Vafadarnikjoo, A. orcid.org/0000-0003-2147-6043, Tavana, M., Chalvatzis, K. et al. (1 more author) (2022) A socio-economic and environmental vulnerability assessment model with causal relationships in electric power supply chains. Socio-Economic Planning Sciences, 80. 101156. ISSN 0038-0121
Abstract
The electric power industry is uniquely vulnerable to natural and human-made risks such as natural disasters, climate change, and cybersecurity. This study proposes a vulnerability assessment framework to identify and assess the risks associated with the electric power supply chain in the United Kingdom and study the causal relationship among them with the neutrosophic revised decision-making trial and evaluation laboratory (NR-DEMATEL) method. We further introduce a novel hesitant expert selection model (HESM) to assist decision-makers with expert selection and weight determination. We present a case study in the United Kingdom power supply chain to demonstrate the applicability and efficacy of the proposed method in this study. This is the first comprehensive risk interdependence analysis of the United Kingdom's power supply chain. The findings reveal natural disasters and climate change are the most crucial risks followed by industrial action, affordability, political instability, and sabotage/terrorism.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 Elsevier Ltd. This is an author produced version of a paper subsequently published in Socio-Economic Planning Sciences. Uploaded in accordance with the publisher's self-archiving policy. Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
Keywords: | Vulnerability assessment; Causal relationship; Environmental economics; Power supply chain; Neutrosophic set theory; DEMATEL |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Management School (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 24 Jan 2022 08:26 |
Last Modified: | 11 Mar 2023 01:13 |
Status: | Published |
Publisher: | Elsevier BV |
Refereed: | Yes |
Identification Number: | 10.1016/j.seps.2021.101156 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:182840 |