Adoption of artificial intelligence (AI) for talent acquisition in IT/ITeS organizations
Abstract
Purpose: Human resource managers are adopting AI technology for conducting various tasks of human resource management, starting from manpower planning till employee exit. AI technology is prominently used for talent acquisition in organizations. This research investigates the adoption of AI technology for talent acquisition. Design/methodology/approach: This study employs Technology-Organization-Environment (TOE) and Task-Technology-Fit (TTF) framework and proposes a model to explore the adoption of AI technology for talent acquisition. The survey was conducted among the 562 human resource managers and talent acquisition managers with a structured questionnaire. The analysis of data was completed using PLS-SEM. Findings: This research reveals that cost-effectiveness, relative advantage, top management support, HR readiness, competitive pressure and support from AI vendors positively affect AI technology adoption for talent acquisition. Security and privacy issues negatively influence the adoption of AI technology. It is found that task and technology characteristics influence the task technology fit of AI technology for talent acquisition. Adoption and task technology fit of AI technology influence the actual usage of AI technology for talent acquisition. It is revealed that stickiness to traditional talent acquisition methods negatively moderates the association between adoption and actual usage of AI technology for talent acquisition. The proposed model was empirically validated and revealed the predictors of adoption and actual usage of AI technology for talent acquisition. Practical implications: This paper provides the predictors of the adoption of AI technology for talent acquisition, which is emerging extensively in the human resource domain. It provides vital insights to the human resource managers to benchmark AI technology required for talent acquisition. Marketers can develop their marketing plan considering the factors of adoption. It would help designers to understand the factors of adoption and design the AI technology algorithms and applications for talent acquisition. It contributes to advance the literature of technology adoption by interweaving it with the human resource domain literature on talent acquisition. Originality/value: This research uniquely validates the model for the adoption of AI technology for talent acquisition using the TOE and TTF framework. It reveals the factors influencing the adoption and actual usage of AI technology for talent acquisition.
Integrity signals
Registry
Cites
Statistics
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?
How people perceive AI is determined by how it works, how much it costs, and what features it includes.
“As a result, how people perceive AI is determined by how it works, how much it costs, and what features it includes (Pillai and Sivathanu, 2020).”
From Exploring the antecedents of AI adoption for effective HRM practices in the Indian pharmaceutical sector (2023) · cites this paper as Pillai and Sivathanu, 2020
Recruiters can delegate mundane tasks to AI systems, freeing up their time and resources for more strategic issues.
“Recruiters can now delegate these mundane tasks to AI systems, freeing up their time and resources for more strategic issues (Pillai and Sivathanu, 2020).”
From Exploring the antecedents of AI adoption for effective HRM practices in the Indian pharmaceutical sector (2023) · cites this paper as Pillai and Sivathanu, 2020
Cites
Evaluating Structural Equation Models with Unobservable Variables and Measurement Error
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.2307/3151312 · Cited by 109,314 · see citing works
Evaluating structural equation models with unobservable variables and measurement error
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.1177/002224378101800104 · Cited by 109,190 · see citing works
The theory of planned behavior
Ajzen, I. (1991) · Organizational Behavior and Human Decision Processes · doi:10.1016/0749-5978(91)90020-t · Cited by 90,587 · see citing works
Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003) · Journal of Applied Psychology · doi:10.1037/0021-9010.88.5.879 · Cited by 82,194 · see citing works
Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483 · see citing works
User Acceptance of Information Technology: Toward A Unified View1
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003) · MIS Quarterly · doi:10.2307/30036540 · Cited by 45,035 · see citing works
Pls-Sem: indeed a silver bullet
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011) · Journal of Marketing Theory and Practice · doi:10.2753/mtp1069-6679190202 · Cited by 21,631 · see citing works
Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research
F. Hair Jr, J., Sarstedt, M., Hopkins, L., & G. Kuppelwieser, V. (2014) · European Business Review · doi:10.1108/ebr-10-2013-0128 · Cited by 11,728 · see citing works
Task-Technology Fit and Individual Performance
Goodhue, D. L., & Thompson, R. L. (1995) · MIS Quarterly · doi:10.2307/249689 · Cited by 6,006 · see citing works
Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., et al. (2021) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2019.08.002 · Cited by 4,611 · see citing works
Extending the technology acceptance model with task–technology fit constructs
Dishaw, M. T., & Strong, D. M. (1999) · Information & Management · doi:10.1016/s0378-7206(98)00101-3 · Cited by 1,772 · see citing works
Alalwan, A. A., Dwivedi, Y. K., & Rana, N. P. (2017) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2017.01.002 · Cited by 1,765 · see citing works
Integrating TTF and UTAUT to explain mobile banking user adoption
Zhou, T., Lu, Y., & Wang, B. (2010) · Computers in Human Behavior · doi:10.1016/j.chb.2010.01.013 · Cited by 1,696 · see citing works
Oliveira, T., Thomas, M. A., & Espadanal, M. (2014) · Information & Management · doi:10.1016/j.im.2014.03.006 · Cited by 1,340 · see citing works
Partial Least Squares Strukturgleichungsmodellierung: Eine anwendungsorientierte Einführung
Hair, J. F., Hauff, S., Hult, G. T. M., Richter, N. F., Ringle, C. M., & Sarstedt, M. (2017) · doi:10.15358/9783800653614 · Cited by 1,327 · see citing works
Advances in Social Media Research: Past, Present and Future
Kapoor, K., Tamilmani, K., Rana, N. P., Patil, P. P., Dwivedi, Y. K., & Nerur, S. P. (2017) · Information Systems Frontiers · doi:10.1007/s10796-017-9810-y · Cited by 1,211 · see citing works
Understanding the determinants of cloud computing adoption
Low, C., Chen, Y., & Wu, M. (2011) · Industrial Management & Data Systems · doi:10.1108/02635571111161262 · Cited by 1,181 · see citing works
