Mediterranean Journal of Social Sciences, 4(1), 29–46. https://doi.org/10.5901/mjss.2013.v4n1p29
    12. Attri, R., Grover, S., Dev, N., & Kumar, D. (2013). Interpretive structural modeling (ISM) approach: A review. Journal of Business Research, 66(11), 2312-2322.
    13. Bacci Silvia,Bruno Bertaccini ,Simone Del Sarto ,Leonardo Grilli ,Carla Rampichini (2023).Statistical methods to estimate the impact of remote teaching on university students performance ,Springer Nature. https://doi.org/10.1007/s11135-023-01612-z.
    14. Bailao Goncalves, M., Anastasiadou, M., & Santos, V. (2022). A.I. and public contests: A model to improve the evaluation and selection of public contest candidates in the police force. Transforming Government: People, Process and Policy, 16(4), 627–648. https://doi.org/10.1108/TG-05-2022-0078
    15. Balcerak, A., & Woźniak, J. (2021). Reactions to some ICT-based personnel selection tools. Economics and Sociology, 14(1), 214–231. https://doi.org/10.14254/2071-789X.2021/14-1/14
    16. Brock, M. E., & Ronald Buckley, M. (2013). Human resource functioning in an information society: Practical suggestions and future implications. Public Personnel Management, 42(2), 272–280. https://doi.org/10.1177/0091026013487047
    17. Butkenova, A. K. (2018). Strategic planning of human capital assets at industrial enterprises. Espacios, 39(4). Retrieved from https://www-scopuscompresiuniv.knimbus.com/inward/record.uri?eid=2-s2.0-85041579509&partnerID=40&md5=bc0c025cd5bd562abb229169546e7dc1
    18. Carrero, J., Krzeminska, A., &Härtel, C. E. J. (2019). The DXC technology work experience program: Disability-inclusive recruitment and selection in action. Journal of Management and Organization, 25(4), 535–542. https://doi.org/10.1017/jmo.2019.23
    19. Chilunjika, A., Intauno, K., &Chilunjika, S. R. (2022). Artificial intelligence and public sector human resource management in South Africa: Opportunities, challenges and prospects. SA Journal of Human Resource Management, 20. https://doi.org/10.4102/sajhrm.v20i0.1972
    20. Chowdhury, S., Dey, P., Joel-Edgar, S., Bhattacharya, S., Rodriguez-Espindola, O., Abadie, A., & Truong, L. (2023). Unlocking the value of artificial intelligence in human resource management through A.I. capability framework. Human Resource Management Review, 33(1), 100899.
    21. Cools, E., van den Broeck, H., &Bouckenooghe, D. (2009). Cognitive styles and person-environment fit: Investigating the consequences of cognitive (mis)fit. European Journal of Work and Organizational Psychology, 18(2), 167–198. https://doi.org/10.1080/13594320802295540
    22. Cronin, B., Morath, R., Curtin, P., & Heil, M. (2006). Public sector use of technology in managing human resources. Human Resource Management Review, 16(3), 416–430. https://doi.org/10.1016/j.hrmr.2006.05.008
    23. Dhabuwala, P. A., & Pitroda, J. R. (2021). Recruitment, selection and training of human resource in construction: A review. Reliability: Theory and Applications, 16(SI1), 111–120. https://doi.org/10.24412/1932-2321-2021-160-111-120
    24. Dorasamy, N. (2021). The search for talent management competence: Incorporating digitalization. International Journal of Entrepreneurship, 25(3). Retrieved from https://www-scopus-com-presiuniv.knimbus.com/inward/record.uri?eid=2-s2.0-
    25. &partnerID=40&md5=f9f5b59a7ee96812f52a4198a7162b9d
    26. Drisko, C. L., & Whittaker, L. P. (2012). Dental school faculty and the academic environment from 1936 to 2011: Familiar features in a new context. Journal of
    27. Dental Education, 76(1), 65–74. Retrieved from https://www-scopus-com-presiuniv.knimbus.com/inward/record.uri?eid=2s2.084856683139&partnerID=40&md5=daedcdd1a5d2925457d1ab9daf411d7a
    28. Duangekanong, D. (2021). Use of strategic human resources management (SHRM) in Thailand’s high-tech firms: Adoption and firm non-financial outcomes. Humanities, Arts and Social Sciences Studies, 21(1), 1–10. https://doi.org/10.14456/hasss.2021.1
    29. Fajčíková, A., Urbancová, H., &Fejfarová, M. (2018). New trends in the recruitment of employees in Czech ICT organizations. Scientific Papers of the University of Pardubice, Series D: Faculty of Economics and Administration, 26(43), 39–49.
