esg2go: A Method to Reduce Bias, Improve Coherence, and Increase Practicality of ESG Rating and Reporting

Isa Cakir, Philipp Aerni (), Manfred Max Bergman and Benjamin Cakir
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Isa Cakir: Center for Corporate Responsibility and Sustainability (CCRS), School of Management Fribourg (HEG-FR), 1700 Fribourg, Switzerland
Philipp Aerni: Center for Corporate Responsibility and Sustainability (CCRS), School of Management Fribourg (HEG-FR), 1700 Fribourg, Switzerland
Manfred Max Bergman: Department of Social Sciences, University of Basel, 4501 Basel, Switzerland
Benjamin Cakir: Center for Corporate Responsibility and Sustainability (CCRS), School of Management Fribourg (HEG-FR), 1700 Fribourg, Switzerland

Sustainability, 2023, vol. 15, issue 24, 1-20

Abstract: Rating agencies that assess a company’s environmental, social, and corporate governance (ESG) impact have been subject to public and academic scrutiny due to divergent and often biased rating outcomes. Concurrently, an evolving regulatory environment mandates publicly listed companies to report on ESG and climate emissions, taking into account supply chain risks as well. As a result, small and medium-sized enterprises (SMEs) are increasingly asked as suppliers to present a credible sustainability certificate. The esg2go rating and reporting system aims at improving the credibility and practicality of corporate sustainability assessment. It was jointly developed with its users and relevant stakeholders and is based on a calibrated benchmarking system from verifiable data. The rating method enables the measurement and comparison of sector- and firm size-specific sustainability performance. Its underlying adaptive parametrization is derived from a coherent and pragmatic definition of SME sustainability as the ‘ability to co-exist’. Our data analyses indicate that our scoring function is able to minimize bias and deliver a fair comparability between SMEs. We conclude that esg2go represents a pragmatic and innovative approach to enhance the fairness and accuracy of corporate sustainability assessment.

Keywords: corporate sustainability assessment; rating bias; ESG; SME; SDG; calibrated benchmarking; transparency; coexistence; footprint; handprint; model arbitrage (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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