Information distortion in a supply chain: the bullwhip effect
Management Science - Special issue on frontier research in manufacturing and logistics
Value of Information in Capacitated Supply Chains
Management Science
Simulation Modeling and Analysis
Simulation Modeling and Analysis
Complexity Theory and Organization Science
Organization Science
Reengineering the order fulfillment process in supply chain networks: a multiagent information system approach
Sisco and scml: software tools for supply chain simulation modeling and information sharing
Sisco and scml: software tools for supply chain simulation modeling and information sharing
Supply Chain Inventory Management and the Value of Shared Information
Management Science
An investigative framework for studying the growth and evolution of complex supply networks
An investigative framework for studying the growth and evolution of complex supply networks
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Agent-based simulation provides a methodology to investigate complex systems behavior, such as supply chains, while incorporating many empirical elements relative to both systems structure and agent behavior. While there is a significant amount of simulation and analytical research investigating the impact of information sharing in supply chains, few studies have used empirical demand for the model. This research utilizes empirical distributions in order to determine the demand process faced by distribution centers in a distribution network. Therefore, the distribution centers face independent and heterogeneous demand that is not normal, and exhibits a much larger coefficient of variation than is generally utilized in similar research. With so much complexity and variability, contrasting different inter-organizational information sharing configurations provides an ideal setting for utilizing common random numbers for variance reduction. Comparisons made using this methodology show clear differences between the different information sharing schemes.