The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Social Media, Knowledge Sharing, and Innovation: Toward a Theory of Communication Visibility
Open accessAbstract
This paper offers a theory of communication visibility based on a field study of the implementation of a new enterprise social networking site in a large financial services organization. The emerging theory suggests that once invisible communication occurring between others in the organization becomes visible for third parties, those third parties could improve their metaknowledge (i.e., knowledge of who knows what and who knows whom). Communication visibility, in this case made possible by the enterprise social networking site, leads to enhanced awareness of who knows what and whom through two interrelated mechanisms: message transparency and network translucence. Seeing the contents of other’s messages helps third-party observers make inferences about coworkers' knowledge. Tangentially, seeing the structure of coworkers' communication networks helps third-party observers make inferences about those with whom coworkers regularly communicate. The emerging theory further suggests that enhanced metaknowledge can lead to more innovative products and services and less knowledge duplication if employees learn to work in new ways. By learning vicariously rather than through experience, workers can more effectively recombine existing ideas into new ideas and avoid duplicating work. Moreover, they can begin to proactively aggregate information perceived daily rather than engaging in reactive search after confronting a problem. I discuss the important implications of this emerging theory of communication visibility for work in the knowledge economy.
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Kapoor, K. K., Tamilmani, K., Rana, N. P., Patil, P., Dwivedi, Y. K., & Nerur, S. (2018) · Information Systems Frontiers · doi:10.1007/s10796-017-9810-y · Cited by 1,285
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Expanding Explainability: Towards Social Transparency in AI systems
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Virtual Work: Bridging Research Clusters
Raghuram, S., Hill, N. S., Gibbs, J. L., & Maruping, L. M. (2019) · Academy of Management Annals · doi:10.5465/annals.2017.0020 · Cited by 426
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Metadata
- Authors
- Leonardi, P. M.
- Venue
- Information Systems Research
- Published
- 2014-12
- Volume
- 25
- Issue
- 4
- Pages
- 796-816
- ISSN
- 1047-7047 (ISSN-L)
- 1526-5536
- OpenAlex
- W2116136245
- Cited by
- 815
- References
- 8
- FWCI
- 112.30
- Type
- journal article
- Language
- en
- Open access
- green
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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.