The Role of Tacit Knowledge in Group Innovation
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AI-employee collaboration is likely to be facilitated by tacit experience within organisations-implicit knowledge sharing communicated by employees with prior understanding of AI and experience working with AI systems.
“Fourthly, AI-employee collaboration is likely to be facilitated by tacit experience (Leonard and Sensiper, 1998) within the organisations, i.e., implicit knowledge sharing which is communicated by employees having prior understanding of AI and experience working with AI systems.”
From Unlocking the value of artificial intelligence in human resource management through AI capability framework (2023) · cites this paper as Leonard and Sensiper, 1998
Cites
Lave, J., & Wenger, E. (1991) · Cambridge University Press eBooks · doi:10.1017/cbo9780511815355 · Cited by 33,219 · see citing works
Blind variation and selective retentions in creative thought as in other knowledge processes
Campbell, D. T. (1960) · Psychological Review · doi:10.1037/h0040373 · Cited by 2,329 · see citing works
Demographic Diversity, Conflict, and Work Group Outcomes: An Intervening Process Theory
Pelled, L. H. (1996) · Organization Science · doi:10.1287/orsc.7.6.615 · Cited by 1,489 · see citing works
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Chowdhury, S., Dey, P., Joel-Edgar, S., Bhattacharya, S., Rodriguez-Espindola, O., Abadie, A., & Truong, L. (2023) · Human Resource Management Review · doi:10.1016/j.hrmr.2022.100899 · Cited by 927 · see citing works
Barthel, S., Folke, C., & Colding, J. (2010) · Global Environmental Change · doi:10.1016/j.gloenvcha.2010.01.001 · Cited by 557 · see citing works
Chowdhury, S., Budhwar, P., Dey, P. K., Joel-Edgar, S., & Abadie, A. (2022) · Journal of Business Research · doi:10.1016/j.jbusres.2022.01.069 · Cited by 531 · see citing works
Capturing the Complexity of Malleable IT Use: Adaptive Structuration Theory for Individuals1
Schmitz, K. W., Teng, J. T. C., & Webb, K. J. (2016) · MIS Quarterly · doi:10.25300/misq/2016/40.3.07 · Cited by 205 · see citing works
Emerging patterns of complex technological innovation
Kash, D. E., & Rycroft, R. (2002) · Technological Forecasting and Social Change · doi:10.1016/s0040-1625(01)00171-8 · Cited by 121 · see citing works
Sigala, M., & Chalkiti, K. (2014) · Computers in Human Behavior · doi:10.1016/j.chb.2013.05.032 · Cited by 117 · see citing works
Hospital organization culture, capacity to innovate and success in technology adoption
do Carmo Caccia‐Bava, M., Guimaraes, T., & Harrington, S. J. (2006) · Journal of Health Organization and Management · doi:10.1108/14777260610662735 · Cited by 86 · see citing works
Gazi, M. A. I., Mamun, A. A., Masud, A. A., Senathirajah, A. R. B. S., & Rahman, T. (2024) · Journal of Open Innovation: Technology, Market, and Complexity · doi:10.1016/j.joitmc.2024.100227 · Cited by 81 · see citing works
Annosi, M. C., Marchegiani, L., & Vicentini, F. (2020) · Management Decision · doi:10.1108/md-11-2019-1532 · Cited by 16
- Authors
- Leonard, D., & Sensiper, S.
- Venue
- California Management Review
- Publisher
- SAGE Publications
- Published
- 1998-04
- Volume
- 40
- Issue
- 3
- Pages
- 112-132
- ISSN
- 0008-1256 (ISSN-L)
- 2162-8564
- OpenAlex
- W1980724258
- Cited by
- 1,702
- References
- 3
- Citations by year
- 2026: 26 · 2025: 24 · 2024: 42 · 2023: 51 · 2022: 64 · 2021: 52 · 2020: 76 · 2019: 69 · 2018: 68 · 2017: 69 · 2016: 70 · 2015: 73 · 2014: 80 · 2013: 97 · 2012: 100
- FWCI
- 157.77
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- California Management Review (publishedVersion)
- Topics
- Social Sciences › Communication › Knowledge Management and Sharing
- Social Sciences › Psychology › Social Psychology › Team Dynamics and Performance
- Social Sciences › Business, Management and Accounting › Strategy and Management › Innovation and Knowledge Management
- Keywords
- tacit knowledge, group innovation, organizational knowledge, knowledge sharing, group decision making
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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.
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