The DOI matches its Crossref record; 94 of the 94 references it cites were found in a registry or an index.
Artificial intelligence, robotics, advanced technologies and human resource management: a systematic review
Open accessAbstract
Although academic production in intelligent automation (e.g. artificial intelligence, robotics) has grown rapidly, we still lack a comprehensive understanding of the impacts of the utilization of these technologies in human resource management (HRM) at an organizational (firms) and individual (employees) level. This study therefore aims to systematize the academic inputs on intelligent automation so far and to clarify what are its main contributions to and challenges for HRM. In a systematic search of 13,136 potentially relevant studies published in the top HRM, international business (IB), general management (GM) and information management (IM) journals, we found 45 articles studying artificial intelligence, robotics and other advanced technologies within HRM settings. Results show that intelligent automation technologies constitute a new approach to managing employees and enhancing firm performance, thus offering several opportunities for HRM but also considerable challenges at a technological and ethical level. The impact of these technologies has been identified to concentrate on HRM strategies, namely, job replacement, human-robot/AI collaboration, decision-making and learning opportunities, and HRM activities, namely, recruiting, training and job performance. This study discusses these shifts in detail, along with the main contributions to theory and practice and directions for future research.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“When AI is used correctly, organizations can build their cultures and that strong cultures can help firms use AI more effectively (Vrontis et al., 2022).”
From Exploring the antecedents of AI adoption for effective HRM practices in the Indian pharmaceutical sector (2023) · cites this paper as Vrontis et al., 2022
In the citing paper
“However, AI’s cognitive capabilities differ significantly from those of traditional e-HRM tools.”
From Exploring the antecedents of AI adoption for effective HRM practices in the Indian pharmaceutical sector (2023) · cites this paper as Vrontis et al., 2022
Citations
Cites
Tranfield, D., Denyer, D., & Smart, P. (2003) · British Journal of Management · doi:10.1111/1467-8551.00375 · Cited by 15,386 · cited 3×
“To delineate research patterns and discern avenues for future studies related to intelligent automation in HRM, we conducted a systematic literature review following the suggestions made by Tranfield et al. (2003) as well as Crossan and Apaydin (2010).”
MethodThe future of employment: How susceptible are jobs to computerisation?
Frey, C. B., & Osborne, M. A. (2017) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2016.08.019 · Cited by 8,727 · cited 1×
“Notably, despite the expectations that these advancements will have a dramatic impact on employment (Frey & Osborne, 2017), our findings suggest that we are still years away from wide-ranging consequences on HRM and levels of employment.”
BackgroundArtificial intelligence in service
Huang, M.-H., & Rust, R. T. (2018) · Journal of Service Research · doi:10.1177/1094670517752459 · Cited by 3,978 · cited 3×
“AI concerns, inter alia, information processing, logical reasoning and mathematical skills (Huang & Rust, 2018).”
BackgroundInfluentialA Multi‐Dimensional Framework of Organizational Innovation: A Systematic Review of the Literature
Crossan, M. M., & Apaydın, M. (2009) · Journal of Management Studies · doi:10.1111/j.1467-6486.2009.00880.x · Cited by 3,667 · cited 3×
“To delineate research patterns and discern avenues for future studies related to intelligent automation in HRM, we conducted a systematic literature review following the suggestions made by Tranfield et al. (2003) as well as Crossan and Apaydin (2010).”
MethodAlgorithms at Work: The New Contested Terrain of Control
Kellogg, K. C., Valentine, M. A., & Christin, A. (2020) · Academy of Management Annals · doi:10.5465/annals.2018.0174 · Cited by 2,732 · cited 1×
“Algorithmic technologies can also help employers direct, evaluate and discipline workers (Kellogg et al., 2020).”
BackgroundThe theory of decision making.
Edwards, W. (1954) · Psychological Bulletin · doi:10.1037/h0053870 · Cited by 2,710 · cited 1×
“First, building on the theory of decision-making (Edwards, 1954) as well as on recent research that has analyzed how data allow HR managers to better informed about employees (Garcia-Arroyo & Osca, 2019), we found that AI algorithms and expert systems facilitate HR processes and allow better…”
Methodvan Doorn, J., Mende, M., Noble, S. M., Hulland, J., Ostrom, A. L., Grewal, D., & Petersen, J. A. (2017) · Journal of Service Research · doi:10.1177/1094670516679272 · Cited by 1,344 · cited 2×
“Van Doorn et al. (2017) argue that situations defined by strong needs for empathy, in which developing original and creative solutions is required or that necessitate high levels of social intelligence are not at high risk for automation and replacement.”
