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.
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When AI is used correctly, organizations can build their cultures and strong cultures can help firms use AI more effectively.
“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
AI's cognitive capabilities differ significantly from those of traditional e-HRM tools.
“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
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Wall, T. D., Jackson, P. R., & Davids, K. (1992) · Journal of Applied Psychology · doi:10.1037/0021-9010.77.3.353 · Cited by 159 · cited 1× · see citing works
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“€ Otting and Maier (2018) emphasize the importance of procedural justice in decision situations because it enhances beneficial employee attitudes and behavior regardless of whether these decisions are taken by human leaders or AI systems.”
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Self-citationInternational Market Entry Strategies: Relational, Digital, and Hybrid Approaches
Watson, G. F., Weaven, S. K., Perkins, H., Sardana, D., & Palmatier, R. W. (2017) · Journal of International Marketing · doi:10.1509/jim.17.0034 · Cited by 148 · cited 2× · see citing works
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“Ferraris, Erhardt, and Bresciani (2019) suggest that the technological knowledge required could be acquired through numerous flexible alliances with various government and public actors, research centers and universities.”
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“AI algorithms in the realm of jour-nalism beyond the initial programming can also assist journalists in basic works, allowing them to focus on more investigative reporting, generating at the same time news faster, at a larger scale and with less errors (Jung et al., 2017).”
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“Specifically, the introduction of AI applications in HRM allows HR employees to conduct background checks of job applications and develop compensation packages for certain positions (Cooke et al., 2019).”
BackgroundMethodInfluentialBig data contributions to human resource management: a systematic review
García-Arroyo, J. A., & Osca, A. (2019) · International journal of human resources management · doi:10.1080/09585192.2019.1674357 · Cited by 137 · cited 3× · see citing works
“…latest HRM developments due to diverse technological advancements are available (Bondarouk & Brewster, 2016; Bondarouk et al., 2017; Fleming, 2019; Garcia-Arroyo & Osca, 2019; Stone et al., 2015), but have partially analyzed technology-enabled HRM and focused on some aspects of technology and HRM.”
BackgroundMethodAbraham, M., Niessen, C., Schnabel, C., Lorek, K., Grimm, V., Möslein, K. M., & Wrede, M. (2019) · Human Resource Management Journal · doi:10.1111/1748-8583.12250 · Cited by 127 · cited 1× · see citing works
“…and other novel technologies offer several opportunities to improve upon and reduce the cost of HRM functions including, among others, the evaluation of job applicants (Bondarouk et al., 2017; Cooke et al., 2019) and employee performance appraisals (Abraham et al., 2019; Parry & Tyson, 2011).”
BackgroundStrohmeier, S. (2018) · The International Journal of Human Resource Management · doi:10.1080/09585192.2018.1443963 · Cited by 115 · cited 2× · see citing works
“In order to gain a deep and comprehensive picture of the topic, we chose not to set any timeframe restriction to the data collection (Andresen & Bergdolt, 2017) and thus included work published before the writing of this paper (January 2020).”
MethodMarler, J. H., Fisher, S. L., & Ke, W. (2009) · Personnel Psychology · doi:10.1111/j.1744-6570.2009.01140.x · Cited by 114 · cited 1× · see citing works
“Employee self-service (ESS) technology allows employees to manage their own data rather than rely on HR professionals and register for training with the objective of effi-ciency-related gains (Marler et al., 2009).”
BackgroundThe Double-Edged Sword of Big Data in Organizational and Management Research
Wenzel, R., & Quaquebeke, N. V. (2017) · Organizational Research Methods · doi:10.1177/1094428117718627 · Cited by 104 · cited 1× · see citing works
“For example, Wenzel and Van Quaquebeke (2018) review potential opportunities and risks in organizational research based on the central characteristics of Big Data and Giacumo and Breman (2016) analyze the utilization of Big Data in workplace learning.”
BackgroundGlobal Innovation Networks – Organizations and People
Cano-Kollmann, M. F., Hannigan, T. J., & Mudambi, R. (2017) · Journal of International Management · doi:10.1016/j.intman.2017.09.008 · Cited by 104 · see citing works
Data Analytics in Human Resources: A Case Study and Critical Review
King, K. G. (2016) · Human Resource Development Review · doi:10.1177/1534484316675818 · Cited by 98 · see citing works
Partners of Humans: A Realistic Assessment of the Role of Robots in the Foreseeable Future
Aleksander, I. (2017) · Journal of Information Technology · doi:10.1057/s41265-016-0032-4 · Cited by 97 · cited 1× · see citing works
“In this regard, more skilled and educated employees are needed in the era of human and robots symbiosis and collaboration to be benefited from possible opportunities and reverse potential threats (Aleksander, 2017).”
