Cited by 422AI and HR TechnologiesEmployer Branding and e-HRMTechnology Adoption and User Behaviour

The DOI matches its Crossref record; 147 of the 147 references it cites were found in a registry or an index.

Adoption of artificial intelligence (AI) for talent acquisition in IT/ITeS organizations

Pillai, Rajasshrie, Sivathanu, Brijesh·2020·Benchmarking: An International Journal

DOI 10.1108/bij-04-2020-0186

Open this paper in CoChat — free account

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

Crossref · 10.1108/bij-04-2020-0186

Cites

147 of 147 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

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?

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
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
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
Common method biases in behavioral research: A critical review of the literature and recommended remedies
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
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
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
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
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
Task-Technology Fit and Individual Performance
Goodhue, D. L., & Thompson, R. L. (1995) · MIS Quarterly · doi:10.2307/249689 · Cited by 6,006
Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy
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
Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust
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 1,944
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
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
Assessing the determinants of cloud computing adoption: An analysis of the manufacturing and services sectors
Oliveira, T., Thomas, M. A., & Espadanal, M. (2014) · Information & Management · doi:10.1016/j.im.2014.03.006 · Cited by 1,340
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
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
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
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
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
Innovation diffusion in global contexts: determinants of post-adoption digital transformation of European companies
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
The global “war for talent”
Beechler, S., & Woodward, I. C. (2009) · Journal of International Management · doi:10.1016/j.intman.2009.01.002 · Cited by 767
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
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
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
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
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
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 608
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 593
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 586
Understanding knowledge management system usage antecedents: An integration of social cognitive theory and task technology fit
Lin, T., & Huang, C.-C. (2008) · Information & Management · doi:10.1016/j.im.2008.06.004 · Cited by 540
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 529
Notes from the Editors: Redefining some methodological criteria for the journal⋆
Guide, V. D. R., & Ketokivi, M. A. (2015) · Journal of Operations Management · doi:10.1016/s0272-6963(15)00056-x · Cited by 518
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 505
A model of acceptance of augmented-reality interactive technology: the moderating role of cognitive innovativeness
Huang, T.-L., & Liao, S. (2015) · Electronic Commerce Research · doi:10.1007/s10660-014-9163-2 · Cited by 476
Effect of perceived value and social influences on mobile app stickiness and in-app purchase intention
Hsu, C., & Lin, J. C. (2016) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2016.04.012 · Cited by 455
Web-based recruitment: Effects of information, organizational brand, and attitudes toward a Web site on applicant attraction.
Allen, D. G., Mahto, R. V., & Otondo, R. F. (2007) · Journal of Applied Psychology · doi:10.1037/0021-9010.92.6.1696 · Cited by 433
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 430
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
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 427
Self-citation
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 415
Understanding the determinants of big data analytics (BDA) adoption in logistics and supply chain management
Lai, Y., Huifen, S., & Ren, J. (2018) · The International Journal of Logistics Management · doi:10.1108/ijlm-06-2017-0153 · Cited by 395
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
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
Antecedents of customers’ acceptance of artificially intelligent robotic device use in hospitality services
Lin, H., Chi, O. H., & Gürsoy, D. (2019) · Journal of Hospitality Marketing & Management · doi:10.1080/19368623.2020.1685053 · Cited by 388
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 388
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 385
Applying artificial intelligence: implications for recruitment
Upadhyay, A. K., & Khandelwal, K. (2018) · Strategic HR Review · doi:10.1108/shr-07-2018-0051 · Cited by 380
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 350
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 335
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
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 317
The adoption of eCommerce communications and applications technologies in small businesses in New Zealand
Al-Qirim, N. A. Y. (2007) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2007.02.012 · Cited by 313
