Technological returns to scale: Identification and visualization

One of the most critical issues for using data envelopment analysis models is the identification of technological returns to scale (TRTS). Recently, the angles method based on data mining is introduced for the identification of TRTS. This objective method uses the angles to measure the gap between t...

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Main Authors: E. Hajinezhad, M.R. Alirezaee
Format: Article
Language:English
Published: Ferdowsi University of Mashhad 2018-10-01
Series:Iranian Journal of Numerical Analysis and Optimization
Subjects:
Online Access:https://ijnao.um.ac.ir/article_24704_76abc322be81300d3b15f245f6508354.pdf
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spelling doaj-891c04676a4247f6adcb1a6b61bd97322021-02-24T08:56:06ZengFerdowsi University of MashhadIranian Journal of Numerical Analysis and Optimization2423-69772423-69692018-10-0182557410.22067/ijnao.v8i2.5196924704Technological returns to scale: Identification and visualizationE. Hajinezhad0M.R. Alirezaee1University of Science and Technology, Hengam St., Resalat, TehranUniversity of Science and Technology, Hengam St., Resalat, TehranOne of the most critical issues for using data envelopment analysis models is the identification of technological returns to scale (TRTS). Recently, the angles method based on data mining is introduced for the identification of TRTS. This objective method uses the angles to measure the gap between the constant and variable TRTS. The gap is calculated in both the increasing and decreasing sections of the frontier. The larger the gap in the increasing and/or decreasing sections of the frontier, the closer TRTS is to the increasing and/or decreasing form of TRTS. In this paper, we propose a heuristic method for visualizing TRTS that would give a better understanding of identification of TRTS in the dataset. To this end, we introduce the maximum angles method for measuring the maximum possible deviation from constant TRTS assumption in the increasing and decreasing sections of the frontier. By the angles and the maximum angles , we can display the dataset’s TRTS in a two-dimensional space. To validate the proposed method, we consider six one input/one output cases. Also, we apply the angles method and the maximum angles method for the Maskan bank of Iran. Using the proposed method, we show that how TRTS of the bank dataset can be displayed in a two-dimensional space.https://ijnao.um.ac.ir/article_24704_76abc322be81300d3b15f245f6508354.pdfdata envelopment analysisreturns to scaletechnologybank
collection DOAJ
language English
format Article
sources DOAJ
author E. Hajinezhad
M.R. Alirezaee
spellingShingle E. Hajinezhad
M.R. Alirezaee
Technological returns to scale: Identification and visualization
Iranian Journal of Numerical Analysis and Optimization
data envelopment analysis
returns to scale
technology
bank
author_facet E. Hajinezhad
M.R. Alirezaee
author_sort E. Hajinezhad
title Technological returns to scale: Identification and visualization
title_short Technological returns to scale: Identification and visualization
title_full Technological returns to scale: Identification and visualization
title_fullStr Technological returns to scale: Identification and visualization
title_full_unstemmed Technological returns to scale: Identification and visualization
title_sort technological returns to scale: identification and visualization
publisher Ferdowsi University of Mashhad
series Iranian Journal of Numerical Analysis and Optimization
issn 2423-6977
2423-6969
publishDate 2018-10-01
description One of the most critical issues for using data envelopment analysis models is the identification of technological returns to scale (TRTS). Recently, the angles method based on data mining is introduced for the identification of TRTS. This objective method uses the angles to measure the gap between the constant and variable TRTS. The gap is calculated in both the increasing and decreasing sections of the frontier. The larger the gap in the increasing and/or decreasing sections of the frontier, the closer TRTS is to the increasing and/or decreasing form of TRTS. In this paper, we propose a heuristic method for visualizing TRTS that would give a better understanding of identification of TRTS in the dataset. To this end, we introduce the maximum angles method for measuring the maximum possible deviation from constant TRTS assumption in the increasing and decreasing sections of the frontier. By the angles and the maximum angles , we can display the dataset’s TRTS in a two-dimensional space. To validate the proposed method, we consider six one input/one output cases. Also, we apply the angles method and the maximum angles method for the Maskan bank of Iran. Using the proposed method, we show that how TRTS of the bank dataset can be displayed in a two-dimensional space.
topic data envelopment analysis
returns to scale
technology
bank
url https://ijnao.um.ac.ir/article_24704_76abc322be81300d3b15f245f6508354.pdf
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