The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Big Data and organizational design–the brave new world of algorithmic management and computer augmented transparency
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“Algorithms also make work more visible to co-workers, sending pings for completed tasks or reminders to slow performers (Schildt, 2017).”
From Working and organizing in the age of the learning algorithm (2018) · cites this paper as Schildt, 2017
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Cites
Organizational Information Requirements, Media Richness and Structural Design
Daft, R. L., & Lengel, R. H. (1986) · Management Science · doi:10.1287/mnsc.32.5.554 · Cited by 9,868
Business intelligence and analytics: from big data to big impact
Chen, H., Chiang, R. H. L., & Storey, V. C. (2012) · MIS Quarterly · doi:10.2307/41703503 · Cited by 6,250
Why Are There Still So Many Jobs? The History and Future of Workplace Automation
Autor, D. H. (2015) · Journal of Economic Perspectives · doi:10.1257/jep.29.3.3 · Cited by 3,917
Big other: Surveillance Capitalism and the Prospects of an Information Civilization
Zuboff, S. (2015) · Journal of Information Technology · doi:10.1057/jit.2015.5 · Cited by 3,205 · cited 4×
“In algorithmic management, computers do not facilitate governance (as in evidence-based management), but instead governance itself is made obsolete through total control provided by data (Zuboff, 2015).”
BackgroundInfluentialNew games, new rules: big data and the changing context of strategy
Constantiou, I. D., & Kallinikos, J. (2015) · Journal of Information Technology · doi:10.1057/jit.2014.17 · Cited by 526
Research works printed but not linked: 17
- Brin, D. (1998). The transparent society . New York, NY: Perseus Books.
- Cowen, T. (2013). Average is over: Powering America beyond the age of the great stagnation . New York, NY: Dutton.
- Daft, R. (2012). Organization theory and design . Mason, OH : Cengage Learning.
- Davenport, T. H. , & Harris, J. G. (2007). Competing on analytics: The new science of winning . Boston, MA : Harvard Business School Press.
- 10.1287/orsc.1120.0807 · DOI
- Fayyad, U. M. , Wierse, A. , & Grinstein, G. G. (2002). Information visualization in data mining and knowledge discovery . San Francisco, CA : Morgan Kaufmann.
- 10.1287/orsc.1050.0179 · DOI
- Gerry, G. , & Lin, Y. (2017). Analytics and innovation. Innovation: Organization and Management , 1, this issue.
- 10.5465/amr.1990.4308227 · DOI · Paper page
- 10.1287/orsc.1070.0286 · DOI · Paper page
- 10.1145/2702123.2702548 · DOI · Paper page
- McAfee, A. , & Brynjolfsson, E. (2014). The second machine age: Work, progress, and prosperity in a Time of Brilliant technologies . New York, NY : W. W. Norton & Company.
- 10.1093/acprof:oso/9780195099171.001.0001 · DOI · Paper page
- 10.1007/s10994-013-5417-9 · DOI
- 10.1111/joms.2012.49.issue-8 · DOI
- 10.1287/orsc.1070.0307 · DOI · Paper page
- 10.1016/0090-2616(85)90033-6 · DOI · Paper page
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
Automation, Algorithms, and Beyond: Why Work Design Matters More Than Ever in a Digital World
Parker, S. K., & Grote, G. (2022) · Applied Psychology · doi:10.1111/apps.12241 · Cited by 960
Working and organizing in the age of the learning algorithm
Faraj, S., Pachidi, S., & Sayegh, K. (2018) · Information and Organization · doi:10.1016/j.infoandorg.2018.02.005 · Cited by 929
Veen, A., Barratt, T., & Goods, C. (2020) · Work, Employment and Society · doi:10.1177/0950017019836911 · Cited by 657
Algorithmic Management of Work on Online Labor Platforms: When Matching Meets Control
Möhlmann, M., Zalmanson, L., Henfridsson, O., & Gregory, R. W. (2021) · MIS Quarterly · doi:10.25300/misq/2021/15333 · Cited by 554
Algorithms as work designers: How algorithmic management influences the design of jobs
Parent-Rocheleau, X., & Parker, S. K. (2022) · Human Resource Management Review · doi:10.1016/j.hrmr.2021.100838 · Cited by 512
Newlands, G. (2021) · Organization Studies · doi:10.1177/0170840620937900 · Cited by 439
The dark sides of people analytics: Reviewing the perils for organisations and employees
Giermindl, L. M., Strich, F., Christ, O., Leicht-Deobald, U., & Redzepi, A. (2022) · European Journal of Information Systems · doi:10.1080/0960085x.2021.1927213 · Cited by 331
When the Machine Meets the Expert: An Ethnography of Developing AI for Hiring
van den Broek, E., Sergeeva, A., & Huysman, M. (2021) · MIS Quarterly · doi:10.25300/misq/2021/16559 · Cited by 330
Corporate digital responsibility in service firms and their ecosystems
Wirtz, J., Kunz, W. H., Hartley, N., & Tarbit, J. (2023) · Journal of Service Research · doi:10.1177/10946705221130467 · Cited by 291
Meijerink, J., Boons, M., Keegan, A., & Marler, J. (2021) · The International Journal of Human Resource Management · doi:10.1080/09585192.2021.1925326 · Cited by 267
Examining the Impact of Algorithmic Control on Uber Drivers’ Technostress
Cram, W. A., Wiener, M., Tarafdar, M., & Benlian, A. (2022) · Journal of Management Information Systems · doi:10.1080/07421222.2022.2063556 · Cited by 246
Keding, C. (2021) · Management Review Quarterly · doi:10.1007/s11301-020-00181-x · Cited by 231
Metadata
- Authors
- Schildt, H.
- Affiliations
- Aalto University School of Business
- Venue
- Innovation
- Publisher
- Informa UK Limited
- Published
- 2016-11-08
- Volume
- 19
- Issue
- 1
- Pages
- 23-30
- ISSN
- 1447-9338
- 2204-0226
- Cited by
- 159
- References
- 5
- Language
- en
- Funders
- Tekes (Project "Organizing for Digitalization")
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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.
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Data sources
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.
