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Board structure and corporate strategic aggressiveness - an examination based on the double machine learning method

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  • Yaowu, Yang
  • Qidong, Cheng
  • Yang, Liu

Abstract

China's newly revised “Company Law” makes clear provisions regarding the composition and powers of the board of directors, which impact the formulation and implementation of corporate strategies. Taking the data of A-share listed companies in Shanghai and Shenzhen from 2008 to 2022 as the research sample, we employ double machine learning (DML) to verify the impact of board structure on corporate strategy aggressiveness, its mechanism of action and heterogeneous effects from the perspective of corporate boards. The study reveals that board structure has a significant effect on corporate strategic aggressiveness. Specifically, CEO duality enhances corporate strategic aggressiveness, a large size of the board of directors reduces corporate strategic aggressiveness, and the percentage of independent directors has a significant positive effect on corporate strategic aggressiveness. These effects can be realized through both internal control and compensation incentives. Further research shows that the effect of board structure on corporate strategic aggressiveness is more pronounced in firms whose executives have overseas backgrounds and in firms in highly competitive environments. Moreover, there is significant heterogeneity in the effect of board structure on corporate strategic aggressiveness in the presence of major exogenous shocks.

Suggested Citation

  • Yaowu, Yang & Qidong, Cheng & Yang, Liu, 2025. "Board structure and corporate strategic aggressiveness - an examination based on the double machine learning method," China Economic Review, Elsevier, vol. 92(C).
    • Handle: RePEc:eee:chieco:v:92:y:2025:i:c:s1043951x2500080x
    DOI: 10.1016/j.chieco.2025.102422
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    References listed on IDEAS

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    1. Ding, Zhiguo & Liu, Xinmiao & Ding, Yuyang, 2025. "How information structure shapes insider valuation bias: Evidence from insider selling in China," Finance Research Letters, Elsevier, vol. 85(PD).

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