BackgroundBuckley, P., Minette, K. A., Joy, D. R., & Michaels, J. (2004) · Human Resource Management · doi:10.1002/hrm.20017 · Cited by 88 · cited 1× · see citing works
“Consistent with this view, several studies highlight the ways in which computer-aided design, manufacturing and process planning are automating many tasks and enhancing effectiveness and speed (Buckley et al., 2004; Park, 2018).”
ResultOrganizational Learning and the Technology of Foolishness: The Case of Virtual Worlds at IBM
Dodgson, M., Gann, D., & Phillips, N. (2013) · Organization Science · doi:10.1287/orsc.1120.0807 · Cited by 86 · cited 1× · see citing works
“Although they have emerged from the computer games industry, they are increasingly being used to enhance interpersonal and organizational interaction and facilitate organizational learning (Dodgson et al., 2013).”
Employee perceptions on the implementation of robotic manufacturing technology.
Chao, G. T., & Kozlowski, S. W. J. (1986) · Journal of Applied Psychology · doi:10.1037/0021-9010.71.1.70 · Cited by 77 · cited 3× · see citing works
“Robotics can support human employees by offering them opportunities for more technical positions that are either created or enhanced by robotic technologies (Chao & Kozlowski, 1986).”
BackgroundInfluentialCooke, F. L., Liu, M., Liu, L. A., & Chen, C. C. (2019) · Human Resource Management · doi:10.1002/hrm.21986 · Cited by 74 · cited 5× · see citing works
“Specifically, the introduction of AI applications in HRM allows HR employees to conduct background checks of job applications and develop compensation packages for certain positions (Cooke et al., 2019).”
BackgroundMethodInfluentialArtificial Intelligence in HRM: An Experimental Study of an Expert System
LAWLER, J. J., & Elliot, R. (1996) · Journal of Management · doi:10.1177/014920639602200104 · Cited by 74 · see citing works
International Management Research: Investigating its Recent Diffusion in Top Management Journals
Pisani, N. (2008) · Journal of Management · doi:10.1177/0149206308321552 · Cited by 73 · cited 2× · see citing works
“For this part of our study, we have used the same lists adopted by Pisani (2009), Pisani et al. (2017), Hewett et al. (2018) and Gaur and Kumar (2018).”
MethodCooke, F. L., Veen, A., & Wood, G. (2016) · The International Journal of Human Resource Management · doi:10.1080/09585192.2016.1245671 · Cited by 73 · cited 3× · see citing works
“The HRM-related keywords were drawn from previous systematic reviews within the area of HRM (e.g. Cooke et al., 2017; De Kock et al., 2020; Voegtlin & Greenwood, 2016).”
BackgroundMethodNew Games, New Rules, New Scoreboards: The Potential Consequences of Big Data
Markus, M. L. (2015) · Journal of Information Technology · doi:10.1057/jit.2014.28 · Cited by 72 · cited 1× · see citing works
“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).”
BackgroundKnowledge acquisition via internet-enabled platforms
Glavas, C., Mathews, S. W., & Russell‐Bennett, R. (2018) · International Marketing Review · doi:10.1108/imr-02-2017-0041 · Cited by 66 · cited 1× · see citing works
“Dealing with queries and customer support internationally, they may enable organizations to operate 24 h a day, without engaging human employees as representatives at physical locations (Glavas et al., 2019).”
BackgroundSimilarity effects in online training: Effects with computerized trainer agents
Behrend, T. S., & Thompson, L. F. (2011) · Computers in Human Behavior · doi:10.1016/j.chb.2010.12.016 · Cited by 65 · cited 3× · see citing works
“Artificially smart technologies complement human employees ’ interactions, enhance problem-solving for effectiveness, provide training, give feedback and support human employees (Behrend & Thompson, 2011; Singh et al., 2017).”
BackgroundRepresentation and Mediation in Digitalized Work: Evidence from Maintenance of Mining Machinery
Jonsson, K., Mathiassen, L., & Holmström, J. (2018) · Journal of Information Technology · doi:10.1057/s41265-017-0050-x · Cited by 65 · cited 3× · see citing works
“This entails assisting diverse actors to use different technologies to coherently perform shared work arrangements (Jonsson et al., 2018).”
