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AI-employee collaboration and business performance: Integrating knowledge-based view, socio-technical systems and organisational socialisation framework
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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
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
Bharadwaj, A. S. (2000) · MIS Quarterly · doi:10.2307/3250983 · Cited by 5,042
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
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
Cited by
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Items 101–200 of 531
Kondapaka, P., Khanra, S., Malik, A., Kagzi, M., & Hemachandran, K. (2023) · Journal of Service Theory and Practice · doi:10.1108/jstp-06-2022-0134 · Cited by 30
Malik, A., Nguyen, M., Budhwar, P. S., Chowdhury, S., & Gugnani, R. (2024) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2024.123463 · Cited by 29
Self-citationWorking with robots: Trends and future directions
Wang, S., Lim, W. M., Cheah, J., & Lim, X. (2024) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2024.123648 · Cited by 39
Wu, Q., Qalati, S. A., Tajeddini, K., & Wang, H. (2025) · Industrial Management & Data Systems · doi:10.1108/imds-06-2023-0378 · Cited by 34
Callari, T. C., & Puppione, L. (2025) · Journal of Workplace Learning · doi:10.1108/jwl-11-2024-0258 · Cited by 48
Liu, Y., & Li, Y. (2025) · Safety Science · doi:10.1016/j.ssci.2025.106872 · Cited by 36
Arya, V., Saraf, A., Юрьевич, Ч. Н., Papa, A., & Romano, M. (2025) · The Journal of Technology Transfer · doi:10.1007/s10961-025-10233-7 · Cited by 41
Chen, N., Xi-nan, Z., & Wang, L. (2024) · Behavioral Sciences · doi:10.3390/bs14100974 · Cited by 38
“However, with the widespread application of AI technology, the skills and abilities required by employees in their work are undergoing fundamental changes [12,13].”
BackgroundJun, Y., & Hoang, K. D. (2025) · Journal of Knowledge Management · doi:10.1108/jkm-02-2025-0209 · Cited by 31
To That of Artificial Intelligence, Passing Through Business Intelligence
Doshi, R., Hiran, K. K., Mijwil, M. M., & Anand, D. (2023) · Advances in computational intelligence and robotics book series · doi:10.4018/978-1-6684-6519-6.ch001 · Cited by 27
Schinello, S. (2025) · Economics & Sociology · doi:10.14254/2071-789x.2025/18-1/10 · Cited by 27
“…to the development of cultural and creative industries (Qin & Lin, 2021), guarantees improvements in the market performance of creative enterprises (Chowdhury et al., 2022; Kaczorowska-Spychalska et al., 2024), and can be applied to judge the aesthetic value of creative output (Liang, 2022).”
Xu, C., & Cho, S.-E. (2025) · Sustainability · doi:10.3390/su17104335 · Cited by 39
Understanding Organizations’ Artificial Intelligence Journey: A Qualitative Approach
Radhakrishnan, J., Gupta, S., & Prashar, S. (2022) · Pacific Asia journal of the Association for Information Systems · doi:10.17705/1pais.14602 · Cited by 41
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Marvi, R., Foroudi, P., & AmirDadbar, N. (2025) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2025.102908 · Cited by 35
Chin, Y. S., Mohamad, A. A., & Lo, M. (2024) · Global Knowledge, Memory and Communication · doi:10.1108/gkmc-06-2024-0355 · Cited by 40
Chuang, S., Shahhosseini, M., Javaid, M., & Wang, G. G. (2024) · Journal of Work-Applied Management · doi:10.1108/jwam-08-2024-0111 · Cited by 32
Ren, S., & Chowdhury, S. (2025) · Human Resource Management · doi:10.1002/hrm.22313 · Cited by 35
Self-citationVasiliu, V., & Yavetz, G. (2024) · Aslib Journal of Information Management · doi:10.1108/ajim-12-2023-0562 · Cited by 24
Xu, J., Wu, T., Duan, W.-Y., & Cui, X. Z. (2025) · Behavioral Sciences · doi:10.3390/bs15070859 · Cited by 35
“Conventional work is characterized by human-to-human partnerships, while AI collaboration is increasingly incorporating AI as a partner or team member (Chowdhury et al., 2022; Seeber et al., 2020).”
