The aim of this study is to propose a method to evaluate the Corporate Social Responsibility (CSR) identity of a firm. Using this method, based on a fuzzy expert system (FES), it is possible to generate a comprehensive rating for the assessment of the sustainability of a firm. Up to now, measurement has been hampered by a lack of clarity in theoretical frameworks and empirical methods for the Corporate Social Responsibility construct. The algorithm of the Fuzzy Expert System aggregates multicriteria evaluations of a problem. The assessments of behavior and the resulting decisions are represented in blocks of rules, drawn up by an inference engine in fuzzy logic. The Fuzzy Expert System unites the ability of an expert system to simulate the decision-making process with the uncertainty typical of human reasoning, present in fuzzy logic. Despite the spread of Corporate Social Responsibility practices among firms, there is not a commonly accepted method of measuring sustainability. Moreover, although Environmental social governance (ESG) rating agencies provide Corporate Social Responsibility ratings, their methods have certain weaknesses. Considering the growing importance of socially responsible financial markets, this topic could be of vital importance for decision-makers in the management of their investments, by remedying deficiencies in methods used by sustainability rating organizations. The outcome of the application is a system designed to measure the CSR identity of a firm. On the management side, the possibility to identify the determinants of the different Corporate Social Responsibility intermediate indicators making up the final Corporate Social Responsibility index would allow CSR-compliant managers to use this information for decision-making purposes.

How can CSR identity be evaluated? A pilot study using a Fuzzy Expert System

Leopizzi, Rossella;
2017-01-01

Abstract

The aim of this study is to propose a method to evaluate the Corporate Social Responsibility (CSR) identity of a firm. Using this method, based on a fuzzy expert system (FES), it is possible to generate a comprehensive rating for the assessment of the sustainability of a firm. Up to now, measurement has been hampered by a lack of clarity in theoretical frameworks and empirical methods for the Corporate Social Responsibility construct. The algorithm of the Fuzzy Expert System aggregates multicriteria evaluations of a problem. The assessments of behavior and the resulting decisions are represented in blocks of rules, drawn up by an inference engine in fuzzy logic. The Fuzzy Expert System unites the ability of an expert system to simulate the decision-making process with the uncertainty typical of human reasoning, present in fuzzy logic. Despite the spread of Corporate Social Responsibility practices among firms, there is not a commonly accepted method of measuring sustainability. Moreover, although Environmental social governance (ESG) rating agencies provide Corporate Social Responsibility ratings, their methods have certain weaknesses. Considering the growing importance of socially responsible financial markets, this topic could be of vital importance for decision-makers in the management of their investments, by remedying deficiencies in methods used by sustainability rating organizations. The outcome of the application is a system designed to measure the CSR identity of a firm. On the management side, the possibility to identify the determinants of the different Corporate Social Responsibility intermediate indicators making up the final Corporate Social Responsibility index would allow CSR-compliant managers to use this information for decision-making purposes.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11586/300663
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