Adoption of new information technologies in rural small businesses
Premkumar, G., & Roberts, M. (1999) · Omega · doi:10.1016/s0305-0483(98)00071-1 · Cited by 1,108 · see citing works
Artificial Intelligence in FinTech: understanding robo-advisors adoption among customers
Belanche, D., Casaló, L. V., & Flavián, C. (2019) · Industrial Management & Data Systems · doi:10.1108/imds-08-2018-0368 · Cited by 851 · see citing works
Zhu, K. X., Dong, S., Xu, S. X., & Kraemer, K. L. (2006) · European Journal of Information Systems · doi:10.1057/palgrave.ejis.3000650 · Cited by 800 · see citing works
An Empirically Derived Model for the Adoption of Customer‐based Interorganizational Systems*
Grover, V. (1993) · Decision Sciences · doi:10.1111/j.1540-5915.1993.tb01295.x · Cited by 757 · see citing works
Beechler, S., & Woodward, I. C. (2009) · Journal of International Management · doi:10.1016/j.intman.2009.01.002 · Cited by 680 · see citing works
The “majority illusion” in social networks
Lerman, K., Yan, X., & Wu, X.-Z. (2016) · PLOS ONE · doi:10.1371/journal.pone.0147617 · Cited by 669 · see citing works
Understanding e-business adoption across industries in European countries
Oliveira, T., & Martins, M. F. (2010) · Industrial Management & Data Systems · doi:10.1108/02635571011087428 · Cited by 641 · see citing works
Determinant Factors of E-commerce Adoption by SMEs in Developing Country: Evidence from Indonesia
Rahayu, R., & Day, J. T. (2015) · Procedia - Social and Behavioral Sciences · doi:10.1016/j.sbspro.2015.06.423 · Cited by 639 · see citing works
Adoption of e‐commerce applications in SMEs
Ghobakhloo, M., Aranda, D. A., & Benítez-Amado, J. (2011) · Industrial Management & Data Systems · doi:10.1108/02635571111170785 · Cited by 621 · see citing works
Key ingredients for evaluating Industry 4.0 readiness for organizations: a literature review
Sony, M., & Naik, S. S. (2019) · Benchmarking An International Journal · doi:10.1108/bij-09-2018-0284 · Cited by 562 · see citing works
A task–technology fit view of learning management system impact
McGill, T. J., & Klobas, J. E. (2008) · Computers & Education · doi:10.1016/j.compedu.2008.10.002 · Cited by 555 · see citing works
Opportunities and risks of software-as-a-service: Findings from a survey of IT executives
Benlian, A., & Heß, T. (2011) · Decision Support Systems · doi:10.1016/j.dss.2011.07.007 · Cited by 541 · see citing works
The psychology of talent management: A review and research agenda
Dries, N. (2013) · Human Resource Management Review · doi:10.1016/j.hrmr.2013.05.001 · Cited by 525 · see citing works
Lin, T., & Huang, C.-C. (2008) · Information & Management · doi:10.1016/j.im.2008.06.004 · Cited by 523 · see citing works
From Use to Effective Use: A Representation Theory Perspective
Burton‐Jones, A., & Grangé, C. (2012) · Information Systems Research · doi:10.1287/isre.1120.0444 · Cited by 498 · see citing works
Notes from the Editors: Redefining some methodological criteria for the journal ☆
Guide, V., & Ketokivi, M. (2015) · Journal of Operations Management · doi:10.1016/s0272-6963(15)00056-x · Cited by 492 · see citing works
Huang, T.-L., & Liao, S. (2015) · Electronic Commerce Research · doi:10.1007/s10660-014-9163-2 · Cited by 476 · see citing works
Augmented reality in support of Industry 4.0—Implementation challenges and success factors
Masood, T., & Egger, J. (2019) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2019.02.003 · Cited by 472 · see citing works
Hsu, C., & Lin, J. C. (2016) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2016.04.012 · Cited by 455 · see citing works
IT Outsourcing Strategies: Universalistic, Contingency, and Configurational Explanations of Success
Lee, J.-N., Miranda, S. M., & Kim, Y. (2004) · Information Systems Research · doi:10.1287/isre.1040.0013 · Cited by 427 · see citing works
Role of artificial intelligence in operations environment: a review and bibliometric analysis
Dhamija, P., & Bag, S. (2020) · The TQM Journal · doi:10.1108/tqm-10-2019-0243 · Cited by 394 · see citing works
Marketing 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 · see citing works
Allen, D. G., Mahto, R. V., & Otondo, R. F. (2007) · Journal of Applied Psychology · doi:10.1037/0021-9010.92.6.1696 · Cited by 390 · see citing works
Lin, H., Chi, O. H., & Gürsoy, D. (2019) · Journal of Hospitality Marketing & Management · doi:10.1080/19368623.2020.1685053 · Cited by 388 · see citing works
Adoption of digital payment systems in the era of demonetization in India
Sivathanu, B. (2018) · Journal of Science and Technology Policy Management · doi:10.1108/jstpm-07-2017-0033 · Cited by 386 · see citing works
Self-citationApplying artificial intelligence: implications for recruitment
Upadhyay, A. K., & Khandelwal, K. (2018) · Strategic HR Review · doi:10.1108/shr-07-2018-0051 · Cited by 380 · see citing works
Integrated technology-organization-environment (T-O-E) taxonomies for technology adoption
Awa, H. O., Ojiabo, O. U., & Orokor, L. E. (2017) · Journal of Enterprise Information Management · doi:10.1108/jeim-03-2016-0079 · Cited by 378 · see citing works
Lai, Y., Huifen, S., & Ren, J. (2018) · The International Journal of Logistics Management · doi:10.1108/ijlm-06-2017-0153 · Cited by 357 · see citing works
Industry 4.0 and digital supply chain capabilities
de Queiroz, M. M., Pereira, S. C. F., Telles, R., & Machado, M. C. (2019) · Benchmarking An International Journal · doi:10.1108/bij-12-2018-0435 · Cited by 352 · see citing works
SMEs' adoption of enterprise applications
Ramdani, B., Chevers, D. A., & Williams, D. A. (2013) · Journal of Small Business and Enterprise Development · doi:10.1108/jsbed-12-2011-0035 · Cited by 348 · see citing works
User acceptance of smart home services: An extension of the theory of planned behavior
Yang, H., Lee, H., & Zo, H. (2017) · Industrial Management & Data Systems · doi:10.1108/imds-01-2016-0017 · Cited by 325 · see citing works
Factors Influencing e-commerce Adoption and Use by Small and Medium Businesses
Wymer, S. A., & Regan, E. (2005) · Electronic Markets · doi:10.1080/10196780500303151 · Cited by 320 · see citing works
Al-Qirim, N. A. Y. (2007) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2007.02.012 · Cited by 313 · see citing works
Talent — Innate or acquired? Theoretical considerations and their implications for talent management
Meyers, M. C., van Woerkom, M., & Dries, N. (2013) · Human Resource Management Review · doi:10.1016/j.hrmr.2013.05.003 · Cited by 304 · see citing works
Online stickiness: its antecedents and effect on purchasing intention
Lin, J. C. (2007) · Behaviour and Information Technology · doi:10.1080/01449290600740843 · Cited by 302 · see citing works
Understanding adoption of intelligent personal assistants
