The use of fuzzy-bayes approach on the causal factors of empty container repositioning

Empty container repositioning (ECR) is one of the major bottlenecks of maritime container transportation that should be minimized. To achieve this, it is crucial to reveal the leading causal factors. From a container liner firm perspective, this paper constructs a novel model of the causal mechanism of ECR with its reflections and prevention measures holistically. For this aim, this study examines the probabilistic relationships among the ECR causal factors, which are revealed qualitatively and quantitatively utilizing a fuzzy Bayes network method. Sensitivity and validation analyses subsequently are carried out to enhance the accuracy of findings. Outcomes of the research point out that the industry-specific and operational causal factors have the largest effect equally to explain the occurrence of ECR. Among the root factors, structural trade imbalance has the largest effect on the occurrence of ECR, and it is followed by seasonal demand. It is also observed that factors leading to equipment inefficiency have the least effect on ECR occurrence. Furthermore, the gray box pooling solution appears as the most effective solution to mitigate the negative impacts of ECR on both firm costs and the environment. What follows the gray box pooling are foldable containers and information technology solutions/intermediaries in order. This paper provides insight into ECR as a way to enhance effectiveness in container operations, and container liner firms can utilize the outcomes of this paper to mitigate the accumulation of empty containers. Keyword