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Review

Artificial Intelligence and Human Resources Management: A Bibliometric Analysis

ORCID Icon, ORCID Icon, & ORCID Icon
Article: 2145631 | Received 24 Jun 2022, Accepted 04 Nov 2022, Published online: 18 Nov 2022

References

  • Abdeldayem, M. M., and S. H. Aldulaimi. 2020. Trends and opportunities of artificial intelligence in human resource management: Aspirations for public sector in Bahrain. International Journal of Scientific and Technology Research 9 (1):3867–3655.
  • Allal-Chérif, O., A. Alba, and R. Castaño. 2021. Intelligent recruitment: How to identify, select, and retain talents from around the world using Artificial Intelligence. Technological Forecasting and Social Change 169:120822.
  • Aloqaily, A., and H. N. Rawash. 2022. The application reality of Artificial Intelligence and its impact on the administrative human resources processes. Journal of Positive School Psychology 6 (5):3520–29.
  • Aria, M., and C. Cuccurullo. 2017. Bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics 11 (4):959–75. doi:10.1016/j.joi.2017.08.007.
  • Arslan, A., C. Cooper, Z. Khan, I. Golgeci, and I. Ali. 2022. Artificial Intelligence and human workers interaction at team level: A conceptual assessment of the challenges and potential HRM strategies. International Journal of Manpower 43 (1):75–88.
  • Basu, S., M. Bishakha, M. Kajari, M. Surender, and P. Chandan. 2022 March. Artificial Intelligence–HRM interactions and outcomes: A systematic review and causal configurational explanation. Human Resource Management Review 100893. doi:10.1016/j.hrmr.2022.100893.
  • Bellucci, M., G. Marzi, B. Orlando, and F. Ciampi. 2021. Journal of intellectual capital: A review of emerging themes and future trends. Journal of Intellectual Capital 22 (4):744–67. doi:10.1108/JIC-10-2019-0239.
  • Bhatt, P. K., and A. Muduli. 2022. Artificial intelligence in learning and development: A systematic literature review. European Journal of Training and Development 248781691. doi:10.1108/ejtd-09-2021-0143.
  • Bilan, S., P. Šuler, O. Skrynnyk, E. Krajňáková, and T. Vasilyeva. 2022. Systematic bibliometric review of Artificial Intelligence technology in organizational management, development, change and culture. Artificial Intelligence technology in organizational management, development, change and culture. Business: Theory and Practice 23 (1):1–13. doi:10.3846/btp.2022.13204.
  • Black, J. S., and P. van Esch. 2020. AI-enabled recruiting: What is it and how should a manager use it? Business Horizons 63 (2):215–22.
  • Black, J. S., and P. van Esch. 2021. AI-enabled recruiting in the war for talent. Business Horizons 64 (4):513–24. doi:10.1016/j.bushor.2021.02.015.
  • Bolander, T. 2019. What do we loose when machines take the decisions? Journal of Management and Governance 23 (4):849–67. doi:10.1007/s10997-019-09493-x.
  • Bolton, R. 2018. The future of HR 2019: In the know or in the No. KPMG International. 1–24 .
  • Bonilla-Chaves, E. F., and P. R. Palos-Sánchez. 2022 A. Mesquita, A. Abreu, & J. V. Carvalho. Perspectives and Trends in Education and Technology. Smart Innovation, Systems and Technologies 256: 607–20. doi:10.1007/978-981-16-5063-5_50.
  • Boustani, N. M. 2022. Artificial intelligence impact on banks clients and employees in an Asian developing country. Journal of Asia Business Studies 16 (2):267–78. doi:10.1108/JABS-09-2020-0376.
  • Bradford, M. M. 1976. A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Analytical Biochemistry 72:248–54. doi:10.1006/abio.1976.9999.
  • Briner, R. B., and D. Denyer. 2012 Systematic Review and Evidence Synthesis as a Practice and Scholarship Tool Rousseau, D.M. Handbook of Evidence-Based Management: Companies, Classrooms and Research (Oxford: Oxford University Press) 112–29. doi:10.1093/oxfordhb/9780199763986.013.0007.
  • Cappelli, P., P. Tambe, and V. Yakubovich. 2019. Artificial Intelligence in human resources management: Challenges and a path forward. California Management Review 61 (4):15–42. doi:10.1177/0008125619867910.
  • Caputo, F., V. Cillo, E. Candelo, and Y. Liu. 2019. Innovating through digital revolution. Management Decision 57 (8):2032–51. doi:10.1108/MD-07-2018-0833.
