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...

Full description

Bibliographic Details
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
Description
Summary: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.
ISSN:2423-6977
2423-6969