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Revenue Efficiency of Fuzzy Sample Decision Making Unit

Revenue Efficiency of Fuzzy Sample Decision Making Unit

Nazila Aghayi, Samira Salehpour
Copyright: © 2015 |Volume: 5 |Issue: 2 |Pages: 14
ISSN: 2156-1737|EISSN: 2156-1729|EISBN13: 9781466680081|DOI: 10.4018/IJMTIE.2015070102
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MLA

Aghayi, Nazila, and Samira Salehpour. "Revenue Efficiency of Fuzzy Sample Decision Making Unit." IJMTIE vol.5, no.2 2015: pp.14-27. http://doi.org/10.4018/IJMTIE.2015070102

APA

Aghayi, N. & Salehpour, S. (2015). Revenue Efficiency of Fuzzy Sample Decision Making Unit. International Journal of Measurement Technologies and Instrumentation Engineering (IJMTIE), 5(2), 14-27. http://doi.org/10.4018/IJMTIE.2015070102

Chicago

Aghayi, Nazila, and Samira Salehpour. "Revenue Efficiency of Fuzzy Sample Decision Making Unit," International Journal of Measurement Technologies and Instrumentation Engineering (IJMTIE) 5, no.2: 14-27. http://doi.org/10.4018/IJMTIE.2015070102

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Abstract

Revenue efficiency measurement is one of the most important issues in data envelopment analysis (DEA). Most of the proposed models calculate the revenue efficiency of decision making units (DMUs) which play a main role in the formation of the production possibility set by implementing exact or fuzzy data. The revenue efficiency value of a sample decision making unit with exact and fuzzy data has not been investigated by these models yet. There exist different types of fuzzy numbers, however, only a special type of them has been used in revenue efficiency models with fuzzy data. The concept of vector has not been employed to calculate the measure of the revenue efficiency in any of the studies conducted thus far. However, in this article the authors propose a model for evaluating the revenue efficiency measure of a fuzzy sample DMU without the limitations of previous models with regards to the formation of the production possibility set. In the proposed model, data can be selected from different types of fuzzy numbers and there is no limitation on the type of the used fuzzy data. In addition, the current article employs the concept of vector for revenue efficiency assessment for the first time.

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