    30. Graham, D. (2023). A Teacher’s Guide to Supporting Gifted Middle School Students: Reaching Adolescents in the Pivotal Years (1st ed.). Routledge. https://doi.org/10.4324/9781003332015
    31. Goel, R., Singh, G., Seema, Garg, V., &Venaik, A. (2019). Diversity at workplace: Performance of human resource management practices in I.T. sector in NCR, India. International Journal of Scientific and Technology Research, 8(12), 3563–3567
    32. Gonçalves, S. P., Dos Santos, J. V., Silva, I. S., Veloso, A., Brandão, C., & Moura, R. (2021). COVID-19 and people management: The view of human resource managers. Administrative Sciences, 11(3). https://doi.org/10.3390/admsci11030069
    33. Gope, S., Elia, G., &Passionate, G. (2018). The effect of HRM practices on knowledge management capacity: A comparative study in Indian I.T. industry. Journal of Knowledge Management, 22(3), 649–677. https://doi.org/10.1108/JKM-10-2017-0453
    34. Hafeez, K., &Abdelmeguid, H. (2003). Dynamics of human resource and knowledge management. Journal of the Operational Research Society, 54(2), 153–164. https://doi.org/10.1057/palgrave.jors.2601513
    35. Jodi, A. (1995). A Pragmatic View of Thematic Analysis. The Qualitative Report. https://doi.org/10.46743/2160-3715/1995.2069
    36. Jolhe, D. A., & Babu, A. S. (2014). Modifications in interpretive structural modelling methodology to enhance its applicability in group decision process and power of discrimination. International Journal of Business Excellence, 7(3), 281. https://doi.org/10.1504/ijbex.2014.060779
    37. Kaur, D., & Kaur, R. (2022). Elucidating the role of gender differences via TAM in e-recruitment adoption in India: A multi-group analysis using MICOM. The Bottom Line, 35(2/3), 115-136.
    38. Kaushal, N., &Ghalawat, S. (2023). Research perspective of artificial intelligence and HRM: A bibliometric study. International Journal of Business Innovation and Research, 31(2), 168–196. https://doi.org/10.1504/ijbir.2023.131432
    39. Kazancoglu, Y., & Ozkan-Ozen, Y. D. (2018). Analyzing Workforce 4.0 in the Fourth Industrial Revolution and proposing a road map from operations management perspective with fuzzy DEMATEL. Journal of Enterprise Information Management, 31(6), 891–907. https://doi.org/10.1108/JEIM-01-2017-0015
    40. Keegan, A., &Meijerink, J. (2023). Dynamism and realignment in the H.R. architecture: Online labor platform ecosystems and the key role of contractors.
    41. Human Resource Management, 62(1), 15–29. https://doi.org/10.1002/hrm.22120
    42. Kelsey, B. (2019). Thematic analysis of sexual and gender minority enrollment in the all of us Pennsylvania project: Implications for public health research.
    43. Kim, S., Ross, B., Wright, A., Wu, M., Benedetti, T., Leland, F., & Pellegrini, C. (2011). Halting the revolving door of faculty turnover recruiting and retaining clinician educators in an academic medical simulation center. Simulation in Healthcare, 6(3), 168–175. https://doi.org/10.1097/SIH.0b013e31820724bf
    44. Kelan, E. K. (2023). Algorithmic inclusion: Shaping the predictive algorithms of artificial intelligence in hiring. Human Resource Management Journal, 1–14.https://doi.org/10.1111/1748-8583.125111
    45. Koivunen, S., Olsson, T., Olshannikova, E., & Lindberg, A. (2019). Understanding decision-making in Recruitment: Opportunities and challenges for information technology. Proceedings of the ACM on Human-Computer Interaction, 3(GROUP). https://doi.org/10.1145/3361123
    46. Kshetri, N. (2020). Evolving uses of artificial intelligence in human resource management in emerging economies in the global South: Some preliminary evidence. Management Research Review, 44(7), 970–990. https://doi.org/10.1108/MRR-03-2020-0168
    47. Kumar, A., & Singh, D. V. (2019). Overview of interpretive structural modeling. International Journal of Engineering Applied Sciences and Technology, 04(05),
    48. –540. https://doi.org/10.33564/ijeast.2019.v04i05.078
    49. Langer, M., König, C. J., Sanchez, D. R.-P., & Samadi, S. (2020). Highly automated interviews: Applicant reactions and the organizational context. Journal of Managerial Psychology, 35(4), 301–314. https://doi.org/10.1108/JMP-09-2018-0402
