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Explainable artificial intelligence modeling for corporate social responsibility and financial performance

Author

Listed:
  • 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))

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.

Suggested Citation

  • Julien Lachuer & Sami Ben Jabeur, 2022. "Explainable artificial intelligence modeling for corporate social responsibility and financial performance," Post-Print hal-03828590, HAL.
    • Handle: RePEc:hal:journl:hal-03828590
    DOI: 10.1057/s41260-022-00291-z
    as

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    Cited by:

    1. Wei Jie Yeo & Wihan van der Heever & Rui Mao & Erik Cambria & Ranjan Satapathy & Gianmarco Mengaldo, 2023. "A Comprehensive Review on Financial Explainable AI," Papers 2309.11960, arXiv.org.

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