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Together we win: The impact of board internationalization and board size on strategic change

Published online by Cambridge University Press:  21 July 2025

Kiattichai Kalasin*
Affiliation:
NIDA Business School, National Institute of Development Administration, Bangkok, Thailand
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Abstract

This study explores the relationships between board internationalization, board size, and strategic change of firms from emerging markets. Building upon resource dependency theory (RDT), this study proposes that board internationalization has a positive impact on strategic change. A higher level of nationality heterogeneity on the board of directors, an organization receives more diverse perspectives and experiences from foreign directors. This, in turn, influences firms to identify areas of improvement and engage in strategic change. In addition, conventional wisdom suggests that board size per se has a negative relationship with strategic change. However, this study proposes that large board sizes together with board internationalization can foster strategic change. In other words, board size and board internationalization can jointly counteract the inertial nature of a large board, resulting in strategic change. The analyses of 255 publicly listed firms from nine emerging countries for the 2013–2018 financial years confirm these predictions.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2025. Published by Cambridge University Press in association with Australian and New Zealand Academy of Management.
Figure 0

Table 1. Descriptive statistics and correlation

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Table 2. Panel data regressions

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Table 3. Multilevel analysis

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Table 4. Robustness check

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Table 5. Robustness check – logistic regression for panel data