InfluentialIqbal, S., Ullah, S., Rizwan, A., Nazeer, N., Rasheed, M., & Siddiqi, A. F. (2024) · South Asian Journal of Business Studies · doi:10.1108/sajbs-01-2024-0038 · Cited by 23
Moghayedi, A., Michell, K., Awuzie, B. O., & Adama, U. J. (2024) · Journal of Corporate Real Estate · doi:10.1108/jcre-09-2023-0041 · Cited by 21
The rise of hybrids: plastic knowledge in human–AI interaction
Sala, A. L., Fuller, R. P., Riolli, L. T., & Temperini, V. (2024) · Journal of Knowledge Management · doi:10.1108/jkm-10-2023-1024 · Cited by 32
Benabou, A., & Touhami, F. (2025) · International journal of production management and engineering · doi:10.4995/ijpme.2025.21900 · Cited by 38
“Trust, clarity, and role understanding in human-AI partnerships enhance collective intelligence, fostering valuable organisational outcomes and the development of strategies for business processes (Chowdhury et al., 2022).”
Hina, M., Azad, N., & Islam, A. K. M. N. (2025) · Information Technology and People · doi:10.1108/itp-06-2024-0808 · Cited by 22
Qian, J., Chen, J., & Zhao, S. (2025) · Behavioral Sciences · doi:10.3390/bs15040465 · Cited by 32
“Lin et al., 2013), and leadership-related factors (Chowdhury et al., 2022) to develop a more robust theoretical model.”
Lu, G., & Li, B. (2025) · Sustainability · doi:10.3390/su17094141 · Cited by 21
Shi, R., Shan, W., Evans, R., & Wang, Q. (2025) · Energy Economics · doi:10.1016/j.eneco.2025.108541 · Cited by 21
Huang, S., Long, L., Zhu, Y., & Zhu, J. N. Y. (2025) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2025.102986 · Cited by 24
Ritz, E., Donisi, F., Elshan, E., & Rietsche, R. (2023) · Hawaii International Conference on System Sciences (HICSS) · doi:10.24251/hicss.2023.020 · Cited by 31
“Chowdhury et al. (2022) examines the AI-human partnership's impact on business success.”
BackgroundAI and HRM in Tourism and Hospitality in Egypt: Inevitability, Impact, and Future
Al‐Romeedy, B. S. (2024) · Springer eBooks · doi:10.1007/978-3-031-62369-1_13 · Cited by 21
Cui, J. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5083169 · Cited by 25
Khan, T., Emon, M. M. H., Rahman, K. M., Nipa, M. N., & Fuad, M. N. (2025) · IEEE International Conference on Quantum Photonics, Artificial Intelligence & Networking (QPAIN) · doi:10.1109/qpain66474.2025.11171949 · Cited by 21
“Co-innovation and knowledge sharing are also supported by partnerships and, as such, enable firms to act more responsively to market forces and consumer needs and demands [19].”
Koh, L. Y., Li, X., Wang, X., & Yuen, K. F. (2022) · Technology Analysis and Strategic Management · doi:10.1080/09537325.2022.2106841 · Cited by 19
“However, the KBV does not de fi ne how to distribute knowledge in a way that fosters and ful fi lls individual outcomes (Chowdhury et al. 2022).”
BackgroundHalbusi, H. A., González, D. P., & Alsuwaiket, M. A. (2025) · Business Process Management Journal · doi:10.1108/bpmj-08-2024-0679 · Cited by 18
Stylos, N., Okumus, F., & Onder, I. (2025) · Tourism Management · doi:10.1016/j.tourman.2025.105205 · Cited by 18
Yan, K., Pang, X., Li, Q., Tian, G., & Dong, X. (2026) · Journal of Innovation & Knowledge · doi:10.1016/j.jik.2026.100960 · Cited by 19
Iqbal, S., Ullah, S., Rizwan, A., Nazeer, N., Rasheed, M., & Siddiqi, A. F. (2025) · Journal of Organizational Effectiveness People and Performance · doi:10.1108/joepp-02-2024-0075 · Cited by 17
Ghosh, V., Chotia, V., Alghafes, R. A., Basahel, S. B., & Nazrul, A. (2025) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2025.124229 · Cited by 17
Human-AI collaborative recovery: How recovery sequence and strategy order drive consumer forgiveness
Yang, G., & Shao, B. (2025) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2025.104452 · Cited by 17
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Regona, M., Yiğitcanlar, T., Hon, C. K. H., & Teo, M. M. (2026) · ACM Computing Surveys · doi:10.1145/3789256 · Cited by 27
“…of AI is underpinned by several core components that enable diverse applications across industries: Machine learning: Facilitates systems that learn from data and refine performance without explicit programming, supporting applications such as fraud detection and predictive analytics [15].”