BackgroundInfluentialHooper, R. S., Galvin, T. P., Kilmer, R. A., & Liebowitz, J. (1998) · Expert Systems with Applications · doi:10.1016/s0957-4174(98)00002-5 · Cited by 57 · see citing works
Park, R. (2016) · The International Journal of Human Resource Management · doi:10.1080/09585192.2016.1180315 · Cited by 56 · cited 1× · see citing works
“Consistent with this view, several studies highlight the ways in which computer-aided design, manufacturing and process planning are automating many tasks and enhancing effectiveness and speed (Buckley et al., 2004; Park, 2018).”
ResultWhen does virtuality help or hinder teams? Core team characteristics as contingency factors
Schaubroeck, J. M., & Yu, A. (2017) · Human Resource Management Review · doi:10.1016/j.hrmr.2016.12.009 · Cited by 55 · cited 1× · see citing works
“HRM embodied by technological advancements is increasingly the focus of internationally oriented HRM studies (e.g. Bondarouk et al., 2017; Cooke et al., 2019; Dulebohn & Hoch, 2017; Schaubroeck & Yu, 2017).”
MethodLindsay, C., Commander, J., Findlay, P., Bennie, M., Dunlop, E., & Meer, R. V. D. (2014) · The International Journal of Human Resource Management · doi:10.1080/09585192.2014.948900 · Cited by 53 · cited 2× · see citing works
“…learning opportunities to HRM. Work on robotics emphasizes the ways in which robotic technologies can eliminate repetitive and routine activities handled by human employees, offering to them the possibility to engage in opportunities to use their skills more effectively (Lindsay et al., 2014).”
BackgroundTraining with automated agents improves people's behavior in negotiation and coordination tasks
Lin, R., Gal, K., Kraus, S., & Mazliah, Y. (2013) · Decision Support Systems · doi:10.1016/j.dss.2013.05.015 · Cited by 50 · cited 1× · see citing works
“Within the same context, AI computer agents have been examined as important tools in enhancing employees ’ skills when interacting in strategic and negotiation settings, saving considerable effort and offering better performance (Lin et al., 2014).”
BackgroundThe profile of the ‘Good Judge’ in HRM: A systematic review and agenda for future research
Kock, F. S. D., Lievens, F., & Born, M. P. (2018) · Human Resource Management Review · doi:10.1016/j.hrmr.2018.09.003 · Cited by 38 · cited 1× · see citing works
“The HRM-related keywords were drawn from previous systematic reviews within the area of HRM (e.g. Cooke et al., 2017; De Kock et al., 2020; Voegtlin & Greenwood, 2016).”
MethodInnovation and HRM: Absences and politics
Zanko, M., Badham, R. J., Couchman, P., & Schubert, M. (2008) · The International Journal of Human Resource Management · doi:10.1080/09585190801953616 · Cited by 35 · cited 1× · see citing works
“Most notably, an increasing body of knowledge pertains to HRM as an enabler of technological change and innovation at a global level through work reorganization, such as working conditions and employee training (Seeck & Diehl, 2017; Zanko et al., 2008).”
BackgroundGiacumo, L. A., & Breman, J. (2016) · Scholar Works (Boise State University) · Cited by 32 · see citing works
Being (more) Human in a Digitized World
Seetharaman, P., Mathew, S. K., Sein, M. K., & Tallamraju, R. B. (2020) · Information Systems Frontiers · doi:10.1007/s10796-020-10020-9 · Cited by 30 · see citing works
Expatriate characteristics and the stickiness of HRM knowledge transfers
Chang, Y., & Smale, A. (2013) · The International Journal of Human Resource Management · doi:10.1080/09585192.2013.781436 · Cited by 28 · cited 1× · see citing works
“Research argues that, as far as organizational processes are concerned, the transfer of HR activities and strategies across borders can be challenging and problematic (e.g. Chang & Smale, 2013; Ferraris et al., 2019).”
BackgroundE-HRM in MNCs: what can be learned from a review of the IS literature?
Geffen, C. V., Ruël, H. J. M., & Bondarouk, T. V. (2013) · European J of International Management · doi:10.1504/ejim.2013.055278 · Cited by 28 · cited 2× · see citing works
“Second, the take up and use of technological innovations seem to be heavily dependent on context (Van Geffen et al., 2013).”
BackgroundAn investigation of paradigm choice in Australian international human resource management research
Sheehan, C., Fenwick, M. S., & Dowling, P. J. (2010) · The International Journal of Human Resource Management · doi:10.1080/09585192.2010.505081 · Cited by 21 · cited 1× · see citing works
“Having selected our publication outlets and following other state-of-the-art systematic reviews, we limited our research to full-length, academic peer-reviewed publications written in the English language (Marler & Boudreau, 2017; Sheehan et al., 2010).”
