AN AGENT-BASED SIMULATION MODEL TO MITIGATE THE BULLWHIP EFFECT VIA INFORMATION SHARING AND RISK POOLING

The bullwhip effect, a phenomenon of progressively larger distortion of demands across a supply chain, can cause chaos and disorder with amplified supply and demand misalignment. In this research, we investigate ways to decrease the bullwhip effect via risk pooling and information sharing through a simulation study. An agent-based simulation model was developed to evaluate how risk pooling and information sharing between distinct entities in a supply chain can reduce the bullwhip effects. Specifically, we are interested in the effectiveness of these two strategies through their interplay when they are applied simultaneously and separately. We simulate a three-echelon supply chain by considering one manufacturer, one wholesaler, and two retailers. Four scenarios are evaluated by varying the information sharing strategy (centralized and decentralized), and with and without a risk pooling policy. The results show that when both strategies are adopted, the supply chain faces less order amplification throughout the supply chain.