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

Chunguang Bai () and Joseph Sarkis ()
Additional contact information
Chunguang Bai: Dongbei University of Finance and Economics
Joseph Sarkis: Clark University

Chapter Chapter 15 in Sustainable Supply Chains, 2012, pp 223-241 from Springer

Abstract: 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 (search for similar items in EconPapers)
Date: 2012
References: Add references at CitEc
Citations: View citations in EconPapers (3)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-1-4419-6105-1_15

Ordering information: This item can be ordered from
http://www.springer.com/9781441961051

DOI: 10.1007/978-1-4419-6105-1_15

Access Statistics for this chapter

More chapters in International Series in Operations Research & Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().