Simulation of supply chain networks using complex adaptive system theory

Why do different supply chain structures emerge and exist? For example, why is the supply chain structure of the educational industry so different from those found in the manufacturing sector? Are there a simple set of rules that trigger the formation and growth of one type of structure over another? This paper is an initial attempt to answer these questions. Researchers have long modeled and analyzed supply chains using numerous approaches like system dynamics, continuous and discrete time differential equation modeling, and discrete event simulation modeling. These approaches, however, typically assume a predefined supply chain structure. Using the concepts of complex adaptive systems (CAS) we "grow" supply chains that are adaptive and evolving to their environments. Using this approach, we consider an environment, consisting of nodes representing suppliers, manufacturers and other entities in a supply chain. We simulate the behavior of supply chain nodes in four environments: munificent resource, scarce resource, information noisy, and clean information environments. By studying the dynamics arising from the interactions between nodes in each type of environment, questions on emergent supply chain networks can be answered. Each node is provided with a simple set of rules. The question for our research is what type of interaction gives rise to what kind of supply chain network structure?.