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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 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
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“Service Encounter 2.0”: An investigation into the roles of technology, employees and customers
Larivière, B., Bowen, D., Andreassen, T. W., Kunz, W., Sirianni, N. J., Voss, C., Wünderlich, N. V., & De Keyser, A. (2017) · Journal of Business Research · doi:10.1016/j.jbusres.2017.03.008 · Cited by 779 · cited 3×
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BackgroundHow global is international CSR research? Insights and recommendations from a systematic review
Pisani, N., Kourula, A. E., Kolk, A., & Meijer, R. (2017) · Journal of World Business · doi:10.1016/j.jwb.2017.05.003 · Cited by 464 · cited 4×
“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).”
MethodInfluentialConceptualising the future of HRM and technology research
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BackgroundInfluentialElectronic HRM: four decades of research on adoption and consequences
Bondarouk, T., Parry, E., & Furtmueller, E. (2017) · The International Journal of Human Resource Management · doi:10.1080/09585192.2016.1245672 · Cited by 423 · cited 9×
“…scholars emphasize how information technologies are changing HRM-related practices by introducing e-recruitment, e-training or e-competence management, contributing positively to HRM service quality in both local and international organizations (Bondarouk & Brewster, 2016; Bondarouk et al., 2017).”
BackgroundMethodInfluentialQuarterly Review of Distance Education
Simonson, M. R. (2025) · Quarterly review of distance education · doi:10.1108/qrde · Cited by 420
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Self-citationLeonidou, E., Christofi, M., Vrontis, D., & Thrassou, A. (2018) · Journal of Business Research · doi:10.1016/j.jbusres.2018.11.054 · Cited by 413 · cited 2×
“We also decided to review both review, empirical and conceptual papers (Leonidou et al., 2020).”
BackgroundSelf-citationMarketing AI recruitment: The next phase in job application and selection
van Esch, P., Black, J. S., & Ferolie, J. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2018.09.009 · Cited by 391 · cited 1×
“AI-enabled recruitment platforms can also extrapolate possible behaviors in terms of job fit and performance while being less biased and more objective than humans (Van Esch et al., 2019).”
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“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).”
MethodMarinova, D., de Ruyter, K., Huang, M., Meuter, M. L., & Challagalla, G. N. (2016) · Journal of Service Research · doi:10.1177/1094670516679273 · Cited by 384 · cited 2×
“Within this context, several authors support the view that AI can be of great value in facilitating service or sales and creating more favorable, customized and valued service interactions (Marinova et al., 2017; Singh et al., 2017).”
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Dulebohn, J. H., & Hoch, J. E. (2017) · Human Resource Management Review · doi:10.1016/j.hrmr.2016.12.004 · Cited by 342 · cited 1×
“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).”
MethodA literature review on HRM and innovation – taking stock and future directions
Seeck, H. M. J., & Diehl, M. (2016) · The International Journal of Human Resource Management · doi:10.1080/09585192.2016.1143862 · Cited by 316 · cited 1×
“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).”
BackgroundHuman resource management, strategic involvement and e-HRM technology
Marler, J. H., & Parry, E. (2016) · The International Journal of Human Resource Management · doi:10.1080/09585192.2015.1091980 · Cited by 315 · cited 1×
“…Artificial Intelligence (AI) and other breakthrough technologies, the interplay between firms, employees and customers is fundamentally changing and the automation of the administrative components of HRM activities and tasks is intensifying (Larivi (cid:1) ere et al., 2017; Marler & Parry, 2016).”
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Fleming, P. (2019) · Organization Studies · doi:10.1177/0170840618765568 · Cited by 297 · cited 2×
“…reviews of the 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…”
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“In doing so, they enhance the accuracy of HRM decisions made by non-experts and eliminate the time needed by them to make HRM decisions (Lindebaum et al., 2020; Lawler & Elliot, 1996).”
BackgroundEPM 20/20: A Review, Framework, and Research Agenda for Electronic Performance Monitoring
Ravid, D. M., Tomczak, D. L., White, J. C., & Behrend, T. S. (2020) · Journal of Management · doi:10.1177/0149206319869435 · Cited by 277 · cited 2×
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“However, these positive effects have been questioned in a number of ways in reference to ethicality of acquiring and progressing of data as well as in terms of favorability among applicants (Suen et al., 2019; Bhave et al., 2020).”
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Ancarani, A., Di Mauro, C., & Mascali, F. (2019) · Journal of World Business · doi:10.1016/j.jwb.2019.04.003 · Cited by 248 · cited 1×
“Today, innovative technologies are dynamically reinventing the human resource management (HRM) landscape on a global scale (Ancarani et al., 2019).”
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“Simulations, defined as AI environments, can provide high degree of interactivity with other users and enhance learning opportunities (Bell et al., 2008).”
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Hewett, R., Shantz, A., Mundy, J., & Alfes, K. (2018) · The International Journal of Human Resource Management · doi:10.1080/09585192.2017.1380062 · Cited by 230 · cited 3×
“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).”
MethodWork–life boundary management and the personal digital assistant
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BackgroundMarketing research on mergers and acquisitions: a systematic review and future directions
Christofi, M., Leonidou, E., & Vrontis, D. (2017) · International Marketing Review · doi:10.1108/imr-03-2015-0100 · Cited by 211 · cited 1×
“In line with other state-of-the-art systematic reviews (Christofi et al., 2017; Christofi et al., 2019; Leonidou et al., 2020; Vrontis & Christofi, 2019), we focus on key findings, rather than providing an exhaustive analysis of each article.”
