Cited by 531AI and HR TechnologiesInformation Systems Theories and ImplementationKnowledge Management and Sharing

The DOI matches its Crossref record; 132 of the 132 references it cites were found in a registry or an index.

AI-employee collaboration and business performance: Integrating knowledge-based view, socio-technical systems and organisational socialisation framework

Chowdhury, Soumyadeb, Budhwar, Pawan, Dey, Prasanta Kumar, Joel-Edgar, Sian, Abadie, Amelie·2022·Journal of Business Research

DOI 10.1016/j.jbusres.2022.01.069

Open this paper in CoChat — free account

Integrity signals

Registry

Crossref · 10.1016/j.jbusres.2022.01.069

Cites

132 of 132 references verified0 citation errors · 0 not checkable

Statistics

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

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

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
Firm Resources and Sustained Competitive Advantage
Barney, J. (1991) · Journal of Management · doi:10.1177/014920639101700108 · Cited by 48,334
A new criterion for assessing discriminant validity in variance-based structural equation modeling
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-014-0403-8 · Cited by 38,459
Statistical Power Analysis for the Behavioral Sciences (2nd ed.).
Lachenbruch, P. A., & Cohen, J. (1989) · Journal of the American Statistical Association · doi:10.2307/2290095 · Cited by 37,421
Multivariate Data Analysis
Einax, J. W., Zwanziger, H. W., & Geiß, S. (1997) · Wiley eBooks · doi:10.1002/352760216x.ch5 · Cited by 18,779
Toward a knowledge-based theory of the firm
Grant, R. M. (1996) · Strategic Management Journal · doi:10.1002/smj.4250171110 · Cited by 16,157
Making sense of cronbach’s alpha.
Tavakol, M., & Dennick, R. (2011) · International Journal of Medical Education · doi:10.5116/ijme.4dfb.8dfd · Cited by 15,126
The future of employment: How susceptible are jobs to computerisation?
Frey, C. B., & Osborne, M. A. (2017) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2016.08.019 · Cited by 8,727
A Resource-Based Perspective on Information Technology Capability and Firm Performance: An Empirical Investigation1
Bharadwaj, A. S. (2000) · MIS Quarterly · doi:10.2307/3250983 · Cited by 5,042
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
Untitled work
(1999) · PubMed · Cited by 4,115
Sample Size Requirements for Structural Equation Models: An Evaluation of Power, Bias, and Solution Propriety
Wolf, E. J., Harrington, K. M., Clark, S. L., & Miller, M. W. (2013) · Educational and Psychological Measurement · doi:10.1177/0013164413495237 · Cited by 3,931
Construct Measurement and Validation Procedures in MIS and Behavioral Research: Integrating New and Existing Techniques1
MacKenzie, S. B., Podsakoff, P. M., & Podsakoff, N. P. (2011) · MIS Quarterly · doi:10.2307/23044045 · Cited by 3,165
Human trust in artificial intelligence: Review of empirical research
Glikson, E., & Woolley, A. W. (2020) · Academy of Management Annals · doi:10.5465/annals.2018.0057 · Cited by 2,921
How artificial intelligence will change the future of marketing
Davenport, T., Guha, A., Grewal, D., & Bressgott, T. (2020) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-019-00696-0 · Cited by 2,875
Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making
Jarrahi, M. H. (2018) · Business Horizons · doi:10.1016/j.bushor.2018.03.007 · Cited by 2,772
Strategic alliance structuring: a game theoretic and transaction cost examination of interfirm cooperation
Parkhe, A. (1993) · Academy of Management Journal · doi:10.2307/256759 · Cited by 2,698
A brief history of artificial intelligence: On the past, present, and future of artificial intelligence
Haenlein, M., & Kaplan, A. (2019) · California Management Review · doi:10.1177/0008125619864925 · Cited by 2,655
Artificial intelligence for decision making in the era of Big Data – evolution, challenges and research agenda
Duan, Y., Edwards, J. S., & Dwivedi, Y. K. (2019) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2019.01.021 · Cited by 2,628
Towards a theory of supply chain management: the constructs and measurements
Chen, I. J., & Paulraj, A. (2004) · Journal of Operations Management · doi:10.1016/j.jom.2003.12.007 · Cited by 2,501
Handbook of Complementary Methods in Education Research
Green, J. L., Green, J. L., Camilli, G., Camilli, G., Elmore, P. B., & Elmore, P. B. (2012) · Routledge eBooks · doi:10.4324/9780203874769 · Cited by 2,029
Issues and Opinion on Structural Equation Modeling
Chin, W. W. (1998) · MIS Quarterly · doi:10.2307/249674 · Cited by 1,859
ARTIFICIAL INTELLIGENCE FOR THE REAL WORLD
Davenport, T. H., & Ronanki, R. (2023) · International Research Journal of Modernization in Engineering Technology and Science · doi:10.56726/irjmets42512 · Cited by 1,829