    50. Lavanchy, M., Reichert, P., Narayanan, J., & Savani, K. (2023). Applicants’ fairness perceptions of algorithm-driven hiring procedures. Journal of Business Ethics. https://doi.org/10.1007/s10551-022-05320-w
    51. Lee, L., Guzzo, R. F., Madera, J. M., &Guchait, P. (2021). Examining applicant online recruitment: The use of fictitious websites in experimental studies. Cornell Hospitality Quarterly, 62(1), 76–88. https://doi.org/10.1177/1938965520965223
    52. Lele, A. (2015). Formation of an efficient team by improvising employee selection process using AHP-LP for software company in India. Management and Labour Studies, 40(1–2), 22–33. https://doi.org/10.1177/0258042X15601531
    53. Llorens, J. J. (2011). A model of public sector e-recruitment adoption in a time of hyper-technological change. Review of Public Personnel Administration, 31(4), 410–423. https://doi.org/10.1177/0734371X11421498
    54. Lousã, E. P., Rodrigues, A. C., & Pinto, E. M. (2020). How do HRM practices relate to innovation performance in information technology firms? IBIMA Business Review, 2020. https://doi.org/10.5171/2020.306950
    55. Lucas, D. S., Bellavitis, C., & Park, U. D. (2023). A cloud's silver lining? The impact of policy interventions on new and maturing technology ventures' online recruitment. Strategic Entrepreneurship Journal, 17(2), 445–484. https://doi.org/10.1002/sej.1454
    56. Mahasumran, W., Thepchit, S., Attavinijtrakarn, P., &Chianchana, C. (2021). The factors of digital human resource management in Thai automotive parts manufacturers. Journal of Management Information and Decision Sciences, 24(1), 1–11. Retrieved from https://www-scopuscompresiuniv.knimbus.com/inward/record.uri?eid=2-s2.0
    57. Majumdar, A. (2022). Thematic analysis in qualitative research. In Research anthology on innovative research methodologies and utilization across multiple disciplines (pp. 604–622). https://doi.org/10.4018/978-1-6684-3881-7.ch031
    58. Mammadova, M., &Jabrayilova, Z. (2017). Development of a multi-scenario approach to intelligent management of human resources in the field of medicine. Eastern-European Journal of Enterprise Technologies, 2(3–86), 4–14. https://doi.org/10.15587/1729-4061.2017.95216
    59. Maree, M., Kmail, A. B., &Belkhatir, M. (2019). Analysis and shortcomings of e-recruitment systems: Towards a semantics-based approach addressing knowledge incompleteness and limited domain coverage. Journal of Information Science, 45(6), 713–735. https://doi.org/10.1177/0165551518811449
    60. Martín-de Castro, Gregorio & González-Masip, Jaime & Fernández-Menéndez, José. (2020). The role of corporate environmental commitment and STP on technological talent recruitment in service firms. Knowledge Management Research & Practice. 21. 1-14. 10.1080/14778238.2020.1808542.
    61. McEntire, L. E., Dailey, L. R., Osburn, H. K., & Mumford, M. D. (2006). Innovations in job analysis: Development and application of metrics to analyze job data. Human Resource Management Review, 16(3), 310–323. https://doi.org/10.1016/j.hrmr.2006.05.004
    62. Menon, P., &Thingujam, N. S. (2012). Recession and job satisfaction of Indian information technology professionals. Journal of Indian Business Research, 4(4),
    63. –285. https://doi.org/10.1108/17554191211274785
    64. Mojeed-Sanni, B. A., &Ajonbadi, H. A. (2019). Dynamics of H.R. practices in disruptive and innovative business models in an emerging economy. Academic Journal of Interdisciplinary Studies, 8(3), 57–70. https://doi.org/10.36941/ajis-2019-0005
    65. Montour, A., Baumann, A., Blythe, J., & Hunsberger, M. (2009). The changing nature of nursing work in rural and small community hospitals. Rural and Remote
    66. Health, 9(1), 1089. https://doi.org/10.22605/rrh1089
    67. Napathorn, C. (2022). The development of green skills across firms in the institutional context of Thailand. Asia-Pacific Journal of Business Administration, 14(4), 539–572. https://doi.org/10.1108/APJBA-10-2020-0370
    68. Nelson, E. J., Loux, T., Arnold, L. D., Siddiqui, S. T., &Schootman, M. (2019). Obtaining contextually relevant geographic data using Facebook recruitment in public health studies. Health and Place, 55, 37–42. https://doi.org/10.1016/j.healthplace.2018.11.002