Han, S.-Y., & Yang, H. (2018) · Industrial Management & Data Systems · doi:10.1108/imds-05-2017-0214 · Cited by 297 · see citing works
Understanding CRM adoption stages: empirical analysis building on the TOE framework
Cruz‐Jesus, F., Pinheiro, A. M. G., & Oliveira, T. (2019) · Computers in Industry · doi:10.1016/j.compind.2019.03.007 · Cited by 292 · see citing works
Review on IT adoption: insights from recent technologies
Gangwar, H., Date, H., & Raoot, A. D. (2014) · Journal of Enterprise Information Management · doi:10.1108/jeim-08-2012-0047 · Cited by 289 · see citing works
Vanduhe, V. Z., Nat, M. C., & Hasan, H. F. (2020) · IEEE Access · doi:10.1109/access.2020.2966179 · Cited by 281 · see citing works
Ifinedo, P. (2011) · International Journal of Information Technology & Decision Making · doi:10.1142/s0219622011004543 · Cited by 277 · see citing works
Lin, W.-S. (2012) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2012.01.006 · Cited by 273 · see citing works
Using T-O-E theoretical framework to study the adoption of ERP solution
Awa, H. O., Ukoha, O., & Emecheta, B. C. (2016) · Cogent Business & Management · doi:10.1080/23311975.2016.1196571 · Cited by 272 · see citing works
Understanding SaaS adoption from the perspective of organizational users: A tripod readiness model
Yang, Z., Sun, J., Zhang, Y., & Wang, Y. (2015) · Computers in Human Behavior · doi:10.1016/j.chb.2014.12.022 · Cited by 269 · see citing works
Ivanov, S. H., & Webster, C. (2017) · SSRN Electronic Journal · Cited by 268 · see citing works
A model of adoption determinants of ERP within T-O-E framework
Awa, H. O., & Ojiabo, O. U. (2016) · Information Technology and People · doi:10.1108/itp-03-2015-0068 · Cited by 267 · see citing works
Alam, S. S., Ali, M. Y., & Jani, M. F. M. (2011) · Journal of Business Economics and Management · doi:10.3846/16111699.2011.576749 · Cited by 263 · see citing works
A Rude Awakening: Internet Shakeout in 2000
Demers, E. A., & Lev, B. I. (2001) · Review of Accounting Studies · doi:10.1023/a:1011675227890 · Cited by 249 · see citing works
AI in talent acquisition: a review of AI-applications used in recruitment and selection
Albert, E. T. (2019) · Strategic HR Review · doi:10.1108/shr-04-2019-0024 · Cited by 243 · see citing works
Wang, Y.-S., Yeh, C.-H., & Liao, Y.-W. (2013) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2012.09.004 · Cited by 222 · see citing works
Big data and predictive analytics in humanitarian supply chains
Dubey, R., Luo, Z., Gunasekaran, A., Akter, S., Hazen, B. T., & Douglas, M. A. (2018) · The International Journal of Logistics Management · doi:10.1108/ijlm-02-2017-0039 · Cited by 217 · see citing works
Hameed, M. A., Counsell, S., & Swift, S. (2012) · Information & Management · doi:10.1016/j.im.2012.05.002 · Cited by 206 · see citing works
Understanding the determinants of business intelligence system adoption stages
Puklavec, B., Oliveira, T., & Popovič, A. (2017) · Industrial Management & Data Systems · doi:10.1108/imds-05-2017-0170 · Cited by 200 · see citing works
Determinants of RFID adoption intention: Evidence from Taiwanese retail chains
Tsai, M., Lee, W., & Wu, H. (2010) · Information & Management · doi:10.1016/j.im.2010.05.001 · Cited by 199 · see citing works
Big data adoption: State of the art and research challenges
Baig, M. I., Shuib, L. M., & Yadegaridehkordi, E. (2019) · Information Processing & Management · doi:10.1016/j.ipm.2019.102095 · Cited by 197 · see citing works
Developing an explorative model for SaaS adoption
Wu, W.-W. (2011) · Expert Systems with Applications · doi:10.1016/j.eswa.2011.05.039 · Cited by 192 · see citing works
Chong, A. Y., & Chan, F. T. S. (2012) · Expert Systems with Applications · doi:10.1016/j.eswa.2012.01.201 · Cited by 190 · see citing works
Revisiting technology-organization-environment (T-O-E) theory for enriched applicability
Awa, H. O., Ukoha, O., & Igwe, S. R. (2017) · The Bottom Line Managing Library Finances · doi:10.1108/bl-12-2016-0044 · Cited by 188 · see citing works
Understanding SaaS adoption: The moderating impact of the environment context
Oliveira, T., Martins, R., Sarker, S., Thomas, M. A., & Popovič, A. (2019) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2019.02.009 · Cited by 183 · see citing works
Understanding the factors affecting the adoption of the Internet of Things
Hsu, C.-W., & Yeh, C.-C. (2016) · Technology Analysis and Strategic Management · doi:10.1080/09537325.2016.1269160 · Cited by 171 · see citing works
Quaddus, M., & Hofmeyer, G. (2007) · European Journal of Information Systems · doi:10.1057/palgrave.ejis.3000671 · Cited by 167 · see citing works
Identifying the ideal fit between mobile work and mobile work support
Yuan, Y., Archer, N., Connelly, C. E., & Zheng, W. (2010) · Information & Management · doi:10.1016/j.im.2009.12.004 · Cited by 164 · see citing works
Howard, M. C., & Rose, J. C. (2018) · Information & Management · doi:10.1016/j.im.2018.12.002 · Cited by 161 · see citing works
The impact of big data on firm performance in hotel industry
Yadegaridehkordi, E., Nilashi, M., Shuib, L. M., Nasir, M. H. N. M., Asadi, S., Samad, S., & Awang, N. F. (2019) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2019.100921 · Cited by 160 · see citing works
The Use of Social Network Sites as an E-Recruitment Tool
Melanthiou, Y., Pavlou, F., & Constantinou, E. (2015) · Journal of Transnational Management · doi:10.1080/15475778.2015.998141 · Cited by 158 · see citing works
Jia, Q., Guo, Y., & Barnes, S. J. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.10.022 · Cited by 156 · see citing works
Henderson, D., Sheetz, S. D., & Trinkle, B. S. (2012) · International Journal of Accounting Information Systems · doi:10.1016/j.accinf.2012.02.001 · Cited by 155 · see citing works
Alaiad, A., & Zhou, L. (2017) · IEEE Transactions on Professional Communication · doi:10.1109/tpc.2016.2632822 · Cited by 155 · see citing works
El-Haddadeh, R. (2019) · Information Systems Frontiers · doi:10.1007/s10796-019-09912-2 · Cited by 149 · see citing works
Performance impact of mobile banking: using the task-technology fit (TTF) approach
Tam, C., & Oliveira, T. (2016) · International Journal of Bank Marketing · doi:10.1108/ijbm-11-2014-0169 · Cited by 143 · see citing works
A study of e‐recruitment technology adoption in Malaysia
Tong, D. Y. K. (2009) · Industrial Management & Data Systems · doi:10.1108/02635570910930145 · Cited by 142 · see citing works
Tsou, H., & Hsu, S. H.-Y. (2014) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2014.09.001 · Cited by 141 · see citing works
Chan, F. T. S., & Chong, A. Y. (2012) · International Journal of Production Research · doi:10.1080/00207543.2012.693961 · Cited by 141 · see citing works
A Recruitment and Human Resource Management Technique Using Blockchain Technology for Industry 4.0