The Role of Tacit Knowledge in Group Innovation
Leonard, D., & Sensiper, S. (1998) · California Management Review · doi:10.2307/41165946 · Cited by 1,702
Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm performance
Mikalef, P., & Gupta, M. (2021) · Information & Management · doi:10.1016/j.im.2021.103434 · Cited by 1,700
Empirical Evaluation of the Revised Technology Acceptance Model
Szajna, B. (1996) · Management Science · doi:10.1287/mnsc.42.1.85 · Cited by 1,656
Artificial Intelligence in Human Resources Management: Challenges and a Path Forward
Tambe, P., Cappelli, P., & Yakubovich, V. (2019) · California Management Review · doi:10.1177/0008125619867910 · Cited by 1,609
Newcomer adjustment during organizational socialization: A meta-analytic review of antecedents, outcomes, and methods.
Bauer, T. N., Bodner, T., Erdoğan, B., Truxillo, D. M., & Tucker, J. S. (2007) · Journal of Applied Psychology · doi:10.1037/0021-9010.92.3.707 · Cited by 1,560
A Confirmatory Factor Analysis of the End-User Computing Satisfaction Instrument
Doll, W. J., Xia, W., & Torkzadeh, G. (1994) · MIS Quarterly · doi:10.2307/249524 · Cited by 1,497
Exploring the relationship between big data analytics capability and competitive performance: The mediating roles of dynamic and operational capabilities
Mikalef, P., Krogstie, J., Pappas, I. O., & Pavlou, P. (2020) · Information & Management · doi:10.1016/j.im.2019.05.004 · Cited by 1,373
The technology acceptance model and the World Wide Web
Lederer, A. L., Maupin, D. J., Sena, M. P., & Zhuang, Y. (2000) · Decision Support Systems · doi:10.1016/s0167-9236(00)00076-2 · Cited by 1,372
A knowledge-based theory of the firm—The problem-solving perspective
Nickerson, J. A., & Zenger, T. R. (2004) · Organization Science · doi:10.1287/orsc.1040.0093 · Cited by 1,342
Artificial intelligence and business models in the sustainable development goals perspective: A systematic literature review
Vaio, A. D., Palladino, R., Hassan, R., & Escobar, O. (2020) · Journal of Business Research · doi:10.1016/j.jbusres.2020.08.019 · Cited by 1,320
Driving forces and barriers of Industry 4.0: Do multinational and small and medium-sized companies have equal opportunities?
Horváth, D., & Szabó, R. Z. (2019) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2019.05.021 · Cited by 1,281
Influence of artificial intelligence (AI) on firm performance: the business value of AI-based transformation projects
Wamba-Taguimdje, S.-L., Fosso Wamba, S., Kala Kamdjoug, J. R., & Tchatchouang Wanko, C. E. (2020) · Business Process Management Journal · doi:10.1108/bpmj-10-2019-0411 · Cited by 1,280
Effect of Information Systems Resources and Capabilities on Firm Performance: A Resource-Based Perspective
RAVICHANDRAN, T., LERTWONGSATIEN, C., & LERTWONGSATIEN, C. (2005) · Journal of Management Information Systems · doi:10.1080/07421222.2005.11045820 · Cited by 1,238
Smart technology, artificial intelligence, robotics, and algorithms (STARA): employees' perceptions of our future workplace
Brougham, D., & Haar, J. (2018) · Journal of Management & Organization · doi:10.1017/jmo.2016.55 · Cited by 1,117
Organizational Decision-Making Structures in the Age of Artificial Intelligence
Shrestha, Y. R., Ben-Menahem, S. M., & von Krogh, G. (2019) · California Management Review · doi:10.1177/0008125619862257 · Cited by 1,108
Role of institutional pressures and resources in the adoption of big data analytics powered artificial intelligence, sustainable manufacturing practices and circular economy capabilities
Bag, S., Pretorius, J. H. C., Gupta, S., & Dwivedi, Y. K. (2020) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2020.120420 · Cited by 1,042
Information technology-enabled dynamic capabilities and their indirect effect on competitive performance: Findings from PLS-SEM and fsQCA
Mikalef, P., & Pateli, A. (2017) · Journal of Business Research · doi:10.1016/j.jbusres.2016.09.004 · Cited by 1,038
Deep Learning for Identifying Metastatic Breast CancerPreprint
Wang, D., Khosla, A., Gargeya, R., Irshad, H., & Beck, A. H. (2016) · arXiv.org · doi:10.48550/arxiv.1606.05718 · Cited by 1,028
Supply chain resilience: Conceptualization and scale development using dynamic capability theory
Chowdhury, M. M. H., & Quaddus, M. (2017) · International Journal of Production Economics · doi:10.1016/j.ijpe.2017.03.020 · Cited by 988
Adoption of AI-based chatbots for hospitality and tourism
Pillai, R., & Sivathanu, B. (2020) · International Journal of Contemporary Hospitality Management · doi:10.1108/ijchm-04-2020-0259 · Cited by 986
