报告人：Srinivas (Sri) Talluri教授 美国密歇根州立大学
In this paper we present a methodology, by utilizing a nonparametric multivariate cumulative sum control chart and data envelopment analysis in tandem, to evaluate and monitor distribution network performance by simultaneously considering multiple performance factors and their interrelationships. While these methods were previously applied individually, we demonstrate that their combined use can provide more powerful results in performance assessment, monitoring, and improvement. Our approach contributes to the domain of supply chain analytics as it can provide new insights and understanding of business performance based on operations research and statistical methods to utilize real-time and past data. We demonstrate the application of our models on data gathered from The Dow Chemical Company, which is a multi-national vertically integrated chemical corporation.
Srinivas (Sri) Talluri is currently the Hoagland Metzler Endowed Professor and a Professor of supply chain management at Michigan State University, East Lansing, MI, USA. His research interests are in the areas of supply risk, buyer–supplier relationships, sustainability in supply chains, and performance evaluation. His methodological expertise includes deterministic and stochastic modeling, game theory, empirical methods, and data envelopment analysis. He has authored or coauthored more than 100 articles in journals, such as IIE Transactions, Journal of Operations Management, Decision Sciences, Production and Operations Management Journal, International Journal of Production Research, European Journal of Operational Research, IEEE Transactions on Engineering Management, and others. Sri currently serves as the Co-Editor in Chief for the Decision Sciences Journal. He is a Fellow of the Decision Sciences Institute, and a member of the Decision Sciences Institute and the Production and Operations Management Society.