TY - JOUR
T1 - Corporate culture and board gender diversity
T2 - Evidence from textual analysis
AU - Wongsinhirun, Nopparat
AU - Chatjuthamard, Pattanaporn
AU - Jiraporn, Pornsit
N1 - Funding Information:
This project was funded by the National Research Council of Thailand (NRCT) : N42A650683 .
Publisher Copyright:
© 2023 Elsevier Inc.
PY - 2023/3
Y1 - 2023/3
N2 - Exploiting a distinctive measure of corporate culture based on advanced machine learning, we investigate the effect of board gender diversity on corporate culture. Our results demonstrate that greater board gender diversity considerably strengthens positive corporate culture. The findings support the notion that board gender diversity enhances board oversight and helps solve agency problems, resulting in managers being compelled to take measures that benefit shareholders and consequently, building a strong company culture. Further analysis validates the results, including propensity score matching (PSM), entropy balancing, an instrumental-variable analysis, Lewbel's (2012) heteroscedastic identification, and Oster's (2019) testing for coefficient stability. Our study is the first to link board gender diversity to corporate culture, using cutting-edge information obtained from sophisticated machine learning.
AB - Exploiting a distinctive measure of corporate culture based on advanced machine learning, we investigate the effect of board gender diversity on corporate culture. Our results demonstrate that greater board gender diversity considerably strengthens positive corporate culture. The findings support the notion that board gender diversity enhances board oversight and helps solve agency problems, resulting in managers being compelled to take measures that benefit shareholders and consequently, building a strong company culture. Further analysis validates the results, including propensity score matching (PSM), entropy balancing, an instrumental-variable analysis, Lewbel's (2012) heteroscedastic identification, and Oster's (2019) testing for coefficient stability. Our study is the first to link board gender diversity to corporate culture, using cutting-edge information obtained from sophisticated machine learning.
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U2 - 10.1016/j.irfa.2023.102534
DO - 10.1016/j.irfa.2023.102534
M3 - Article
AN - SCOPUS:85148492722
SN - 1057-5219
VL - 86
JO - International Review of Financial Analysis
JF - International Review of Financial Analysis
M1 - 102534
ER -