Estimating Returns to Scale of Two-Stage Network Technologies Using Total Scale Elasticity by Considering the Intermediate Output

Tayebe Ahangary (), Mohsen Rostamy Malkhalifeh and Farhad Hosseinzadeh Lotfi ()
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Tayebe Ahangary: Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran
Mohsen Rostamy Malkhalifeh: Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran
Farhad Hosseinzadeh Lotfi: Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran

International Journal of Information Technology & Decision Making (IJITDM), 2023, vol. 22, issue 04, 1319-1339

Abstract: The structure of production technology has been made of a few stages. Therefore, it generates an intermediate output, which is important to estimate the quantitative and qualitative returns to scale and for managers to make decisions. Estimates of scale elasticity have long been considered in two-stage technologies, many researchers have suggested methods to estimate it, but they were not investigated from the base, and the intermediate output was also ignored. There were no strong relationships between the total scale elasticity and the scale elasticity of both stages. The proposed method can estimate the scale elasticity from the base and from the production transfer function, which in turn has a stronger basic structure compared to previously proposed methods. It is much simpler and easier to be understood than previous methods. The scale elasticity of the entire network can be estimated by multiplying the scale elasticity of both stages. By expressing the parametric and nonparametric approaches of two-stage network scale elasticity, the ratio of the final output to primary input changes can be obtained according to the change of the intermediate output compared to primary input as well as the final output to intermediate input. Finally, the superiority of the proposed method is illustrated by practical examples.

Keywords: Data envelopment analysis; left returns to scale; right returns to scale; network DEA; nonradial; scale elasticity (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1142/S0219622022500705

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