An application of artificial neural networks in corporate social responsibility decision making

Abstract

SummaryNeural networks in deep learning are changing the way we interact with the world. This paper focuses on building a logit artificial neural network (ANN) and through it finds out the factors affecting the decision to join corporate social responsibility (CSR) of firms. This study contributes to suggesting new directions for research in the artificial intelligence (AI) era on the relationship between corporate governance and CSR. The dataset of 817 Taiwanese electronic firms is analyzed for the period 2014–2020. The empirical results show that when the power of the board of directors, supervisors, and CEOs are higher, firms do not choose to participate in CSR. The independent board has not yet promoted its corporate oversight of CSR participation. The decision not to participate in CSR of the firms is made when they are more equipped with the background of accounting, finance, and law. Only firms with higher debt, asset value, and profitability are willing to join CSR. These research results suggest some important points for future policy reforms towards sustainability.

Unveiling the Impacts of Corporate Environmental, Social, and Governance Disclosure

“…Through learning from testing data, ANNs can autonomously discern complex patterns and relationships, making them invaluable tools in various fields, such as machine learning, pattern recognition, and predictive analytics. Binh (2024) [41] conducted a study on the construction of an artificial neural network (ANN) to analyze the determinants influencing firms' decisions to engage in corporate social responsibility (CSR) and found the ANN to be superior to the traditional logit model. By accurately forecasting emissions, ANN can inform decision-making processes to reduce environmental impact and promote sustainability.…”

The board director’s role in the relationship between organizational innovation and organizational learning in the sustainability innovation performance: an approximation from culture context

“…In addition to the previous conditions, the board of directors has also been the focus of different research in fields such as gender (Shittu & Che-Ahmad, 2023;Khan & Kent Baker, 2023;Zheng & Wang, 2023;Wagner et al al., 2023;Gavana et al, 2023;Deng et al, 2023), market dynamics (Stenzaly, 2023;Rees & Briône, 2023;Zhang et al, 2023;Akhter et al, 2023;Tang, 2023;Ferreira et al, 2023), environment (Ali et al, 2023), corporate social responsibility (Binh, 2023;García-Gómez et al, 2023), Leadership (Thomas, 2023), Cultural studies (Dodd et al, 2022;Hasan et al, 2023;Pi & Yang, 2023;Ferris et al, 2022).…”