Average revenue efficiency and optimal scale sizes in stochastic data envelopment analysis: A case study of post offices

Estimating the revenue efficiency of entities being evaluated is crucial as it provides valuable information about organizations, assuming that the output prices are known. This research introduces a new definition of optimal scale size (OSS) based on maximizing the average revenue efficiency (ARE)....

Full description

Bibliographic Details
Main Authors: Leila Parhizkar Miyandehi, Alireza Amirteimoori, Sohrab Kordrostami, Mansour Soufi
Format: Article
Language:fas
Published: Allameh Tabataba'i University Press 2022-09-01
Series:Muṭāli̒āt-i Mudīriyyat-i Ṣan̒atī
Subjects:
Online Access:https://jims.atu.ac.ir/article_14397_0559b52669e0e97659934d4e415a5663.pdf
_version_ 1797367696127426560
author Leila Parhizkar Miyandehi
Alireza Amirteimoori
Sohrab Kordrostami
Mansour Soufi
author_facet Leila Parhizkar Miyandehi
Alireza Amirteimoori
Sohrab Kordrostami
Mansour Soufi
author_sort Leila Parhizkar Miyandehi
collection DOAJ
description Estimating the revenue efficiency of entities being evaluated is crucial as it provides valuable information about organizations, assuming that the output prices are known. This research introduces a new definition of optimal scale size (OSS) based on maximizing the average revenue efficiency (ARE). Additionally, the ARE is defined for both convex and non-convex sets, independent of returns to scale and the assumption that the vector of input-output prices of units is uniform. Moreover, to address the presence of uncertain data in real-world applications, the introduced ARE model is extended to evaluate systems with random inputs and outputs, along with approaches for its calculation. Finally, the proposed method is applied in an experimental example, calculating the ARE for a dataset of postal areas in Iran.IntroductionThe concept of optimal scale size has been extensively studied in the field of data envelopment analysis. Cesaroni and Giovannola's research on non-convex FDH technology reveals that the optimal scale size is a point in the production possibility set that minimizes average cost efficiency. Average cost efficiency, a new measure combining scale and allocation efficiencies, provides a more accurate performance assessment compared to cost and scale efficiencies. When evaluating units with known output prices instead of input prices, assessing revenue efficiency can offer more valuable insights. This paper extends the research on cost evaluation to revenue evaluation. It introduces the concepts of average revenue efficiency and optimal scale size based on revenue maximization. The optimal scale size based on revenue maximization is defined as the point in the production possibility set that maximizes the average radial income for the unit under investigation. Average revenue efficiency serves as an evaluation measure of unit revenue, surpassing revenue and scale efficiencies in accuracy. The paper examines methods for calculating average revenue efficiency in both convex and non-convex technologies. It demonstrates that the average revenue efficiency model in convex technology with variable returns to scale is equivalent to the revenue model with constant returns to scale. Furthermore, the relationship between optimal scale size points based on revenue maximization and the most productive scale size is determined. Next, the paper presents the average revenue efficiency model for stochastic sets with the presence of stochastic data. An experimental example is used to calculate the average revenue efficiency and obtain the optimal scale size for a set of postal areas in Iran.Materials and MethodsThe study builds upon Cesaroni and Giovannola's method for calculating average cost efficiency and optimal scale size to develop models for average revenue efficiency and optimal scale size based on revenue. It also utilizes chance-constrained probabilistic models with a deterministic objective function in DEA literature to present average revenue efficiency for stochastic sets. The model is transformed from stochastic to deterministic and then converted into a linear model using the error structure method.Discussion and ResultsThis paper introduces average revenue efficiency and optimal revenue scale size, demonstrating the equivalence between the average revenue efficiency models in convex technology with variable returns to scale and those with constant returns to scale. It also presents the average revenue efficiency model for stochastic sets, enabling the calculation of average revenue efficiency and optimal revenue scale size for units with random inputs and outputs.ConclusionIn many real-world scenarios, particularly when output prices are known, evaluating revenue efficiency holds greater significance than cost efficiency. This study develops the concepts of average cost efficiency and optimal scale size for revenue evaluation, expanding upon the existing literature on data envelopment analysis. The paper demonstrates how average revenue efficiency can be calculated as a valuable and accurate measure of efficiency in convex and non-convex technologies, without making assumptions about returns to scale. By assuming the randomness of input and output variables and employing chance-constrained models, a quadratic deterministic model is presented to calculate average revenue efficiency. It is then transformed into a linear model assuming uncorrelated variables, enabling the determination of average revenue efficiency and optimal scale size based on revenue maximization for random units. The proposed models are applied to a real-world sample, evaluating the average revenue efficiency of twelve postal units. The results highlight the models' ability to provide a more accurate evaluation of revenue efficiency and identify the best revenue scale size as the reference for inefficient units.
