Explainable artificial intelligence modeling for corporate social responsibility and financial performance

Julien Lachuer () and Sami Ben Jabeur ()
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Julien Lachuer: CREM - Centre de recherche en économie et management - UNICAEN - Université de Caen Normandie - NU - Normandie Université - UR - Université de Rennes - CNRS - Centre National de la Recherche Scientifique
Sami Ben Jabeur: ESDES - ESDES, Lyon Business School - UCLy - UCLy - UCLy (Lyon Catholic University), UR CONFLUENCE : Sciences et Humanités (EA 1598) - UCLy - UCLy (Lyon Catholic University)

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Abstract: In this paper, we examine the relation between corporate social responsibility and corporate financial performance in a bullish market. Previous studies have heterogeneous results, mainly due to differences in the samples and statistical approaches used. To resolve these issues, we use an innovative approach through explainable artificial intelligence (XAI). To reflect the recent expansions of CSR practices, we propose a longitudinal analysis of the US market from 2014-2019. We find that in a bullish market, CSR is negatively related to financial market performance. Through the use of XAI, we show that CSR exclusively improves the financial performance of the most sustainable companies. We also highlight the existence of thresholds that modify the relation between the level of CSR and our financial variables.

Keywords: corporate social responsibility; financial performance; machine learning; stakeholder (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

Published in Journal of Asset Management, 2022, ⟨10.1057/s41260-022-00291-z⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-03828590

DOI: 10.1057/s41260-022-00291-z

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