BackgroundLoebbecke, C., & Picot, A. (2015) · The Journal of Strategic Information Systems · doi:10.1016/j.jsis.2015.08.002 · Cited by 1,317 · cited 2×
“In fact, our study responds to several calls to synthesise the current state of knowledge beyond the boundaries of individual academic disciplines in reference to intelligent automation (e.g. AI, machine learning, digitization) and work (Loebbecke & Picot, 2015; Markus, 2015).”
BackgroundLuo, X., Tong, S., Fang, Z., & Qu, Z. (2019) · Marketing Science · doi:10.1287/mksc.2019.1192 · Cited by 1,262 · cited 1×
“…developments, however, are increasingly providing alternatives to human resources in functions traditionally requiring human interaction and communication (Malik et al., 2019; Luo et al., 2019), thereby changing both the organizational structures and the nature of work (Colbert et al., 2016).”
BackgroundInformation Technology and the Changing Fabric of Organization
Zammuto, R. F., Griffith, T. L., Majchrzak, A., Dougherty, D. J., & Faraj, S. A. (2007) · Organization Science · doi:10.1287/orsc.1070.0307 · Cited by 1,213 · cited 1×
“Zammuto et al. (2007) describe five affordances – visualizing entire work processes, real-time/flexible product and service innovation, virtual collaboration, mass collaboration, and simulation/synthetic reality – that can result from this interplay.”
Background
Cited by
Sorted by citations
Items 601–700 of 1,135
Uncertainty in the Age of Digital Transformation
Matsunaga, M. (2024) · Future of business and finance · doi:10.1007/978-981-99-8409-1_2 · Cited by 5
Automated Sales Management System Empowered with Artificial Intelligence
Alshurideh, M. T., Nuseir, M. T., Kurdi, B. H. A., Alzoubi, H. M., Hamadneh, S., & AlHamad, A. (2024) · Studies in big data · doi:10.1007/978-3-031-31801-6_14 · Cited by 3
Generation Z’s expectations towards the employers
(2022) · Scientific Papers of Silesian University of Technology Organization and Management Series · doi:10.29119/1641-3466.2022.167.15 · Cited by 3
“Solutions such as robots, artificial intelligence, advanced technologies are used (Vrontis et al., 2021).”
Prediction of Risks Using Artificial Intelligence in Digitalized Human Resource Management
Shetty, K. S., Nakkeeran, I., Ganesh, K. S., Bansa, K., Sundararajan, S., & Lourens, M. (2023) · International Conference on Computation, Automation and Knowledge Management (ICCAKM) · doi:10.1109/iccakm58659.2023.10449648 · Cited by 5
“Digitalization in HRM has witnessed an exponential surge in recent years, with organizations leveraging technology to streamline recruitment, employee engagement, performance evaluation, and talent management processes [2].”
BackgroundAlsheikh, G. A. A., Al-Ghalabi, R. R., Altarawneh, A. S., & Al-Shamaileh, L. R. (2024) · Heritage and Sustainable Development · doi:10.37868/hsd.v6i1.490 · Cited by 3
“Training, performance management, and compensation and benefits administration are three areas where businesses are increasingly turning to innovative technology [4].”
BackgroundAlnasser, E. M., Alkhozaim, S. M., Alshiha, A. A., & Al‐Romeedy, B. S. (2024) · Advances in hospitality, tourism and the services industry (AHTSI) book series · doi:10.4018/979-8-3693-6755-1.ch022 · Cited by 3
Human Intelligent-Things Interaction Application Using 6G and Deep Edge Learning
Kedwan, F., & Rahman, M. A. (2024) · Journal on internet of things · doi:10.32604/jiot.2024.052325 · Cited by 3
“Advanced technologies, such as the Internet of Things (IoT), Artificial Intelligence (AI), and 6G network connectivity, have become an integral part of the civilized modern lifestyle and how businesses are run [1].”
Natural Language Processing Technology Based on Artificial Intelligence in Software Testing
Liu, Y. (2024) · International Conference on Artificial Intelligence and Computer Information Technology (AICIT) · doi:10.1109/aicit62434.2024.10730603 · Cited by 3
“This can enable the testing team to focus more on the development of testing strategies and in-depth analysis of software quality [13-14].”