BackgroundAlcaraz, J. M. M., Domènech, M., & Tirado, F. (2012) · Information and Organization · doi:10.1016/j.infoandorg.2012.01.004 · Cited by 21 · cited 1× · see citing works
“…also referred to as eHRM, has gained increasing attention as scholars have sought to understand the external influences rather than internal influences on organizational operations and HRM practices in particular (e.g. Alcaraz et al., 2012; Parry & Tyson, 2011; Strohmeier, 2007; Strohmeier, 2009).”
BackgroundDeveloping an employee turnover risk evaluation model using case-based reasoning
Wang, X., Wang, L., Zhang, L., Xu, X., Zhang, W., & Xu, Y. (2015) · Information Systems Frontiers · doi:10.1007/s10796-015-9615-9 · Cited by 15 · cited 1× · see citing works
“…highlight the ability to process large amounts of data at high speeds (Lindebaum et al., 2020), the possibility to help salespeople to acquire new customers more efficiently (Watson et al., 2018) and the potentiality to effectively evaluate and manage employee turnover risk (Wang et al., 2017).”
Background
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Artificial intelligence, machine learning and deep learning in advanced robotics, a review
Soori, M., Arezoo, B., & Dastres, R. (2023) · Cognitive Robotics · doi:10.1016/j.cogr.2023.04.001 · Cited by 1,131 · see citing works
Artificial intelligence (AI) applications for marketing: A literature-based study
Haleem, A., Javaid, M., Qadri, M. A., Singh, R., & Suman, R. (2022) · Int. J. Intell. Networks · doi:10.1016/j.ijin.2022.08.005 · Cited by 713 · see citing works
Chowdhury, S., Dey, P., Joel-Edgar, S., Bhattacharya, S., Rodriguez-Espindola, O., Abadie, A., & Truong, L. (2023) · Human Resource Management Review · doi:10.1016/j.hrmr.2022.100899 · Cited by 927 · see citing works
Budhwar, P., Malik, A., De Silva, M. T. T., & Thevisuthan, P. (2022) · The International Journal of Human Resource Management · doi:10.1080/09585192.2022.2035161 · Cited by 723 · see citing works
“The final paper by Vrontis et al. (2021) presents a systematic review of 45 articles on the literature examining the emergent themes around intelligent automation in HRM and how it impacts firm performance and employment conditions and areas for future research.”
BackgroundWorker and workplace Artificial Intelligence (AI) coexistence: Emerging themes and research agenda
Zirar, A., Ali, S. I., & Islam, N. (2023) · Technovation · doi:10.1016/j.technovation.2023.102747 · Cited by 484 · see citing works
Man Tang, P., Koopman, J., McClean, S. T., Zhang, J. H., Li, C. H., De Cremer, D., Lu, Y., & Ng, C. T. S. (2022) · Academy of Management Journal · doi:10.5465/amj.2020.1516 · Cited by 370 · see citing works
Arslan, A., Cooper, C. L., Khan, Z., Gölgeci̇, İ., & Ali, I. (2021) · International Journal of Manpower · doi:10.1108/ijm-01-2021-0052 · Cited by 428 · see citing works
Liang, X., Guo, G., Shu, L., Gong, Q., & Luo, P. (2022) · Tourism Management · doi:10.1016/j.tourman.2022.104564 · Cited by 376 · see citing works
Yam, K. C., Tang, P. M., Jackson, J. C., Su, R., & Gray, K. J. (2022) · Journal of Applied Psychology · doi:10.1037/apl0001045 · Cited by 352 · see citing works
Artificial Intelligence in Tactical Human Resource Management: A Systematic Literature Review
Votto, A. M., Valecha, R., Najafirad, P., & Rao, H. R. (2021) · International Journal of Information Management Data Insights · doi:10.1016/j.jjimei.2021.100047 · Cited by 322 · see citing works
The impact of automation and artificial intelligence on worker well-being
Nazareno, L. D. A., & Schiff, D. S. (2021) · Technology in Society · doi:10.1016/j.techsoc.2021.101679 · Cited by 331 · see citing works
Malik, A., Budhwar, P. S., Mohan, H., & Srikanth, N. R. (2022) · Human Resource Management · doi:10.1002/hrm.22133 · Cited by 285 · see citing works
“…the design of workplace and HRM practices are changing at both local and global levels (Lepak & Snell, 1999, 2002; Morris et al., 2016), as evidenced by the debates on Industry 4.0 (Schwab, 2017) and increasing adoption of AI-enabled HR applications (Jaiswal et al., 2022; Vrontis et al., 2022).”
