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Crowdsourcing-Based Business Models: How to Create and Capture Value
Abstract
Technology has transformed individuals from mere consumers of products to empowered participants in value co-creation. While numerous firms experiment with involving a crowd in value creation, few companies turn crowdsourcing projects into thriving platforms with a powerful business model. To address this challenge, this article analyzes successful platforms to identify patterns of effective crowdsourcing-based business models. The results provide guidance for managers who need to create new (or adapt existing) business models.
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Citations
Cited by
Mapping out the sharing economy: A configurational approach to sharing business modeling
Muñoz, P., & Cohen, B. (2017) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2017.03.035 · Cited by 432
The Rise of Crowd Logistics: A New Way to Co‐Create Logistics Value
Carbone, V., Rouquet, A., & Roussat, C. (2017) · Journal of Business Logistics · doi:10.1111/jbl.12164 · Cited by 283
Business model innovation and value-creation: the triadic way
Andreassen, T. W., Lervik-Olsen, L., Snyder, H., Van Riel, A. C. R., Sweeney, J. C., & Van Vaerenbergh, Y. (2018) · Journal of Service Management · doi:10.1108/josm-05-2018-0125 · Cited by 160
Metadata
- Authors
- Kohler, T.
- Venue
- California Management Review
- Publisher
- SAGE Publications
- Published
- 2015-08
- Volume
- 57
- Issue
- 4
- Pages
- 63-84
- ISSN
- 0008-1256 (ISSN-L)
- 2162-8564
- OpenAlex
- W2530214029
- Cited by
- 183
- References
- 0
- FWCI
- 39.93
- Type
- journal article
- Language
- en
- Open access
- closed
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- Kohler, T. (2015). Crowdsourcing-Based Business Models: How to Create and Capture Value. California Management Review. https://doi.org/10.1525/cmr.2015.57.4.63
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.