Abstract

Companies are aware of the benefits of developing industrial clusters, and spend a great deal of time and money attempting to develop these relationships. Yet, the traditional techniques for identifying these relationships, Cluster Supply Chains (CSCs), have strong theoretical antecedents but seem to have little traction in the field. We believe this is because the standard techniques fail to capture evolution over time, nor provide useful intervention measures to reach goals. To address these problems, we introduce an agent-based computational experiment approach to evaluate CSCs, which explicitly accounts for dynamic change in the procurement process. We evaluate the procurement problem under different service charge strategies. These results will help us to understand the evolution mechanism and related phenomena, and provide valuable decision support applications to industry.

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