A BIBLIOMETRIC ANALYSIS ON THE ROLE OF ARTIFICIAL INTELLIGENCE-ENABLED RECRUITMENT TOWARDS SUSTAINABILITY: TRENDS AND FUTURE DIRECTIONS
DOI:
https://doi.org/10.55955/430002Keywords:
Artificial Intelligence (AI), Bibliometric analysis, Recruitment, Systematic literature review (SLR), Human resource (HR) managersAbstract
Purpose: By increasing productivity, decreasing bias, and promoting long-term workforce development, artificial intelligence (AI) in sustainable recruitment is revolutionizing talent acquisition. For HR experts, job seekers, employees, and AI developers, this study offers a thorough bibliometric review of AI-driven hiring processes. Through examination of research trends, methodologies, and applications of AI in sustainable recruitment, this study highlights key advancements, challenges, and future research directions. Design/ Methodology/ Approach: A comprehensive literature review using PRISMA was carried out, looking at 105 publications from the Scopus database that were published between 2015 and 2025. Multiple analytical software tools were utilized to conduct bibliometric and network analysis. Findings: According to the study's findings, the topic's considerable increase in researchers has led to a notable boom in research in recent years. The topic of “AI and Sustainable Recruitment” has seen expanding publications, now reaching a total of 49. Technological Forecasting and Social Change stands out as the leading contributing journal, having published four articles on the subject. India and the USA emerge as the most productive countries in this domain, challenging the traditional distinction between developed and developing nations. Additionally, the study identifies Malik A as the most prolific author, with three published papers and a total of 63 citations. Furthermore, the thematic analysis conducted in this study has helped outline epochal arenas for emerging research, offering priceless insights into forthcoming trends and directions within the field. Originality: This study offers a multi-dimensional analysis of AI-based sustainable recruitment literature. By employing advanced visualization techniques, this research provides a greater understanding on the topic. The perceptivity from this work bridges the gap between academic research and technology, fostering innovation, efficiency, and strategic decision-making in talent acquisition.
References
Abdul, C., Wang, W., & Li, Y. (2020). The Impact of Technology on Recruitment Process. Issues in Information Systems, 21(4), 9–17. https://doi.org/10.48009/4_iis_2020_9-17
Agarwal, V., Mathiyazhagan, K., Malhotra, S., & Saikouk, T. (2022). Analysis of challenges in sustainable human resource management due to disruptions by Industry 4.0: an emerging economy perspective. International Journal of Manpower, 43(2), 513–541. https://doi.org/10.1108/IJM-03-2021-0192
Allal-Chérif, O., Yela Aránega, A., & Castaño Sánchez, R. (2021). Intelligent recruitment: How to identify, select, and retain talents from around the world using artificial intelligence. Technological Forecasting and Social Change, 169. https://doi.org/10.1016/j.techfore.2021.120822
Almansoori, A. H. M. A., bin Othman, M. F., & Siam, M. R. A. (2021). Moderating Interact of Artificial Intelligence Use in the Influences of Recruitment, Selection, And Staffing on the Organizational Performance in the UAE Manufacturing Industry. Academy of Entrepreneurship Journal, 27(Special Issue 2), 1–14. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112383053&partnerID=40&md5=c384d6c537933595226bac9141adc6c2
Anghel, D. (2023). New Perspectives for Human and Artificial Intelligence Interactions for Leadership e-Recruitment. Societies, 13(3). https://doi.org/10.3390/soc13030055