Continuance Intentions to Use Gamification for Training in Higher Education: Integrating the Technology Acceptance Model (TAM), Social Motivation, and Task Technology Fit (TTF)
Vanduhe, V. Z., Nat, M. C., & Hasan, H. F. (2020) · IEEE Access · doi:10.1109/access.2020.2966179 · Cited by 313
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 302
Online stickiness: its antecedents and effect on purchasing intention
Lin, J. C. (2007) · Behaviour and Information Technology · doi:10.1080/01449290600740843 · Cited by 302
AN EMPIRICAL ANALYSIS OF FACTORS INFLUENCING INTERNET/E-BUSINESS TECHNOLOGIES ADOPTION BY SMES IN CANADA
Ifinedo, P. (2011) · International Journal of Information Technology & Decision Making · doi:10.1142/s0219622011004543 · Cited by 301
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 301
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
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
Perceived fit and satisfaction on web learning performance: IS continuance intention and task-technology fit perspectives
Lin, W.-S. (2012) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2012.01.006 · Cited by 285
Adoption of Robots, Artificial Intelligence and Service Automation by Travel, Tourism and Hospitality Companies – A Cost-Benefit AnalysisPreprint
Ivanov, S. H., & Webster, C. (2017) · SSRN Electronic Journal · Cited by 278
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
AN EMPIRICAL STUDY OF FACTORS AFFECTING ELECTRONIC COMMERCE ADOPTION AMONG SMES IN MALAYSIA / VEIKSNIŲ, TURINČIŲ ĮTAKOS ELEKTORINEI PREKYBAI, STUDIJA: MALAIZIJOS PAVYZDYS
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
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
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
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 227
What drives purchase intention in the context of online content services? The moderating role of ethical self-efficacy for online piracy
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
A meta-analysis of relationships between organizational characteristics and IT innovation adoption in organizations
Hameed, M. A., Counsell, S., & Swift, S. (2012) · Information & Management · doi:10.1016/j.im.2012.05.002 · Cited by 219
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 219
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 215
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 207
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
Structural equation modeling for multi-stage analysis on Radio Frequency Identification (RFID) diffusion in the health care industry
Chong, A. Y., & Chan, F. T. S. (2012) · Expert Systems with Applications · doi:10.1016/j.eswa.2012.01.201 · Cited by 199
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
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
Refining and extending task–technology fit theory: Creation of two task–technology fit scales and empirical clarification of the construct
Howard, M. C., & Rose, J. C. (2018) · Information & Management · doi:10.1016/j.im.2018.12.002 · Cited by 176
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
Digital Innovation Dynamics Influence on Organisational Adoption: The Case of Cloud Computing Services
El-Haddadeh, R. (2019) · Information Systems Frontiers · doi:10.1007/s10796-019-09912-2 · Cited by 169
An investigation into the factors influencing the adoption of B2B trading exchanges in small businesses
Quaddus, M., & Hofmeyer, G. (2007) · European Journal of Information Systems · doi:10.1057/palgrave.ejis.3000671 · Cited by 167
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
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 164
Patients' Adoption of WSN-Based Smart Home Healthcare Systems: An Integrated Model of Facilitators and Barriers
Alaiad, A., & Zhou, L. (2017) · IEEE Transactions on Professional Communication · doi:10.1109/tpc.2016.2632822 · Cited by 160
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
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
Enterprise 2.0 post-adoption: Extending the information system continuance model based on the technology-Organization-environment framework
Jia, Q., Guo, Y., & Barnes, S. J. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.10.022 · Cited by 156
The determinants of inter-organizational and internal in-house adoption of XBRL: A structural equation model
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
Determinants of mobile supply chain management system diffusion: a structural equation analysis of manufacturing firms
Chan, F. T. S., & Chong, A. Y. (2012) · International Journal of Production Research · doi:10.1080/00207543.2012.693961 · Cited by 150
A study of e‐recruitment technology adoption in Malaysia
Tong, D. Y. K. (2009) · Industrial Management & Data Systems · doi:10.1108/02635570910930145 · Cited by 149
Performance effects of technology–organization–environment openness, service co-production, and digital-resource readiness: The case of the IT industry
Tsou, H., & Hsu, S. H.-Y. (2014) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2014.09.001 · Cited by 148
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
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
From websites to social media: exploring the adoption of internet marketing in emerging industrial markets
Shaltoni, A. M. (2017) · Journal of Business and Industrial Marketing · doi:10.1108/jbim-06-2016-0122 · Cited by 123
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
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 112
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 112
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 110
Analyzing manufacturing strategies and Industry 4.0 supplier performance relationships from a resource-based perspective
Salam, M. A. (2019) · Benchmarking An International Journal · doi:10.1108/bij-12-2018-0428 · Cited by 89