BackgroundInfluentialMeijerink, J., Boons, M., Keegan, A., & Marler, J. (2021) · The International Journal of Human Resource Management · doi:10.1080/09585192.2021.1925326 · Cited by 267 · see citing works
“…the same irrespective of the data inputted (e.g. use of an Excel spreadsheet to rank job applicants or use of SPSS to predict turn-over intentions), in the case of AI these evolve with the data they process based on, for example, machine learning (Strohmeier & Piazza, 2015; Vrontis et al., 2021).”
BackgroundMethodKong, H., Yin, Z., Baruch, Y., & Yuan, Y. (2023) · Journal of Vocational Behavior · doi:10.1016/j.jvb.2023.103928 · Cited by 291 · see citing works
Artificial intelligence (AI)-assisted HRM: Towards an extended strategic framework
Malik, A., Budhwar, P. S., & Kazmi, B. A. (2022) · Human Resource Management Review · doi:10.1016/j.hrmr.2022.100940 · Cited by 310 · see citing works
AI-based decision support systems in Industry 4.0, a review
Soori, M., Jough, F. K. G., Dastres, R., & Behrooz Arezoo, B. (2024) · Journal of Economy and Technology · doi:10.1016/j.ject.2024.08.005 · Cited by 295 · see citing works
A study of Artificial Intelligence impacts on Human Resource Digitalization in Industry 4.0
Murugesan, U., Subramanian, P., Srivastava, S., & Dwivedi, A. (2023) · Decision Analytics Journal · doi:10.1016/j.dajour.2023.100249 · Cited by 217 · see citing works
The adoption of artificial intelligence in human resources management practices
Nawaz, N., Arunachalam, H., Pathi, B. K., & Gajenderan, V. (2024) · International Journal of Information Management Data Insights · doi:10.1016/j.jjimei.2023.100208 · Cited by 302 · see citing works
Assessing digital self-efficacy: Review and scale development
Ulfert, A., & Schmidt, I. (2022) · Computers & Education · doi:10.1016/j.compedu.2022.104626 · Cited by 270 · see citing works
“For instance, while specific action steps are eliminated (such as sorting information), digital systems now enable individuals to accomplish increasingly complex tasks or interact with highly personalized systems (Vrontis et al., 2021).”
BackgroundAI-augmented HRM: Antecedents, assimilation and multilevel consequences
Prikshat, V., Malik, A., & Budhwar, P. (2023) · Human Resource Management Review · doi:10.1016/j.hrmr.2021.100860 · Cited by 200 · see citing works
Adoption of artificial intelligence (AI) based employee experience (EEX) chatbots
Pillai, R., Ghanghorkar, Y., Sivathanu, B., Algharabat, R., & Rana, N. P. (2023) · Information Technology and People · doi:10.1108/itp-04-2022-0287 · Cited by 215 · see citing works
Chen, D., Esperança, J. P., & Wang, S. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.884830 · Cited by 198 · see citing works
Mas, F. D., Massaro, M., Rippa, P., & Secundo, G. (2023) · Technovation · doi:10.1016/j.technovation.2023.102716 · Cited by 195 · see citing works
Charting the progress of technology adoption in tourism and hospitality in the era of industry 4.0
Buhalis, D., Efthymiou, L., Uzunboylu, N., & Thrassou, A. (2024) · EuroMed Journal of Business · doi:10.1108/emjb-11-2023-0310 · Cited by 193 · see citing works
Proposed managerial competencies for Industry 4.0 – Implications for social sustainability
Shet, S. V., & Pereira, V. (2021) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2021.121080 · Cited by 205 · see citing works
Self-citationArtificial Intelligence and Human Resources Management: A Bibliometric Analysis
Palos‐Sánchez, P. R., Luna, P. B., Badicu, A., & Infante-Moro, J. C. (2022) · Applied Artificial Intelligence · doi:10.1080/08839514.2022.2145631 · Cited by 243 · see citing works
“(Vrontis et al. 2022) SLR unspecified 3,4 Holistic SLR on HRM strategies, namely: job replacement,”
BackgroundInfluentialKong, H., Yin, Z., Chon, K., Yuan, Y., & Yu, J. (2023) · Journal of Hospitality Marketing & Management · doi:10.1080/19368623.2023.2258116 · Cited by 194 · see citing works
“Specifically, AI expert systems can process large amounts of data at high speed and provide explanations to increase the accuracy of HRM decisions in the workplace; this helps employees eliminate decision-making time and learn why a particular decision was made (Vrontis et al., 2022).”