Aydın, E., & Turan, M. (2023). An AI-Based Shortlisting Model for Sustainability of Human Resource Management. Sustainability (Switzerland), 15(3). https://doi.org/10.3390/su15032737
Bailao Goncalves, M., Anastasiadou, M., & Santos, V. (2022). AI 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
Basit, A. (2020). COVID-19: a challenge or opportunity for terrorist groups? Journal of Policing, Intelligence and Counter Terrorism, 15(3), 263–275. https://doi.org/10.1080/18335330.2020.1828603
Bedemariam, R., & Wessel, J. L. (2023). The roles of outcome and race on applicant reactions to AI systems. Computers in Human Behavior, 148. https://doi.org/10.1016/j.chb.2023.107869
Bello, M., Luna, A., Bonilla, E., Hernandez, C., Pedroza, B., & Portilla, A. (2020). A novel profile’s selection algorithm using AI. Applied Computer Science, 16(1), 18–32. https://doi.org/10.23743/acs-2020-02
Bonomi Savignon, A., Zecchinelli, R., Costumato, L., & Scalabrini, F. (2024). Automation in public sector jobs and services: a framework to analyze public digital transformation’s impact in a data-constrained environment. Transforming Government: People, Process and Policy, 18(1), 49–70. https://doi.org/10.1108/TG-04-2023-0044
Bukartaite, R., & Hooper, D. (2023). Automation, artificial intelligence and future skills needs: an Irish perspective. European Journal of Training and Development, 47(10), 163–185. https://doi.org/10.1108/EJTD-03-2023-0045
Buranasing, A. (2020). Efficiency assessment of undergraduate students based on academic record using deep learning methodology. International Journal of Information and Education Technology, 10(7), 511–515. https://doi.org/10.18178/ijiet.2020.10.7.1416
Bursell, M., & Roumbanis, L. (2024). After the algorithms: A study of meta-algorithmic judgments and diversity in the hiring process at a large multisite company. Big Data and Society, 11(1). https://doi.org/10.1177/20539517231221758
Cardon, D., & John-Mathews, J.-M. (2023). The displacement of reality tests. The selection of individuals in the age of machine learning. Distinktion, 24(2), 217–240. https://doi.org/10.1080/1600910X.2023.2221398
Chakraborty, S., Giri, A., Aich, A., & Biswas, S. (2020). Evaluating influence of artificial intelligence on human resource management using PLS-SEM (Partial least squares-structural equation modeling). International Journal of Scientific and Technology Research, 9(3), 5876–5880. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082871684&partnerID=40&md5=7062edf421daa0b2514520f78a0dc12f
Chen, Z. (2023). Collaboration among recruiters and artificial intelligence: removing human prejudices in employment. Cognition, Technology and Work, 25(1), 135–149. https://doi.org/10.1007/s10111-022-00716-0
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
Chopra, A., & Bhilare, P. (2020). Future of Work: An Empirical Study to Understand Expectations of the Millennials from Organizations. Business Perspectives and Research, 8(2), 272–288. https://doi.org/10.1177/2278533719887457
Cug, J., Kubala, P., & Pera, A. (2023). Generative Artificial Intelligence and Virtual Recruitment Tools, Wearable Self-Tracking and Augmented Reality Devices, and Multimodal Behavioral Analytics in Virtual Workplaces. Analysis and Metaphysics, 22. https://doi.org/10.22381/am2220238
da Costa, R. L., Costa, B., Martinho, F., Pereira, L., Gonçalves, R., & Dias, Á. (2023). Artificial intelligence contribution to recruitment and selection. International Journal of Management Practice, 16(4), 434–453. https://doi.org/10.1504/IJMP.2023.132081
Dalv, D. S. (2021). Employer brand equity and its impact on the application intent of the prospective employees. International Journal of Business Intelligence Research, 12(1), 1–25. https://doi.org/10.4018/IJBIR.20210101.oa1
