Computational Experiment Approach to Controlled Evolution of Procurement Pattern in Cluster Supply Chain

• Main Authors: Xiao Xue, Shufang Wang, Baoyun Lu
• Format: Article
• Language: English
• Published: MDPI AG 2015-01-01
• Series: Sustainability
• Subjects: Cluster Supply Chains (CSCs); procurement pattern; controlled evolution; agent-based modeling; computational experiment
• Online Access: http://www.mdpi.com/2071-1050/7/2/1516

Companies have been aware of the benefits of developing Cluster Supply Chains (CSCs), and they are spending a great deal of time and money attempting to develop the new business pattern. Yet, the traditional techniques for identifying 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 modeling approach to evaluate CSCs. Taking collaborative procurement as research object, our approach is composed of three parts: model construction, model instantiation, and computational experiment. We use the approach to explore the service charging policy problem in collaborative procurement. Three kinds of service charging polices are compared in the same experiment environment. Finally, “Fixed Cost” is identified as the optimal policy under the stable market environment. The case study can help us to understand the workflow of applying the approach, and provide valuable decision support applications to industry.