Dynamic capabilities, creativity and innovation capability and their impact on competitive advantage and firm performance: The moderating role of entrepreneurial orientation
Ferreira, J., Coelho, A., & Moutinho, L. (2018) · Technovation · doi:10.1016/j.technovation.2018.11.004 · Cited by 958
Mapping the challenges of artificial intelligence in the public sector: Evidence from public healthcare
Sun, T. Q., & Medaglia, R. (2019) · Government Information Quarterly · doi:10.1016/j.giq.2018.09.008 · Cited by 948
Big data and predictive analytics and manufacturing performance: integrating institutional theory, resource‐based view and big data culture
Dubey, R., Gunasekaran, A., Childe, S. J., Blome, C., & Papadopoulos, T. (2019) · British Journal of Management · doi:10.1111/1467-8551.12355 · Cited by 881
A Contingency Theory of Socialization
Feldman, D. C. (1976) · Administrative Science Quarterly · doi:10.2307/2391853 · Cited by 867
Machines as teammates: A research agenda on AI in team collaboration
Seeber, I., Bittner, E., Briggs, R. O., de Vreede, T., de Vreede, G.-J., Elkins, A., Maier, R., Merz, A. B., Oeste-Reiß, S., Randrup, N., et al. (2020) · Information & Management · doi:10.1016/j.im.2019.103174 · Cited by 835
Rising with the machines: A sociotechnical framework for bringing artificial intelligence into the organization
Makarius, E. E., Mukherjee, D., Fox, J. D., & Fox, A. K. (2020) · Journal of Business Research · doi:10.1016/j.jbusres.2020.07.045 · Cited by 780
The impact of the blockchain on the supply chain: a theory-based research framework and a call for action
Treiblmaier, H. (2018) · Supply Chain Management · doi:10.1108/scm-01-2018-0029 · Cited by 737
Implementing a digital strategy: Learning from the experience of three digital transformation projects
Correani, A., De Massis, A., Frattini, F., Petruzzelli, A. M., & Natalicchio, A. (2020) · California Management Review · doi:10.1177/0008125620934864 · Cited by 727
A LONGITUDINAL INVESTIGATION OF THE RELATIONSHIPS BETWEEN JOB INFORMATION SOURCES, APPLICANT PERCEPTIONS OF FIT, AND WORK OUTCOMES
Saks, A. M., & Ashforth, B. E. (1997) · Personnel Psychology · doi:10.1111/j.1744-6570.1997.tb00913.x · Cited by 719
Rulers of the world, unite! The challenges and opportunities of artificial intelligence
Kaplan, A., & Haenlein, M. (2020) · Business Horizons · doi:10.1016/j.bushor.2019.09.003 · Cited by 718
The Multiple Socialization Of Organization Members
Feldman, D. C. (1981) · Academy of Management Review · doi:10.5465/amr.1981.4287859 · Cited by 715
Ready or not, AI comes—an interview study of organizational AI readiness factors
Jöhnk, J., Weißert, M., & Wyrtki, K. (2021) · Business & Information Systems Engineering · doi:10.1007/s12599-020-00676-7 · Cited by 637
A supply chain traceability system for food safety based on HACCP, blockchain & Internet of things
Tian, F. (2017) · International Conference on Service Systems and Service Management · doi:10.1109/icsssm.2017.7996119 · Cited by 594
The Feeling Economy: Managing in the Next Generation of Artificial Intelligence (AI)
Huang, M.-H., Rust, R., & Maksimovic, V. (2019) · California Management Review · doi:10.1177/0008125619863436 · Cited by 591
Strategic alignment between business and information technology: a knowledge-based view of behaviors, outcome, and consequences
Kearns, G. S., & Sabherwal, R. (2006) · Journal of Management Information Systems · doi:10.2753/mis0742-1222230306 · Cited by 573
Understanding managers’ attitudes and behavioral intentions towards using artificial intelligence for organizational decision-making
Cao, G., Duan, Y., Edwards, J. S., & Dwivedi, Y. K. (2021) · Technovation · doi:10.1016/j.technovation.2021.102312 · Cited by 571
Platform Ecosystems: Aligning Architecture, Governance, and Strategy
Tiwana, A. (2013) · Cited by 563
Dynamics between blockchain adoption determinants and supply chain performance: An empirical investigation
Wamba, S. F., de Queiroz, M. M., & Trinchera, L. (2020) · International Journal of Production Economics · doi:10.1016/j.ijpe.2020.107791 · Cited by 554
Socio-Technical Systems Theory: An Intervention Strategy for Organizational Development
Appelbaum, S. H. (1997) · Management Decision · doi:10.1108/00251749710173823 · Cited by 551
Unearthing the determinants of Blockchain adoption in supply chain management
Wong, L., Tan, G. W., Lee, V., Ooi, K., & Sohal, A. S. (2020) · International Journal of Production Research · doi:10.1080/00207543.2020.1730463 · Cited by 440
Ambient Intelligence—the Next Step for Artificial Intelligence
Ramos, C. A., Augusto, J. C., & Shapiro, D. (2008) · IEEE Intelligent Systems · doi:10.1109/mis.2008.19 · Cited by 434
Circular economy to enhance sustainability of small and medium‐sized enterprises