Deepa, R., Sekar, S., Malik, A., Kumar, J., & Attri, R. (2024). Impact of AI-focussed technologies on social and technical competencies for HR managers – A systematic review and research agenda. Technological Forecasting and Social Change, 202. https://doi.org/10.1016/j.techfore.2024.123301
Denis, G., Krishnakumar, T., Karthikeyan, M., & Sasipriya, S. (2020). Recruitment based on personality traits from digital footprints on social media by using machine learning language. International Journal of Scientific and Technology Research, 9(2), 951–955. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079673101&partnerID=40&md5=ffc7a939c4e3366605986e9ce8890dc0
Dominique-Ferreira, S., Rodrigues, B. Q., & Braga, R. J. (2022). Personal marketing and the recruitment and selection process: Hiring attributes and particularities in tourism and hospitality. Journal of Global Scholars of Marketing Science: Bridging Asia and the World, 32(3), 351–371. https://doi.org/10.1080/21639159.2020.1808845
Drage, E., & Mackereth, K. (2022). Does AI Debias Recruitment? Race, Gender, and AI’s “Eradication of Difference.” Philosophy and Technology, 35(4). https://doi.org/10.1007/s13347-022-00543-1
Elmohandes, N., & Marghany, M. (2024). Effective or ineffective? Using ChatGPT for staffing in the hospitality industry. European Journal of Tourism Research, 36. https://doi.org/10.54055/ejtr.v36i.3286
Fan, Q., DuBose, L., Ory, M. G., Lee, S., Hoang, M.-N., Vennatt, J., Kew, C. L., Doyle, D., & Falohun, T. (2023). Financial, Legal, and Functional Challenges of Providing Care for People Living with Dementia and Needs for a Digital Platform: Interview Study Among Family Caregivers. JMIR Aging, 6(1). https://doi.org/10.2196/47577
Fritts, M., & Cabrera, F. (2021). AI recruitment algorithms and the dehumanization problem. Ethics and Information Technology, 23(4), 791–801. https://doi.org/10.1007/s10676-021-09615-w
G, M., Antony, S. P., & George, E. P. (2020). Understanding job and organizational attributes as signals from recruitment advertisement. Journal of Indian Business Research, 13(1), 134–153. https://doi.org/10.1108/JIBR-04-2018-0112
Gamage, A., Pyke, J., & de Lacy, T. (2024). Building resilience and sustainable HRM in the visitor economy: An uneasy relationship. Journal of Hospitality and Tourism Management, 58, 497–505. https://doi.org/10.1016/j.jhtm.2023.05.006
Gélinas, D., Sadreddin, A., & Vahidov, R. (2022). Artificial intelligence in human resources management: A review and research agenda. Pacific Asia Journal of the Association for Information Systems, 14(6), 1–42. https://doi.org/10.17705/1pais.14601
Gethe, R. K. (2022). Extrapolation of talent acquisition in AI aided professional environment. International Journal of Business Innovation and Research, 27(4), 462–479. https://doi.org/10.1504/IJBIR.2022.122510
Glasby, J., Litchfield, I., Parkinson, S., Hocking, L., Tanner, D., Roe, B., & Bousfield, J. (2023). New and emerging technology for adult social care – the example of home sensors with artificial intelligence (AI) technology. Health and Social Care Delivery Research, 11(9). https://doi.org/10.3310/HRYW4281
Gupta, P., Fernandes, S. F., & Jain, M. (2018). Automation in recruitment: a new frontier. Journal of Information Technology Teaching Cases, 8(2), 118–125. https://doi.org/10.1057/s41266-018-0042-x
Guyard, K. C., & Deriaz, M. (2023). A Scalable Recommendation System Approach for a Companies - Seniors Matching. International Journal of Semantic Computing, 17(2), 275–291. https://doi.org/10.1142/S1793351X23610019
