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Performance Measurement and Evaluation for Sustainable Supply Chains using Rough Set and Data Envelopment Analysis

  • Chunguang Bai
  • Joseph Sarkis
Chapter
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 174)

Abstract

Performance measurement of sustainable supply chains is not a trivial issue. The complexities associated with measurement of supply chains is well known. Expanded sustainability measures for organizations and their supply chains only causes additional complexity. With many and varied measures helping organizations to distill information such that only the most pertinent and direct measures that provide information can make the process both more effective and efficient. In order to meet these goals this chapter provides an integrative approach that will help first distill and filter measures that are less redundant and then utilize these measures to arrive at a single performance value that managers can use for comparative and benchmarking analysis. We utilize a novel rough set theoretic approach and data envelopment analysis (DEA) as tools for distillation and integration of a variety of sustainable supply chainperformance measures. An example from sustainable supply chain data helps provide insights into the methodology.

Keywords

Supply Chain Data Envelopment Analysis Data Envelopment Analysis Model Very High Relative Performance Evaluation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgment

This work is supported by the National Natural Science Foundation of China Project (71102090)

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Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  1. 1.School of Management Science and EngineeringDongbei University of Finance and EconomicsDalianPeople’s Republic of China
  2. 2.Graduate School of ManagementClark UniversityWorcesterUSA

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