first_indexed 2024-03-08T17:20:57Z
format Article
id doaj.art-8963a31c62cc48c89227ddc4bf1e4440
institution Directory Open Access Journal
issn 2251-8029
2476-602X
language fas
last_indexed 2024-03-08T17:20:57Z
publishDate 2022-09-01
publisher Allameh Tabataba'i University Press
record_format Article
series Muṭāli̒āt-i Mudīriyyat-i Ṣan̒atī
spelling doaj.art-8963a31c62cc48c89227ddc4bf1e44402024-01-03T04:46:34ZfasAllameh Tabataba'i University PressMuṭāli̒āt-i Mudīriyyat-i Ṣan̒atī2251-80292476-602X2022-09-0120667311010.22054/jims.2022.62190.267714397Average revenue efficiency and optimal scale sizes in stochastic data envelopment analysis: A case study of post officesLeila Parhizkar Miyandehi0Alireza Amirteimoori1Sohrab Kordrostami2Mansour Soufi3PhD student in Applied Mathematics, Rasht Branch, Islamic Azad University, Rasht, IranProfessor, Department of Applied Mathematics, Rasht Branch, Islamic Azad University, Rasht,IranProfessor, Department of Mathematics, Lahijan Branch, Islamic Azad University, Lahijan, IranAssistant Professor, Department of Management, Rasht Branch, Islamic Azad University, Rasht, IranEstimating the revenue efficiency of entities being evaluated is crucial as it provides valuable information about organizations, assuming that the output prices are known. This research introduces a new definition of optimal scale size (OSS) based on maximizing the average revenue efficiency (ARE). Additionally, the ARE is defined for both convex and non-convex sets, independent of returns to scale and the assumption that the vector of input-output prices of units is uniform. Moreover, to address the presence of uncertain data in real-world applications, the introduced ARE model is extended to evaluate systems with random inputs and outputs, along with approaches for its calculation. Finally, the proposed method is applied in an experimental example, calculating the ARE for a dataset of postal areas in Iran.IntroductionThe concept of optimal scale size has been extensively studied in the field of data envelopment analysis. Cesaroni and Giovannola's research on non-convex FDH technology reveals that the optimal scale size is a point in the production possibility set that minimizes average cost efficiency. Average cost efficiency, a new measure combining scale and allocation efficiencies, provides a more accurate performance assessment compared to cost and scale efficiencies. When evaluating units with known output prices instead of input prices, assessing revenue efficiency can offer more valuable insights. This paper extends the research on cost evaluation to revenue evaluation. It introduces the concepts of average revenue efficiency and optimal scale size based on revenue maximization. The optimal scale size based on revenue maximization is defined as the point in the production possibility set that maximizes the average radial income for the unit under investigation. Average revenue efficiency serves as an evaluation measure of unit revenue, surpassing revenue and scale efficiencies in accuracy. The paper examines methods for calculating average revenue efficiency in both convex and non-convex technologies. It demonstrates that the average revenue efficiency model in convex technology with variable returns to scale is equivalent to the revenue model with constant returns to scale. Furthermore, the relationship between optimal scale size points based on revenue maximization and the most productive scale size is determined. Next, the paper presents the average revenue efficiency model for stochastic sets with the presence of stochastic data. An experimental example is used to calculate the average revenue efficiency and obtain the optimal scale size for a set of postal areas in Iran.Materials and MethodsThe study builds upon Cesaroni and Giovannola's method for calculating average cost efficiency and optimal scale size to develop models for average revenue efficiency and optimal scale size based on revenue. It also utilizes