BackgroundRevolutionizing HRM: A Comprehensive Survey on AI-Integrated Motivational Enhancement through KPIs
Akshatha, P. S., Shankar, P., Danoosh, R. S., Basu, S., Rohit, V. S., & Bindu, S. (2024) · International Conference on Computing, Communication and Networking Technologies (ICCCNT) · doi:10.1109/icccnt61001.2024.10725850 · Cited by 3
Arora, M., Goel, R., & Singla, J. (2024) · Emerald Group Publishing Limited eBooks · doi:10.1108/978-1-83608-634-520241014 · Cited by 3
The Evolution of Global Smart Systems and Future Technologies in Human Resource Management Systems
Ghosh, V., Mukherjee, R., Liu, Y., Upadhyay, S., & Puniyani, A. R. (2025) · Journal of Global Information Management · doi:10.4018/jgim.366390 · Cited by 7
Assessing employee readiness for AI in HR: A banking industry perspective
Sharma, P., Saluja, (. R., & Sharma, V. (2025) · AIP conference proceedings · doi:10.1063/5.0248354 · Cited by 3
Exploring the Role of AI in Career Access Through a Social Justice Lens
Buchanan, R. (2025) · Nordic Journal of Transitions Careers and Guidance · doi:10.16993/njtcg.77 · Cited by 4
Szőke-Milinte, E. (2023) · Mester és Tanítvány · doi:10.61178/mt.2023.i.1.3 · Cited by 4
Impact of HR Analytics on the Productivity of the HR Department
Dhole, V., Yadav, P. V., Phule, P. N., Kollimath, U. S., & Dharmadhikari, S. (2023) · International Conference on Emerging Smart Technologies and Applications (eSmarTA) · doi:10.1109/esmarta59349.2023.10293388 · Cited by 3
Özdemir, İ. (2025) · OPUS Toplum Araştırmaları Dergisi · doi:10.26466/opusjsr.1715067 · Cited by 3
Navigating the intellectual terrain of AI–HRM integration: a bibliometric review (2000–2024)
Usman, M. B., Naveed, S., Nazeer, S., Siddique, N., & Rana, A. H. (2026) · Journal of Organizational Effectiveness People and Performance · doi:10.1108/joepp-08-2025-0670 · Cited by 7
Artificial intelligence and its impact on corporate social responsibility
Vásquez, C. Y. P., & Rodríguez, G. G. (2024) · Perspectiva austral. · doi:10.56294/pa202532 · Cited by 3
Sibarani, I. J., & GUNAWAN, F. E. (2024) · IEEE International Conference on Computing, Engineering and Design (ICCED) · doi:10.1109/icced64257.2024.10983133 · Cited by 4
“Unlike previous experiences, there was only repair-action response to deal with employee attrition, but now indeed the possibility of taking preventive-action by predicting the possibility of employee attrition through advanced AI [13], [14].”
Shi, L. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.933507 · Cited by 3
“According to comments from practitioners, HR is still struggling to develop strategic management proficiency in areas like costing and analysis of data, program and project management, budgeting acumen, and cross-functional competence (Vrontis et al., 2022).”
