Sustainability and WEB-BASED Corporate Social Responsibility Disclosure: Could Machine Learning Models Explain the Impact on Bank’s Cash Holding.

KOTB, Elhassan, EL FAKIR, Adil and RUSSO, Antonella (2024). Sustainability and WEB-BASED Corporate Social Responsibility Disclosure: Could Machine Learning Models Explain the Impact on Bank’s Cash Holding. In: EZZIYYANI, Mostafa, KACPRZYK, Janusz and BALAS, Valentina-Emilia, (eds.) International Conference on Advanced Intelligent Systems for Sustainable Development (AI2SD'2023) Advanced Intelligent Systems on Energy, Environment and Agriculture. Lecture Notes in Networks and Systems, 2 (931). Cham, Springer, 69-81.

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Abstract

The current study aims to explore the impact of the quality and quantity of web-based Corporate Social Reporting Disclosure (CSRD) on corporate cash holdings in the context of top global Islamic and non-Islamic banks. To do So we use regression analysis through the Pearson Rank correlation and apply three machine learning models (ML regression, KNN (1,5), and SVM). Our Sample has taken into consideration Sustainability and Corporate Social reporting disclosure parameters of 100 conventional banks and 92 Islamic banks. We found empirical evidence that the quantity and quality Web based CSRD had no significant impact on the Cash holdings of both type of banks. This implies that there are other factors other than the CSRD factors that dictate the level of the cash holdings that banks would preserve.

Item Type:	Book Section
Additional Information:	Series ISSN: 2367-3370
Identification Number:	https://doi.org/10.1007/978-3-031-54288-6
Page Range:	69-81
SWORD Depositor:	Symplectic Elements
Depositing User:	Symplectic Elements
Date Deposited:	14 Mar 2024 15:56
Last Modified:	14 Mar 2024 15:57
URI:	https://shura.shu.ac.uk/id/eprint/33423

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