Leveraging an Uncertainty Methodology to Appraise Risk Factors Threatening Sustainability of Food Supply Chain

Abstract

By diminishing the risk factors associated with the food supply chain (FSC), we have recourse to strengthen the food supply chain's resilience, decrease food waste, and increase its sustainability. Prioritizing and identifying the risk factors impacting the sustainability of the food supply chain is essential for managing uncertainty and averting unfavorable consequences. This study attempts to identify and rank the most significant risks affecting the sustainability of the food supply chain under an uncertain environment. We use the α-Discounting multi-criteria decision-making (α-D MCDM) method for the main three risk factors: the risks of supply, the risks of demand, and the risks of operations. The primary causes of the challenges in assessing the food supply chain's risk elements include inaccurate assessment data, DMs' subjective preferences, and DMs' differing opinions and thoughts about the criteria. Unfortunately, earlier research fell short of fully resolving these issues. A hybrid three-phase neutrosophic MCDM method is proposed by integrating triangular neutrosophic numbers (TNNs), TNN-AHP, and TNN-CoCoSo to close this gap. In this manner, it may efficiently handle ambiguity. The application of the suggested framework is then explored using the top six food and beverage businesses in the world: Nestle (A1), PepsiCo (A2), Coca-Cola (A3), Danon (A4), Anheuser-Busch InBev SA (A5), and Mondelez International (A6). The results show the sustainability rankings from best to worst, which were established on the groups of decision-makers assessments based on the importance of the risk factors that have to be handled. To gain additional insight into the rationale and resilience of this framework, sensitivity evaluation and comparative analysis have been employed in this study.