A novel hybrid fuzzy PROMETHEE-IDEA approach to efficiency evaluation

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F21%3A10246129" target="_blank" >RIV/61989100:27510/21:10246129 - isvavai.cz</a>

Result on the web

<a href="https://link.springer.com/content/pdf/10.1007/s00500-020-05416-3.pdf" target="_blank" >https://link.springer.com/content/pdf/10.1007/s00500-020-05416-3.pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s00500-020-05416-3" target="_blank" >10.1007/s00500-020-05416-3</a>

Result language

angličtina

Original language name

A novel hybrid fuzzy PROMETHEE-IDEA approach to efficiency evaluation

Original language description

Efficiency evaluation is a desirable kind of a decision making analysis for experts in various fields because if something can be measured, it can also be improved more easily. Measuring efficiency has been a topic of many research studies, and many quantitative methods to deal with this problem under various assumptions have already been established. However, most methods struggle with barriers limiting their use in practice. The aim of this paper is to establish a method for efficiency evaluation which is as traceable as possible, provides a graphical representation of the results, and yields results that are easily interpretable for problems with uncertain input data expressed by fuzzy evaluations. In particular, a new hybrid method for efficiency evaluation is presented. This method is based on a combination of the PROMETHEE (i.e. outranking multi-criteria decision making method) and data envelopment analysis (DEA) under uncertainty, similar to the study published by Ishizaka et al. (Soft Comput 22(22):7325-7338, 2018) who, however, worked only with deterministic data. The PROMETHEE method allows a computationally easy and traceable evaluation of alternatives. The DEA method is currently the most popular method for efficiency evaluation. However, its original version provides a graphical representation only for very simple models. In addition, the results are usually not easy to interpret because it mixes scale-dependent and scale-independent data together. Fuzziness in the DEA model is handled using measures of possibility and necessity, which provide easily interpretable results for a decision maker. In particular, the results reveal to what extent each unit under evaluation can possibly be, or certainly is, efficient. The proposed algorithm is applied to one artificial and one real-life numerical example, and the results are compared with the pure DEA model. (C) 2020, Springer-Verlag GmbH Germany, part of Springer Nature.

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

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/EE2.3.20.0296" target="_blank" >EE2.3.20.0296: Research team for modelling of economic and financial processes at VSB-TU Ostrava</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year

2021

Confidentiality

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

Name of the periodical

Soft computing

ISSN

1432-7643

e-ISSN

—

Volume of the periodical

25

Issue of the periodical within the volume

5

Country of publishing house

US - UNITED STATES

Number of pages

17

Pages from-to

3913-3929

UT code for WoS article

000594246000001

EID of the result in the Scopus database

2-s2.0-85096807752