Abstract

Logistics parks served as critical logistics facilities during the coronavirus disease 2019 pandemic. Constructing these large-scale projects including their subsequent operations involved unusual risk factors that required comprehensive risk evaluations. Therefore, it is vital to examine the potential risk factors across the entire life cycle of these projects in accordance with the complexity of these large-scale logistics park projects (LLPPs) during the pandemic. This study proposes a new risk analysis model that evaluates a comprehensive list of risk factors based on the failure mode and effects analysis (FMEA). The hesitant uncertain linguistic Z-numbers (HULZNs) and fuzzy C-means (FCM) clustering algorithm are incorporated into the FMEA model to evaluate the risk. The practicability of the model was assessed in a case study. The findings identified and distinguished risk factors based on their levels of influences and priorities in dealing with uncertainties during the decision-making process in LLPPs. The FMEA model’s new methodological assessment also contributes to the efficient risk evaluation process through its more reliable and reasonable failure mode risk clustering, particularly for complex group decision-making environments during the pandemic.

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