Clustering structure and logistics: A new framework for supply network analysis

Abstract

Analysis of supply networks has been receiving abundant attention and enormous progress during the past decades. Most of the works focused on the detailed functionality of individuals in a small scale supply system while the network topology is often overlooked. Recently, network theory is introduced to study the structure–activity relations in supply networks. However, the understanding of connectivity pattern and collective behavior in large scale system is still limited. In our work, we propose a framework to model the supply network and analyze the relation between the clustering structure of the system and the dynamical logistic processes. In this framework, Configuration Models are used to build supply networks with different connectivity structures. Then by applying the logistic model on the networks, we could simulate the dynamical processes and evaluate the logistic performance. Simulation results demonstrate that the logistic dynamics of supply networks are highly related to the clustering structure. Using two measurements, we show that the supply networks with clustering structure can provide better services than those without by performing shorter Order lead-time and higher Delivery efficiency.