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Cited by 166

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Consequences of high and low adaptive capability in UK companies

Oktemgil, Mehmet, Greenley, Gordon·1997·European Journal of Marketing

Abstract

Abstract In the literature it is proposed that high adaptive capability is associated with high costs and internal inefficiency, despite the potential benefits to be gained from being adaptive. Investigates a set of adaptability variables that have not been previously researched and, therefore, takes an alternative focus on adaptive capability. Identifies two distinct degrees of high and low adaptive capability in an empirical UK study. Suggests that companies with high adaptive capability seemingly perform better than low adapters, despite the implication of high costs and inefficiency. High adapters also seem to have more comprehensive market orientation and decision‐making style, although they appear to operate in more turbulent external environments. The results extend the current adaptive capability literature, and directions for further research are proposed.

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Crossref · 10.1108/03090569710176619

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Metadata

Authors
Oktemgil, M., & Greenley, G.
Venue
European Journal of Marketing
Publisher
Emerald
Published
1997-08
Volume
31
Issue
7
Pages
445-466
ISSN
0309-0566 (ISSN-L)
OpenAlex
W2054993278
Cited by
166
References
2
FWCI
5.20
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Consequences of high and low adaptive capability in UK companies. https://app.cochat.ai/papers/10.1108/03090569710176619
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Oktemgil, M., & Greenley, G. (1997). Consequences of high and low adaptive capability in UK companies. European Journal of Marketing. https://doi.org/10.1108/03090569710176619

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.