Hunkenschroer, A. L., & Luetge, C. (2022). Ethics of AI-Enabled Recruiting and Selection: A Review and Research Agenda. Journal of Business Ethics (Vol. 178, Issue 4, pp. 977–1007). Springer Science and Business Media B.V. https://doi.org/10.1007/s10551-022-05049-6
Islam, M., Mamun, A. A., Afrin, S., Ali Quaosar, G. M. A., & Uddin, M. A. (2022). Technology Adoption and Human Resource Management Practices: The Use of Artificial Intelligence for Recruitment in Bangladesh. South Asian Journal of Human Resources Management, 9(2), 324–349. https://doi.org/10.1177/23220937221122329
Islam, M., Rahman, Md. M., Taher, Md. A., Quaosar, G. M. A. A., & Uddin, Md. A. (2024). Using artificial intelligence for hiring talents in a moderated mechanism. Future Business Journal, 10(1). https://doi.org/10.1186/s43093-024-00303-x
Johnson, R. D., Stone, D. L., & Lukaszewski, K. M. (2020). The benefits of eHRM and AI for talent acquisition. Journal of Tourism Futures, 7(1), 40–52. https://doi.org/10.1108/JTF-02-2020-0013
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
Kaushal, N., Kaurav, R. P. S., Sivathanu, B., & Kaushik, N. (2023). Artificial intelligence and HRM: identifying future research Agenda using systematic literature review and bibliometric analysis. Management Review Quarterly, 73(2), 455–493. https://doi.org/10.1007/s11301-021-00249-2
Kazim, E., Koshiyama, A. S., Hilliard, A., & Polle, R. (2021). Systematizing audit in algorithmic recruitment. Journal of Intelligence, 9(3). https://doi.org/10.3390/jintelligence9030046
Keppeler, F. (2024). No Thanks, Dear AI! Understanding the Effects of Disclosure and Deployment of Artificial Intelligence in Public Sector Recruitment. Journal of Public Administration Research and Theory, 34(1), 39–52. https://doi.org/10.1093/jopart/muad009
Kim, J.-Y., & Heo, W. (2022). Artificial intelligence video interviewing for employment: perspectives from applicants, companies, developer and academicians. Information Technology and People, 35(3), 861–878. https://doi.org/10.1108/ITP-04-2019-0173
Kong, Y., & Ding, H. (2024). Tools, Potential, and Pitfalls of Social Media Screening: Social Profiling in the Era of AI-Assisted Recruiting. Journal of Business and Technical Communication, 38(1), 33–65. https://doi.org/10.1177/10506519231199478
Kot, S., Hussain, H. I., Bilan, S., Haseeb, M., & Mihardjo, L. W. W. (2021). The role of artificial intelligence recruitment and quality to explain the phenomenon of employer reputation. Journal of Business Economics and Management, 22(4), 867–883. https://doi.org/10.3846/jbem.2021.14606
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
Lee, C., & Cha, K. (2023). FAT-CAT—Explainability and augmentation for an AI system: A case study on AI recruitment-system adoption. International Journal of Human Computer Studies, 171. https://doi.org/10.1016/j.ijhcs.2022.102976
Lee, J. Y., & Ma, Y. (2021). The Impact of the Exchange of Sustainable Technological HR Innovation Knowledge within Chaebols on the Performance of Global Subsidiaries. Journal of Korea Trade, 25(4), 108–127. https://doi.org/10.35611/jkt.2021.25.4.108
Lematta, G. J., Corral, C. C., Buchanan, V., Johnson, C. J., Mudigonda, A., Scholcover, F., Wong, M. E., Ezenyilimba, A., Baeriswyl, M., Kim, J., Holder, E., Chiou, E. K., & Cooke, N. J. (2022). Remote research methods for Human–AI–Robot Teaming. Human Factors and Ergonomics In Manufacturing, 32(1), 133–150. https://doi.org/10.1002/hfm.20929
Lin, Y.-T., Hung, T.-W., & Huang, L. T.-L. (2021). Engineering Equity: How AI Can Help Reduce the Harm of Implicit Bias. Philosophy and Technology, 34, 65–90. https://doi.org/10.1007/s13347-020-00406-7
Liu, B., Wei, L., Wu, M., & Luo, T. (2023). Speech production under uncertainty: how do job applicants experience and communicate with an AI interviewer? Journal of Computer-Mediated Communication, 28(4). https://doi.org/10.1093/jcmc/zmad028