chance-constrained probabilistic models with a deterministic objective function in DEA literature to present average revenue efficiency for stochastic sets. The model is transformed from stochastic to deterministic and then converted into a linear model using the error structure method.Discussion and ResultsThis paper introduces average revenue efficiency and optimal revenue scale size, demonstrating the equivalence between the average revenue efficiency models in convex technology with variable returns to scale and those with constant returns to scale. It also presents the average revenue efficiency model for stochastic sets, enabling the calculation of average revenue efficiency and optimal revenue scale size for units with random inputs and outputs.ConclusionIn many real-world scenarios, particularly when output prices are known, evaluating revenue efficiency holds greater significance than cost efficiency. This study develops the concepts of average cost efficiency and optimal scale size for revenue evaluation, expanding upon the existing literature on data envelopment analysis. The paper demonstrates how average revenue efficiency can be calculated as a valuable and accurate measure of efficiency in convex and non-convex technologies, without making assumptions about returns to scale. By assuming the randomness of input and output variables and employing chance-constrained models, a quadratic deterministic model is presented to calculate average revenue efficiency. It is then transformed into a linear model assuming uncorrelated variables, enabling the determination of average revenue efficiency and optimal scale size based on revenue maximization for random units. The proposed models are applied to a real-world sample, evaluating the average revenue efficiency of twelve postal units. The results highlight the models' ability to provide a more accurate evaluation of revenue efficiency and identify the best revenue scale size as the reference for inefficient units.https://jims.atu.ac.ir/article_14397_0559b52669e0e97659934d4e415a5663.pdfoptimal scale sizeefficiencyaverage revenue efficiencystochastic data envelopment analysis
spellingShingle Leila Parhizkar Miyandehi
Alireza Amirteimoori
Sohrab Kordrostami
Mansour Soufi
Average revenue efficiency and optimal scale sizes in stochastic data envelopment analysis: A case study of post offices
Muṭāli̒āt-i Mudīriyyat-i Ṣan̒atī
optimal scale size
efficiency
average revenue efficiency
stochastic data envelopment analysis
title Average revenue efficiency and optimal scale sizes in stochastic data envelopment analysis: A case study of post offices
title_full Average revenue efficiency and optimal scale sizes in stochastic data envelopment analysis: A case study of post offices
title_fullStr Average revenue efficiency and optimal scale sizes in stochastic data envelopment analysis: A case study of post offices
title_full_unstemmed Average revenue efficiency and optimal scale sizes in stochastic data envelopment analysis: A case study of post offices
title_short Average revenue efficiency and optimal scale sizes in stochastic data envelopment analysis: A case study of post offices
title_sort average revenue efficiency and optimal scale sizes in stochastic data envelopment analysis a case study of post offices
topic optimal scale size
efficiency
average revenue efficiency
stochastic data envelopment analysis
url https://jims.atu.ac.ir/article_14397_0559b52669e0e97659934d4e415a5663.pdf
work_keys_str_mv AT leilaparhizkarmiyandehi averagerevenueefficiencyandoptimalscalesizesinstochasticdataenvelopmentanalysisacasestudyofpostoffices
AT alirezaamirteimoori averagerevenueefficiencyandoptimalscalesizesinstochasticdataenvelopmentanalysisacasestudyofpostoffices
AT sohrabkordrostami averagerevenueefficiencyandoptimalscalesizesinstochasticdataenvelopmentanalysisacasestudyofpostoffices
AT mansoursoufi averagerevenueefficiencyandoptimalscalesizesinstochasticdataenvelopmentanalysisacasestudyofpostoffices