Dey, P. K., Malesios, C., De, D., Budhwar, P. S., Chowdhury, S., & Cheffi, W. (2020) · Business Strategy and the Environment · doi:10.1002/bse.2492 · Cited by 434
Self-citation
Ai for social good: unlocking the opportunity for positive impact
Tomašev, N., Cornebise, J., Hutter, F., Mohamed, S., Picciariello, A., Connelly, B., Belgrave, D. C. M., Ezer, D., Haert, F. C. V. D., Mugisha, F., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-15871-z · Cited by 357
Understanding technology management as a dynamic capability: A framework for technology management activities
Çetindamar, D., Phaal, R., & Probert, D. R. (2008) · Technovation · doi:10.1016/j.technovation.2008.10.004 · Cited by 322
Organizational Learning Ambidexterity, Strategic Flexibility, and New Product Development
Wei, Z., Yi, Y., & Guo, H. (2013) · Journal of Product Innovation Management · doi:10.1111/jpim.12126 · Cited by 315
The Oxford Handbook of Organizational Socialization
Thomas, H. C., & Burke, S. (2012) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780199763672.001.0001 · Cited by 308
The Impact of Lean Management Practices and Sustainably‐Oriented Innovation on Sustainability Performance of Small and Medium‐Sized Enterprises: Empirical Evidence from the UK
Dey, P. K., Malesios, C., De, D., Chowdhury, S., & Abdelaziz, F. B. (2019) · British Journal of Management · doi:10.1111/1467-8551.12388 · Cited by 302
Self-citation
Robots and organization studies: Why robots might not want to steal your job
Fleming, P. (2019) · Organization Studies · doi:10.1177/0170840618765568 · Cited by 297
Locally noisy autonomous agents improve global human coordination in network experiments
Shirado, H., & Christakis, N. A. (2017) · Nature · doi:10.1038/nature22332 · Cited by 288
Testing the combined effects of newcomer information seeking and manager behavior on socialization.
Bauer, T. N., & Green, S. G. (1998) · Journal of Applied Psychology · doi:10.1037/0021-9010.83.1.72 · Cited by 277
Can HR adapt to the paradoxes of artificial intelligence?
Charlwood, A., & Guenole, N. (2022) · Human Resource Management Journal · doi:10.1111/1748-8583.12433 · Cited by 271
Antecedents and consequences of cloud computing adoption in education to achieve knowledge management
Arpaci, I. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2017.01.024 · Cited by 270
Does the use of synchrony and artificial intelligence in video interviews affect interview ratings and applicant attitudes?
Suen, H.-Y., Chen, M. Y.-C., & Lu, S. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2019.04.012 · Cited by 260
A machine learning based approach for predicting blockchain adoption in supply Chain
Kamble, S., Gunasekaran, A., Kumar, V., Belhadi, A., & Foropon, C. R. H. (2020) · Technological forecasting & social change · doi:10.1016/j.techfore.2020.120465 · Cited by 259
Big data in an HR context: Exploring organizational change readiness, employee attitudes and behaviors
Shah, N., Irani, Z., & Sharif, A. (2017) · Journal of Business Research · doi:10.1016/j.jbusres.2016.08.010 · Cited by 251
Using Structural Equation Modeling to Assess Functional Connectivity in the Brain: Power and Sample Size Considerations
Sideridis, G., Simos, P., Papanicolaou, A., & Fletcher, J. (2014) · Educational and Psychological Measurement · doi:10.1177/0013164414525397 · Cited by 246
The Jobs That Artificial Intelligence Will Create
Wilson, H. J., Daugherty, P. R., & Morini-Bianzino, N. (2018) · What the Digital Future Holds · doi:10.7551/mitpress/11645.003.0020 · Cited by 246
Robot will take your job: Innovation for an era of artificial intelligence
Rampersad, G. (2020) · Journal of Business Research · doi:10.1016/j.jbusres.2020.05.019 · Cited by 240
The Knowledge Management Yearbook 1999-2000.
Hoff, K. S. (1999) · Educational Technology & Society · Cited by 239
The intermediating role of organizational culture and internal analytical knowledge between the capability of big data analytics and a firm’s performance
Upadhyay, P., & Kumar, A. (2020) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2020.102100 · Cited by 237
Understanding the interplay of artificial intelligence and strategic management: four decades of research in review
Keding, C. (2021) · Management Review Quarterly · doi:10.1007/s11301-020-00181-x · Cited by 231
Application of sampling methods for the research design
Mweshi, G. K., & Sakyi, K. A. (2020) · Archives of Business Research · doi:10.14738/abr.811.9042 · Cited by 218
Implementing mixed methods research in supply chain management
Golicic, S. L., & Davis, D. F. (2012) · International Journal of Physical Distribution & Logistics Management · doi:10.1108/09600031211269721 · Cited by 218
Dynamic capability, knowledge, learning, and firm performance
