Links Between Risk Source Identification and Resilience Capability Building in Agri-Food Supply Chains: A Comprehensive Analysis

【Author】 Zhao, Guoqing; Olan, Femi; Liu, Shaofeng; Hormazabal, Jorge Hernandez; Lopez, Carmen; Zubairu, Nasiru; Zhang, Jinhua; Chen, Xiaoning

【Source】IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT

【影响因子】8.702

【Abstract】Agri-food supply chain (AFSC) resilience is receiving increasing attention as AFSC stakeholders perceive its benefits in recovering from unexpected disruptions. However, which resilience capabilities are more effective in mitigating AFSC risks remains unclear. To address this gap, this article presents a novel AFSC risk and resilience analysis based on a systematic literature review (SLR). In total, 95 journal articles on AFSC risk and resilience management published between 2004 and 2020 are analyzed to identify key risks and resilience capabilities in AFSCs, the relationships, correlations and causalities between them, and research gaps and future research directions in the field. Our SLR reveals eight types of AFSC risk and seven types of AFSC resilience capability, and enables us to develop a one-to-one resilience-risk correspondence model. Suggestions for future research include: cross-country comparative analysis to gain a deeper understanding of risk and resilience management; identification of risk and resilience strengthening strategies through a multi-sectoral approach; longitudinal studies to determine the long-term effects of resilience capabilities; research to understand resilience from the perspectives of supply-chain collaboration, traceability, redundancy, knowledge management, innovation, leadership, and flexibility; investigations of the positive effects of AFSC risks in triggering resilience capabilities; and cross-disciplinary research to understand the relationships between resilience and other disciplines.

【Keywords】Agri-food supply chain; relationships between risk and resilience; supply chain resilience; supply chain risks; systematic literature review

【发表时间】

【收录时间】2022-12-16

【文献类型】理论模型

【主题类别】

区块链应用-实体经济-农牧领域