Lukaszewski, K. M., & Stone, D. L. (2024). Will the use of AI in human resources create a digital Frankenstein? Organizational Dynamics, 53(1). https://doi.org/10.1016/j.orgdyn.2024.101033
Mačernyte-Panomarioviene, I. (2023). Discrimination on the Basis of Personal Data in Employment: The Case Study of Lithuania. Baltic Journal of Law and Politics, 16(1), 24–41. https://doi.org/10.2478/bjlp-2023-0002
Manroop, L., Malik, A., & Milner, M. (2024). The ethical implications of big data in human resource management. Human Resource Management Review, 34(2). https://doi.org/10.1016/j.hrmr.2024.101012
Mühlhoff, R., & Willem, T. (2023). Social media advertising for clinical studies: Ethical and data protection implications of online targeting. Big Data and Society, 10(1). https://doi.org/10.1177/20539517231156127
Nawaz, N. (2019). How Far have we come with the study of artificial intelligence for recuritment process. International Journal of Scientific and Technology Research, 8(7), 488–493. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85071738284&partnerID=40&md5=bc18683f4a83381535b42915a63c5289
Nawaz, N. (2020). Artificial Intelligence Applications for Face Recognition in Recruitment Process. Journal of Management Information and Decision Sciences, 23, 499–509. https://www.scopus.com/inward/record.uri?eid=2-s2.085099628951&partnerID=40&md5=90d8a4f94b848c285e04799f0f78da88
Nayal, K., Raut, R. D., Mangla, S. K., Kumar, M., Tuček, D., & Gavurova, B. (2023). Achieving market performance via industry 4.0 enabled dynamic marketing capability, sustainable human resource management, and circular product design. Industrial Marketing Management, 115, 86–98. https://doi.org/10.1016/j.indmarman.2023.09.010
Niehueser, W., & Boak, G. (2020). Introducing artificial intelligence into a human resources function. Industrial and Commercial Training, 52(2), 121–130. https://doi.org/10.1108/ICT-10-2019-0097
Oberst, U., de Quintana, M., del Cerro, S., & Chamarro, A. (2021). Recruiters prefer expert recommendations over digital hiring algorithm: a choice-based conjoint study in a pre-employment screening scenario. Management Research Review, 44(4), 625–641. https://doi.org/10.1108/MRR-06-2020-0356
Ogbeibu, S., Emelifeonwu, J., Pereira, V., Oseghale, R., Gaskin, J., Sivarajah, U., & Gunasekaran, A. (2024). Demystifying the roles of organisational smart technology, artificial intelligence, robotics and algorithms capability: A strategy for green human resource management and environmental sustainability. Business Strategy and the Environment, 33(2), 369–388. https://doi.org/10.1002/bse.3495
Oncioiu, I., Anton, E., Ifrim, A. M., & Mândricel, D. A. (2022). The Influence of Social Networks on the Digital Recruitment of Human Resources: An Empirical Study in the Tourism Sector. Sustainability (Switzerland), 14(6). https://doi.org/10.3390/su14063693
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
Pan, Y., Froese, F., Liu, N., Hu, Y., & Ye, M. (2022). The adoption of artificial intelligence in employee recruitment: The influence of contextual factors. International Journal of Human Resource Management, 33(6), 1125–1147. https://doi.org/10.1080/09585192.2021.1879206
Pandya, B., & al Janahi, M. M. (2021). The intervention of artificial intelligence in the recruitment function in UAE’s hospitality industry. Transnational Marketing Journal, 9(1), 89–105. https://doi.org/10.33182/tmj.v9i1.1033
Pessach, D., Singer, G., Avrahami, D., Chalutz Ben-Gal, H., Shmueli, E., & Ben-Gal, I. (2020). Employees recruitment: A prescriptive analytics approach via machine learning and mathematical programming. Decision Support Systems, 134. https://doi.org/10.1016/j.dss.2020.113290