Chien, S., & Tsai, C. (2012) · Journal of Organizational Change Management · doi:10.1108/09534811211228148 · Cited by 206
Innovating through digital revolution: The role of soft skills and Big Data in increasing firm performance
Caputo, F., Cillo, V., Candelo, E., & Liu, Y. (2019) · Management Decision · doi:10.1108/md-07-2018-0833 · Cited by 199
The evolutionary implications of social media for organizational knowledge management
Kane, G. C. (2017) · Information and Organization · doi:10.1016/j.infoandorg.2017.01.001 · Cited by 192
Development and validation of an instrument to measure organizational cultures’ support of Business Process Management
Schmiedel, T., Brocke, J. V., & Recker, J. (2013) · Information & Management · doi:10.1016/j.im.2013.08.005 · Cited by 191
Competitive advantage and strategy formulation
López, S. V. (2005) · Management Decision · doi:10.1108/00251740510597699 · Cited by 180
The science and practice of workforce analytics: Introduction to the HRM special issue
Huselid, M. A. (2018) · Human Resource Management · doi:10.1002/hrm.21916 · Cited by 179
Using AI to Enhance Business Operations
Tarafdar, M., Beath, C. M., & Ross, J. W. (2020) · The MIT Press eBooks · doi:10.7551/mitpress/12588.003.0015 · Cited by 174
The impact of human resource management practices and career satisfaction on employee’s turnover intention
Aburumman, O. J., Salleh, A. M. M., Omar, K. B., & Abadi, M. (2019) · Management Science Letters · doi:10.5267/j.msl.2019.9.015 · Cited by 170
Working in the digitized economy: HRM theory & practice
Connelly, C. E., Fieseler, C., Černe, M., Giessner, S. R., & Wong, S. I. (2020) · Human Resource Management Review · doi:10.1016/j.hrmr.2020.100762 · Cited by 168
Managing knowledge transfer by knowledge technologies
Garavelli, A. C., Gorgoglione, M., & Scozzi, B. (2002) · Technovation · doi:10.1016/s0166-4972(01)00009-8 · Cited by 167
Global Knowledge Management Strategies
Desouza, K. C., & Evaristo, R. (2003) · European Management Journal · doi:10.1016/s0263-2373(02)00152-4 · Cited by 158
Supply chain sustainability performance measurement of small and medium sized enterprises using structural equation modeling
Malesios, C., Dey, P. K., & Abdelaziz, F. B. (2018) · Annals of Operations Research · doi:10.1007/s10479-018-3080-z · Cited by 140
Self-citation
The learning of socialization content: A framework for researching orientating practices
Klein, H. J., & Heuser, A. E. (2008) · Research in personnel and human resources management · doi:10.1016/s0742-7301(08)27007-6 · Cited by 139
Using Artificial Intelligence to Promote Diversity
Daugherty, P. R., Wilson, H. J., & Chowdhury, R. (2020) · How AI Is Transforming the Organization · doi:10.7551/mitpress/12588.003.0006 · Cited by 129
Research Handbook on the Law of Artificial Intelligence
Pagallo, W. B., & Pagallo, U. (2018) · Edward Elgar Publishing eBooks · doi:10.4337/9781786439055 · Cited by 123
Research in personnel and human resources management
(2009) · Research in personnel and human resources management · doi:10.1108/s0742-7301(2009)0000028012 · Cited by 116
Human resources analytics: A legitimacy process
Belizón, M. J., & Kieran, S. (2021) · Human Resource Management Journal · doi:10.1111/1748-8583.12417 · Cited by 115
A Systematic Review on the Use of AI and ML for Fighting the COVID-19 Pandemic
Islam, M. N., Inan, T. T., Rafi, S., Akter, S. S., Sarker, I. H., & Islam, A. K. M. N. (2020) · IEEE Transactions on Artificial Intelligence · doi:10.1109/tai.2021.3062771 · Cited by 110
Are Organizations On Board with Best Practices Onboarding?
Klein, H. J., & Polin, B. (2012) · Oxford Handbooks Online · doi:10.1093/oxfordhb/9780199763672.013.0014 · Cited by 98
Partners of Humans: A Realistic Assessment of the Role of Robots in the Foreseeable Future
Aleksander, I. (2017) · Journal of Information Technology · doi:10.1057/s41265-016-0032-4 · Cited by 97
Work design in a digitized gig economy
Schroeder, A. N., Bricka, T. M., & Whitaker, J. H. (2019) · Human Resource Management Review · doi:10.1016/j.hrmr.2019.100692 · Cited by 88
Explaining the competitive advantage generated from Analytics with the knowledge-based view: the example of Logistics and Supply Chain Management
Herden, T. T. (2019) · BuR - Business Research · doi:10.1007/s40685-019-00104-x · Cited by 87
Business value appropriation roadmap for artificial intelligence
Mishra, A. N., & Pani, A. K. (2021) · VINE Journal of Information and Knowledge Management Systems · doi:10.1108/vjikms-07-2019-0107 · Cited by 82
How Human–Computer “Superminds” Are Redefining the Future of Work
Malone, T. W. (2019) · Why Humans Matter More Than Ever · doi:10.7551/mitpress/12450.003.0010 · Cited by 81