    69. Nieves, J., &Quintana, A. (2018). Human resource practices and innovation in the hotel industry: The mediating role of human capital. Tourism and Hospitality Research, 18(1), 72–83. https://doi.org/10.1177/1467358415624137
    70. Ogbeibu, S., Emelifeonwu, J., Pereira, V., Oseghale, R., Gaskin, J., Sivarajah, U., & Gunasekaran, A. (2023). Demystifying the roles of organizational smart technology, artificial intelligence, robotics, and algorithms capability: A strategy for green human resource management and environmental sustainability. Business Strategy and the Environment. https://doi.org/10.1002/bse.3495
    71. Oltra, V., Donada, C., & Alegre, J. (2022). Facilitating radical innovation through secret technology-oriented skunkworks projects: Implications for human resource practices. Human Resource Management Journal, 32(1), 133–150. https://doi.org/10.1111/1748-8583.12397
    72. 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
    73. Pramod, D., & Bharathi, S. V. (2016). Social media impact on the recruitment and selection process in the information technology industry. International Journal of Human Capital and Information Technology Professionals, 7(2), 36–52. https://doi.org/10.4018/IJHCITP.2016040103
    74. Paaske, N., Øhrn, S.T.,Holm, L.B. and Walter, A.B. (2023) ‘Middle management in academia: social skills and academic professional awareness wanted’, Int. J. Management in Education, Vol. 17, No. 1, pp.68–88.
    75. Ramadevi, D., Gunasekaran, A., Roy, M., Rai, B. K., & Senthilkumar, S. A. (2016). Human resource management in a healthcare environment: Framework and case study. Industrial and Commercial Training, 48(8), 387–393. https://doi.org/10.1108/ICT-03-2016-0014
    76. Rahimi, Sonia & Hall, Nathan & Sticca, Fabio. (2023). Understanding academic procrastination: A Longitudinal analysis of procrastination and emotions in undergraduate and graduate students. Motivation and Emotion. 47. 1-21. 10.1007/s11031-023-10010-9.
    77. Ramirez, J. (2005). Neo-contingency analysis of recruitment and selection: An Anglo-French study of high-tech and mid-tech vs. low-tech firms. International Journal of Technology Management, 31(3–4), 288–316. https://doi.org/10.1504/IJTM.2005.006636
    78. Ramkumar, A., & Rajini, G. (2019). Innovative way of using human resource portals for e-recruitment and selection. International Journal of Scientific and Technology Research, 8(10), 401–408
    79. Rebecca, T., Middleton, P., & Crowther, C. A. (2008). A thematic analysis of factors influencing recruitment to maternal and perinatal trials. BMC Pregnancy and Childbirth. https://doi.org/10.1186/1471-2393-8-36 Recruitment goes virtual: Use web-based technology intelligently for best results in recruitment. (2013). Human Resource Management International Digest, 21(3), 19–21. https://doi.org/10.1108/09670731311318424
    80. Rodríguez-Sánchez, J.-L., Montero-Navarro, A., & Gallego-Losada, R. (2019). The opportunity presented by technological innovation to attract valuable human resources. Sustainability, 11(20). https://doi.org/10.3390/su11205785
    81. Rowan, Willa, "A Mixed-Methods Study of Geoscience Identity, Race/Ethnicity, and Gender in Senior Undergraduate Geoscience Majors" (2023). WWU Graduate School Collection. 1237.https://cedar.wwu.edu/wwuet/1237
    82. Sandhu, K., Brady, G., & Barrett, H. (2023). Reaching out: Using social media to recruit 'invisible groups': The case of South Asian women in the U.K. experiencing gender-related violence. Social Sciences, 12(4), 212.
    83. Sharif, M. M., &Ghodoosi, F. (2022). The ethics of blockchain in organizations. Journal of Business Ethics, 178(4), 1009–1025. https://doi.org/10.1007/s10551-
    84. -05058-5
    85. Shipton, H., Fay, D., West, M., Patterson, M., & Birdi, K. (2005). Managing people to promote innovation. Creativity and Innovation Management, 14(2), 118– 128. https://doi.org/10.1111/j.1467-8691.2005.00332.x
    86. Silvia Bacci & Bruno Bertaccini& Alessandra Petrucci, 2023. "Insights from the co-authorship network of the Italian academic statisticians," Scientometrics, Springer;AkadémiaiKiadó, vol. 128(8), pages 4269-4303, August.
