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Assessing Climate Transition Risks in the Colombian Processed Food Sector: A Fuzzy Logic and Multi-Criteria Decision-Making Approach

Juan F. Pérez-Pérez Orcid Logo, Pablo Isaza Gómez, Isis Bonet Orcid Logo, María Solange Sánchez-Pinzón, Fabio Caraffini Orcid Logo, Christian Lochmuller Orcid Logo

Mathematics, Volume: 12, Issue: 17, Start page: 2713

Swansea University Author: Fabio Caraffini Orcid Logo

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DOI (Published version): 10.3390/math12172713

Abstract

Climate risk assessment is critical for organisations, especially in sectors such as the processed food sector in Colombia. This study addresses the identification and assessment of the main climate transition risks using an approach that combines fuzzy logic with several multi-criteria decision-mak...

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Published in: Mathematics
ISSN: 2227-7390
Published: MDPI AG 2024
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URI: https://cronfa.swan.ac.uk/Record/cronfa67548
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Abstract: Climate risk assessment is critical for organisations, especially in sectors such as the processed food sector in Colombia. This study addresses the identification and assessment of the main climate transition risks using an approach that combines fuzzy logic with several multi-criteria decision-making methods. This approach makes it possible to handle the inherent imprecision of these risks and to use linguistic expressions to better describe them. The results indicate that the most critical risks are price volatility and availability of raw materials, the shift towards less carbon-intensive production models, increased carbon taxes, technological advances, and associated development or implementation costs. These risks are the most significant for the organisation studied and underline the need for investments to meet regulatory requirements, which are the main financial drivers for organisations. This analysis highlights the importance of a robust framework to anticipate and mitigate the impacts of the climate transition.
Keywords: climate transition risk; risk matrix; risk assessment; fuzzy logic; multi-criteria decision making
College: Faculty of Science and Engineering
Funders: This research received no external funding.
Issue: 17
Start Page: 2713