Onik, M. M. H., Miraz, M. H., & Kim, C. (2018) · Smart Cities Symposium (SCS) · doi:10.1049/cp.2018.1371 · Cited by 135 · see citing works
Critical Factors Influencing Decision to Adopt Human Resource Information System (HRIS) in Hospitals
Alam, M. G. R., Masum, A. K. M., Beh, L.-S., & Hong, C. S. (2016) · PLOS ONE · doi:10.1371/journal.pone.0160366 · Cited by 133 · see citing works
Shaltoni, A. M. (2017) · Journal of Business and Industrial Marketing · doi:10.1108/jbim-06-2016-0122 · Cited by 123 · see citing works
Factors Activating Big Data Adoption by Korean Firms
Park, J.-H., & Kim, Y. B. (2019) · Journal of Computer Information Systems · doi:10.1080/08874417.2019.1631133 · Cited by 115 · see citing works
Developing and validating a technology upgrade model
Wang, Y.-Y., Wang, Y.-S., & Lin, T. (2017) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2017.07.003 · Cited by 106 · see citing works
Task-Technology Fit Theory: A Survey and Synopsis of the Literature
Furneaux, B. (2011) · Integrated series on information systems/Integrated series in information systems · doi:10.1007/978-1-4419-6108-2_5 · Cited by 102 · see citing works
Salam, M. A. (2019) · Benchmarking An International Journal · doi:10.1108/bij-12-2018-0428 · Cited by 89 · see citing works
Human resource information systems: Information security concerns for organizations
Zafar, H. (2012) · Human Resource Management Review · doi:10.1016/j.hrmr.2012.06.010 · Cited by 88 · see citing works
Review of business intelligence through data analysis
Xia, B. S., & Gong, P. (2014) · Benchmarking An International Journal · doi:10.1108/bij-08-2012-0050 · Cited by 83 · see citing works
Assessing the role of IT-enabled process virtualization on green IT adoption
Thomas, M. A., Costa, D. S. A., & Oliveira, T. (2015) · Information Systems Frontiers · doi:10.1007/s10796-015-9556-3 · Cited by 78 · see citing works
Determinants of RFID adoption intention by SMEs: an empirical investigation
Wamba, S. F., Gunasekaran, A., Bhattacharya, M., & Dubey, R. (2016) · Production Planning & Control · doi:10.1080/09537287.2016.1167981 · Cited by 76 · see citing works
Demographic determinants of electronic commerce (EC) adoption by SMEs: A twist by location factors
Awa, H. O., Baridam, D. M., & Nwibere, B. M. (2015) · Journal of Enterprise Information Management · doi:10.1108/jeim-10-2013-0073 · Cited by 70 · see citing works
Social Media in Employee Selection and Recruitment
Landers, R. N., & Schmidt, G. B. (2016) · Springer eBooks · doi:10.1007/978-3-319-29989-1 · Cited by 68 · see citing works
Factors influencing E-HRM implementation in government organisations
Rahman, M., Mordi, C., & Nwagbara, U. (2018) · Journal of Enterprise Information Management · doi:10.1108/jeim-05-2017-0066 · Cited by 66 · see citing works
Industry 4.0: defining the research agenda
Erro‐Garcés, A. (2019) · Benchmarking An International Journal · doi:10.1108/bij-12-2018-0444 · Cited by 65 · see citing works
A practical review and taxonomy of fuzzy expert systems: methods and applications
Tavana, M., & Hajipour, V. (2019) · Benchmarking An International Journal · doi:10.1108/bij-04-2019-0178 · Cited by 64 · see citing works
Adoption of Industrial IoT (IIoT) in Auto-Component Manufacturing SMEs in India
Sivathanu, B. (2019) · Information Resources Management Journal · doi:10.4018/irmj.2019040103 · Cited by 63 · see citing works
Self-citationUnderstanding cloud ERP continuance intention and individual performance: a TTF-driven perspective
Cheng, Y. (2020) · Benchmarking An International Journal · doi:10.1108/bij-05-2019-0208 · Cited by 59 · see citing works
Adoption of Internet and Web Technology for Hotel Marketing: A Study of Hotels in Thailand
Khemthong, S., & Roberts, L. M. (2006) · Journal of Business Systems, Governance and Ethics · doi:10.15209/jbsge.v1i2.74 · Cited by 53 · see citing works
Assessing user experiences and usage intentions of m-banking service
Shih, K., Hung, H. F., & Lin, B. (2010) · International Journal of Mobile Communications · doi:10.1504/ijmc.2010.032974 · Cited by 52 · see citing works
Wang, S. L., & Lin, H. I. (2019) · Behaviour and Information Technology · doi:10.1080/0144929x.2019.1626486 · Cited by 52 · see citing works
E‐recruitment service providers review
Tong, D. Y. K., & Sivanand, C. N. (2005) · Employee Relations · doi:10.1108/01425450510569337 · Cited by 50 · see citing works
Hossain, M. A., Standing, C., & Chan, C. (2017) · Information Technology & People · doi:10.1108/itp-06-2016-0133 · Cited by 47 · see citing works
Daradkeh, M. K. (2019) · Information Technology & People · doi:10.1108/itp-10-2017-0359 · Cited by 47 · see citing works
The role of the government and E-Commerce adoption in small businesses in New Zealand
Al-Qirim, N. A. Y. (2006) · International Journal of Internet and Enterprise Management · doi:10.1504/ijiem.2006.011042 · Cited by 46 · see citing works
Information and Communication Technologies in Tourism 2019
(2018) · Springer eBooks · doi:10.1007/978-3-030-05940-8 · Cited by 42 · see citing works
Multi-level framework of open source software adoption
Qu, W. G., Yang, Z., & Wang, Z. (2010) · Journal of Business Research · doi:10.1016/j.jbusres.2010.11.023 · Cited by 41 · see citing works
A modelling approach to study learning processes with a focus on knowledge creation
Naeve, A., Yli-Luoma, P., Kravčík, M., & Lytras, M. D. (2008) · International Journal of Technology Enhanced Learning · doi:10.1504/ijtel.2008.020228 · Cited by 37 · see citing works
Information and Communication Technologies in Tourism 2018
(2017) · Springer eBooks · doi:10.1007/978-3-319-72923-7 · Cited by 36 · see citing works
Boudreau, J. W. (2013) · Human Resource Management Review · doi:10.1016/j.hrmr.2013.08.001 · Cited by 35 · see citing works
Benchmarking the human capital strategies of MNCs in Singapore
Huang, G. Z. D., Roy, M. H., Ahmed, Z. U., Heng, J. S. T., & Lim, J. H. M. (2002) · Benchmarking An International Journal · doi:10.1108/14635770210442699 · Cited by 34 · see citing works
Developments in Recruitment and Selection Research
Derous, E., & Fruyt, F. D. (2016) · International Journal of Selection and Assessment · doi:10.1111/ijsa.12123 · Cited by 33 · see citing works
Artificial intelligence divulges effective tactics of top management institutes of India
Kumar, S. (2019) · Benchmarking An International Journal · doi:10.1108/bij-08-2018-0251 · Cited by 33 · see citing works
Troshani, I., Jerram, C., & Gerrard, M. B. (2010) · Adelaide Research & Scholarship (AR&S) (University of Adelaide) · Cited by 32 · see citing works
A Novel Approach for Learning How to Automatically Match Job Offers and Candidate Profiles
Martínez-Gil, J., Paoletti, A. L., & Pichler, M. (2019) · Information Systems Frontiers · doi:10.1007/s10796-019-09929-7 · Cited by 31 · see citing works