Blockchain in general management and economics: a systematic literature review
Alkhudary, R., Brusset, X., & Féniès, P. (2020) · European Business Review · doi:10.1108/ebr-11-2019-0297 · Cited by 80
Developing an Artificial Intelligence Capability: A Theoretical Framework for Business Value
Mikalef, P., Fjørtoft, S. O., & Torvatn, H. Y. (2019) · Lecture Notes in Business Information Processing · doi:10.1007/978-3-030-36691-9_34 · Cited by 72
Measuring efficiency of innovation using combined Data Envelopment Analysis and Structural Equation Modeling: empirical study in EU regions
Kalapouti, K., Petridis, K., Malesios, C., & Dey, P. K. (2017) · Annals of Operations Research · doi:10.1007/s10479-017-2728-4 · Cited by 70
Self-citation
Are users threatened by credibility assessment systems?
Elkins, A. C., Dunbar, N. E., Adame, B., & Nunamaker, J. F. (2013) · Journal of Management Information Systems · doi:10.2753/mis0742-1222290409 · Cited by 69
Of leaders and laggards - Towards digitalization of the process industries
Aaldering, L. J., & Song, C. H. (2021) · Technovation · doi:10.1016/j.technovation.2020.102211 · Cited by 66
Creating competitive advantages: Interactions between ambidextrous diversification strategy and contextual factors from a dynamic capability perspective
Lin, H., Hsu, I., Hsu, A. W.-H., & Chung, H. (2020) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2020.119952 · Cited by 64
Antecedents and consequences of electronic supply chain management diffusion
Lin, H. (2017) · The International Journal of Logistics Management · doi:10.1108/ijlm-01-2016-0023 · Cited by 52
The impacts of artificial intelligence (AI) on jobs: an industry perspective
Poba‐Nzaou, P., Galani, M., Uwizeyemungu, S., & Cerić, A. (2021) · Strategic HR Review · doi:10.1108/shr-01-2021-0003 · Cited by 52
Filling in the “Blank Slate”: Examining Newcomers’ Schemas of Supervisors During Organizational Socialization
Nifadkar, S. (2018) · Journal of Management · doi:10.1177/0149206318807288 · Cited by 49
AI in the media and creative industries
Amato, G., Behrmann, M., Bimbot, F., Caramiaux, B., Falchi, F., Garcia, A., Geurts, J., Gibert, J., Gravier, G., Holken, H., et al. (2019) · arXiv · doi:10.48550/arxiv.1905.04175 · Cited by 46
TUTORIAL: AI research without coding: The art of fighting without fighting: Data science for qualitative researchers
Ciechanowski, L., Jemielniak, D., & Gloor, P. A. (2020) · Journal of Business Research · doi:10.1016/j.jbusres.2020.06.012 · Cited by 44
Artificial Intelligence ―Creating Automated Insights for Customer Relationship Management
Deb, S. K., Jain, R., & Deb, V. (2018) · International Conference on Cloud Computing, Data Science & Engineering (Confluence) · doi:10.1109/confluence.2018.8442900 · Cited by 40
Harnessing Artificial Intelligence
Durai, S., Manoharan, G., & Ashtikar, S. P. (2024) · Advances in finance, accounting, and economics book series · doi:10.4018/979-8-3693-2881-1.ch003 · Cited by 38
Beyond artificial intelligence: why companies need to go the extra step
Lichtenthaler, U. (2020) · Journal of Business Strategy · doi:10.1108/jbs-05-2018-0086 · Cited by 37
Explainable AI for the Choquet Integral
Murray, B. J., Islam, M. A., Pinar, A. J., Anderson, D. T., Scott, G. J., Havens, T. C., & Keller, J. M. (2021) · IEEE Transactions on Emerging Topics in Computational Intelligence · doi:10.1109/tetci.2020.3005682 · Cited by 36
Harnessing Artificial Intelligence
(2024) · Advances in educational marketing, administration, and leadership book series · doi:10.4018/979-8-3693-7190-9.ch003 · Cited by 23
Competing In The Age of AI
Iansiti, M., & Lakhani, K. R. (2020) · Cited by 21
Analysis of top kayakers’ training-intensity distribution and physiological adaptation based on structural modelling
Dadelienė, R., Dadelo, S., Pozniak, N., & Sakalauskas, L. L. (2020) · Annals of Operations Research · doi:10.1007/s10479-020-03560-5 · Cited by 18
Artificial intelligence and the creative industry: new challenges for the EU paradigm for art and technology by autonomous creation
Buning, M. D. C. (2018) · Edward Elgar Publishing eBooks · doi:10.4337/9781786439055.00032 · Cited by 17
Advancing the Science of Human Cognition and Behavior
Phan, P., & Wright, M. (2018) · Academy of Management Perspectives · doi:10.5465/amp.2018.0058 · Cited by 8
Short Paper: Swarm Intelligence Amplifies the IQ of Collaborating Teams
Willcox, G., & Rosenberg, L. B. (2019) · International Conference on Artificial Intelligence for Industries (AI4I) · doi:10.1109/ai4i46381.2019.00036 · Cited by 6
Dynamic capabilities and strategic management
Teece, D. J., Pisano, G., & Shuen, A. (1997) · Strategic Management Journal · doi:10.1002/(sici)1097-0266(199708)18:7

