Identification, establishment of connection, and clustering of social risks involved in the agri-food supply chains: a cross-country comparative study

Guoqing Zhao (), Shaofeng Liu (), Carmen Lopez (), Yi Wang (), Haiyan Lu () and Jinhua Zhang ()
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Guoqing Zhao: Swansea University
Shaofeng Liu: University of Plymouth
Carmen Lopez: University of Southampton
Yi Wang: University of Bedfordshire
Haiyan Lu: Newcastle University
Jinhua Zhang: University of Plymouth

Annals of Operations Research, 2024, vol. 338, issue 2, No 16, 1282 pages

Abstract: Abstract Supply chain risk management (SCRM) literature is heterogeneous. While much attention has been given to the economic and environmental dimensions, the social dimension has so far received less focus. Thus, this study analyzes the social risks involved in the agri-food supply chains (AFSCs) of Argentina and China by employing an integrated approach. Semi-structured interviews were used to collect data, followed by using a combination of three complementary data analysis methods: thematic analysis to identify social risks, total interpretive structural modeling (TISM) to build interrelationships among the identified social risks, and fuzzy MICMAC (cross-impact matrix multiplication applied to classification analysis) to cluster social risks into four categories. Next, we conducted a comparative analysis between the two countries. Theoretical contributions are mainly threefold. First, we identified various social risks involved in the AFSCs of Argentina and China, including those just touched on by scholars, such as cultural issues, government’s weak monitoring system, the power differential between managers and subordinates, inappropriate disposal of agrichemical containers, and the lack of basic literacy skills. Second, we believe that our study is the first to establish connections among the identified AFSC social risks, which represents the originality of this work. Third, we discover that cultural issues is the key risk that has the highest capability to elicit other social risks involved in the AFSCs. Our work extends scholarship’s knowledge to understand AFSC social risks from the cultural perspective. This study also generates contributions to policymakers, migrant associations, and the government tax departments of Argentina and China.

Keywords: Social risks; Agri-food supply chain; Thematic analysis; Total interpretive structural modeling; Fuzzy MICMAC analysis; Cross-country study (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10479-024-06040-2

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