BackgroundAI-Augmented HRM: Literature review and a proposed multilevel framework for future research
Prikshat, V., Islam, M., Patel, P., Malik, A., Budhwar, P. S., & Gupta, S. (2023) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2023.122645 · Cited by 242 · see citing works
“…techniques employing advanced artificial intelligence (AI) tools and techniques has seen an emergence of AI applications for human resource management (HRM) with significant implications for the HRM function (Saukkonen et al., 2019; Malik et al., 2021; Pereira et al., 2021; Vrontis et al., 2021).”
BackgroundChaudhary, S., Dhir, A., Ferraris, A., & Bertoldi, B. (2021) · Journal of Business Research · doi:10.1016/j.jbusres.2021.07.052 · Cited by 162 · see citing works
Navigating Generative Artificial Intelligence Promises and Perils for Knowledge and Creative Work
Benbya, H., Strich, F., & Tamm, T. (2024) · Journal of the Association for Information Systems · doi:10.17705/1jais.00861 · Cited by 157 · see citing works
Artificial Intelligence and Its Role in Shaping Organizational Work Practices and Culture
Murire, O. (2024) · Administrative Sciences · doi:10.3390/admsci14120316 · Cited by 154 · see citing works
Artificial Intelligence and Automation in Human Resource Development: A Systematic Review
Ekuma, K. (2024) · Human Resource Development Review · doi:10.1177/15344843231224009 · Cited by 151 · see citing works
“These range from job displacement and increased stress levels to ethical concerns such as privacy and fairness (Arslan et al., 2021; Tambe et al., 2019; Vrontis et al., 2021).”
Creation of the algorithmic management questionnaire: A six‐phase scale development process
Parent‐Rocheleau, X., Parker, S. K., Bujold, A., & Gaudet, M. (2023) · Human Resource Management · doi:10.1002/hrm.22185 · Cited by 157 · see citing works
Tang, P.-M., Koopman, J., Yam, K.-C., Cremer, D. D., Zhang, J. H., & Reynders, P. (2022) · Human Resource Management · doi:10.1002/hrm.22154 · Cited by 137 · see citing works
AI for managing open innovation: Opportunities, challenges, and a research agenda
Broekhuizen, T., Dekker, H. C., de Faria, P., Firk, S., Nguyen, D. K., & Sofka, W. (2023) · Journal of Business Research · doi:10.1016/j.jbusres.2023.114196 · Cited by 163 · see citing works
Chowdhury, S., Joel-Edgar, S., Dey, P. K., Bhattacharya, S., & Kharlamov, A. (2023) · The International Journal of Human Resource Management · doi:10.1080/09585192.2022.2066981 · Cited by 140 · see citing works
“Therefore, from the viewpoint of a HR manager, they will be keen on recall value to focus on employees who are highly likely to leave the organisation, based on the prediction made by the model.”
BackgroundDonald, W. E., HEIJDEN, B. I. J. M. V. D., & Baruch, Y. (2024) · Journal of Vocational Behavior · doi:10.1016/j.jvb.2024.103989 · Cited by 155 · see citing works
“Organizations plan and manage their workforce careers, applying HRM practices and policies (Bagdadli & Gianecchini, 2019).”
From traditional to smart human resources management
Kambur, E., & Yıldırım, T. (2022) · International Journal of Manpower · doi:10.1108/ijm-10-2021-0622 · Cited by 135 · see citing works
Dong, X., Tian, Y., He, M., & Wang, T. (2024) · Journal of Knowledge Management · doi:10.1108/jkm-02-2024-0222 · Cited by 143 · see citing works
Yang, Y., Siau, K. L., Xie, W., & Sun, Y. P. (2022) · Journal of Organizational and End User Computing · doi:10.4018/joeuc.308814 · Cited by 132 · see citing works
Technological innovation-enabling industry 4.0 paradigm: A systematic literature review
Cannavacciuolo, L., Ferraro, G., Ponsiglione, C., Primario, S., & Quinto, I. (2023) · Technovation · doi:10.1016/j.technovation.2023.102733 · Cited by 144 · see citing works
Vecchio, P. D., Secundo, G., & Garzoni, A. (2023) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2023.122342 · Cited by 135 · see citing works
Ogbeibu, S., Emelifeonwu, J., Pereira, V. E., Oseghale, R. O., Gaskin, J. E., Sivarajah, U., & Gunasekaran, A. (2023) · Business Strategy and the Environment · doi:10.1002/bse.3495 · Cited by 154 · see citing works
“Recent contentions suggest that GPC's competitive role could be the outcome of unsup-portive or inadequate environmental guidelines and green reward policies (Arulrajah et al., 2015; Renwick et al., 2016; Vrontis et al., 2021).”