Research works printed but not linked: 16

Amabile, 2020, Creativity, Artificial Intelligence, and a World of Surprises, Academy of Management Discoveries, 6
Anderson, N. and Thomas, H. D. (1996). Work group socialization. In M. West (Ed) Handbook of work group psychology (pp. 423-450).
Barro, 2019, People and machines: Partners in innovation, MIT Sloan Management Review, 60, 22
Bieda, 2020, How Organizations Can Build Analytics Agility, MIT Sloan Management Review
Bughin, 2018, Why digital strategies fail, McKinsey Quarterly.
Chowdhury, 2020, Putting Responsible AI Into Practice, MIT Sloan Management Review
Chui, 2018, AI adoption advances, but foundational barriers remain, McKinsey Global Institute Research
Davenport, 2017, How P&G and American Express are approaching AI, Harvard Business Review
Fountaine, 2019, Building the AI-powered organization, Harvard Business Review, 97, 62
Kiron, 2019, Strategy For and With AI, MIT Sloan Management Review, 60, 30
Knickrehm, 2018, How will AI change work? Here are 5 schools of thought, Harvard Business Review
Mahidhar, 2018, Why companies that wait to adopt AI may never catch up, Harvard Business Review
Ransbotham, 2017, Reshaping business with artificial intelligence: Closing the gap between ambition and action, MIT Sloan Management Review, 59
Ransbotham, S., Gerbert, P., Reeves, M., Kiron, D. & Spira, M., (2018). Artificial intelligence in business gets real. MIT Sloan Management Review and Boston Consulting Group, 60280.
Ransbotham S., Kiron D., Khodabandeh S., Fehling R., LaFountain B., (2019). Winning with AI. MIT Sloan Management Review and Boston Consulting Group, 61180.
Wilson, 2018, Collaborative intelligence: Humans and AI are joining forces, Harvard Business Review, 96, 114

