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Simulating Complex Supply Chain Relationships Using Copulas

Simulating Complex Supply Chain Relationships Using Copulas
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Author(s): Krishnamurty Muralidhar (University of Oklahoma, USA) and Rathindra Sarathy (Oklahoma State University, USA)
Copyright: 2019
Pages: 14
Source title: Advanced Methodologies and Technologies in Business Operations and Management
Source Author(s)/Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-5225-7362-3.ch095

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Abstract

Simulation is often used as a tool to analyze and understand complex systems in supply chain management research. Supply chains involve complex relationships between different variables. Hence, it is necessary to simulate related non-normal distributions to simulate these systems. The simulation of related normal distributions is relatively easy and can be found in most simulation texts. However, when the marginal distributions under investigation do not have a normal distribution, it becomes very difficult to generate values from these related distributions. In this study, the authors illustrate a method based on copulas that allows for the generation of related distributions with arbitrary marginals. The procedure suggested in this study is simple and easy to implement. Using this procedure will enable researchers in supply chain management to more effectively simulate complex real-world scenarios resulting in better analysis and understanding of supply chains.

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