Estimating most productive scale size with stochastic data in data envelopment analysis
This article estimates most productive scale size in stochastic data envelopment analysis (DEA). Jahanshahloo and Khodabakhshi [Jahanshahloo, G.R. and Khodabakhshi, M., Using input-output orientation model for determining most productive scale size in DEA. Applied Mathematics and Computation 2003, 146(2-3), 849-855.] studied most productive scale size in classic data envelopment analysis. The classic data envelopment analysis requires that the values for all inputs and outputs be known exactly. However, this assumption may not be true, because data in many real applications cannot be precisely measured. One of the important methods to deal with imprecise data is considering stochastic data in DEA. Therefore, this research studies most productive scale size with considering stochastic data in DEA. To that end, input-output orientation model introduced in Jahanshahloo and Khodabakhshi [Jahanshahloo, G.R. and Khodabakhshi, M., Using input-output orientation model for determining most productive scale size in DEA. Applied Mathematics and Computation 2003, 146(2-3), 849-855.] is extended in stochastic data envelopment analysis. To solve the stochastic model, a deterministic equivalent is obtained. Although the deterministic equivalent is non-linear, it can be converted to a quadratic program. Furthermore, data of software companies is used to apply the proposed approach. Performance of software companies are evaluated based on their scale sizes in classic and stochastic data envelopment analysis.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
- William Cooper & Zhimin Huang & Vedran Lelas & Susan Li & Ole Olesen, 1998. "Chance Constrained Programming Formulations for Stochastic Characterizations of Efficiency and Dominance in DEA," Journal of Productivity Analysis, Springer, vol. 9(1), pages 53-79, January.
- Banker, Rajiv D., 1984. "Estimating most productive scale size using data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 17(1), pages 35-44, July.
- Huang, Zhimin & Li, Susan X., 1996. "Dominance stochastic models in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 95(2), pages 390-403, December.
- Cooper, William W. & Deng, H. & Huang, Zhimin & Li, Susan X., 2004. "Chance constrained programming approaches to congestion in stochastic data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 155(2), pages 487-501, June.
- Li, Susan X., 1998. "Stochastic models and variable returns to scales in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 104(3), pages 532-548, February.
- Adler, Nicole & Friedman, Lea & Sinuany-Stern, Zilla, 2002. "Review of ranking methods in the data envelopment analysis context," European Journal of Operational Research, Elsevier, vol. 140(2), pages 249-265, July.
- R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
When requesting a correction, please mention this item's handle: RePEc:eee:ecmode:v:26:y:2009:i:5:p:968-973. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.