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
Self-citation
A multilevel review of artificial intelligence in organizations: Implications for organizational behavior research and practice
Bankins, S., Ocampo, A. C., Marrone, M., Restubog, S. L. D., & Woo, S. E. (2024) · Journal of Organizational Behavior · doi:10.1002/job.2735 · Cited by 799
Artificial intelligence in logistics and supply chain management: A primer and roadmap for research
Richey, R. G., Chowdhury, S., Davis‐Sramek, B., Giannakis, M., & Dwivedi, Y. K. (2023) · Journal of Business Logistics · doi:10.1111/jbl.12364 · Cited by 471
“Organizations might increasingly lean towards a workforce that can collaborate seamlessly with AI systems, fostering a symbiotic relationship that leverages the strengths of both humans and machines, i.e., collaborative intelligence (Chowdhury et al., 2022; Peng et al., 2022).”
Self-citation
Artificial intelligence-driven supply chain resilience in Vietnamese manufacturing small- and medium-sized enterprises
Dey, P. K., Chowdhury, S., Abadie, A., Vann Yaroson, E., & Sarkar, S. (2024) · International Journal of Production Research · doi:10.1080/00207543.2023.2179859 · Cited by 330
“…workforce needs, government policies and regulations, external turbulent and dynamic business environment, consumer needs and evolving preferences, SC partners’ requirements, organisations’ corporate social responsibility and ethos and sustain unprecedented disruptions ( Chowdhury et al. 2022b).”
BackgroundInfluentialSelf-citation
The impact of trust in AI on career sustainability: The role of employee–AI collaboration and protean career orientation
Kong, H., Yin, Z., Baruch, Y., & Yuan, Y. (2023) · Journal of Vocational Behavior · doi:10.1016/j.jvb.2023.103928 · Cited by 305

See all 531

Authors: Chowdhury, S., Budhwar, P., Dey, P. K., Joel-Edgar, S., & Abadie, A.
Affiliations: TBS Education (FR)
Aston University (GB)
Northeastern University London (GB)
Corresponding author: Chowdhury, Soumyadeb
ORCID: Chowdhury, Soumyadeb
Budhwar, Pawan
Dey, Prasanta Kumar
Joel-Edgar, Sian
Venue: Journal of Business Research
Publisher: Elsevier BV
Published: 2022-05
Volume: 144
Pages: 31-49
ISSN: 0148-2963 (ISSN-L)
DOI: 10.1016/j.jbusres.2022.01.069
OpenAlex: W4210465889
Cited by: 531
References: 128
Citations by year: 2026: 195 · 2025: 177 · 2024: 88 · 2023: 55 · 2022: 16
FWCI: 79.37
Type: journal article
Language: en
Open access: closed
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
doi.org/10.15223/policy-017 (stm-asf)
doi.org/10.15223/policy-037 (stm-asf)
doi.org/10.15223/policy-012 (stm-asf)
doi.org/10.15223/policy-029 (stm-asf)
doi.org/10.15223/policy-004 (stm-asf)
Locations: Journal of Business Research (publishedVersion)
RePEc: Research Papers in Economics (submittedVersion)
Topics: Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › AI and HR Technologies
Social Sciences › Business, Management and Accounting › Management Information Systems › Information Systems Theories and Implementation
Social Sciences › Decision Sciences › Information Systems and Management › Knowledge Management and Sharing
Keywords: human-AI collaboration, collaborative intelligence, firm performance, knowledge sharing, AI competencies, trust, role clarity, knowledge-based view, socio-technical systems, organizational socialization, creative industries

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

AI-employee collaboration and business performance: Integrating knowledge-based view, socio-technical systems and organisational socialisation framework

Overview

Integrity signals

Verification

Claims the paper makes

Citations

Cites

Cited by

Related

Metadata

Record

About these checks