Prikshat, V., Islam, M., Patel, P., Malik, A., Budhwar, P., & Gupta, S. (2023). AI-Augmented HRM: Literature review and a proposed multilevel framework for future research. Technological Forecasting and Social Change, 193. https://doi.org/10.1016/j.techfore.2023.122645
Rab-Kettler, K., & Lehnervp, B. (2019). Recruitment in the Times of Machine Learning. Management Systems in Production Engineering, 27(2), 105–109. https://doi.org/10.1515/mspe-2019-0018
Renier, L. A., Schmid Mast, M., & Bekbergenova, A. (2021). To err is human, not algorithmic – Robust reactions to erring algorithms. Computers in Human Behavior, 124. https://doi.org/10.1016/j.chb.2021.106879
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/s10551-022-05058-5
Saputra, A. R. P., Widarta, W., & Iswiyanto, I. (2024). The impact of green training, green reward, and green recruitment on organizational citizenship behavior for environment. International Journal of Human Capital in Urban Management, 9(1), 75–84. https://doi.org/10.22034/IJHCUM.2024.01.06
Shao, D., Ji, Y., Zhou, R., & Liu, T. (2024). Unpacking the Mixed Influences of Sustainable Human Resource Management on Employee Resilience: Effects of Challenge–Hindrance Appraisal and Trait Mindfulness. Asia Pacific Journal of Human Resources, 63(1). https://doi.org/10.1111/1744-7941.12433
Sharma, M., Luthra, S., Joshi, S., & Kumar, A. (2022). Analysing the impact of sustainable human resource management practices and industry 4.0 technologies adoption on employability skills. International Journal of Manpower, 43(2), 463–485. https://doi.org/10.1108/IJM-02-2021-0085
Sinicropi, S., & Cortese, D. (2021). (Re)Thinking diversity within sustainable development: A systematic mapping study. Corporate Social Responsibility and Environmental Management, 28(1), 299–309. https://doi.org/10.1002/csr.2050
Shayegan, S., Bazrkar, A., & Yadegari, R. (2023). Realization of Sustainable Organizational Performance Using New Technologies and Green Human Resource Management Practices. Foresight and STI Governance, 17(2), 95–105. https://doi.org/10.17323/2500-2597.2023.2.95.105
Shulner-Tal, A., Kuflik, T., & Kliger, D. (2023). Enhancing Fairness Perception–Towards Human-Centred AI and Personalized Explanations Understanding the Factors Influencing Laypeople’s Fairness Perceptions of Algorithmic Decisions. International Journal of Human-Computer Interaction, 39(7), 1455–1482. https://doi.org/10.1080/10447318.2022.2095705
Sima, V., Gheorghe, I. G., Subić, J., & Nancu, D. (2020). Influences of the industry 4.0 revolution on the human capital development and consumer behavior: A systematic review. Sustainability (Switzerland), 12(10). https://doi.org/10.3390/SU12104035
Simon, V., Rabin, N., & Gal, H. C.-B. (2023). Utilizing data driven methods to identify gender bias in LinkedIn profiles. Information Processing and Management, 60(5). https://doi.org/10.1016/j.ipm.2023.103423
Sithambaram, R. A., & Tajudeen, F. P. (2023). Impact of artificial intelligence in human resource management: a qualitative study in the Malaysian context. Asia Pacific Journal of Human Resources, 61(4), 821–844. https://doi.org/10.1111/1744-7941.12356
Soleimani, M., Intezari, A., & Pauleen, D. J. (2022). Mitigating cognitive biases in developing ai-assisted recruitment systems: A knowledge-sharing approach. International Journal of Knowledge Management, 18(1). https://doi.org/10.4018/IJKM.290022
Sommer, L. (2023). The Digital Talent Trap in the SME Sector: Make or Buy Solution Approach. Intellectual Economics, 17(1), 8–29. https://doi.org/10.13165/IE-23-17-1-01