BackgroundHow Can Artificial Intelligence Improve Organizational Psychology?: A Systematic Review
Navarro, C.-G. (2023) · doi:10.53902/jpssr.2023.03.000537 · Cited by 2
Ingram, T. (2024) · International May Conference on Strategic Management (IMCSM) · doi:10.5937/imcsm24001i · Cited by 3
Service Oikos as a complex self-perpetuating system: a bibliometric study of service ecosystems
Nazemi, A., Zamanfashami, P. R., Foroudi, P., Haghighinasab, M., Seyyedamiri, N., & Mehrjardy, M. Z. (2024) · Journal of strategy and management · doi:10.1108/jsma-03-2023-0044 · Cited by 2
Transhumanist Approaches in HR
Sharma, B., & Sharma, P. (2024) · Advances in human resources management and organizational development book series · doi:10.4018/979-8-3693-8855-6.ch012 · Cited by 2
Application of Blockchain in Human Resources Management
Monteiro, A., Casais, B., & Ferreira, A. P. (2024) · Lecture notes in business information processing · doi:10.1007/978-3-031-76368-7_4 · Cited by 2
Artificial Intelligence in Human Resource Management Through a Bibliometric Lens
Anayat, S. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3693-6507-6.ch007 · Cited by 2
AI Tools in Recruitment and Selection: A Comparative Analysis Across Industries
Kalra, B., & Dikshit, S. (2025) · Emerald Group Publishing Limited eBooks · doi:10.1108/978-1-83708-808-920251010 · Cited by 2
System dynamics model for evaluating ESG-based strategies to reduce turnover in manufacturing
Lopez-Sanchez, E., Ramírez–Nafarrate, A., Zavala, A., Elizondo-Noriega, A., & Corzo, R. F. M. (2025) · European Business Review · doi:10.1108/ebr-01-2025-0029 · Cited by 5
Peláez, A., Clemente‐Almendros, J. A., Saldaña‐Larrondo, D. E., & Erasso‐Arango, N. (2025) · Canadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l Administration · doi:10.1002/cjas.70030 · Cited by 2
Schreibelmayr, S., & Mara, M. (2025) · Computers in Human Behavior Artificial Humans · doi:10.1016/j.chbah.2025.100235 · Cited by 3
Critical Review on Brain–Computer Interfaces (BCIs) for Effective Human–Machine Interactions (HMIs)
Bi, Z., Gad, A., Younis, N., & Abu-Mulaweh, H. I. (2025) · Journal of Engineering · doi:10.1155/je/6682954 · Cited by 2
AI in human resources: efficiency, ethics, and emerging challenges
Majumder, S., Salman, S., & Dey, N. (2025) · AI and Ethics · doi:10.1007/s43681-025-00862-x · Cited by 2
Lorenzo, G., Meliá, S., Lorenzo-Lledó, ., Gadzhimusieva, D., & Cerdán-Chacón, A. (2025) · Interactive Technology and Smart Education · doi:10.1108/itse-04-2025-0081 · Cited by 4
Future of MSMEs With Digitally Matured Vision
Singh, R., Sharma, G., Dixit, A., & Hasan, A. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-8142-8.ch002 · Cited by 2
THE ROLE OF AI IN MANAGING PERFORMING ARTS INSTITUTIONS
Pathak, A., Bhilare, D. M., Kalra, H., Gupta, M., S.Jancy, & Rathore, A. (2025) · ShodhKosh Journal of Visual and Performing Arts · doi:10.29121/shodhkosh.v6.i1s.2025.6621 · Cited by 2
EVALUATING THE IMPACT OF AI ON DANCE PEDAGOGY
Swain, M. K., Simonthomas, S., Sharma, M., Singh, P., Kulkarni, N., & Dev, R. (2025) · ShodhKosh Journal of Visual and Performing Arts · doi:10.29121/shodhkosh.v6.i5s.2025.6912 · Cited by 2
Bayo‐Moriones, A., Erro‐Garcés, A., & Lera‐López, F. (2025) · Personnel Review · doi:10.1108/pr-06-2024-0561 · Cited by 2
The Impact of Artificial Intelligence on Job Performance: A Systematic Review
Yusuph, M. L., Kisumbe, L. A., & Kasubi, J. W. (2026) · African Journal of Empirical Research · doi:10.51867/ajernet.7.1.11 · Cited by 4
Li, Y., He, J., & Sun, Y. (2026) · Behaviour and Information Technology · doi:10.1080/0144929x.2026.2619107 · Cited by 2
Wei, X., Tan, W., & Tian, R. (2026) · Information Technology and People · doi:10.1108/itp-01-2025-0020 · Cited by 2
Service Robot Failures’ Effect on Employees and Customers in Hospitality
Gong, T. (2026) · Cornell Hospitality Quarterly · doi:10.1177/19389655261426343 · Cited by 3
“…linking employee behavior during robotic service failures to customer outcomes, the study highlights the strategic importance of managing employee–robot dynamics not only for work-force well-being but also for guest satisfaction and operational success (Ivanov et al., 2020; Vrontis et al., 2021).”