Benchmarking of factors influencing adoption of innovation in software product SMEs
Hungund, S. S., & Mani, V. (2019) · Benchmarking An International Journal · doi:10.1108/bij-05-2018-0127 · Cited by 31 · see citing works
Recruitment methods, recruitment outcomes and information credibility and sufficiency
Muduli, A., & Trivedi, J. J. (2020) · Benchmarking An International Journal · doi:10.1108/bij-07-2019-0312 · Cited by 31 · see citing works
Creating a value proposition with a social media strategy for talent acquisition
Phillips-Wren, G. E., Doran, R., & Merrill, K. L. (2016) · Journal of Decision System · doi:10.1080/12460125.2016.1187398 · Cited by 30 · see citing works
Sun, J., & Teng, J. T. C. (2017) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2017.04.010 · Cited by 29 · see citing works
Best practices for talent acquisition in 21st-century academic libraries
Bugg, K. (2015) · Library Leadership & Management · doi:10.5860/llm.v29i4.7162 · Cited by 27 · see citing works
Moghddam, H. A., Rezaei, S., & Amin, M. (2015) · J for Global Business Advancement · doi:10.1504/jgba.2015.071331 · Cited by 25 · see citing works
The use of the Internet in recruitment—case studies from West Lothian, Scotland
Kinder, T. (2000) · Technovation · doi:10.1016/s0166-4972(00)00017-1 · Cited by 25 · see citing works
Osmonbekov, T. (2009) · Journal of Business Research · doi:10.1016/j.jbusres.2009.01.012 · Cited by 25 · see citing works
Virdyananto, A. L., Dewi, M. A. A., Hidayanto, A. N., & Hanief, S. (2016) · International Conference on Information Technology Systems and Innovation · doi:10.1109/icitsi.2016.7858227 · Cited by 25 · see citing works
McDonald, K., Fisher, S. L., & Connelly, C. E. (2017) · Emerald Group Publishing Limited eBooks · doi:10.1108/978-1-78714-315-920161004 · Cited by 25 · see citing works
Strategic human resource practices for innovation performance
Singh, N. (2018) · Benchmarking An International Journal · doi:10.1108/bij-08-2017-0215 · Cited by 25 · see citing works
Revaluation of FDI on the Economy Development of China ----- Is It an Entirely Unalloyed Benefit?
Lian, L., & Ma, H. (2010) · International Journal of Business and Management · doi:10.5539/ijbm.v5n10p184 · Cited by 22 · see citing works
Understanding the Adoption of Business Analytics and Intelligence
Cruz‐Jesus, F., Oliveira, T., & Naranjo-Zolotov, M. (2018) · Advances in intelligent systems and computing · doi:10.1007/978-3-319-77703-0_106 · Cited by 21 · see citing works
Strategic human resource management: a power based critique
Das, R., & Kodwani, A. D. (2018) · Benchmarking An International Journal · doi:10.1108/bij-09-2016-0143 · Cited by 20 · see citing works
Investigating a New Framework for Hospital Information System Adoption: A Case on Malaysia
Ahmadi, H., Ibrahim, O., & Nilashi, M. (2015) · Cited by 18 · see citing works
Job Search Sustem in Android Environment - Application of Intelligent Agents
Bogle, S. (2012) · International Journal of Information Sciences and Techniques · doi:10.5121/ijist.2012.2301 · Cited by 15 · see citing works
Exploring factors driving social recruiting: The case of Australian organizations
Kashi, K., Zheng, C. S.-M., & Molineux, J. (2016) · Journal of Organizational Computing and Electronic Commerce · doi:10.1080/10919392.2016.1194055 · Cited by 14 · see citing works
Repositioning the Non-incremental Changes and Business Strategic Windows Correlates
Awa, H. O., & Kalu, S. E. (2010) · International Journal of Business and Management · doi:10.5539/ijbm.v5n2p184 · Cited by 13 · see citing works
Qureshi, M. A., Sharif, A., & Afshan, S. (2018) · International Journal of Technology Enhanced Learning · doi:10.1504/ijtel.2018.10017608 · Cited by 12 · see citing works
Integration of TTF and network externalities for RFID adoption in healthcare industry
Gu, V. C., & Black, K. U. (2020) · International Journal of Productivity and Performance Management · doi:10.1108/ijppm-11-2018-0418 · Cited by 12 · see citing works
Phahlane, M. M., & Kekwaletswe, R. M. (2017) · Conference on Information Communications Technology and Society (ICTAS) · doi:10.1109/ictas.2017.7920654 · Cited by 11 · see citing works
Jia, Q., Guo, Y., & Barnes, S. J. (2016) · Journal of the Association for Information Systems · Cited by 11 · see citing works
Balaid, A., Rozan, M. Z. A., & Abdullah, N. S. (2014) · doi:10.1109/mysec.2014.6986014 · Cited by 3 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
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
Gama, F., & Magistretti, S. (2025) · Journal of Product Innovation Management · doi:10.1111/jpim.12698 · Cited by 388 · see citing works
Kinkel, S., Baumgartner, M., & Cherubini, E. (2022) · Technovation · doi:10.1016/j.technovation.2021.102375 · Cited by 316 · see citing works
Rodríguez-Espíndola, O., Chowdhury, S., Dey, P. K., Albores, P., & Emrouznejad, A. (2022) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2022.121562 · Cited by 279 · see citing works
Bag, S., Srivastava, G., Bashir, M. A., Kumari, S., Giannakis, M., & Chowdhury, A. H. (2021) · Benchmarking An International Journal · doi:10.1108/bij-07-2021-0415 · Cited by 225 · 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
Kaushal, N., Kaurav, R. P. S., Sivathanu, B., & Kaushık, N. (2021) · Management Review Quarterly · doi:10.1007/s11301-021-00249-2 · Cited by 157 · see citing works
Self-citationPerceptions and Acceptance of Artificial Intelligence: A Multi-Dimensional Study
Gerlich, M. (2023) · Social Sciences · doi:10.3390/socsci12090502 · Cited by 247 · see citing works
Adoption of AI-empowered industrial robots in auto component manufacturing companies
Pillai, R., Sivathanu, B., Mariani, M., Rana, N. P., Yang, B., & Dwivedi, Y. K. (2022) · Production Planning & Control · doi:10.1080/09537287.2021.1882689 · Cited by 195 · see citing works
Self-citationChowdhury, S., Rodríguez-Espíndola, O., Dey, P. K., & Budhwar, P. S. (2022) · Annals of Operations Research · doi:10.1007/s10479-021-04487-1 · Cited by 202 · see citing works
Artificial 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
Students' adoption of AI-based teacher-bots (T-bots) for learning in higher education
Pillai, R., Sivathanu, B., Metri, B., & Kaushik, N. (2024) · Information Technology & People · doi:10.1108/itp-02-2021-0152 · Cited by 176 · see citing works
Self-citationThe critical determinants impacting artificial intelligence adoption at the organizational level
Horani, O., Al-Adwan, A., Yaseen, H., Hmoud, H. Y., Al-rahmi, W., & Alkhalifah, A. A. (2023) · Information Development · doi:10.1177/02666669231166889 · Cited by 162 · 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
Why Do SMEs Adopt Artificial Intelligence-Based Chatbots?