BackgroundResultInfluentialSelf-citationRaghu Raman, R., Pattnaik, D., Hughes, L., & Nedungadi, P. (2024) · Journal of Innovation & Knowledge · doi:10.1016/j.jik.2024.100517 · Cited by 141 · see citing works
Deepa, R., Sekar, S., Malik, A., Kumar, J., & Attri, R. (2024) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2024.123301 · Cited by 160 · see citing works
“…bring technological maturity in organizations and develop HRM procedures to adopt AI assets and develop intelligent technologies (Hmoud, 2021; Giraud et al., 2022; Manuti and Monachino, 2020; Nankervis et al., 2021; Pan et al., 2021; Rodgers et al., 2023; Varma et al., 2022; Vrontis et al., 2022).”
BackgroundMethodInfluentialContemporary Role and Applications of Artificial Intelligence in Dentistry
Bonny, T., Nassan, W. A., Obaideen, K., Mallahi, M. N. A., Mohammad, Y., & El-Damanhoury, H. M. (2023) · F1000Research · doi:10.12688/f1000research.140204.1 · Cited by 132 · see citing works
Wongsansukcharoen, J., & Thaweepaiboonwong, J. (2023) · European Research on Management and Business Economics · doi:10.1016/j.iedeen.2022.100210 · Cited by 124 · see citing works
Artificial intelligence in learning and development: a systematic literature review
Bhatt, P., & Muduli, A. (2022) · European journal of training and development · doi:10.1108/ejtd-09-2021-0143 · Cited by 123 · see citing works
Critical exploration of AI-driven HRM to build up organizational capabilities
Böhmer, N., & Schinnenburg, H. (2023) · Employee Relations · doi:10.1108/er-04-2022-0202 · Cited by 162 · see citing works
Rawas, S. (2024) · Discover Artificial Intelligence · doi:10.1007/s44163-024-00118-3 · Cited by 119 · see citing works
“AI comprises a wide range of techniques and technologies, including computer vision, deep learning, machine learning, and symbolic AI [3].”
Research on Artificial-Intelligence-Assisted Medicine: A Survey on Medical Artificial Intelligence
Gou, F., Liu, J., Xiao, C., & Wu, J. (2024) · Diagnostics · doi:10.3390/diagnostics14141472 · Cited by 128 · see citing works
Li, J., Zhang, R.-X., Wu, T., & Mao, M. (2023) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2023.103654 · Cited by 120 · see citing works
Kumar, M., Raut, R. D., Mangla, S., Ferraris, A., & Choubey, V. K. (2022) · Production Planning & Control · doi:10.1080/09537287.2022.2131620 · Cited by 124 · see citing works
Menzies, J. L., Sabert, B., Hassan, R., & Mensah, P. K. (2024) · Thunderbird International Business Review · doi:10.1002/tie.22370 · Cited by 145 · see citing works
Kim, B., & Lee, J. (2024) · Humanities and Social Sciences Communications · doi:10.1057/s41599-024-04018-w · Cited by 114 · see citing works
Why do employees hide their knowledge and what are the consequences? A systematic literature review
Siachou, E., Trichina, E., Papasolomou, I., & Sakka, G. (2021) · Journal of Business Research · doi:10.1016/j.jbusres.2021.06.031 · Cited by 112 · see citing works
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Gong, Q., Fan, D., & Bartram, T. (2024) · International journal of human resources management · doi:10.1080/09585192.2024.2440065 · Cited by 110 · see citing works
“…robotics, and advanced technologies, on organizational and employee outcomes (Budhwar et al., 2022; Malik et al., 2023; Pereira et al., 2023; Vrontis et al., 2022); the organizational resources necessary for developing AI capabilities in HRM (Chowdhury et al., 2023); and the application of…”
InfluentialRathore, S. P. S. (2023) · International Journal for Global Academic & Scientific Research · doi:10.55938/ijgasr.v2i2.50 · Cited by 108 · see citing works
Transformative AI in human resource management: enhancing workforce planning with topic modeling
Venugopalan, M., Madhavan, V., Prasad, R., & Raghu Raman, R. (2024) · Cogent Business & Management · doi:10.1080/23311975.2024.2432550 · Cited by 166 · see citing works
“Vrontis et al. (2023) identified how intelligent automation technologies provide a novel approach to managing employees and improving firm performance.”