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 88
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
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 81
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 78
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
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
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 65
Self-citation
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
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
Understanding 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
Integrating TTF and IDT to evaluate user intention of big data analytics in mobile cloud healthcare system
Wang, S. L., & Lin, H. I. (2019) · Behaviour and Information Technology · doi:10.1080/0144929x.2019.1626486 · Cited by 54
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
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
E‐recruitment service providers review
Tong, D. Y. K., & Sivanand, C. N. (2005) · Employee Relations · doi:10.1108/01425450510569337 · Cited by 50
The development and validation of a two-staged adoption model of RFID technology in livestock businesses
Hossain, M. A., Standing, C., & Chan, C. (2017) · Information Technology & People · doi:10.1108/itp-06-2016-0133 · Cited by 47
Determinants of visual analytics adoption in organizations: Knowledge discovery through content analysis of online evaluation reviews
Daradkeh, M. K. (2019) · Information Technology & People · doi:10.1108/itp-10-2017-0359 · Cited by 47
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
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 44
Information and Communication Technologies in Tourism 2019
(2018) · Springer eBooks · doi:10.1007/978-3-030-05940-8 · Cited by 42
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
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
Information and Communication Technologies in Tourism 2018
(2017) · Springer eBooks · doi:10.1007/978-3-319-72923-7 · Cited by 36
Appreciating and ‘retooling’ diversity in talent management conceptual models: A commentary on “The psychology of talent management: A review and research agenda”
Boudreau, J. W. (2013) · Human Resource Management Review · doi:10.1016/j.hrmr.2013.08.001 · Cited by 35
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
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
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
Exploring the organizational adoption of Human Resources Information Systems (HRIS) in the Australian public sector
Troshani, I., Jerram, C., & Gerrard, M. B. (2010) · Adelaide Research & Scholarship (AR&S) (University of Adelaide) · Cited by 32
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
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
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
The construct of information systems use benefits: Theoretical explication of its underlying dimensions and the development of a measurement scale
Sun, J., & Teng, J. T. C. (2017) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2017.04.010 · Cited by 29
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
Examining job seekers' perception and behavioural intention toward online recruitment: a PLS path modelling approach
Moghddam, H. A., Rezaei, S., & Amin, M. (2015) · J for Global Business Advancement · doi:10.1504/jgba.2015.071331 · Cited by 25
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
Reseller adoption of manufacturers' e-business tools: The impact of social enforcement, technology–relationship fit and the mediating role of reseller benefits
Osmonbekov, T. (2009) · Journal of Business Research · doi:10.1016/j.jbusres.2009.01.012 · Cited by 25
User acceptance of human resource information system: An integration model of Unified Theory of Acceptance and Use of Technology (UTAUT), Task Technology Fit (TTF), and Symbolic Adoption
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
e-HRM Systems in Support of “Smart” Workforce Management: An Exploratory Case Study of System Success
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
Strategic human resource practices for innovation performance
Singh, N. (2018) · Benchmarking An International Journal · doi:10.1108/bij-08-2017-0215 · Cited by 25
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
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
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
Investigating a New Framework for Hospital Information System Adoption: A Case on Malaysia
Ahmadi, H., Ibrahim, O., & Nilashi, M. (2015) · Cited by 18
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 16
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
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
Acceptance of Learning Management System in University Students: An integrating framework of Modified UTAUT2 and TTF Theories
Qureshi, M. A., Sharif, A., & Afshan, S. (2018) · International Journal of Technology Enhanced Learning · doi:10.1504/ijtel.2018.10017608 · Cited by 12
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
A conceptual research framework for human resource information systems adoption and use in universities
Phahlane, M. M., & Kekwaletswe, R. M. (2017) · Conference on Information Communications Technology and Society (ICTAS) · doi:10.1109/ictas.2017.7920654 · Cited by 11
E2.0 Post-Adoption: Extending the IS Continuance Model Based on the Technology-Organization-Environment Framework
Jia, Q., Guo, Y., & Barnes, S. J. (2016) · Journal of the Association for Information Systems · Cited by 11
Influential factors of knowledge maps adoption in software development organizations: A pilot case study
Balaid, A., Rozan, M. Z. A., & Abdullah, N. S. (2014) · doi:10.1109/mysec.2014.6986014 · Cited by 3

