EconPapers    
Economics at your fingertips  
 

Finding efficient surfaces in DEA-R models

Mohammad Reza Mozaffari, Fatemeh Dadkhah, Josef Jablonsky and Peter Fernandes Wanke

Applied Mathematics and Computation, 2020, vol. 386, issue C

Abstract: Finding efficient surfaces is quite an important task in data envelopment analysis (DEA) because scale efficiency, returns to scale, and other characteristics of decision making units (DMUs) may easily be derived using them. Traditional DEA models assume that the inputs and outputs are given as non-ratio characteristics. In cases where only a ratio of inputs to outputs (or vice versa) is available for our DMUs, the decision maker is forced to make use of ratio data envelopment analysis (DEA-R) models for efficiency and performance evaluation. This paper deals with identification of efficient surfaces in DEA-R models. The axioms for specifying the production possibility set in constant returns to scale technology for DEA-R are discussed, and, finally an original algorithm for identification of efficient surfaces in this class of models is proposed. In the following, we will find the efficient hyper planes for the 10 bank branches under study. To expand the present study, a comparison was made between the BCC models in DEA and DEA-R, and DEA-R-efficient surfaces were calculated under CRS and VRS assumptions in a simple numerical example.

Keywords: DEA-R; Production possibility set; Efficient surface; Numerical examples (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0096300320304550
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:386:y:2020:i:c:s0096300320304550

DOI: 10.1016/j.amc.2020.125497

Access Statistics for this article

Applied Mathematics and Computation is currently edited by Theodore Simos

More articles in Applied Mathematics and Computation from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:apmaco:v:386:y:2020:i:c:s0096300320304550