InfluentialEmployee learning and skilling in AI embedded organizations – predictors and outcomes
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Weng, C., Yuan, R., Ye, D., Huang, B., & Xun, J. (2024) · Service Industries Journal · doi:10.1080/02642069.2024.2361291 · Cited by 17
“In addition, in line with prior research on employees ’ direct experience with AI (e.g. Cheng et al., 2023; Chowdhury et al., 2022), respondents in this study knew and understood AI technology used in the organization and had experience with using AI in their jobs.”
Rulandari, N., & Silalahi, A. D. K. (2025) · Transforming Government People Process and Policy · doi:10.1108/tg-01-2025-0011 · Cited by 16
Alonso, A. D., Vu, O. T. K., Nguyen, T. Q., McClelland, R., Nguyen, N. M., Huynh, H. T. N., & Tran, T. D. (2024) · Journal of Business Research · doi:10.1016/j.jbusres.2024.114538 · Cited by 18
Castaneda, A. R., Surachartkumtonkun, J., Maseeh, H. I., Thaichon, P., & Shao, W. (2025) · Journal of Service Theory and Practice · doi:10.1108/jstp-04-2024-0099 · Cited by 18
Generative artificial intelligence use and employees' digital performance
Qi, Z., Zhang, X., Ma, L., & Wang, G. (2025) · Management Decision · doi:10.1108/md-09-2024-2060 · Cited by 14
Shen, L., Li, Z., Liang, Y., Feng, Y., & Zhang, Z. (2025) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2025.1691468 · Cited by 15
Castaneda, A. R., Maseeh, H. I., Surachartkumtonkun, J., Shao, W., & Thaichon, P. (2025) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2025.104446 · Cited by 15
AI-driven HRM digitization in effect: Mechanisms, conditions, and employee outcomes
Ali, A., Cichoń, D., & Abbas, A. (2026) · Journal of Innovation & Knowledge · doi:10.1016/j.jik.2025.100919 · Cited by 24
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Wang, Y. M., Matook, S., & Dennis, A. R. (2024) · Journal of Business Research · doi:10.1016/j.jbusres.2024.114509 · Cited by 18
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Pavone, G., Meyer‐Waarden, L., & Munzel, A. (2024) · Recherche et Applications en Marketing (English Edition) · doi:10.1177/20515707241283311 · Cited by 15
“We also identify dependent variables related to the business performance and evaluation (including metrics such as sales, stock returns, and investment intentions), mostly used in the context of B2B settings (e.g. Chowdhury et al., 2022; Franck and Dampérat, 2022).”