Špadina, H. (2023). Legal aspects of artificial intelligence in the employment process. Stanovnistvo, 61(2), 167–181. https://doi.org/10.59954/stnv.546
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
Tambe, P., Cappelli, P., & Yakubovich, V. (2019). Artificial intelligence in human resources management: Challenges and A path forward. California Management Review, 61(4), 15–42. https://doi.org/10.1177/0008125619867910
Tian, X., Pavur, R., Han, H., & Zhang, L. (2023). A machine learning-based human resources recruitment system for business process management: using LSA, BERT and SVM. Business Process Management Journal, 29(1), 202–222. https://doi.org/10.1108/BPMJ-08-2022-0389
Tilmes, N. (2022). Disability, fairness, and algorithmic bias in AI recruitment. Ethics and Information Technology, 24(2). https://doi.org/10.1007/s10676-022-09633-2
Todolí-Signes, A. (2019). Algorithms, artificial intelligence and automated decisions concerning workers and the risks of discrimination: the necessary collective governance of data protection. Transfer, 25(4), 465–481. https://doi.org/10.1177/1024258919876416
Vaassen, B. (2022). AI, Opacity, and Personal Autonomy. Philosophy and Technology, 35(4). https://doi.org/10.1007/s13347-022-00577-5
van Esch, P., & Black, J. S. (2019). Factors that influence new generation candidates to engage with and complete digital, AI-enabled recruiting. Business Horizons, 62(6), 729–739. https://doi.org/10.1016/j.bushor.2019.07.004
van Esch, P., Black, J. S., & Ferolie, J. (2019). Marketing AI recruitment: The next phase in job application and selection. Computers in Human Behavior, 90, 215–222. https://doi.org/10.1016/j.chb.2018.09.009
Vochozka, M., Horak, J., & Morley, N. (2023). Generative Artificial Intelligence and Voice and Gesture Recognition Technologies, Virtual Team Movement and Behavior Tracking, and Haptic and Biometric Sensors in Virtual Immersive Workspaces. Contemporary Readings in Law and Social Justice, 15(2), 160–178. https://doi.org/10.22381/CRLSJ15220239
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). https://doi.org/10.1016/j.jjimei.2021.100047
Walkowiak, E. (2021). Neurodiversity of the workforce and digital transformation: The case of inclusion of autistic workers at the workplace. Technological Forecasting and Social Change, 168. https://doi.org/10.1016/j.techfore.2021.120739
Wang, X., Haque, M. J., Li, W., Butt, A., Ahmad, H., & Shaikh, H. A. (2021). AI-enabled E-recruitment services make job searching, application submission, and employee selection more interactive. Information Resources Management Journal, 34(4), 48–68. https://doi.org/10.4018/IRMJ.2021100103
Will, P., Krpan, D., & Lordan, G. (2023). People versus machines: introducing the HIRE framework. Artificial Intelligence Review, 56(2), 1071–1100. https://doi.org/10.1007/s10462-022-10193-6
Wuisan, D. S. S., Sunardjo, R. A., Aini, Q., Yusuf, N. A., & Rahardja, U. (2023). Integrating Artificial Intelligence in Human Resource Management: A SmartPLS Approach for Entrepreneurial Success. APTISI Transactions on Technopreneurship, 5(3), 334–345. https://doi.org/10.34306/att.v5i3.355
Yam, J., & Skorburg, J. A. (2021). From human resources to human rights: Impact assessments for hiring algorithms. Ethics and Information Technology, 23(4), 611–623. https://doi.org/10.1007/s10676-021-09599-7
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). https://doi.org/10.1186/s12909-022-03872-z
Yu, G., Cong, W., & Chong, W. (2024). Point and interval estimation: The influence of algorithmic prediction presentation on human-algorithm-integrated decision-making. Journal of Industrial Engineering and Engineering Management, 38(1), 46–59. https://doi.org/10.13587/j.cnki.jieem.2024.01.004
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