Decision Support System Modelling and Analysis for Sustainable Smart Supply Chain Network

The chapter is more emphatic on the possibility of developing statistical techniques coping with the competition science to create a powerful decision making tool appropriate for sustainable supply chain network analysis. It highlights two independent techniques, to improve the quality of the outcomes in the decision making process. The former one focuses on the deployment of natural risk involved in the network. The concept of conditional probability is assigned to the conventional deterministic adjacency matrix in order to figure the uncertain interactions in the network. This will be useful to identify the crucial nodes in any supply chain and advantageous to classify these nodes based on their natural risk factor. The model concentrates on the delay time deviations from the mean delay time as the main competition. The combination of the two methodologies will find their position in improving the quality of the decision making actively.