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Chen, E., & Zhang, H. (2025) · Frontiers in Public Health · doi:10.3389/fpubh.2024.1506930 · Cited by 14
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Bonamigo, A., Werner, S. M., & de Oliveira, M. S. (2024) · Revista Meta Avaliação · doi:10.22347/2175-2753v16i50.4335 · Cited by 16
Navigating human-AI dynamics: implications for organizational performance (SLR)
Khushk, A., Zhiying, L., Xu, Y., & Zhang, X. (2024) · International journal of organizational analysis · doi:10.1108/ijoa-04-2024-4456 · Cited by 18
Duan, Y., Wang, K., Chang, H., Liu, W., & Xie, C. (2024) · Journal of Knowledge Management · doi:10.1108/jkm-08-2023-0678 · Cited by 13
Critical success and failure factors in the AI lifecycle: a knowledge graph-based ontological study
Hao, X., Demir, E., & Eyers, D. R. (2025) · Journal of Modelling in Management · doi:10.1108/jm2-06-2024-0204 · Cited by 13
Ali, Q., & Mahmood, M. A. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3693-8960-7.ch009 · Cited by 14
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Chaudhary, S., Khalil, A., Attri, R., & Ractham, P. (2025) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2025.124324 · Cited by 16
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Hadid, W., Horii, S., & Yokota, A. (2024) · International Journal of Production Research · doi:10.1080/00207543.2024.2358409 · Cited by 13
“…empirical research on the impact of AI, its enablers and scale of implementation in practice (Brock and Von Wangenheim 2019; Chiarini 2021; Chowdhury et al. 2022;; Duan, Edwards, and Dwivedi 2019; Giermindl et al. 2022; Jaiswal, Arun, and Varma 2022; Johnson et al. 2022; Merhi and…”
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Ali, M. I. A., Khassawneh, O., Haak‐Saheem, W., Zeng, J., & Darwish, T. K. (2023) · Global Knowledge, Memory and Communication · doi:10.1108/gkmc-06-2023-0214 · Cited by 14
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Deng, F., Zhang, Z., Lin, Y., Xiaoping, M., & Zhang, Y. (2025) · Telematics and Informatics · doi:10.1016/j.tele.2025.102283 · Cited by 16
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Dai, T., & Swaminathan, J. M. (2025) · Production and Operations Management · doi:10.1177/10591478251412943 · Cited by 17
“Organizations that maintain meaningful human involvement while enhancing decision quality through AI augmentation achieve superior performance compared to full automation approaches (Chowdhury et al., 2022).”
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“When employees perceive AI as an essential component of their self-concept, this strong AI identity can mitigate AI-based threats to human identity (Mirbabaie et al., 2022), promote role clarity, and improve performance (Chowdhury et al., 2022).”
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“In this study, robot trust was assessed using an 11-item scale developed by Chowdhury et al. (2022).”
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Lee, J., Park, J., & Mostafa, N. A. (2025) · Data Science and Management · doi:10.1016/j.dsm.2025.05.002 · Cited by 13
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“…industry, AI CSR maximizes the advantages of existing CSR and improves their awareness by strengthening aspects such as equality, human rights, and customer protections in employment in addition to the environmental, social, and governance benefits (Chowdhury et al., 2022; Liu et al., 2024).”
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Zhang, Q., Wang, F., Liao, G., & Li, M. (2025) · Behavioral Sciences · doi:10.3390/bs15081064 · Cited by 14
“Prior research has confirmed that AI trust positively influences employee outcomes, such as AI acceptance, job performance, and productivity (Chowdhury et al., 2022; Kong et al., 2023; C. S. Lin et al., 2025).”
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Bawa, S., Benin, I. W., & Xie, Y. (2025) · Kybernetes · doi:10.1108/k-12-2024-3394 · Cited by 11
Zhang, J., Hussain, Y., Abbass, K., & Tufail, U. (2025) · Journal of Environmental Management · doi:10.1016/j.jenvman.2025.127145 · Cited by 10
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Cao, J., Yao, J., Sun, S., Song, Z., & Zhang, F. (2025) · Journal of Open Innovation: Technology, Market, and Complexity · doi:10.1016/j.joitmc.2025.100521 · Cited by 10
Chen, J., Xue, J.-X., Li, Y.-H., & Luo, W. (2025) · International journal of human computer interactions · doi:10.1080/10447318.2025.2474460 · Cited by 14
“An illustrative example is that working in a human-AI collaborative context requires individuals to develop proficient skills in using AI (Chowdhury et al., 2022).”
