Board gender diversity and emissions performance: Insights from panel regressions, machine learning, and explainable AI

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Authors: Mohammad Hassan Shakil, Arne Johan Pollestad, Khine Kyaw, Ziaul Haque Munim
Cited by: 5
References: 47

Abstract

With European Union initiatives mandating gender quotas on corporate boards, a key question arises: Is greater board gender diversity (BGD) associated with better emissions performance (EP)? To answer this question, we examine the influence of BGD on EP across a sample of European firms from 2016 to 2022. Using panel regressions, advanced machine learning algorithms, and explainable AI, we reveal a non-linear relationship. Specifically, EP improves with BGD up to an optimal level of approximately 35 %, beyond which further increases in BGD yield no additional improvement in EP. A minimum BGD threshold of 22 % is necessary for meaningful improvements in EP. To assess the legitimacy of EP outcomes, this study examines whether ESG controversies weaken the BGD-EP relationship. The results show no significant effect, suggesting that BGD's impact is driven by governance mechanisms rather than symbolic actions. Additionally, path analysis indicates that while environmental innovation contributes to EP, it is not the mediating channel through which BGD promotes EP. The results have implications for academics, businesses, and regulators. • Board gender diversity (BGD) improves firms′ emissions performance (EP). • Emissions performance improves with BGD up to an optimal threshold of 35 %. • A minimum BGD threshold of 22 % is necessary for meaningful improvements in EP. • ESG controversies do not influence the BGD–EP relationship. • Environmental innovation improves emissions performance.

Fields of Study & Subjects

Aviation Industry Analysis and Trends Impact of AI and Big Data on Business and Society

Publication details

Journal / source
Journal of Environmental Management
Publisher
Elsevier BV
Volume
401
Pages
128776–128776
Publication date
4 February 2026
Language
EN