  • Coron, C. 2022. Quantifying Human Resource Management: A literature review. Personnel Review 51 (4):1386–409. doi:10.1108/PR-05-2020-0322.
  • Crossan, M. M., and M. Apaydin. 2010. A multi-dimensional framework of organizational innovation: A systematic review of the literature. Journal of Management Studies 47 (6):1154–91. doi:10.1111/j.1467-6486.2009.00880.x.
  • Dabirian, A., J. Kietzmann, and H. Diba. 2017. A great place to work⁉ Understanding crowdsourced employer branding. Business Horizons 60 (2):197–205.
  • Denyer, D., and D. Tranfield. 2009. Producing a Systematic Review D. A. Buchanan & A. Bryman . In The Sage Handbook of Organizational Research Methods, 671–89. Thousand Oaks: Sage Publications Ltd.
  • Di Vaio, A., R. Palladino, R. Hassan, and O. Escobar. 2020. Artificial Intelligence and business models in the sustainable development goals perspective: A systematic literature review. Journal of Business Research 121 (December):283–314. doi:10.1016/j.jbusres.2020.08.019.
  • Fritts, M., and F. Cabrera. 2021. AI recruitment algorithms and the dehumanization problem. Ethics and Information Technology 23 (4):791–801. doi:10.1007/s10676-021-09615-w.
  • Garg, S., S. Sinha, A. Kumar, and M. Mani. 2022. A review of machine learning applications in Human Resource Management. International Journal of Productivity and Performance Management 71 (5):1590–610. doi:10.1108/IJPPM-08-2020-0427.
  • Giermindl, L. M., F. Strich, O. Christ, U. Leicht-Deobald, and A. Redzepi. 2022. The dark sides of people analytics: Reviewing the perils for organisations and employees. European Journal of Information Systems 31 (3):410–35. doi:10.1080/0960085X.2021.1927213.
  • Guleria, D., and G. Kaur. 2021. Bibliometric analysis of ecopreneurship using VOSviewer and RStudio Bibliometrix, 1989–2019. Library Hi Tech 39 (4):1001–24. doi:10.1108/LHT-09-2020-0218.
  • Gupta, P., S. Fernandes, and M. Jain. 2018. Automation in recruitment: A new frontier. Journal of Information Technology Teaching Cases 8 (2):118–25. doi:10.1057/s41266-018-0042-x.
  • Gutiérrez, Á., and A. Maz. 2004. Cimentando un proyecto de investigación: undefined revisión de literatura. Revista EMA 9 (1):20–37.
  • Hamilton, R. H., and H. K. Davison. 2022. Legal and ethical challenges for HR in machine learning. Employee Responsibilities and Rights Journal 34 (1):19–39. doi:10.1007/s10672-021-09377-z.
  • Huang, M. J., Y. L. Tsou, and S. C. Lee. 2006. Integrating fuzzy data mining and fuzzy artificial neural networks for discovering implicit knowledge. Knowledge-Based Systems 19 (6):396–403. doi:10.1016/j.knosys.2006.04.003.
  • Iden, J., and T. R. Eikebrokk. 2013. Implementing IT service management: A systematic literature review. International Journal of Information Management 33 (3):512–23. doi:10.1016/j.ijinfomgt.2013.01.004.
  • Jatobá, M., J. Santos, I. Gutierriz, D. Moscon, P. O. Fernandes, and J. P. Teixeira. 2019. Evolution of Artificial Intelligence research in Human Resources. Evolution of Artificial Intelligence research in human resources. Procedia Computer Science 164: 137–42. doi: 10.1016/j.procs.2019.12.165.
  • Johnson, R. D., D. L. Stone, and K. M. Lukaszewski. 2021. The benefits of eHRM and AI for talent acquisition. Journal of Tourism Futures 7 (1):40–52. doi:10.1108/JTF-02-2020-0013.
  • Kearney, C., and T. Meynhardt. 2016. Directing corporate entrepreneurship strategy in the public sector to public value: Antecedents, components, and outcomes. International Public Management Journal 19 (4):543–72. doi:10.1080/10967494.2016.1160013.
  • Kimseng, T., A. Javed, C. Jeenanunta, and Y. Kohda. 2020. Applications of fuzzy logic to reconfigure human resource management practices for promoting product innovation in formal and non-formal R&D firms. Journal of Open Innovation: Technology, Market, and Complexity 6 (2). doi: 10.3390/JOITMC6020038.