    87. Shurville, S., Browne, T., & Whitaker, M. (2010). An appetite for creative destruction: Should the role of senior academic technology officer be modeled on a CIO or a CTO? Campus-Wide Information Systems, 27(3), 137–147. https://doi.org/10.1108/10650741011054447
    88. Smith, J. A., Flowers, P., & Larkin, M. (2016). Interpretative phenomenological analysis: Theory, method and research. SAGE Publications.
    89. Sridhar, K. (2013). Employment branding at Google: A challenge to attract and/or build talent. International Journal of Sustainable Society, 5(4), 350–356. https://doi.org/10.1504/IJSSOC.2013.056844
    90. Stanley, D. S., & Aggarwal, V. (2019). Impact of disruptive technology on human resource management practices. International Journal of Business Continuity and Risk Management, 9(4), 350–361. https://doi.org/10.1504/IJBCRM.2019.102608
    91. Straughair, C. (2019). Cultivating compassion in nursing: A grounded theory study to explore the perceptions of individuals who have experienced nursing care as patients. Nurse Education in Practice, 35, 98–103. https://doi.org/10.1016/j.nepr.2019.02.002
    92. Sushil. (2012). Interpreting the interpretive structural model. Global Journal of Flexible Systems Management, 13(2), 87–106. https://doi.org/10.1007/s40171-
    93. -0008-3
    94. Seyed Mohammad Sadegh Khaksar & Mei-Tai Chu & Sophia Rozario & Bret Slade, 2023. "Knowledge-based dynamic capabilities and knowledge worker productivity in professional service firms The moderating role of organisational culture," Knowledge Management Research & Practice, Taylor & Francis Journals, vol. 21(2), pages 241-258, March.
    95. Thakkar, J. J. (2021). Interpretive structural modelling (ISM). In Studies in Systems, Decision and Control: Multi-Criteria Decision Making (pp. 311–324). https://doi.org/10.1007/978-981-33-4745-8_18
    96. Toshiyuki, T., Yokoyama, M., Okada, M., & Taniguchi, T. (2021). Panacea: Visual exploration system for analyzing trends in annual recruitment using time varying graphs. PLOS ONE. https://doi.org/10.1371/journal.pone.0247587
    97. Tuttle, M., & Carter, E. W. (2022). Examining high-tech assistive technology use of students with visual impairments. Journal of Visual Impairment & Blindness, 116(4), 473–484.
    98. Vaismoradi, M., Jones, J., Turunen, H., &Säljö, R. (2016). Theme analysis in qualitative research. Qualitative Research in Psychology, 13(6), 441–463.
    99. Wang, Xuequn & Lin, Xiaolin & Shao, Bin. (2022). Artificial intelligence changes the way we work: A close look at innovating with chat bots. Journal of the Association for Information Science and Technology. 74. 10.1002/asi.24621.
    100. Warner, M. (1986). Human-resources implications of new technology. Human Systems Management, 6(4), 279–287. https://doi.org/10.3233/HSM-1986-6403
    101. Weerakoon, R. K. (2016). Human resource management in sports: A critical review of its importance and pertaining issues. Physical Culture and Sport, Studies and Research, 69(1), 15–21. https://doi.org/10.1515/pcssr-2016-0005
    102. Wieringa, R. J. (2003). Entity-relationship diagrams. In Design Methods for Reactive Systems (pp. 77–88). https://doi.org/10.1016/B978-155860755-2/50013-
    103. Wong, M. M. L., & Hendry, C. (1999). Comparing international human resource management practices between Yaohan and Jusco in Hong Kong. Asia Pacific Business Review, 6(1), 104–122. https://doi.org/10.1080/13602380012331289130
    104. Xia Song, Bo Xu, Zhenzhen Zhao (2022). Can people experience romantic love for artificial intelligence? An empirical study of intelligent assistants, Information & Management, Volume 59, Issue 2,103595,ISSN:03787206. doi.org/ 10.1016/j.im.2022.103595
    105. Zhao, H., Zhao, Q. H., & Ślusarczyk, B. (2019). Sustainability and digitalization of corporate management based on augmented/virtual reality tools usage: China and other world IT companies' experience. Sustainability, 11(17). https://doi.org/10.3390/su11174717

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Gaddi, A., Kulkarni, P., Shetty, S. K., Birau, R., Popescu, V., & Hiremath, G. S. (2024). Exploring evolving H.R. and recruitment strategies in the age of technology advancements based on artificial intelligence . Multidisciplinary Science Journal, 7(2), 2025043. https://doi.org/10.31893/multiscience.2025043
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