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“Humanoid service robots and artificial intelligence bots, for example, are increasingly attracting industry attention (Araujo, 2018; Go & Sundar, 2019; Larivi (cid:1) ere et al., 2017; Thomaz et al., 2020).”
BackgroundDoes e-HRM lead to better HRM service?
Bondarouk, T. V., Harms, R., & Lepak, D. P. (2015) · The International Journal of Human Resource Management · doi:10.1080/09585192.2015.1118139 · Cited by 202 · cited 9×
“…scholars emphasize how information technologies are changing HRM-related practices by introducing e-recruitment, e-training or e-competence management, contributing positively to HRM service quality in both local and international organizations (Bondarouk & Brewster, 2016; Bondarouk et al., 2017).”
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The Emergent Field of Organizational Frontlines
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“Within this context, several authors support the view that AI can be of great value in facilitating service or sales and creating more favorable, customized and valued service interactions (Marinova et al., 2017; Singh et al., 2017).”
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“Research thus far reveals that companies establish an e-recruit-ing system to reduce costs, to access more people, get quicker response and increase applicants ’ positive perceptions about the company (e.g. Parry & Tyson, 2008).”
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“Feldman and Klaas (2002) and Stone et al. (2015) discuss these issues in depth.”
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“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).”
MethodSajjadiani, S., Sojourner, A. J., Kammeyer-Mueller, J. D., & Mykerezi, E. (2019) · Journal of Applied Psychology · doi:10.1037/apl0000405 · Cited by 173 · cited 1×
“Consistent with this view, Sajjadiani et al. (2019) suggest that machine learning can greatly assist HR practitioners and firms by transforming the selection process into a more systematic process by eliminating the occurrence of recruiters ’ biases or even applicants ’ influence methods to deviate…”
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“…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).”
BackgroundInternational 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 171 · cited 2×
“…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).”
BackgroundÖtting, S. K., & Maier, G. W. (2018) · Computers in Human Behavior · doi:10.1016/j.chb.2018.07.022 · Cited by 168 · cited 1×
“€ 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.”
BackgroundOperator work design and robotics system performance: A serendipitous field study.
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×
“Yet, these technologies offer the opportunity for the design of problem-solving strategies that will be of great value (Wall et al., 1992).”
BackgroundChristofi, M., Vrontis, D., Thrassou, A., & Shams, S. M. R. (2019) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2019.05.026 · Cited by 154 · cited 1×
“In line with other state-of-the-art systematic reviews (Christofi et al., 2017; Christofi et al., 2019; Leonidou et al., 2020; Vrontis & Christofi, 2019), we focus on key findings, rather than providing an exhaustive analysis of each article.”
Self-citationFerraris, A., Erhardt, N., & Bresciani, S. (2017) · The International Journal of Human Resource Management · doi:10.1080/09585192.2017.1291530 · Cited by 150 · cited 2×
“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.”
BackgroundCooke, F. L., Wood, G., Wang, M., & Veen, A. (2018) · Human Resource Management Review · doi:10.1016/j.hrmr.2018.05.001 · Cited by 149 · cited 5×
“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).”
BackgroundMethodInfluentialJung, J., Song, H., Kim, Y., Im, H., & Oh, S.-W. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2017.02.022 · Cited by 139 · cited 1×
“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).”
BackgroundStrohmeier, S. (2018) · The International Journal of Human Resource Management · doi:10.1080/09585192.2018.1443963 · Cited by 134 · cited 2×
“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).”
MethodAbraham, 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×
“…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).”
BackgroundMarler, J. H., Fisher, S. L., & Ke, W. (2009) · Personnel Psychology · doi:10.1111/j.1744-6570.2009.01140.x · Cited by 121 · cited 1×
“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).”
BackgroundBig data contributions to human resource management: a systematic review
Garcia-Arroyo, J., & Osca, A. (2021) · The International Journal of Human Resource Management · doi:10.1080/09585192.2019.1674357 · Cited by 118 · cited 3×
“…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.”
BackgroundMethodGlobal 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 115
The 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 107 · cited 1×
“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.”
BackgroundData 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
Organizational 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 97 · cited 1×
“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).”
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×
“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×
“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).”
ResultEmployee 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×
“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).”
BackgroundInfluentialRepresentation 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 74 · cited 3×
“This entails assisting diverse actors to use different technologies to coherently perform shared work arrangements (Jonsson et al., 2018).”
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×
“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
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×
“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×
“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).”
BackgroundMethodKnowledge 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 73 · cited 1×
“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).”
BackgroundNew 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×
“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).”
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×
“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).”
BackgroundPark, R. (2016) · The International Journal of Human Resource Management · doi:10.1080/09585192.2016.1180315 · Cited by 65 · cited 1×
“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).”
ResultHooper, 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
When 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×
“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×
“…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×
“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 50 · cited 1×
“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×
“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
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
E-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×
“Second, the take up and use of technological innovations seem to be heavily dependent on context (Van Geffen et al., 2013).”
BackgroundExpatriate 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 27 · cited 1×
“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).”
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×
“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×
“…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×
“…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
Cited by
Sorted by citations
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
Artificial intelligence (AI) applications for marketing: A literature-based study
Haleem, A., Javaid, M., Qadri, M. A., Singh, R. P., & Suman, R. (2022) · International Journal of Intelligent Networks · doi:10.1016/j.ijin.2022.08.005 · Cited by 1,364
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
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
“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
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
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