The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
On the measurement of corporate diversification strategy: Evidence from large U.S. service firms
Abstract
Actual, not potential, relatedness determines the results of diversification strategies. An external examination of a firm's businesses, products, markets and technologies permits an assessment of potential relatedness among its various businesses. Potential relatedness is, however, often not realized. Also, relatedness may be externally invisible. Hence, actual relatedness may diverge from externally measured potential relatedness. This paper provides evidence suggesting that measures of corporate diversification strategy based on internal data differ significantly from those based on externally available data.
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Citations
Cites
Organizational Strategy, Structure, and Process
Miles, R. E., Snow, C. C., Meyer, A. D., & Coleman, H. J. (1978) · Academy of Management Review · doi:10.5465/amr.1978.4305755 · Cited by 4,527
Cited by
Agency Relationships in Family Firms: Theory and Evidence
Schulze, W. S., Lubatkin, M. H., Dino, R. N., & Buchholtz, A. K. (2001) · Organization Science · doi:10.1287/orsc.12.2.99.10114 · Cited by 2,332
Metadata
- Authors
- Nayyar, P. R.
- Venue
- Strategic Management Journal
- Publisher
- Wiley
- Published
- 1992-03
- Volume
- 13
- Issue
- 3
- Pages
- 219-235
- ISSN
- 0143-2095 (ISSN-L)
- 1097-0266
- OpenAlex
- W1989572299
- Cited by
- 195
- References
- 1
- FWCI
- 10.29
- Type
- journal article
- Language
- en
- Open access
- closed
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- Nayyar, P. R. (1992). On the measurement of corporate diversification strategy: Evidence from large U.S. service firms. Strategic Management Journal. https://doi.org/10.1002/smj.4250130305
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.
