Measuring Dairy Supply Chain Resilience Using the Entropy Weight-TOPSIS Method

Abstract

In the context of globalization, the dairy supply chain faces increasingly complex risks and challenges, making the enhancement of its resilience to respond to emergencies a critical issue. This paper addresses this issue by employing the Entropy Weight-TOPSIS method to measure the resilience of dairy agricultural supply chains. An evaluation indicator system was constructed, with weights assigned to each indicator using the entropy weight method. Combined with the TOPSIS method, the relative strengths and weaknesses of each supply chain segment were calculated, thereby identifying vulnerabilities and areas for improvement. The findings reveal significant disparities in supply chain resilience development capabilities among the five listed dairy companies. In single-indicator assessments, Company Y Corporation stands out, ranking first in resistance capacity, recovery capacity, and learning capacity, outperforming its peers. Comprehensive evaluation revealed Company Y's dairy supply chain resilience as the strongest, while Company N, Company S, Company B, and Company T demonstrated relatively weaker resilience capabilities. Based on these findings, the study proposes measures to enhance dairy supply chain resilience, including strengthening government policy guidance and support, establishing diversified and risk-managed supply chain systems, and improving corporate capabilities.