Risk analysis of the agri-food supply chain: A multi-method approach

Zhao, Guoqing; Liu, Shaofeng; Lopez, Carmen; Chen, Huilan; Lu, Haiyan; Mangla, Sachin Kumar; Elgueta, Sebastian

doi:10.1080/00207543.2020.1725684

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Risk analysis of the agri-food supply chain: A multi-method approach

Guoqing Zhao, Shaofeng Liu, Carmen Lopez

, Huilan Chen, Haiyan Lu, Sachin Kumar Mangla, Sebastian Elgueta

International Journal of Production Research, Volume: 58, Issue: 16, Pages: 4851 - 4876

Swansea University Author: Guoqing Zhao

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DOI (Published version): 10.1080/00207543.2020.1725684

Abstract

Agri-food supply chains (AFSCs) are becoming more complex in structure, and thus more susceptible to different vulnerabilities and risks. Therefore, to enhance performance, we need to manage the risks in AFSCs effectively and efficiently. This study analyses various AFSC risks using a multi-method a...

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Published in:	International Journal of Production Research
ISSN:	0020-7543 1366-588X
Published:	Informa UK Limited 2020
Online Access:	Check full text
URI:	https://cronfa.swan.ac.uk/Record/cronfa62345
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first_indexed	2023-01-17T12:23:45Z
last_indexed	2023-02-18T04:13:55Z
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spelling	2023-02-17T14:53:16.4850856 v2 62345 2023-01-17 Risk analysis of the agri-food supply chain: A multi-method approach 2ff29aa347835abe2af6d98fa89064b4 Guoqing Zhao Guoqing Zhao true false 2023-01-17 BBU Agri-food supply chains (AFSCs) are becoming more complex in structure, and thus more susceptible to different vulnerabilities and risks. Therefore, to enhance performance, we need to manage the risks in AFSCs effectively and efficiently. This study analyses various AFSC risks using a multi-method approach, including thematic analysis, total interpretive structural modelling (TISM) and fuzzy cross-impact matrix multiplication applied to classification (MICMAC) analysis. Based on the empirical data collected from experienced AFSC practitioners and following thematic analysis, eight categories of risk and 16 risk factors were identified as important. Furthermore, the interrelationships among the identified risks were built using TISM. Finally, the identified risks were classified into various categories according to their dependence and driving power using fuzzy MICMAC analysis. The research results indicate that the weather-related and political risks have the highest driving power and are located at the lowest level in the TISM hierarchy. These risks have a high tendency to disturb the whole flow of AFSC and so should be managed effectively. This study advances existing literature on identifying risk factors, defining interrelations between different AFSC risks, and determining the key risks. The risk analysis results can help AFSC practitioners in AFSC to identify, categorise and analyse the risks. Journal Article International Journal of Production Research 58 16 4851 4876 Informa UK Limited 0020-7543 1366-588X agri-food supply chain; risk identification; thematic analysis; total interpretive structural modelling; fuzzy MICMAC 17 8 2020 2020-08-17 10.1080/00207543.2020.1725684 COLLEGE NANME Business COLLEGE CODE BBU Swansea University 2023-02-17T14:53:16.4850856 2023-01-17T12:21:17.0420069 Faculty of Humanities and Social Sciences School of Management - Business Management Guoqing Zhao 1 Shaofeng Liu 2 Carmen Lopez 0000-0002-5510-1920 3 Huilan Chen 4 Haiyan Lu 5 Sachin Kumar Mangla 6 Sebastian Elgueta 7 62345__26613__20e09390d2d44db0bd0724c9ca87634e.pdf 62345.pdf 2023-02-17T14:51:31.3697922 Output 165552 application/pdf Accepted Manuscript true Released under the terms of a Creative Commons Attribution Non-Commercial License (CC-BY-NC) true eng https://creativecommons.org/licenses/by-nc/4.0/
title	Risk analysis of the agri-food supply chain: A multi-method approach
spellingShingle	Risk analysis of the agri-food supply chain: A multi-method approach Guoqing Zhao
title_short	Risk analysis of the agri-food supply chain: A multi-method approach
title_full	Risk analysis of the agri-food supply chain: A multi-method approach
title_fullStr	Risk analysis of the agri-food supply chain: A multi-method approach
title_full_unstemmed	Risk analysis of the agri-food supply chain: A multi-method approach
title_sort	Risk analysis of the agri-food supply chain: A multi-method approach
author_id_str_mv	2ff29aa347835abe2af6d98fa89064b4
author_id_fullname_str_mv	2ff29aa347835abe2af6d98fa89064b4_***_Guoqing Zhao
author	Guoqing Zhao
author2	Guoqing Zhao Shaofeng Liu Carmen Lopez Huilan Chen Haiyan Lu Sachin Kumar Mangla Sebastian Elgueta
format	Journal article
container_title	International Journal of Production Research
container_volume	58
container_issue	16
container_start_page	4851
publishDate	2020
institution	Swansea University
issn	0020-7543 1366-588X
doi_str_mv	10.1080/00207543.2020.1725684
publisher	Informa UK Limited
college_str	Faculty of Humanities and Social Sciences
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hierarchy_top_id	facultyofhumanitiesandsocialsciences
hierarchy_top_title	Faculty of Humanities and Social Sciences
hierarchy_parent_id	facultyofhumanitiesandsocialsciences
hierarchy_parent_title	Faculty of Humanities and Social Sciences
department_str	School of Management - Business Management{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}School of Management - Business Management
document_store_str	1
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description	Agri-food supply chains (AFSCs) are becoming more complex in structure, and thus more susceptible to different vulnerabilities and risks. Therefore, to enhance performance, we need to manage the risks in AFSCs effectively and efficiently. This study analyses various AFSC risks using a multi-method approach, including thematic analysis, total interpretive structural modelling (TISM) and fuzzy cross-impact matrix multiplication applied to classification (MICMAC) analysis. Based on the empirical data collected from experienced AFSC practitioners and following thematic analysis, eight categories of risk and 16 risk factors were identified as important. Furthermore, the interrelationships among the identified risks were built using TISM. Finally, the identified risks were classified into various categories according to their dependence and driving power using fuzzy MICMAC analysis. The research results indicate that the weather-related and political risks have the highest driving power and are located at the lowest level in the TISM hierarchy. These risks have a high tendency to disturb the whole flow of AFSC and so should be managed effectively. This study advances existing literature on identifying risk factors, defining interrelations between different AFSC risks, and determining the key risks. The risk analysis results can help AFSC practitioners in AFSC to identify, categorise and analyse the risks.
published_date	2020-08-17T04:21:53Z
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score	11.017797

Risk analysis of the agri-food supply chain: A multi-method approach

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