  • Kong, H., Y. Yuan, Y. Baruch, N. Bu, X. Jiang, and K. Wang. 2021. Influences of Artificial Intelligence (AI) awareness on career competency and job burnout. International Journal of Contemporary Hospitality Management 33 (2):717–34. doi:10.1108/IJCHM-07-2020-0789.
  • Kshetri, N. 2021. Evolving Uses of Artificial Intelligence in Human Resource Management in emerging economies in the global south: Some preliminary evidence. Management Research Review 44(7): 970–90. doi:10.1108/MRR-03-2020-0168.
  • Macke, J., and D. Genari. 2019. Systematic literature review on sustainable Human Resource Management. Journal of Cleaner Production 208:806–15. doi:10.1016/j.jclepro.2018.10.091.
  • MacKenzie, H., A. Dewey, A. Drahota, S. Kilburn, P. Kalra, C. Fogg, and D. Zachariah. 2012. Systematic reviews: What they are, why they are important, and how to get involved. Journal of Clinical and Preventive Cardiology 1 (4):193–202.
  • Malik, A., P. Thevisuthan, and T. De Sliva. 2022Artificial Intelligence, Employee Engagement, Experience, and HRM BT - Strategic Human Resource Management and Employment Relations: An International PerspectiveA. Maliked. 171–84Springer International Publishing. doi:10.1007/978-3-030-90955-0_16.
  • Malik, N., S. N. Tripathi, A. K. Kar, and S. Gupta. 2021. Impact of Artificial Intelligence on employees working in industry 4.0 led organizations. International Journal of Manpower. doi:10.1108/IJM-03-2021-0173.
  • Marx, W., L. Bornmann, A. Barth, and L. Leydesdorff. 2014. Detecting the historical roots of research fields by Reference Publication Year Spectroscopy (RPYS). Journal of the Association for Information Science and Technology 65 (4):751–64. doi:10.1002/asi.23089.
  • McCarthy, J. 1956. Measures of the value of information. Proceedings of the National Academy of Sciences 42 (9):654–55. doi:10.1073/pnas.42.9.654.
  • Michailidis, M. P. 2018. The challenges of AI and blockchain on HR recruiting practices. Cyprus Review 30 (2):169–80.
  • Minbaeva, D. 2021. Disrupted HR? Human Resource Management Review 31 (4):100820. doi:10.1016/j.hrmr.2020.100820.
  • Minsky, M. 1968. Semantic Information Processing. Massachusetts: The MIT Press.
  • Mitchell, T., and E. Brynjolfsson. 2017. Track how technology is transforming work. Nature 544 (7650):290–92. doi:10.1038/544290a.
  • Mori, S., H. Maeta, T. Sasada, K. Yoshino, A. Hashimoto, T. Funatomi, and Y. Yamakata. (2014). FlowGraph2text: Automatic sentence skeleton compilation for procedural text generation. INLG 2014 - Proceedings of the 8th International Natural Language Generation Conference, Including - Proceedings of the INLG and SIGDIAL 2014 Joint Session, June, 118–22. doi:10.3115/v1/w14-4418.
  • Nankervis, A., J. Connell, R. Cameron, A. Montague, and V. Prikshat. 2021. ‘Are we there yet?’ Australian HR professionals and the fourth industrial revolution. Asia Pacific Journal of Human Resources 59 (1):3–19. doi:10.1111/1744-7941.12245.
  • Nawaz, N. 2020. Artificial Intelligence applications for face recognition in recruitment process. Journal of Management Information and Decision Sciences 23:499–509.
  • Nedelkoska, L., and G. Quintini. 2018. Automation, Skills Use and Training. Paris: OECD doi:10.1787/1815199X.
  • Nilsson, N. J. (1998). Artificial Intelligence: A New Synthesis. Morgan Kaufmann. https://doi.org/10.1016/C2009-0-27773-7
  • Ogbeibu, S., C. J. Chiappetta Jabbour, J. Burgess, J. Gaskin, and D. W. S. Renwick. 2022. Green talent management and turnover intention: The roles of leader STARA competence and digital task interdependence. Journal of Intellectual Capital 23 (1):27–55.
  • Paesano, A. 2021. Artificial Intelligence and creative activities inside organizational behavior. International Journal of Organizational Analysis. ahead-of-p(ahead-of-print. doi: 10.1108/IJOA-09-2020-2421.