Sharma, S., Singh, G., Islam, N., & Dhir, A. (2022) · IEEE Transactions on Engineering Management · doi:10.1109/tem.2022.3203469 · Cited by 161 · see citing works
Rožman, M., Oreški, D., & Tominc, P. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.1014434 · Cited by 135 · 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
Rožman, M., Oreški, D., & Tominc, P. (2023) · Sustainability · doi:10.3390/su15065019 · Cited by 124 · see citing works
Ayinaddis, S. G. (2025) · Journal of Innovation & Knowledge · doi:10.1016/j.jik.2025.100682 · Cited by 172 · see citing works
Rožman, M., Tominc, P., & Milfelner, B. (2023) · Cogent Business & Management · doi:10.1080/23311975.2023.2248732 · Cited by 115 · 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
Ghobakhloo, M., Asadi, S., Iranmanesh, M., Foroughi, B., Mubarak, M. F., & Yadegaridehkordi, E. (2023) · Technology in Society · doi:10.1016/j.techsoc.2023.102301 · Cited by 122 · see citing works
Rathore, S. P. S. (2023) · International Journal for Global Academic & Scientific Research · doi:10.55938/ijgasr.v2i2.50 · Cited by 108 · see citing works
Adewale, M. D., Azeta, A. A., Abayomi-Alli, A. A., & Sambo-Magaji, A. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e40025 · Cited by 97 · see citing works
Ronaghi, M. H. (2022) · Environment Development and Sustainability · doi:10.1007/s10668-022-02670-3 · Cited by 93 · 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
França, T. J. F., Mamede, H. S., Barroso, J., & Santos, V. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e14694 · Cited by 121 · see citing works
Dark side of algorithmic management on platform worker behaviors: A mixed‐method study
Lu, Y., Yang, M. M.-H., Zhu, J., & Wang, Y. (2024) · Human Resource Management · doi:10.1002/hrm.22211 · Cited by 85 · see citing works
Zadeh, A. V., Nikbin, D., Wong, S. L., & Hanifah, H. M. (2024) · Asia Pacific Journal of Marketing and Logistics · doi:10.1108/apjml-05-2024-0570 · Cited by 101 · see citing works
Prospects, drivers of and barriers to artificial intelligence adoption in project management
Shang, G., Low, S. P., & Lim, X. Y. V. (2023) · Built Environment Project and Asset Management · doi:10.1108/bepam-12-2022-0195 · Cited by 87 · see citing works
Agarwal, A. (2022) · foresight · doi:10.1108/fs-10-2021-0199 · Cited by 90 · see citing works
Shafie, M. R., Khosravi, H., Farhadpour, S., Das, S., & Ahmed, I. (2024) · Decision Analytics Journal · doi:10.1016/j.dajour.2024.100461 · Cited by 94 · see citing works
Akbarighatar, P., Pappas, I. O., & Vassilakopoulou, P. (2023) · International Journal of Information Management Data Insights · doi:10.1016/j.jjimei.2023.100193 · Cited by 76 · see citing works
AI Applications and Regulation: Mapping the Regulatory Strata
Viljanen, M., & Parviainen, H. (2022) · Frontiers in Computer Science · doi:10.3389/fcomp.2021.779957 · Cited by 70 · see citing works
Arora, A., Gupta, S., Devi, C., & Walia, N. (2023) · Benchmarking An International Journal · doi:10.1108/bij-10-2021-0621 · Cited by 80 · see citing works
Factors influencing the adoption of artificial intelligence systems: a systematic literature review
Khanfar, A. A. A., Mavi, R. K., Iranmanesh, M., & Gengatharen, D. E. (2025) · Management Decision · doi:10.1108/md-05-2023-0838 · Cited by 73 · see citing works
Artificial Intelligence: The Attitude of the Public and Representatives of Various Industries
Vasiljeva, T., Kreituss, I., & Lulle, I. (2021) · Journal of risk and financial management · doi:10.3390/jrfm14080339 · Cited by 77 · see citing works
How artificial intelligence impacts the competitive position of healthcare organizations
Mohamad, T. A., Bastone, A., Bernhard, F., & Schiavone, F. (2023) · Journal of Organizational Change Management · doi:10.1108/jocm-03-2023-0057 · Cited by 68 · see citing works
Shahzad, M. F., Xu, S., Naveed, W., Nusrat, S., & Zahid, I. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e21818 · Cited by 77 · see citing works
Gurjar, K., Jangra, A., Baber, H., Islam, M., & Sheikh, S. A. (2024) · IEEE Engineering Management Review · doi:10.1109/emr.2024.3355973 · Cited by 71 · see citing works
Delecraz, S., Eltarr, L., Becuwe, M., Bouxin, H., Boutin, N., & Oullier, O. (2022) · Journal of Responsible Technology · doi:10.1016/j.jrt.2022.100041 · Cited by 60 · see citing works
Huang, L., Chin, T., Papa, A., & Pisano, P. (2025) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2025.124013 · Cited by 60 · see citing works
Check the box! How to deal with automation bias in AI-based personnel selection
Kupfer, C., Prassl, R., Fleiß, J., Malin, C., Thalmann, S., & Kubicek, B. (2023) · Frontiers in Psychology · doi:10.3389/fpsyg.2023.1118723 · Cited by 59 · see citing works
Islam, M., Mamun, A. A., Afrin, S., Quaosar, G. M. A. A., & Uddin, M. A. (2022) · South Asian Journal of Human Resources Management · doi:10.1177/23220937221122329 · Cited by 74 · see citing works
Solaimani, S., & Swaak, L. (2023) · Journal of Engineering and Technology Management · doi:10.1016/j.jengtecman.2023.101760 · Cited by 62 · see citing works
Mukherjee, S., & Chittipaka, V. (2021) · FIIB Business Review · doi:10.1177/23197145211059243 · Cited by 56 · see citing works
A critical review of HR analytics: visualization and bibliometric analysis approach
Arora, M., Prakash, A., Dixit, S., Mittal, A., & Singh, S. (2022) · Information Discovery and Delivery · doi:10.1108/idd-05-2022-0038 · Cited by 25 · see citing works