Research works printed but not linked: 25

1980, Understanding Attitudes and Predicting Behavior
2012, Conceptual model for examining knowledge management system (KMS) adoption in public sector organizations in Saudi Arabia, Gov Workshop, 2, 1
2001, Social cognitive theory of mass communication media psychology, Psychology, 3, 265
2017, Jobs Lost, Jobs Gained: Workforce Transitions in a Time of Automation, 1
2018, Insight - Amazon Scraps Secret AI Recruiting Tool that Showed Bias against Women
1990, The context for change: organization, technology and environment. The processes of technological innovation, The Processes of Technological Innovation, 199, 151
2017, Biometrics won't solve our data-security crisis, Harvard Business Review
2016, Impact of technology on recruitment process and its impact on service quality of HR service provider, BIMS Journal of Management, 3, 26
2000, Web portals usher in, drive away business, National Underwriter/Property and Casualty Risk and Benefits, 104, 19
1955, A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence
2001, The War for Talent
1978, Psychometric Theory
2011, Literature Review of Information Technology Adoption Models at Firm Level
2017, A Multidimensional Framework for Human Resource Information Systems Adoption and Use in a South African University
2016, E-recruitment–an organizational change. International, Journal of Multidisciplinary Approach and Studies, 3, 78
2017, Factors influencing E-HRM implementation in government organisations, Journal of Enterprise Information Management, 31, 247
2003, Diffusion of Innovations
1983, Diffusion of. Innovations. Glencoe
2006, Information System Success: Individual and Organizational Determinants
2007, Research in E-HRM: Review and Implications, 19
2009, Trust and Electronic Government Success: An Empirical Study, 99
1991, An integrated model of information system Adoption in small business, Journal of Managemnet Inforamtion System, 15, 187
1990, The Process of Technology Innovation
2005, Adoption of Electronic Government Services Among Business Organizations in Singapore, 417
2013, Computers in Human Behavior Why Aren' T Organizations Adopting Virtual Worlds?, 772

Sorted by citations

Unlocking the value of artificial intelligence in human resource management through AI capability framework
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
Artificial intelligence in innovation management: A review of innovation capabilities and a taxonomy of AI applications
Gama, F., & Magistretti, S. (2025) · Journal of Product Innovation Management · doi:10.1111/jpim.12698 · Cited by 388
Prerequisites for the adoption of AI technologies in manufacturing: evidence from a worldwide sample of manufacturing companies
Kinkel, S., Baumgartner, M., & Cherubini, E. (2022) · Technovation · doi:10.1016/j.technovation.2021.102375 · Cited by 316
Analysis of the adoption of emergent technologies for risk management in the era of digital manufacturing
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
Journey of customers in this digital era: Understanding the role of artificial intelligence technologies in user engagement and conversion
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 286
“engage customers via social media websites (Pillai and Sivathanu, 2020).”

See all 422

Authors: Pillai, R., & Sivathanu, B.
Affiliations: Sri Balaji University, Pune (IN)
ORCID: Pillai, Rajasshrie
Sivathanu, Brijesh
Venue: Benchmarking: An International Journal
Publisher: Emerald
Published: 2020-08-14
Volume: 27
Issue: 9
Pages: 2599-2629
ISSN: 1463-5771 (ISSN-L)
DOI: 10.1108/bij-04-2020-0186
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
Licence: www.emerald.com/insight/site-policies (tdm)
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

Adoption of artificial intelligence (AI) for talent acquisition in IT/ITeS organizations

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Citations

Cites

Cited by

Related

Metadata

Record

About these checks