  • Pan, Y., F. Froese, N. Liu, Y. Hu, and M. Ye. 2022. The adoption of artificial intelligence in employee recruitment: The influence of contextual factors. International Journal of Human Resource Management 33 (6):1125–47. doi:10.1080/09585192.2021.1879206.
  • Parris, D. L., and J. W. Peachey. 2013. A systematic literature review of servant leadership theory in organizational contexts. Journal of Business Ethics 113 (3):377–93. doi:10.1007/s10551-012-1322-6.
  • Paul, J., A. Merchant, Y. K. Dwivedi, and G. Rose. 2021. Writing an impactful review article: What do we know and what do we need to know? Journal of Business Research 133:337–40. doi:10.1016/j.jbusres.2021.05.005.
  • Pereira, V., E. Hadjielias, M. Christofi, and D. Vrontis. 2021, September. A systematic literature review on the impact of Artificial Intelligence on workplace outcomes: A multi-process perspective. Human Resource Management Review 100857. doi:10.1016/j.hrmr.2021.100857.
  • Perello, M. R., and M. Tuffaha. 2021. Artificial Intelligence definition, applications and adoption in Human Resource Management: A systematic literature review. International Journal of Business Innovation and Research 1:1. doi:10.1504/IJBIR.2021.10040005.
  • Pickering, C., and J. Byrne. 2014. The benefits of publishing systematic quantitative literature reviews for PhD candidates and other early-career researchers. Higher Education Research & Development 33 (3):534–48. doi:10.1080/07294360.2013.841651.
  • Pietronudo, M., G. Croidieu, and F. Schiavone. 2022. A solution looking for problems? A systematic literature review of the rationalizing influence of Artificial Intelligence on decision-making in innovation management. Technological Forecasting and Social Change 182 (September):121828. doi:10.1016/j.techfore.2022.121828.
  • Pillai, R., and B. Sivathanu. 2020. Adoption of Artificial Intelligence (AI) for talent acquisition in IT/ITeS organizations. Benchmarking: An International Journal 27 (9):2599–629. doi:10.1108/BIJ-04-2020-0186.
  • Poba-Nzaou, P., M. Galani, and A. Tchibozo. 2020. Transforming Human Resources Management in the age of Industry 4.0: A matter of survival for HR professionals. Strategic HR Review 19 (6):273–78. doi:10.1108/SHR-06-2020-0055.
  • Podsakoff, P. M., S. B. MacKenzie, D. G. Bachrach, and N. P. Podsakoff. 2005. The influence of management journals in the 1980s and 1990s. Strategic Management Journal 26 (5):473–88. doi:10.1002/smj.454.
  • Popkova, E. G., and B. Sergi. 2020. Human capital and AI in industry 4.0. convergence and divergence in social entrepreneurship in Russia. Journal of Intellectual Capital 21 (4):565–81. doi:10.1108/JIC-09-2019-0224.
  • Qamar, Y., R. K. Agrawal, T. A. Samad, and C. J. Chiappetta Jabbour. 2021. When technology meets people: The interplay of artificial intelligence and human resource management. Journal of Enterprise Information Management 34 (5):1339–70. doi:10.1108/JEIM-11-2020-0436.
  • Rąb-Kettler, K., and B. Lehnervp. 2019. Recruitment in the Times of Machine Learning. Management Systems in Production Engineering 27 (2):105–09. doi:10.1515/mspe-2019-0018.
  • Rykun, E. 2019 Artificial Intelligence in HR Management–What Can We Expect? The Boss Magazine. https://thebossmagazine.com/ai-hr-management/
  • Sahota, N., and M. Ashley. 2019. When Robots Replace Human Managers: Introducing the Quantifiable Workplace. IEEE Engineering Management Review 47 (3):21–23. doi:10.1109/EMR.2019.2931654.
  • Salmerón, J. L., and P. R. Palos-Sánchez. 2019. Uncertainty Propagation in Fuzzy Grey Cognitive Maps with Hebbian-Like Learning Algorithms. IEEE Transactions on Cybernetics 49 (1):211–20. doi:10.1109/TCYB.2017.2771387.
  • Snyder, H. 2019. Literature Review as a Research Methodology: An Overview and Guidelines. Journal of Business Research 104:333–39. doi:10.1016/j.jbusres.2019.07.039.
