Research on fresh supply chain risk evaluation of community group purchase based on hybrid multi-attribute decision-making method

The community group purchase (CGP) is rapidly evolving as a novel e-commerce mode that combines modern ecommerce with community integration in China. However, the core products of CGP are mainly fresh goods, where the fresh supply chain demands higher quality, faster processing, and greater freshness compared to the traditional product supply chain. Therefore, a risk evaluation of the CGP's fresh supply chain is crucial to ensure supplier stability, logistics efficiency, and storage conditions. This study presents a comprehensive risk evaluation model of CGP's fresh supply chain to enhance risk management and maintain product and freshness. Firstly, the social network analysis (SNA) method and the grounded theory are used to extract key indicators from existing literature and textual data. Secondly, the weight of each indicator is determined from the subjective and objective dimensions by using the order relationship analysis (G1) method and the Criteria Importance Through Intercriteria Correlation (CRITIC) method, and the decision matrix is constructed by the Fermatean hesitant fuzzy set. Then, considering that decision-maker (DM) may not be in a completely rational state during the evaluation process, the regret theory is introduced to quantify the DM's regret psychology. In addition, after obtaining the relative dominance through the TOmada de Decisao Iterativa Multicrite<acute accent>rio (TODIM) method, the risk evaluation is completed by using the VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method. Finally, sensitivity analysis validates the model's validity and applicability. This study offers a dynamic fresh supply chain risk evaluation model for the CGP industry, contributing to stable CGP enterprise operations.