Emergent supply networks: system dynamics simulation of adaptive supply agents

Abstract

Supply chain networks of independent firms collaborating to serve a final market are becoming a normal business phenomenon. Yet at present it is not clear if and how such networks can achieve stability. Nor is it obvious what successful managerial guidelines might be for individual companies operating in such networks regarding collaboration with the other firms involved. This exploratory study investigates these questions using a generic simulation model of 100 actors distributed over three supply echelons. The model was developed in a system dynamics simulation environment using design principles from agent-based modeling. In this model, each actor holds mental models of the performance of the other actors he is interacting with. Preferences for doing business with these other agents are driven by this performance. Agents differ in the degree in which they value long-term relationships over short-term performance. Model analysis shows that stability in this complex network emerges spontaneously as relative preferences become fixed over time. This lock-in occurs fairly early in the simulation during a period of considerable stress in the various supply chain echelons. Overall, those agents that base their relative preferences primarily on the short-term performance of their counterparts fare somewhat better than agents focussing on the nature of their long-term relationships. A real-world example of a supply network exhibiting characteristics such as the ones observed in the model is presented. Methodological considerations, model limitations and tentative managerial guidelines are discussed.

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