A modified slacks-based measure of efficiency in data envelopment analysis
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F20%3A10244988" target="_blank" >RIV/61989100:27510/20:10244988 - isvavai.cz</a>
Výsledek na webu
<a href="https://doi.org/10.1016/j.ejor.2020.04.019" target="_blank" >https://doi.org/10.1016/j.ejor.2020.04.019</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.ejor.2020.04.019" target="_blank" >10.1016/j.ejor.2020.04.019</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
A modified slacks-based measure of efficiency in data envelopment analysis
Popis výsledku v původním jazyce
The slacks-based measure (SBM) model can divide the set of observations into two mutually exclusive and collectively exhaustive sets: efficient and inefficient. However, it fails to provide more details about efficient DMUs, which reveals the lack of discrimination power in the SBM model. With the aim of addressing this issue, the super SBM (SupSBM) model has been suggested which can rank the SBM-efficient DMUs without providing any useful information about SBM-inefficient DMUs. As a result, in order to fully rank both efficient and inefficient DMUs, one needs to run both SBM and SupSBM models which leads to a significant increase in the number of required computations. This paper tackles this problem and modifies the SBM model which measures SBM-efficiency score for inefficient DMUs and SupSBM-efficiency score for strong efficient DMUs, simultaneously. Finally, a simulation study is presented to illustrate the superiority of our proposed model over the existing models with various problem sizes. (C) 2020 Elsevier B.V.
Název v anglickém jazyce
A modified slacks-based measure of efficiency in data envelopment analysis
Popis výsledku anglicky
The slacks-based measure (SBM) model can divide the set of observations into two mutually exclusive and collectively exhaustive sets: efficient and inefficient. However, it fails to provide more details about efficient DMUs, which reveals the lack of discrimination power in the SBM model. With the aim of addressing this issue, the super SBM (SupSBM) model has been suggested which can rank the SBM-efficient DMUs without providing any useful information about SBM-inefficient DMUs. As a result, in order to fully rank both efficient and inefficient DMUs, one needs to run both SBM and SupSBM models which leads to a significant increase in the number of required computations. This paper tackles this problem and modifies the SBM model which measures SBM-efficiency score for inefficient DMUs and SupSBM-efficiency score for strong efficient DMUs, simultaneously. Finally, a simulation study is presented to illustrate the superiority of our proposed model over the existing models with various problem sizes. (C) 2020 Elsevier B.V.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
10102 - Applied mathematics
Návaznosti výsledku
Projekt
<a href="/cs/project/GA19-13946S" target="_blank" >GA19-13946S: Hodnocení výkonnosti při výskytu neklasifikovaných faktorů</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Ostatní
Rok uplatnění
2020
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
European Journal of Operational Research
ISSN
0377-2217
e-ISSN
—
Svazek periodika
287
Číslo periodika v rámci svazku
2
Stát vydavatele periodika
US - Spojené státy americké
Počet stran výsledku
12
Strana od-do
560-571
Kód UT WoS článku
000550057300012
EID výsledku v databázi Scopus
2-s2.0-85086432081