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Charnes, A., W.W. Cooper, and E. Rhodes, Measuring the efficiency of decision making units. European Journal of Operational Research, 1978. 2 (6): p. 429-444.

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Article

Measuring Efficiency and Effectiveness for Non-Storable Commodities: A Mixed Separate Data Envelopment Analysis Spproaches with Real and Fuzzy Data

1Department of Mathematics, Mashhad Branch, Islamic Azad University, Mashhad, Iran


International Journal of Data Envelopment Analysis and *Operations Research*. 2014, Vol. 1 No. 1, 1-11
DOI: 10.12691/ijdeaor-1-1-1
Copyright © 2014 Science and Education Publishing

Cite this paper:
Babooshka Shavazipour. Measuring Efficiency and Effectiveness for Non-Storable Commodities: A Mixed Separate Data Envelopment Analysis Spproaches with Real and Fuzzy Data. International Journal of Data Envelopment Analysis and *Operations Research*. 2014; 1(1):1-11. doi: 10.12691/ijdeaor-1-1-1.

Correspondence to: Babooshka  Shavazipour, Department of Mathematics, Mashhad Branch, Islamic Azad University, Mashhad, Iran. Email: b.shavazipour@gmail.com

Abstract

Data Envelopment Analysis (DEA) is a technique for measuring the relative efficiency of Decision Making Units (DMUs) which produce similar products. Measures of both technical efficiency and service effectiveness for storable commodities are essentially the same. However, these measures for non-storable commodities, such as transport services, represent two distinct dimensions and a joint measurement of both or measurement with their impression mutual is necessary to fully capture the overall performance. In this paper, a Mixed Separate Data Envelopment Analysis (MSDEA) approach is introduced to analyze the overall performance of non-storable commodities. Then, the case of ten intercity car companies is described as the application of this novel approach. Moreover, when some observations are fuzzy, the efficiencies and effectiveness become fuzzy as well. For more extension, MSDEA approach with fuzzy observations called Fuzzy Mixed Separate Data Envelopment Analysis (FMSDEA) approach will be presented and illustrated with a numerical example.

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