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Cited by 314

The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

Modelling the Joint Impact of the CEO and the TMT on Organizational Ambidexterity

Cao, Qing, Simsek, Zeki, Zhang, Hongping·2010·Journal of Management Studies

Abstract

While researchers continue to debate how firms might attain ambidexterity, recent research demonstrates that top management teams (TMTs) play a pivotal role. We enrich this line of inquiry by specifying a model that blends the effect of the CEO and the TMT on ambidexterity. Specifically, given the importance of networking and building social capital to the access of timely, valuable, and diverse information, we first envision that the CEO's network extensiveness will positively impact ambidexterity. Next, we argue that this impact will be bolstered when the CEO–TMT interactional interface, including communication richness, functional complementarity, and power decentralization, enable the entire TMT to process disparate information demands essential to attaining ambidexterity. We test and find general support for our model using multi‐source survey data from 122 small‐ to medium‐sized enterprises (SMEs).

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Metadata

Authors
Cao, Q., Simsek, Z., & Zhang, H.
Venue
Journal of Management Studies
Publisher
Wiley
Published
2009-09-23
Volume
47
Issue
7
Pages
1272-1296
ISSN
  • 0022-2380 (ISSN-L)
  • 1467-6486
OpenAlex
W1964765358
Cited by
314
References
7
FWCI
15.41
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Modelling the Joint Impact of the CEO and the TMT on Organizational Ambidexterity. https://app.cochat.ai/papers/10.1111/j.1467-6486.2009.00877.x
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Cao, Q., Simsek, Z., & Zhang, H. (2010). Modelling the Joint Impact of the CEO and the TMT on Organizational Ambidexterity. Journal of Management Studies. https://doi.org/10.1111/j.1467-6486.2009.00877.x

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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.