The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
The Transparency Paradox: A Role for Privacy in Organizational Learning and Operational Control
Open accessAbstract
Using data from embedded participant-observers and a field experiment at the second largest mobile phone factory in the world, located in China, I theorize and test the implications of transparent organizational design on workers’ productivity and organizational performance. Drawing from theory and research on learning and control, I introduce the notion of a transparency paradox, whereby maintaining observability of workers may counterintuitively reduce their performance by inducing those being observed to conceal their activities through codes and other costly means; conversely, creating zones of privacy may, under certain conditions, increase performance. Empirical evidence from the field shows that even a modest increase in group-level privacy sustainably and significantly improves line performance, while qualitative evidence suggests that privacy is important in supporting productive deviance, localized experimentation, distraction avoidance, and continuous improvement. I discuss implications of these results for theory on learning and control and suggest directions for future research.
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Cited by
Algorithms at Work: The New Contested Terrain of Control
Kellogg, K. C., Valentine, M. A., & Christin, A. (2020) · Academy of Management Annals · doi:10.5465/annals.2018.0174 · Cited by 2,732
Schnackenberg, A. K., & Tomlinson, E. C. (2016) · Journal of Management · doi:10.1177/0149206314525202 · Cited by 762
E-leadership: Re-examining transformations in leadership source and transmission
Avolio, B. J., Sosik, J. J., Kahai, S. S., & Baker, B. (2014) · The Leadership Quarterly · doi:10.1016/j.leaqua.2013.11.003 · Cited by 584
Organizational Transparency: Conceptualizations, Conditions, and Consequences
Albu, O. B., & Flyverbom, M. (2019) · Business & Society · doi:10.1177/0007650316659851 · Cited by 361
Shadow Learning: Building Robotic Surgical Skill When Approved Means Fail
Beane, M. (2019) · Administrative Science Quarterly · doi:10.1177/0001839217751692 · Cited by 286
Metadata
- Authors
- Bernstein, E. S.
- Venue
- Administrative Science Quarterly
- Publisher
- SAGE Publications
- Published
- 2012-06
- Volume
- 57
- Issue
- 2
- Pages
- 181-216
- ISSN
- 0001-8392 (ISSN-L)
- 1930-3815
- OpenAlex
- W2041384361
- Cited by
- 394
- References
- 14
- FWCI
- 28.15
- Type
- journal article
- Language
- en
- Open access
- green
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
