Please use this identifier to cite or link to this item:
|Title:||Supply chain performance measurement system: A Monte Carlo DEA-based approach|
|Keywords:||Data Envelopment Analysis|
Supply chain efficiency
|Source:||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. https://doi.org/10.1504/IJISE.2008.016743|
|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|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Dec 12, 2017
checked on Dec 14, 2017
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.