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Related diversification, core competences and corporate performance

Markides, Constantinos C., Williamson, Peter J.·2007·Strategic Management Journal

Abstract

Despite nearly 30 years of academic research on the benefits of related diversification, there is still considerable disagreement about precisely how and when diversification can be used to build long-run competitive advantage. In this paper we argue that the disagreement exists for two main reasons: (a) the traditional way of measuring relatedness between two businesses is incomplete because it ignores the ‘strategic importance’ and similarity of the underlying assets residing in these businesses, and (b) the way researchers have traditionally thought of relatedness is limited, primarily because it has tended to equate the benefits of relatedness with the static exploitation of economies of scope (asset amortization), thus ignoring the main contribution of related diversification to long-run, competitive advantage; namely the potential for the firm to expand its stock of strategic assets and create new ones more rapidly and at lower cost than rivals who are not diversified across related businesses. An empirical test supports our view that ‘strategic’ relatedness is superior to market relatedness in predicting when related diversifies outperform unrelated ones.

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Metadata

Authors
Markides, C. C., & Williamson, P. J.
Venue
Strategic Management Journal
Publisher
Wiley
Published
2007-06-14
Volume
15
Issue
S2
Pages
149-165
ISSN
  • 0143-2095 (ISSN-L)
  • 1097-0266
OpenAlex
W2167895888
Cited by
863
References
2
FWCI
151.03
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Related diversification, core competences and corporate performance. https://app.cochat.ai/papers/10.1002/smj.4250151010
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Markides, C. C., & Williamson, P. J. (2007). Related diversification, core competences and corporate performance. Strategic Management Journal. https://doi.org/10.1002/smj.4250151010

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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.