Zheng, J., Cooke, F. L., Jasimuddin, S. M., & Zhang, Z. (2026) · Asia Pacific Journal of Management · doi:10.1007/s10490-026-10125-w · Cited by 2
Energy security in Central and Eastern Europe: the nuclear policy dilemma
Morales, L., Zherdeva, A., Zreık, M., & Alotaibi, T. A. N. M. S. (2026) · Journal of Contemporary Central and Eastern Europe · doi:10.1080/25739638.2026.2676684 · Cited by 2
Generative AI’s Impact on Individuals and Organizations: An Analysis Based on Human-AI Collaboration
Latto, C., Leyer, M., Khac, L. T. D., Mezger, M. F., Tate, M., & Richter, A. (2026) · Group Decision and Negotiation · doi:10.1007/s10726-026-10007-y · Cited by 3
A Genetic Algorithm Model for Human Resource Management Optimization in the Internet Marketing Era
Li, Y., & Linna, W. (2022) · Mathematical Problems in Engineering · doi:10.1155/2022/6931386 · Cited by 2
“Of the above-given tasks, 3 has the highest priority, so A[3] 3.”
BackgroundMethodInfluentialKyriakidou, N., Trem, K., Ogbemudia, J., & Mahtab, N. (2022) · Palgrave studies in cross-disciplinary business research, in association with EuroMed Academy of Business · doi:10.1007/978-3-031-07765-4_8 · Cited by 2
Application of Machine Learning Algorithms in Online Marketing
Srivastava, A. V., Umrao, M. L. S., & Kumar, M. D. (2023) · International Journal for Research in Applied Science and Engineering Technology · doi:10.22214/ijraset.2023.49585 · Cited by 3
The Impact of Artificial Intelligence on Employee and Employer Risks
Kurochkina, A. A., Lukina, O. V., Degtereva, V., & Bikezina, T. V. (2023) · Lecture notes in networks and systems · doi:10.1007/978-3-031-32719-3_3 · Cited by 2
Kubryak, O. V., Kovalchuk, S. V., & Bagdasaryan, N. G. (2023) · Philosophies · doi:10.3390/philosophies8050075 · Cited by 2
Luna, P. B. (2023) · Revista CEA · doi:10.22430/24223182.2777 · Cited by 2
“However, despite the increasing presence of AI in HRM, it remains true that although many HR managers recognize the potentialities these tools offer, they also acknowledge that their use often lacks a clear objective or fails to align with the organization’s strategy (Vrontis et al., 2022).”
BackgroundStein, J., Messingschlager, T. V., & Hutmacher, F. (2023) · Springer eBooks · doi:10.1007/978-3-662-66608-1_17 · Cited by 3
PETRESCU, G.-M., ȘTEF, A. L., Cîmpan, I., Crișan, E. L., Salanță, I.-I., & SRL, P. I. S. (2023) · Annals of Faculty of Economics · doi:10.47535/1991auoes32(1)058 · Cited by 2
The Impact of Artificial Intelligence on Human Resource Practices
-, T. S. (2024) · International Journal For Multidisciplinary Research · doi:10.36948/ijfmr.2024.v06i02.17040 · Cited by 2
“…overall productivity by freeing up resources, there is still room for improvement in this area (Meshram, 2023), Organizations lack a thorough grasp of these advanced technologies and the effects of using them in HRM at both an organizational and individual employee level (Vrontis et al., 2021).”
BackgroundSaloni, S., Gupta, N., Kamalpreet, Ghosh, M., & Agarwal, A. K. (2023) · International Conference on Artificial Intelligence for Innovations in Healthcare Industries (ICAIIHI) · doi:10.1109/icaiihi57871.2023.10489804 · Cited by 3
Revisiting Artificial Intelligence in HRM
Rastogi, S., & Sharma, P. (2022) · SJCC Management Research Review · doi:10.35737/sjccmrr/v12/i2/2022/177 · Cited by 2
Looking forward to the debate of future business towards digital transformation
Mboungou, M. S. (2024) · i-manager’s Journal on Management · doi:10.26634/jmgt.18.3.20455 · Cited by 2
Strategies To Improve Teachers' Pedagogical Skills in Science Learning
Juanda, A., Wahyudin, D., & Ansori, Y. Z. (2024) · Asian Journal of Engineering Social and Health · doi:10.46799/ajesh.v3i4.291 · Cited by 2
“A nation is advanced if it contains quality human resources (Vrontis et al., 2022).”
