A new non-radial directional distance model for data envelopment analysis problems with negative and flexible measures

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F21%3A10247572" target="_blank" >RIV/61989100:27510/21:10247572 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S030504832030709X?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S030504832030709X?via%3Dihub</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.omega.2020.102355" target="_blank" >10.1016/j.omega.2020.102355</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A new non-radial directional distance model for data envelopment analysis problems with negative and flexible measures

Popis výsledku v původním jazyce

Data envelopment analysis (DEA) is a mathematical approach for evaluating the efficiency of decision making units that convert multiple inputs into multiple outputs. Traditional DEA models measure technical (radial) efficiencies by assuming the input and output status of each performance measure is known, and the data associated with the performance measures are non-negative. These assumptions are restrictive and limit the applications of DEA to real-world problems. We propose a new extended non-radial directional distance model, which is a variant of the weighted additive model, to cope with negative data. We then extend our model and use flexible measures, which play the role of both inputs and outputs, to cope with the unknown status of the performance measures. We also present a case study in the automotive industry to exhibit the efficacy of the models proposed in this study. (c) 2020 Elsevier Ltd. All rights reserved.

Název v anglickém jazyce

A new non-radial directional distance model for data envelopment analysis problems with negative and flexible measures

Popis výsledku anglicky

Data envelopment analysis (DEA) is a mathematical approach for evaluating the efficiency of decision making units that convert multiple inputs into multiple outputs. Traditional DEA models measure technical (radial) efficiencies by assuming the input and output status of each performance measure is known, and the data associated with the performance measures are non-negative. These assumptions are restrictive and limit the applications of DEA to real-world problems. We propose a new extended non-radial directional distance model, which is a variant of the weighted additive model, to cope with negative data. We then extend our model and use flexible measures, which play the role of both inputs and outputs, to cope with the unknown status of the performance measures. We also present a case study in the automotive industry to exhibit the efficacy of the models proposed in this study. (c) 2020 Elsevier Ltd. All rights reserved.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10102 - Applied mathematics

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)

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název periodika

Omega

ISSN

0305-0483

e-ISSN

—

Svazek periodika

102

Číslo periodika v rámci svazku

July

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

14

Strana od-do

102355

Kód UT WoS článku

000641439200011

EID výsledku v databázi Scopus

2-s2.0-85095957409