  • Soleimani, M., A. Intezari, and D. J. Pauleen. 2022. Mitigating cognitive biases in developing ai-assisted recruitment systems: A knowledge-sharing approach. International Journal of Knowledge Management 18 (1):1–18. doi:10.4018/IJKM.290022.
  • Stanley, D. S., and V. Aggarwal. 2019. Impact of disruptive technology on human resource management practices. International Journal of Business Continuity and Risk Management 9 (4):350. doi:10.1504/ijbcrm.2019.10021173.
  • Strohmeier, S., and F. Piazza. 2013. Domain Driven Data Mining in Human Resource Management: A Review of Current Research. Expert Systems with Applications 40 (7):2410–20. doi:10.1016/j.eswa.2012.10.059.
  • Suen, H. Y., M. Yi-Ching, and L. Shih-Hao. 2019. Does the Use of Synchrony and Artificial Intelligence in Video Interviews Affect Interview Ratings and Applicant Attitudes? Computers in Human Behavior 98:93–101. doi:10.1016/j.chb.2019.04.012.
  • Tambe, P., P. Cappelli, and V. Yakubovich. 2019. Artificial Intelligence in Human Resources Management: Challenges and a Path Forward. California Management Review 61 (4):15–42. doi:10.1177/0008125619867910.
  • Tranfield, D., D. Denyer, and P. Smart. 2003. Towards a Methodology for Developing Evidence-Informed Management Knowledge by Means of Systematic Review. British Journal of Management 14 (3):207–22. doi:10.1111/1467-8551.00375.
  • Turing, A. M. 1937. On Computable Numbers, with an Application to the Entscheidungsproblem. Proceedings of the London Mathematical Society s2-42 (1):230–65. doi:10.1112/plms/s2-42.1.230.
  • Turing, A. M. 1950. Computing Machinery and Intelligence. Mind LIX (236):433–60. doi:10.1093/mind/LIX.236.433.
  • van Esch, P., and J. S. Black. 2019. Factors that influence new generation candidates to engage with and complete digital, AI-enabled recruiting. Business Horizons 62 (6):729–39. doi:10.1016/j.bushor.2019.07.004.
  • Varma, A., C. Dawkins, and K. Chaudhuri. 2022. Artificial intelligence and people management: A critical assessment through the ethical lens. Human Resource Management Review, April, human Resource Management Review, April 100923. doi:10.1016/j.hrmr.2022.100923.
  • Vinichenko, M. V., M. V. Rybakova, O. L. Сhulanova, I. V. Kuznetsova, S. A. Makushkin, and A. S. Lobacheva. 2019. Using natural and artificial intelligence in the talent management system. International Journal of Recent Technology and Engineering 8 (3):7417–23. doi:10.35940/ijrte.C6152.098319.
  • Vlačić, B., L. Corbo, S. Costa E Silva, and M. Dabić. 2021. The evolving role of artificial intelligence in marketing: A review and research agenda. Journal of Business Research 128 (March 2020):187–203. doi:10.1016/j.jbusres.2021.01.055.
  • Votto, A., R. Valecha, P. Najafirad, and R. Rao. 2021. Artificial Intelligence in Tactical Human Resource Management: A Systematic Literature Review. International Journal of Information Management Data Insights 1 (2):100047. doi:10.1016/j.jjimei.2021.100047.
  • Vrontis, D., M. Christofi, V. Pereira, S. Tarba, A. Makrides, and E. Trichina. 2022. Artificial intelligence, robotics, advanced technologies and human resource management: A systematic review. International Journal of Human Resource Management 33 (6):1237–66. doi:10.1080/09585192.2020.1871398.
  • Welsh, R. 2019. Defining artificial intelligence. SMPTE Motion Imaging Journal 128 (1):26–32. doi:10.5594/JMI.2018.2880366.
  • Wong, G., T. Greenhalgh, G. Westhorp, J. Buckingham, and R. Pawson. 2013. Publication Standards: Meta-Narrative Reviews. Journal of Advanced Nursing 69 (5):987–1004. doi:10.1111/jan.12092.
  • Yahia, N. B., J. Hlel, and R. Colomo-Palacios. 2021. From Big Data to Deep Data to Support People Analytics for Employee Attrition Prediction. IEEE Access 9:60447–58. doi:10.1109/ACCESS.2021.3074559.
  • Zhang, Y., S. Xu, L. Zhang, and M. Yang. 2021. Big data and human resource management research: An integrative review and new directions for future research. Journal of Business Research 133 (April):34–50. doi:10.1016/j.jbusres.2021.04.019.