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Lookup NU author(s): Dr Haiyan LuORCiD
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© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.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.
Author(s): Zhao G, Liu S, Lopez C, Wang Y, Lu H, Zhang J
Publication type: Article
Publication status: Published
Journal: Annals of Operations Research
Year: 2024
Volume: 338
Pages: 1241–1282
Print publication date: 01/07/2024
Online publication date: 09/05/2024
Acceptance date: 26/04/2024
ISSN (print): 0254-5330
ISSN (electronic): 1572-9338
Publisher: Springer
URL: https://doi.org/10.1007/s10479-024-06040-2
DOI: 10.1007/s10479-024-06040-2
