An extended multiple criteria data envelopment analysis model

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F17%3A86098952" target="_blank" >RIV/61989100:27510/17:86098952 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1016/j.eswa.2016.12.030" target="_blank" >http://dx.doi.org/10.1016/j.eswa.2016.12.030</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.eswa.2016.12.030" target="_blank" >10.1016/j.eswa.2016.12.030</a>

Result language

angličtina

Original language name

An extended multiple criteria data envelopment analysis model

Original language description

Several researchers have adapted the data envelopment analysis (DEA) models to deal with two inter-related problems: weak discriminating power and unrealistic weight distribution. Improving discrimination power and yielding more reasonable dispersion of input and output weights simultaneously remain a challenge for DEA and multiple criteria DEA (MCDEA) models. This paper puts emphasis on weight restrictions to boost discriminating power as well as to generate true weight dispersion of MCDEA when a priori information about the weights is not available. To this end, we modify a very recent MCDEA models in the literature by determining an optimum lower bound for input and output weights. The contribution of this paper is sevenfold: first, we show that a larger amount for the lower bound on weights often leads to improving discriminating power and reaching realistic weights in MCDEA models due to imposing more weight restrictions; second, the procedure for sensitivity analysis is designed to define stability for the weights of each evaluation criterion; third, we extend a weighted MCDEA model to three evaluation criteria based on the maximum lower bound for input and output weights; fourth, we develop a super-efficiency model for efficient units under the proposed MCDEA model in this paper; fifth, we extend an epsilon-based minsum BCC-DEA model to proceed our research objectives under variable returns to scale (VRS); sixth, we present a simulation study to statistically analyze weight dispersion and rankings between five different methods in terms of non-parametric tests; and seventh, we demonstrate the applicability of the proposed models with an application to European Union member countries.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

50202 - Applied Economics, Econometrics

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2017

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Expert Systems with Applications

ISSN

0957-4174

e-ISSN

—

Volume of the periodical

73

Issue of the periodical within the volume

není uveden

Country of publishing house

GB - UNITED KINGDOM

Number of pages

19

Pages from-to

201-219

UT code for WoS article

000394632200015

EID of the result in the Scopus database

2-s2.0-85009069180