Performance evaluation of supply chain in stochastic environment: using a simulation based DEA framework

Wai Peng Wong

International Journal of Business Performance and Supply Chain Modelling, 2009, vol. 1, issue 2/3, 203-228

Abstract: Supply chain operates in a dynamic platform and its performance measurement requires intensive data collection from the entire value chain. The task of collecting data in supply chain is not trivial and it often faces with uncertainties. This paper develops a simple tool to measure supply chain performance in the real environment, which is stochastic. Firstly, it introduces the data envelopment analysis (DEA) supply chain model in combination with Monte Carlo simulation to measure the supply chain performance in the stochastic environment. Secondly, a GA-based heuristic technique will be presented to improve the prediction of the performance measurement. This methodology offers an alternative to handle uncertainties in supply chain efficiency measurement and could also be used in other relevant fields, to measure efficiency.

Keywords: supply chain management; SCM; business performance; data envelopment analysis; DEA; Monte Carlo simulation; performance measurement; supply chain performance; modelling; stochastic environments. (search for similar items in EconPapers)
Date: 2009
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.inderscience.com/link.php?id=30642 (text/html)
Access to full text is restricted to subscribers.

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:ids:ijbpsc:v:1:y:2009:i:2/3:p:203-228

Access Statistics for this article

More articles in International Journal of Business Performance and Supply Chain Modelling from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().