Faqihi, A. Y. A., & Miah, S. J. (2023) · Journal of risk and financial management · doi:10.3390/jrfm16010031 · Cited by 137 · see citing works
Yin, Z., Kong, H., Baruch, Y., Decosta, P. L., & Yuan, Y. (2024) · Tourism Management · doi:10.1016/j.tourman.2024.104966 · Cited by 120 · see citing works
Antecedents of human-robot collaboration: theoretical extension of the technology acceptance model
Parvez, M. O., Araslı, H., Öztüren, A., Lodhi, R. N., & Ongsakul, V. (2022) · Journal of Hospitality and Tourism Technology · doi:10.1108/jhtt-09-2021-0267 · Cited by 109 · see citing works
Chatterjee, S., Chaudhuri, R., Vrontis, D., & Siachou, E. (2021) · International Journal of Manpower · doi:10.1108/ijm-02-2021-0087 · Cited by 112 · see citing works
Self-citationChatterjee, S., Chaudhuri, R., & Vrontis, D. (2021) · Information Systems Frontiers · doi:10.1007/s10796-021-10197-7 · Cited by 103 · see citing works
“It is expected that domestic robots will be able to perform all domestic work (Gates, 2007; You & Robert, 2018; Vrontis et al., 2021; Jha & Saha, 2021).”
Self-citationDima, J., Gilbert, M., Dextras-Gauthier, J., & Giraud, L. (2024) · Frontiers in Psychology · doi:10.3389/fpsyg.2024.1360401 · Cited by 164 · see citing works
Li, J., Wu, T., Wu, Y. J., & Goh, M. (2023) · Management Decision · doi:10.1108/md-09-2022-1183 · Cited by 102 · see citing works
Artificial intelligence in tourism: insights and future research agenda
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“Surgical-assistance robots are designed to enhance existing surgical treatments, including minimally invasive surgeries and orthopedic surgeries [14].”
BackgroundHR Analytics and Artificial Intelligence-Transforming Human Resource Management
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Systematic review on customer citizenship behavior: Clarifying the domain and future research agenda
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From greenwashing to green B2B marketing: A systematic literature review
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Let us talk about something: The evolution of e-WOM from the past to the future
Akbari, M., Foroudi, P., Fashami, R. Z., Mahavarpour, N., & Khodayari, M. (2022) · Journal of Business Research · doi:10.1016/j.jbusres.2022.05.061 · Cited by 100 · see citing works
Jatobá, M. N., Ferreira, J. J., Fernandes, P. O., & Teixeira, J. P. (2023) · Journal of Organizational Change Management · doi:10.1108/jocm-03-2022-0075 · Cited by 120 · see citing works
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Mapping the greenwashing research landscape: a theoretical and field analysis
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“This approach ensures transparency, replicability, and verifiability, maintaining the integrity of the research (Baima et al. 2020; Vrontis et al. 2022).”
Bao, Y., Gong, W., & Yang, K. (2023) · Systems · doi:10.3390/systems11090442 · Cited by 96 · see citing works
Talwar, S., Dhir, A., Islam, N., Kaur, P., & Almusharraf, A. I. (2023) · Journal of Business Research · doi:10.1016/j.jbusres.2023.114135 · Cited by 90 · see citing works
“First, although we followed recent studies (e.g., Christofi, Pereira, et al., 2021; Vrontis et al., 2022) to execute a robust and systematic search and review of congruent studies, there might be certain keywords or studies that we have missed due to our inclusion and exclusion criteria.”
ResultChatGPT: The Brightest Student in the Class
Vázquez-Cano, E., Ramírez-Hurtado, J. M., Sáez-López, J., & López-Meneses, E. (2023) · Thinking Skills and Creativity · doi:10.1016/j.tsc.2023.101380 · Cited by 79 · see citing works
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“According to Vrontis et al. [9], AI integration into HRM processes requires cutting-edge tech like cloud computing and big data analytics.”
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“Because AI is being used outside of its original purposes to solve existing problems (human-bound unfairness or bias), AI’s seamless application to HRM is still far away [67, 69, 83, 87].”
BackgroundInfluence of artificial intelligence (AI) perception on career resilience and informal learning
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Development and challenges of object detection: A survey
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How does artificial intelligence impact employees’ engagement in lean organisations?
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Can Artificial Intelligence (AI) Manage Behavioural Biases Among Financial Planners?
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“AI attempts to extend human capabilities and accomplish tasks that neither humans nor machines could on their own (Jarrahi, 2018; Vrontis et al., 2022).”
BackgroundSelf-citationExploring the impact of language models, such as ChatGPT , on student learning and assessment
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Optimizing Project Management using Artificial Intelligence
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Self-citationServitization innovation: A systematic review, integrative framework, and future research directions
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- 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
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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.
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