Board Expertise Background and Firm Performance

Chiou-Yann Lee, Chun-Ru Wen and Binh Thi-Thanh-Nguyen ()
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Chiou-Yann Lee: Department of Accounting, Chaoyang University of Technology, 168 Jifong E. Road, Wufong District, Taichung City 41349, Taiwan
Chun-Ru Wen: Department of Accounting, Chaoyang University of Technology, 168 Jifong E. Road, Wufong District, Taichung City 41349, Taiwan
Binh Thi-Thanh-Nguyen: Department of Accounting, Chaoyang University of Technology, 168 Jifong E. Road, Wufong District, Taichung City 41349, Taiwan

IJFS, 2024, vol. 12, issue 1, 1-15

Abstract: This study presents a novel financial performance forecasting method that combines the threshold technique with Artificial Neural Networks (ANN). It applies the threshold regression method to identify the factors within the board of directors that influence the financial performance of traditional industries in Taiwan. The findings indicate that the ANN method effectively predicts financial performance by using relevant board structure data. Furthermore, the empirical results suggest that boards with more members demonstrate increased profitability. Additionally, a more significant presence of board members with accounting expertise contributes to more consistent profits. In contrast, an increased presence of members with financial expertise has a more pronounced impact on profitability.

Keywords: artificial neural networks; multi-threshold model; financial performance (search for similar items in EconPapers)
JEL-codes: F2 F3 F41 F42 G1 G2 G3 (search for similar items in EconPapers)
Date: 2024
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