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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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first_indexed 2024-10-28T13:27:38Z
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spelling v2 67548 2024-09-03 Assessing Climate Transition Risks in the Colombian Processed Food Sector: A Fuzzy Logic and Multi-Criteria Decision-Making Approach d0b8d4e63d512d4d67a02a23dd20dfdb 0000-0001-9199-7368 Fabio Caraffini Fabio Caraffini true false 2024-09-03 MACS 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. Journal Article Mathematics 12 17 2713 MDPI AG 2227-7390 climate transition risk; risk matrix; risk assessment; fuzzy logic; multi-criteria decision making 30 8 2024 2024-08-30 10.3390/math12172713 COLLEGE NANME Mathematics and Computer Science School COLLEGE CODE MACS Swansea University This research received no external funding. 2024-10-28T13:29:58.7270899 2024-09-03T20:45:32.7765877 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Juan F. Pérez-Pérez 0000-0002-5650-2451 1 Pablo Isaza Gómez 2 Isis Bonet 0000-0002-3031-2334 3 María Solange Sánchez-Pinzón 4 Fabio Caraffini 0000-0001-9199-7368 5 Christian Lochmuller 0009-0008-7322-5311 6 67548__32746__1c72aa11e74d4c8a871db3db4c8bc48e.pdf 67548.VoR.pdf 2024-10-28T13:28:03.2775665 Output 1233401 application/pdf Version of Record true © 2024 by the authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. true eng https://creativecommons.org/licenses/by/4.0/
title Assessing Climate Transition Risks in the Colombian Processed Food Sector: A Fuzzy Logic and Multi-Criteria Decision-Making Approach
spellingShingle Assessing Climate Transition Risks in the Colombian Processed Food Sector: A Fuzzy Logic and Multi-Criteria Decision-Making Approach
Fabio Caraffini
title_short Assessing Climate Transition Risks in the Colombian Processed Food Sector: A Fuzzy Logic and Multi-Criteria Decision-Making Approach
title_full Assessing Climate Transition Risks in the Colombian Processed Food Sector: A Fuzzy Logic and Multi-Criteria Decision-Making Approach
title_fullStr Assessing Climate Transition Risks in the Colombian Processed Food Sector: A Fuzzy Logic and Multi-Criteria Decision-Making Approach
title_full_unstemmed Assessing Climate Transition Risks in the Colombian Processed Food Sector: A Fuzzy Logic and Multi-Criteria Decision-Making Approach
title_sort Assessing Climate Transition Risks in the Colombian Processed Food Sector: A Fuzzy Logic and Multi-Criteria Decision-Making Approach
author_id_str_mv d0b8d4e63d512d4d67a02a23dd20dfdb
author_id_fullname_str_mv d0b8d4e63d512d4d67a02a23dd20dfdb_***_Fabio Caraffini
author Fabio Caraffini
author2 Juan F. Pérez-Pérez
Pablo Isaza Gómez
Isis Bonet
María Solange Sánchez-Pinzón
Fabio Caraffini
Christian Lochmuller
format Journal article
container_title Mathematics
container_volume 12
container_issue 17
container_start_page 2713
publishDate 2024
institution Swansea University
issn 2227-7390
doi_str_mv 10.3390/math12172713
publisher MDPI AG
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
document_store_str 1
active_str 0
description 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.
published_date 2024-08-30T13:29:56Z
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score 11.036706

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