BackgroundManagement and Organization of Human Resources in Science and Technology of the Republic of Serbia
Milutinović, O., Anđelić, S., Garabinović, D., & Bajac, M. (2024) · International Journal of Cognitive Research in Science Engineering and Education · doi:10.23947/2334-8496-2024-12-1-89-101 · Cited by 2
Enhancing Capacity Building Prior to Appointment as Heads of Departments in Universities
Dogbatse, D. A. (2024) · Organization and Human Capital Development · doi:10.31098/orcadev.v3i1.1944 · Cited by 2
“…(Peccei & Van De Voorde, 2019; Hamadamin & Atan, 2019), Public Policy and Development (Werdhiastutie et al., 2020), Business and Management (Werdhiastutie et al., 2020), Environmental Economics (Amrutha & Geetha, 2020; Vrontis et al., 2022), and Innovation and Technology (Donald et al., 2019).”
BackgroundCurrent and Future Research Directions
Das, H. S. (2024) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3693-2399-1.ch008 · Cited by 2
Critical Analysis of the Ethical Consequences of AI Adoption in Human Resource Management
Joseph, N. P., Nassa, V. K., Krishna, M. H., Sobti, R., Revathi, V., & Sahai, A. (2024) · International Conference on Communication, Computer Sciences and Engineering (IC3SE) · doi:10.1109/ic3se62002.2024.10593640 · Cited by 2
“According to the research, intelligent automation technologies offer a fresh approach to managing employees and enhancing organisational performance, even if they also pose serious technological and regulatory challenges for HRM [3].”
Monitoring of Smart Human Resource (HR) Using Artificial Intelligence and Internet of Things
Bhatt, A., Singh, T., Pandey, S., Chauhan, A. S., Kumar, R., & Sunil, G. (2024) · International Conference on Sentiment Analysis and Deep Learning (ICSADL) · doi:10.1109/icsadl61749.2024.00105 · Cited by 2
Artificial Intelligence and Robotic Adoption by Customers in the Global Hotel Sector
Ndhlovu, E., & Thwala, K. C. (2024) · Springer eBooks · doi:10.1007/978-3-031-63077-4_2 · Cited by 2
DİJİTAL DÖNÜŞÜM VE İNSAN KAYNAKLARI YÖNETİMİ: ULUSLARARASI YAZININ BİBLİYOMETRİK ANALİZİ
Tanış, Z. S. (2024) · Yönetim Bilimleri Dergisi · doi:10.35408/comuybd.1514730 · Cited by 2
Managing Workforce Diversity with AI-Based HRM
Evangelista, V. C., & Barone, L. (2024) · Emerald Group Publishing Limited eBooks · doi:10.1108/978-1-83549-284-020241011 · Cited by 2
Application of Artificial Intelligence Technology in the Field of Driving New Energy Fire Trucks
Jiang, C., Nan, Q., & Wang, X. (2024) · International Conference on Artificial Intelligence and Autonomous Robot Systems (AIARS) · doi:10.1109/aiars63200.2024.00172 · Cited by 2
Zhou, Z., Xiang, S., & Xie, Q. (2025) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2025.1451944 · Cited by 3
Advancing robotic systems with Ensemble and Modular Deep Learning: research idea and framework
Artiushenko, V., Reider, R., Reggelin, T., & Lang, S. (2025) · Procedia Computer Science · doi:10.1016/j.procs.2025.01.315 · Cited by 2
Yang, P., & Li, J. (2025) · Journal of Computational Methods in Sciences and Engineering · doi:10.1177/14727978251318814 · Cited by 6
Antecedents of Enhancing Diversity and Inclusion with AI Tools—An HR Perspective
Zheng, C. S.-M., & Wilkens, U. (2025) · Springer eBooks · doi:10.1007/978-981-96-2516-1_12 · Cited by 2
Çeliker, N., & Gürsoy, S. (2025) · İşletme Bilimi Dergisi · doi:10.22139/jobs.1594699 · Cited by 3
Vuyyuru, S. R. (2025) · International Journal of Innovative Research in Engineering & Multidisciplinary Physical Sciences · doi:10.37082/ijirmps.v13.i2.232405 · Cited by 2
Chen, T., Wang, R., & Li, X. (2025) · IEEE Instrumentation & Measurement Magazine · doi:10.1109/mim.2025.11021357 · Cited by 2
“In recent years, with the development of intelligent robots [1]–[3], medical testing devices [4]–[6]. electronic skin [7]–[9], and wearable devices [10]–[12], the core technology of a flexible pressure sensor has become a hotspot for the majority of scholars and researchers due to its ability to be…”
Digital solutions for risk management in sustainable development conditions of business ecosystems
Hniezdovskyi, O., Домашенко, Д., DOMASHENKO, S., MOROZOV, D., & Shylo, S. (2025) · Applied Computer Science · doi:10.35784/acs_6935 · Cited by 2
Leveraging AI for Disruptive Green Human Resource Management
Carôla, M., Rodrigues, R., & Figueiredo, P. C. N. (2025) · IGI Global eBooks · doi:10.4018/979-8-3693-4030-1.ch016 · Cited by 2
Okul Yöneticilerinin İş Süreçlerinde Yapay Zekâ Kullanımına İlişkin Görüşleri: Ankara İli Örneği
Yiğittekin, M., & Köybaşı, F. (2025) · MANAS Sosyal Araştırmalar Dergisi · doi:10.33206/mjss.1638526 · Cited by 4
AI-Driven Talent Acquisition: Predicting Employee Success in Indian Public Sector Recruitment
Karthik, M., Malhotra, P., Rautrao, R. R., Manikandan, G., Indrapriya, M., & Tiwari, M. (2025) · International Conference on Intelligent Computing and Knowledge Extraction (ICICKE) · doi:10.1109/icicke65317.2025.11136259 · Cited by 2
“It explores how AI-based technologies transform the recruiting process candidate assessment and employment procedures of organizations [14].”
