Fuzzy Bayesian network analysis of the factors causing food losses in reefer containers

Abstract

It is crucial to ensure food security to continue the sustainable nutrition of the world population. Food losses in the global food supply chain pose a significant risk to food security. Especially foods that require cold chain logistics are prone to deterioration and eventually food losses. Therefore, cold chain logistics processes require operational expertise and specialized equipment. Reefer (refrigerated) container is the most used cold chain transport equipment for perishable foods requiring atmospheric control. Analyzing operational and hardware-related causes and implementing relevant countermeasures are necessary to prevent food losses in reefer containers. With this motivation in the study, the relationships between the factors causing food losses in the reefer containers were evaluated qualitatively and quantitatively via the model built using the Fuzzy Bayesian network method. The findings indicate that the most critical root causes of food losses in reefer containers are excessive time off-power, inappropriate preload conditions, and refrigerant faults, respectively. Moreover, the riskiest combination of factors that causes food loss consists of excessive time-off power, refrigerant faults, and adverse weather conditions during navigation and in port. When the existing legal framework and professional practices are examined, in light of the results of the study, the following will be recommended: Establishing minimum standard and maintenance arrangements for cooling systems, ensuring safety margin in the shelf life of the foods carried in the reefer containers, making mandatory the automatic temperature recordings systems, and increasing the number of personnel specialized in product types and transportation. The study results will benefit supply chain stakeholders for process planning and implementation to mitigate the risk of food losses in reefer containers.