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Dsouza, A., & Panakaje, N. (2023) · International Journal of Case Studies in Business IT and Education · doi:10.47992/ijcsbe.2581.6942.0260 · Cited by 9
AI types and organizational implications in various task contexts: a quantitative review from China
Kan, Z., Zhao, S., Chi, W., & Zhou, J. (2024) · Asia Pacific Business Review · doi:10.1080/13602381.2024.2409804 · Cited by 11
Thirunagalingam, A., Addanki, S., Vemula, V. R., & Selvakumar, P. (2024) · Advances in business strategy and competitive advantage book series · doi:10.4018/979-8-3693-8442-8.ch005 · Cited by 8
Yang, Y., Yee, R. W. Y., Lee, P. K. C., & Zhu, J. H. (2025) · Information & Management · doi:10.1016/j.im.2025.104238 · Cited by 8
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Behera, M. K., Behera, R. K., & Bala, P. K. (2025) · Journal of Enterprise Information Management · doi:10.1108/jeim-06-2025-0490 · Cited by 14
Srivastava, S., Shardeo, V., Dwivedi, A., & Paul, S. K. (2025) · Annals of Operations Research · doi:10.1007/s10479-025-06843-x · Cited by 8
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Wang, T., Aw, E. C., Tan, G. W., Sthapit, E., & Li, X. (2025) · Current Issues in Tourism · doi:10.1080/13683500.2025.2481486 · Cited by 7
“AI understanding was adapted from Chowdhury et al. (2022).”
InfluentialKirkby, A., Baumgarth, C., & Henseler, J. (2025) · Journal of Brand Management · doi:10.1057/s41262-025-00387-y · Cited by 16
“Establishing clear roles, tasks, and expectations of AI can reduce ambiguity, negative expectations, and uncertainty, which should enhance both performance and commitment (Brougham and Haar 2018; Chowdhury et al. 2022).”
InfluentialInnovations in Food Technology: Intelligent Packaging and Advanced Traceability Solutions
Oyegbade, S. A., Mameh, E. O., Oni, G. J., Gbate, M. A., Oluwaseyi, T. A., Wurie, A. W., Azeta, J. I., Joda, J. F., Oyewole, O. A., & Adetunji, C. O. (2025) · Royal Society of Chemistry eBooks · doi:10.1039/9781837679119-00001 · Cited by 7
Jiang, W., Li, Y., Hu, X., & Ma, D. (2025) · Frontiers in Psychology · doi:10.3389/fpsyg.2025.1652130 · Cited by 9
AI–human collaboration in services: an integrative framework to uncover the key success factors
Jeong, E., & Lee, D. (2025) · Service Business · doi:10.1007/s11628-025-00591-5 · Cited by 8
Chong, J. L. L., & Duan, S. X. (2025) · Journal of Knowledge Management · doi:10.1108/jkm-12-2024-1479 · Cited by 7
Survey on Chinese users’ acceptance of AI assistants: expanding technology acceptance model
Wang, W., & Lu, Y. (2025) · Scientific Reports · doi:10.1038/s41598-025-18123-6 · Cited by 12
“…in the functional cognitive dimension: users with AI knowledge reserves are better able to tap into the potential of the system (such as prompt engineering optimization answer quality), and even if their basic functional performance is mediocre, they can still gain a higher sense of value 52 .”
Harnessing AI and digital innovation for green innovation and sustainable performance
Dinh, T. H., Nguyen, N. H., Nguyen, A. N., & Bui, T. T. K. (2025) · Journal of Hospitality and Tourism Insights · doi:10.1108/jhti-04-2025-0501 · Cited by 9
Zhang, Z., Lin, M., & Liu, X. (2026) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2026.104620 · Cited by 7
How and when organizational AI adoption improves employee innovation performance
Hu, W., Wang, L., Ren, J., Bai, G., Cui, S., & Xu, Y. (2026) · Service Industries Journal · doi:10.1080/02642069.2026.2632108 · Cited by 8
“It enables them to more clearly understand the collaborative relationship between humans and AI, and to believe that AI can provide reliable support in task execution, knowledge acquisition, and decision-making assistance (Chowdhury et al., 2022; Kong et al., 2023).”
InfluentialVocino, A. (2026) · Technovation · doi:10.1016/j.technovation.2026.103551 · Cited by 10
Metadata
- 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
- Venue
- Journal of Business Research
- Publisher
- Elsevier BV
- Published
- 2022-05
- Volume
- 144
- Pages
- 31-49
- ISSN
- 0148-2963 (ISSN-L)
- 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
- 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
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