Complexity analysis through the modeling of human behavior in a complex supply chain planning environment

The global supply chain is a complex network including multiple autonomous agents, and one representative of which is the supply chain planers, whose interactive activities bring in various uncertainty and complexity to the decision making. To better manage the dynamics, it is necessary to investigate the agents behaviors and their impacts on the supply chain. Our research starts with some hypotheses and then verifies them via an experiment. A prior questionnaire is distributed in order to analyze the correlation between human performance and risk literacy scale. Then a beer game is employed to demonstrate the ordering behaviors under different environmental settings. The bullwhip effect and the overreacting behaviors are observed and can be illustrated by the prospect theory. Finally an agent-based modeling approach is adopted to simulate the human behaviors, using the empirical threshold values derived from the example as the inputs to the model.