Role of Artificial Intelligence (AI) In meeting Diversity, Equality and Inclusion (DEI) Goals
Jora, R. B., Sodhi, K. K., Mittal, P., & Saxena, P. (2022) · International Conference on Advanced Computing and Communication Systems (ICACCS) · doi:10.1109/icaccs54159.2022.9785266 · Cited by 55 · see citing works
Designing Collaborative Intelligence Systems for Employee-AI Service Co-Production
Blaurock, M., Büttgen, M., & Schepers, J. (2024) · Journal of Service Research · doi:10.1177/10946705241238751 · Cited by 58 · see citing works
Bhatnagr, P., & Rajesh, A. (2024) · Management Decision · doi:10.1108/md-07-2023-1145 · Cited by 63 · see citing works
Sandeep, M. M., Lavanya, V., & Balakrishnan, J. (2025) · Journal of Intellectual Capital · doi:10.1108/jic-05-2024-0155 · Cited by 61 · see citing works
Artificial Intelligence in Human Resources Management: A Review and Research Agenda
Gélinas, D., Sadreddin, A., & Vahidov, R. M. (2022) · Pacific Asia journal of the Association for Information Systems · doi:10.17705/1pais.14601 · Cited by 46 · see citing works
Digital HR Implementation for Business Growth in Industrial 5.0
Boopathi, S. (2024) · Advances in human resources management and organizational development book series · doi:10.4018/979-8-3693-1343-5.ch001 · Cited by 46 · see citing works
Transforming Financial Reporting with AI: Enhancing Accuracy and Timeliness
Antwi, B. O., Adelakun, B. O., & Eziefule, A. O. (2024) · International Journal of Advanced Economics · doi:10.51594/ijae.v6i6.1229 · Cited by 45 · see citing works
Smart HRM 4.0 for achieving organizational performance: a dynamic capability view perspective
Pillai, R., & Srivastava, K. B. L. (2022) · International Journal of Productivity and Performance Management · doi:10.1108/ijppm-04-2022-0174 · Cited by 44 · see citing works
Self-citationMahade, A., Elmahi, A., Alomari, K. M., & Abdalla, A. A. (2025) · Discover Sustainability · doi:10.1007/s43621-025-01114-y · Cited by 82 · see citing works
Revisiting the bullwhip effect: how can AI smoothen the bullwhip phenomenon?
Weisz, E., Herold, D. M., & Kummer, S. (2022) · The International Journal of Logistics Management · doi:10.1108/ijlm-02-2022-0078 · Cited by 48 · see citing works
Basnet, S. (2024) · International Journal of Research Publication and Reviews · doi:10.55248/gengpi.5.0124.0107 · Cited by 42 · see citing works
Determinants of artificial intelligence adoption: research themes and future directions
Khanfar, A. A. A., Mavi, R. K., Iranmanesh, M., & Gengatharen, D. E. (2024) · Information Technology and Management · doi:10.1007/s10799-024-00435-0 · Cited by 53 · see citing works
Human resources analytics: where do we go from here?
Bahuguna, P. C., Srivastava, R., & Tiwari, S. (2023) · Benchmarking An International Journal · doi:10.1108/bij-06-2022-0401 · Cited by 50 · see citing works
Adoption of artificial intelligence in financial services: a policy framework
Kumari, B., Kaur, J., & Swami, S. (2022) · Journal of Science and Technology Policy Management · doi:10.1108/jstpm-03-2022-0062 · Cited by 40 · see citing works
Armenia, S., Franco, E., Iandolo, F., Maielli, G., & Vito, P. (2024) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2023.123131 · Cited by 46 · see citing works
Hasani, T., Rezania, D., & Mohammadi, M. (2024) · International Journal of Engineering Business Management · doi:10.1177/18479790241257118 · Cited by 46 · see citing works
Hello! How Can I Help You? Role of Technology Appetite on AI Adoption in the Post‐Pandemic Era
Sharma, N., Payal, R., & Paul, J. (2025) · R and D Management · doi:10.1111/radm.12771 · Cited by 38 · see citing works
AL-Shboul, M. A. (2022) · Business Process Management Journal · doi:10.1108/bpmj-07-2022-0334 · Cited by 37 · see citing works
Exploring the Chatbot usage intention-A mediating role of Chatbot initial trust
Jyothsna, M., Venkata Subbaiah, P., & Kryvinska, N. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e33028 · Cited by 50 · see citing works
Sharma, S., & Singh, G. (2024) · International Journal of Systems Assurance Engineering and Management · doi:10.1007/s13198-024-02558-7 · Cited by 51 · see citing works
Abulail, R., Badran, O. N., Shkoukani, M., & Omeish, F. (2025) · De Computis · doi:10.3390/computers14060230 · Cited by 50 · see citing works
Mwita, K., & Kitole, F. A. (2025) · Discover Global Society · doi:10.1007/s44282-025-00175-8 · Cited by 34 · see citing works
Goswami, M., Jain, S., Alam, T., Deifalla, A. F., Ragab, A. E., & Khargotra, R. (2023) · Frontiers in Pharmacology · doi:10.3389/fphar.2023.1215706 · Cited by 33 · see citing works
Using artificial intelligence for hiring talents in a moderated mechanism
Islam, M., Rahman, M. M., Taher, M. A., Quaosar, G. M. A. A., & Uddin, M. A. (2024) · Future Business Journal · doi:10.1186/s43093-024-00303-x · Cited by 27 · see citing works
Bhatnagr, P., Rajesh, A., & Misra, R. (2024) · Management Decision · doi:10.1108/md-06-2023-0977 · Cited by 33 · see citing works
Raj, A., Shukla, D., Quadir, A., & Sharma, P. (2024) · Journal of Business and Industrial Marketing · doi:10.1108/jbim-09-2023-0512 · Cited by 46 · see citing works
Ali, M., Khan, T., & Sener, I. (2025) · Journal of Hospitality and Tourism Technology · doi:10.1108/jhtt-04-2024-0261 · Cited by 24 · see citing works
Wang, M., & Xue, F. (2021) · Sustainability · doi:10.3390/su132212627 · Cited by 33 · see citing works
Bodhi, R., Singh, T., & Joshi, Y. (2021) · Benchmarking An International Journal · doi:10.1108/bij-03-2021-0152 · Cited by 34 · see citing works
