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Title: Supply chain performance measurement system: A Monte Carlo DEA-based approach
Authors: Wong, W.P.
Jaruphongsa, J. 
Lee, L.H. 
Keywords: Data Envelopment Analysis
Monte Carlo
Stochastic data
Supply chain efficiency
Issue Date: Jan-2008
Citation: Wong, W.P.,Jaruphongsa, J.,Lee, L.H. (2008-01). Supply chain performance measurement system: A Monte Carlo DEA-based approach. International Journal of Industrial and Systems Engineering 3 (2) : 162-188. ScholarBank@NUS Repository.
Abstract: A supply chain operates in a dynamic platform and its performance efficiency measurement requires intensive data collection. The task of collecting data in a 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 introduced the Data Envelopment Analysis (DEA) supply chain model to measure the supply chain performance. Next, it enhanced the model with Monte Carlo (random sampling) methodology to cater for efficiency measurement in stochastic environment. Monte Carlo approximations to stochastic DEA have not been practically used in empirical analysis, despite being an important tool to make statistical inferences on the efficiency point estimator. This method proves to be a cost saving and efficient way to handle uncertainties and could be used in other relevant field other than supply chain, to measure efficiency. Copyright © 2008 Inderscience Enterprises Ltd.
Source Title: International Journal of Industrial and Systems Engineering
ISSN: 17485037
DOI: 10.1504/IJISE.2008.016743
Appears in Collections:Staff Publications

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