Eftimov, L. (2023) · DIEM Dubrovnik International Economic Meeting · doi:10.17818/diem/2023/1.7 · Cited by 1
“When it comes to performance management, FIR-associated technologies can analyze employee data, performance ratings, and professional history and present top performers, head count, and transactions for benefits and rewards with the use of specialized chatbots (Vrontis et al., 2022).”
BackgroundSiu, K.-M., Chan, K., & Im, S. (2022) · IEEE International Conference on Computer and Communication Engineering Technology (CCET) · doi:10.1109/ccet55412.2022.9906345 · Cited by 2
“For instance, human resource management can gain a competitive advantage by using IT to improve the efficiency of human resource operations and rapidly increase production [11].”
BackgroundShaping AI Transformation: Digital Competencies and Augmentation Strategies of HRD Professionals
Spirgi, J., Guggemos, J., & Seufert, S. (2022) · Advances in analytics for learning and teaching · doi:10.1007/978-3-031-14489-9_3 · Cited by 2
The Task based Human Resource Control and Management Model using AI based Deep Learning Model
Gildhiyal, S., & Prasad, R. (2023) · International Conference on Integrated Circuits and Communication Systems (ICICACS) · doi:10.1109/icicacs57338.2023.10099558 · Cited by 2
“Chief among such challenges is bridging the gap between capacity and demand [23].”
BackgroundRisk prediction of enterprise human resource management based on deep learning
Ding, M., & Wu, H. (2023) · Human Systems Management · doi:10.3233/hsm-230064 · Cited by 2
An Investigation into the Left Side of Green Human Resource Management
Ampofo, E. T., & Karatepe, O. M. (2024) · Springer eBooks · doi:10.1007/978-981-99-7104-6_5 · Cited by 2
Technological Trends in Human Resource Management—Innovation Analysis
Vugec, D. S., Pivar, J., & Stjepić, A.-M. (2024) · Management and industrial engineering · doi:10.1007/978-3-031-52811-8_1 · Cited by 2
Kumar, P., Radwan, N., Vij, M., & Vij, A. (2024) · International Conference on Cyber Resilience (ICCR) · doi:10.1109/iccr61006.2024.10532969 · Cited by 2
“For instance, the studies done by [1] clearly elaborate on how robotic system starting from automated check-in kiosks to a robotic concierge imply a more personalized yet efficient service delivery.”
BackgroundControl and Design of Dancing Robot based on STM32
Li, Y., & Wang, Y. (2023) · Journal of Electrical Engineering and Automation · doi:10.36548/jeea.2023.1.003 · Cited by 2
Chakraborty, S. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4149595 · Cited by 2
Alnefaie, A., Kang, K., & Sohaib, O. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4657676 · Cited by 4
Dedication of Machine Learning for Trend of Digital HRM
Dasmadi, D. (2023) · Jurnal Penelitian Pendidikan IPA · doi:10.29303/jppipa.v9ispecialissue.5804 · Cited by 2
Bridging the Divide: A Systems Thinking Approach to Inclusivity in AI Development and EducationPreprint
Sarkar, A. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5097669 · Cited by 4
Giudice, M. D., Pereira, V., Malhotra, A., & Scuotto, V. (2026) · Technology in Society · doi:10.1016/j.techsoc.2026.103476 · Cited by 2
Self-citationIs the Idea of Human Replacement too Far-Fetched?