Arora, M., & Mittal, A. (2024) · Benchmarking An International Journal · doi:10.1108/bij-11-2023-0795 · Cited by 41 · see citing works
Talent acquisition-artificial intelligence to manage recruitment
Radhakrishna, V., Ravi, H., Praveenraj, D. D. W., Sudha, E., & Ashok, J. (2023) · E3S Web of Conferences · doi:10.1051/e3sconf/202337605001 · Cited by 32 · see citing works
AI and the Future of Talent Management
Tariq, M. U. (2024) · Advances in human resources management and organizational development book series · doi:10.4018/979-8-3693-1938-3.ch001 · Cited by 31 · see citing works
Chau, H. K. L., Ngo, T. T. A., Bui, C. T., & Tran, N. P. N. (2025) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2025.100725 · Cited by 52 · see citing works
Srivastava, G., Bag, S., Rahman, M. S., Pretorius, J. H. C., & Gani, M. O. (2022) · Benchmarking An International Journal · doi:10.1108/bij-03-2022-0160 · Cited by 31 · see citing works
Smart HRM 4.0 practices for organizational performance: the role of dynamic capabilities
Pillai, R., & Srivastava, K. B. L. (2023) · Benchmarking An International Journal · doi:10.1108/bij-05-2023-0288 · Cited by 37 · see citing works
Self-citationSalah, O. H., & Ayyash, M. M. (2024) · VINE Journal of Information and Knowledge Management Systems · doi:10.1108/vjikms-03-2023-0055 · Cited by 30 · see citing works
AI adoption in the hiring process – important criteria and extent of AI adoption
Bhatt, P. (2022) · foresight · doi:10.1108/fs-07-2021-0144 · Cited by 33 · see citing works
Fareri, S., Apreda, R., Mulas, V., & Alonso, R. (2023) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2023.122844 · Cited by 29 · see citing works
What Hinders Adoption of Artificial Intelligence for Cybersecurity in the Banking Sector
Ali, A. G., & Shah, M. H. (2024) · Information · doi:10.3390/info15120760 · Cited by 28 · see citing works
Assessing the Determinants of Metaverse Adoption for E-Commerce Retailing
Pillai, R., Sivathanu, B., Rana, N. P., & Niemann‐Struweg, I. (2024) · Journal of Computer Information Systems · doi:10.1080/08874417.2024.2416452 · Cited by 31 · see citing works
Self-citationPenpokai, S., Vuthisopon, S., & Saengnoree, A. (2023) · International Journal of Professional Business Review · doi:10.26668/businessreview/2023.v8i3.971 · Cited by 27 · see citing works
Arora, R., & Damarla, R. B. (2025) · Procedia Computer Science · doi:10.1016/j.procs.2025.03.247 · Cited by 26 · see citing works
Artificial Intelligence and the UK Construction Industry – Empirical Study
Jallow, H., Renukappa, S., Suresh, S., & Rahimian, F. P. (2022) · Engineering Management Journal · doi:10.1080/10429247.2022.2147381 · Cited by 26 · see citing works
Big Data Analytics Adoption in Manufacturing Companies: The Contingent Role of Data-Driven Culture
Thanabalan, P., Zadeh, A. V., Hanifah, H. M., & Ramayah, T. (2024) · Information Systems Frontiers · doi:10.1007/s10796-024-10491-0 · Cited by 27 · see citing works
A classification framework for generative artificial intelligence for social good
Crumbly, J., Pal, R., & Nezih Altay, A. (2024) · Technovation · doi:10.1016/j.technovation.2024.103129 · Cited by 28 · see citing works
Kaur, M., & Gandolfi, F. (2023) · Review of International Comparative Management · doi:10.24818/rmci.2023.3.382 · Cited by 24 · see citing works
Al‐Khatib, A. W. (2024) · Management Decision · doi:10.1108/md-09-2023-1525 · Cited by 24 · see citing works
Yu, Z., Hu, N., Zhao, Q., Hu, X. Y., Jia, C., Zhang, C., Liu, B., & Li, Y. (2024) · Journal of Medical Internet Research · doi:10.2196/62768 · Cited by 28 · see citing works
Abdulkareem, A. K., Oladimeji, K. A., Ishola, A. A., Lawan, B. M., Umar, A. Y., & Adejumo, A. (2024) · International Journal of Public Sector Management · doi:10.1108/ijpsm-10-2023-0307 · Cited by 25 · see citing works
Chapano, M., Mey, M. R., & Werner, A. (2023) · SA Journal of Human Resource Management · doi:10.4102/sajhrm.v21i0.2085 · Cited by 23 · see citing works
Ioakeimidou, D., Chatzoudes, D., Symeonidis, S., & Chatzoglou, P. (2023) · International Journal of Manpower · doi:10.1108/ijm-10-2022-0496 · Cited by 27 · see citing works
Yang, Y. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.600218 · Cited by 22 · see citing works
Benabou, A., & Touhami, F. (2025) · International journal of production management and engineering · doi:10.4995/ijpme.2025.21900 · Cited by 33 · see citing works
- Authors
- Pillai, R., & Sivathanu, B.
- Affiliations
- Sri Balaji University, Pune (IN)
- Venue
- Benchmarking: An International Journal
- Publisher
- Emerald
- Published
- 2020-08-14
- Volume
- 27
- Issue
- 9
- Pages
- 2599-2629
- ISSN
- 1463-5771 (ISSN-L)
- OpenAlex
- W3049223401
- Cited by
- 422
- References
- 146
- Citations by year
- 2026: 67 · 2025: 104 · 2024: 116 · 2023: 72 · 2022: 41 · 2021: 22
- FWCI
- 36.47
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Benchmarking An International Journal (publishedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › AI and HR Technologies
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Employer Branding and e-HRM
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Keywords
- artificial intelligence adoption, talent acquisition, technology adoption, task-technology fit, technology-organization-environment framework, cost-effectiveness, relative advantage, top management support, competitive pressure, privacy and security concerns, human resource management
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