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Building theory of agri-food supply chain resilience using Total Interpretive Structural Modelling and MICMAC analysis

Building theory of agri-food supply chain resilience using Total Interpretive Structural Modelling and MICMAC analysis
Building theory of agri-food supply chain resilience using Total Interpretive Structural Modelling and MICMAC analysis
Agri-food supply chains are inherent with some unique characteristics and that can be easily disrupted compared with other supply chains. Therefore, supply chain resilience factors are relevant and can be taken into consideration. In this paper an attempt has been made to build a theoretical framework of resilience factors in agri-food supply chains with the help of total interpretive structural modelling and matrix of cross impact multiplications applied to classification analysis. The results of the total interpretive structural modelling demonstrate that leadership plays a vital role in enhancing the resilience of the agri-food supply chain. Furthermore, the matrix of cross impact multiplications applied to classification analysis results indicate that leadership and working team stability along with strong driving power should be given critical focus by agri-food supply chain managers to facilitate the improvement of agri-food supply chain resilience. This paper contributes to the extant theory building in the field of agri-food supply chain resilience, to fill the gap that a few researches have been conducted on agri-food supply chain resilience theory building.
Agri-food supply chain resilience, Total Interpretive Structural Modelling, MICMAC analysis
2054-5819
Zhao, Guoqing
6fa035d1-56b1-46ea-a8fd-f91d7010674e
Liu, Shaofeng
9e435733-c5c6-49f8-b2b8-d0b44c24fc96
Lu, Haiyan
cde0410d-9843-43a7-b596-509e844a19ec
Lopez, Carmen
f11f88d5-36c4-4beb-a4c5-ceb16a6df19c
Elgueta, Sebastian
c316c8a3-f60b-440f-883a-70058a556103
Zhao, Guoqing
6fa035d1-56b1-46ea-a8fd-f91d7010674e
Liu, Shaofeng
9e435733-c5c6-49f8-b2b8-d0b44c24fc96
Lu, Haiyan
cde0410d-9843-43a7-b596-509e844a19ec
Lopez, Carmen
f11f88d5-36c4-4beb-a4c5-ceb16a6df19c
Elgueta, Sebastian
c316c8a3-f60b-440f-883a-70058a556103

Zhao, Guoqing, Liu, Shaofeng, Lu, Haiyan, Lopez, Carmen and Elgueta, Sebastian (2019) Building theory of agri-food supply chain resilience using Total Interpretive Structural Modelling and MICMAC analysis. International Journal of Sustainable Agricultural Management and Informatics, 4 (3-4). (doi:10.1504/IJSAMI.2018.099236).

Record type: Article

Abstract

Agri-food supply chains are inherent with some unique characteristics and that can be easily disrupted compared with other supply chains. Therefore, supply chain resilience factors are relevant and can be taken into consideration. In this paper an attempt has been made to build a theoretical framework of resilience factors in agri-food supply chains with the help of total interpretive structural modelling and matrix of cross impact multiplications applied to classification analysis. The results of the total interpretive structural modelling demonstrate that leadership plays a vital role in enhancing the resilience of the agri-food supply chain. Furthermore, the matrix of cross impact multiplications applied to classification analysis results indicate that leadership and working team stability along with strong driving power should be given critical focus by agri-food supply chain managers to facilitate the improvement of agri-food supply chain resilience. This paper contributes to the extant theory building in the field of agri-food supply chain resilience, to fill the gap that a few researches have been conducted on agri-food supply chain resilience theory building.

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More information

Published date: 16 April 2019
Keywords: Agri-food supply chain resilience, Total Interpretive Structural Modelling, MICMAC analysis

Identifiers

Local EPrints ID: 434143
URI: http://eprints.soton.ac.uk/id/eprint/434143
ISSN: 2054-5819
PURE UUID: 4496911a-d04a-40a4-9e6f-e7bf083eb3ce
ORCID for Carmen Lopez: ORCID iD orcid.org/0000-0002-5510-1920

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Date deposited: 13 Sep 2019 16:30
Last modified: 27 Jan 2020 13:59

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Contributors

Author: Guoqing Zhao
Author: Shaofeng Liu
Author: Haiyan Lu
Author: Carmen Lopez ORCID iD
Author: Sebastian Elgueta

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