García-Contreras, R., Muñoz-Chávez, J. P., & Muñoz-Chávez, R. L. (2022) · Advances in computational intelligence and robotics book series · doi:10.4018/978-1-6684-5624-8.ch005 · Cited by 1
Robotic-based takraw blocker technique skill tool: Development and students’ perceptions
Arwandi, J., Bais, S., Soniawan, V., Sari, S. N., Padli, P., & Ridwan, M. (2022) · Cypriot Journal of Educational Sciences · doi:10.18844/cjes.v17i10.8248 · Cited by 1
“Artificial intelligence plays an important role in the world of robotics because it allows robots to move automatically with just simple commands (Raj & Seamans, 2019; Siau & Wang, 2018; Vrontis et al., 2022).”
BackgroundCOVID-19 Salgını, Belirsizlikler ve Teknoloji Çağında İnsan Kaynakları Yönetimi
Başaran, A., & Gündoğdu, M. (2022) · JOURNAL OF SOCIAL HUMANITIES AND ADMINISTRATIVE SCIENCES · doi:10.29228/joshas.64534 · Cited by 1
Bowne, A., McEvoy, L., Gupta, D., Brown, C., Gadepally, V. N., & Rezig, E. K. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-23905-2_2 · Cited by 1
FACTORS THAT INFLUENCE ADOPTION OF AI IN ORGANIZATIONS
Tasić, A., Ćulibrk, J., Medić, N., Jokanović, B., & Vidicki, P. (2023) · International Scientific Conference on Industrial Systems (IS) · doi:10.24867/is-2023-t1.1-8_05041 · Cited by 1
Interplay of Sports and Education: A Review of Dual Career Literature
Hassan, Y., Mukherjee, S., Carlsson‐Wall, M., Njavro, M., & Schmidt, S. L. (2023) · Dykinson eBooks · doi:10.14679/2137 · Cited by 1
Tapping into AI Advancement: Strategies for Boosting Productivity and Performance
Rastogi, S., & Pandita, D. (2024) · ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS) · doi:10.1109/icetsis61505.2024.10459385 · Cited by 1
“Advancements in artificial intelligence have the potential to transform the fundamental nature of work and provide a significant risk to jobs for humans [1].”
BackgroundJiang, X. H. (2024) · International Journal of High Speed Electronics and Systems · doi:10.1142/s0129156424400111 · Cited by 1
The Effect of Artificial Intelligence Awareness on Job Performance
Toumia, O., & Zouari, F. (2024) · Advances in marketing, customer relationship management, and e-services book series · doi:10.4018/979-8-3693-2153-9.ch005 · Cited by 1
Metadata
- Authors
- Vrontis, D., Christofi, M., Pereira, V., Tarba, S., Makrides, A., & Trichina, E.
- Affiliations
- University of Nicosia (CY)
- NEOMA Business School (FR)
- University of Birmingham (GB)
- Corresponding author
- Christofi, Michael
- Venue
- The International Journal of Human Resource Management
- Publisher
- Informa UK Limited
- Published
- 2021-02-12
- Volume
- 33
- Issue
- 6
- Pages
- 1237-1266
- ISSN
- 0958-5192 (ISSN-L)
- 1466-4399
- OpenAlex
- W3130894836
- Cited by
- 1,134
- References
- 94
- Citations by year
- 2026: 233 · 2025: 245 · 2024: 301 · 2023: 229 · 2022: 97 · 2021: 29
- FWCI
- 27.96
- Type
- journal article
- Language
- en
- Open access
- green
- api.elsevier.com
- Licence
- cc-by-nc-nd
- Locations
- The International Journal of Human Resource Management (publishedVersion)
- University of Birmingham Research Portal (University of Birmingham) (publishedVersion)
- Ktisis at Cyprus University of Technology (Cyprus University of Technology) (submittedVersion, cc-by-nc-nd)
- Topics
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › AI and HR Technologies
- Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Employer Branding and e-HRM
- Keywords
- artificial intelligence, robotics, intelligent automation, human resource management, human-robot collaboration, job replacement, recruitment, employee training, employee performance, decision-making, ethical considerations, firm performance, high technology
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review