Data Envelopment Analyses
Zeinab Tavassoli; Mohsen Rostami-MalKhalifeh; Farhad Hosseinzadeh Lotfi; Tofigh allahVieanloo
Abstract
Purpose: The current paper tries to determine the type of returns to scale in a decision-making unit under the condition that integer-valued inputs or outputs are present.Methodology: This paper introduces radial models for determining the value and type of Returns to Scale (RTS) in 4 scenarios, including ...
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Purpose: The current paper tries to determine the type of returns to scale in a decision-making unit under the condition that integer-valued inputs or outputs are present.Methodology: This paper introduces radial models for determining the value and type of Returns to Scale (RTS) in 4 scenarios, including single integer-valued input – single real output (scenario one), mixed inputs – exclusively real outputs (scenario two), exclusively integer-valued inputs – exclusively real outputs (scenario three), and exclusively integer-valued inputs – exclusively integer-valued outputs (scenario four); in each scenario, the values of the left RTS and right RTS are determined, and the RTS type is then determined on that basis. Finally, by presenting three examples based on two scenarios, namely single integer-valued input – single real output and single integer-valued input – single integer-valued output, the new method is compared with previous methods using GAMS software, and the conclusions are provided.Findings: The type of returns to scale differs when integer-valued inputs or outputs are present as compared with the case where the inputs and outputs are assumed to have real values.Originality/Value: This study focuses on the value and type of returns to scale for integer-valued data. For this purpose, returns to scale was modeled in 4 scenarios using input-oriented radial models, and in the fourth scenario (exclusively integer-valued inputs – exclusively integer-valued outputs), the modeling was carried out for output orientation as well. The existence of a difference between the results produced by our proposed model and those of the classical model was demonstrated through two examples, one using hypothetical data and the other real-world data.
Data Envelopment Analyses
Fatemeh Gholami Golsefid; Behrooz Daneshian; Mohsen Rostamy-Malkhalifeh
Abstract
Purpose: The providing a proposed model pair for ranking interval data and their application to evaluate and improve the performance of a service system using results of simulation.Methodology: Mathematical techniques (data envelopment analysis) and computer simulation.Findings: By presenting proposed ...
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Purpose: The providing a proposed model pair for ranking interval data and their application to evaluate and improve the performance of a service system using results of simulation.Methodology: Mathematical techniques (data envelopment analysis) and computer simulation.Findings: By presenting proposed models pair, we were able to improve the performance of a service system by simulating different scenarios for that system. The results show that the introduced scenario could increase the efficiency of system by 22%.Originality/Value: Introducing new applied methods using mathematical models (Data Envelopment Analysis) and simulations to improve the performance of systems
Data Envelopment Analyses
nasrin bagheri mazraeh; Mohsen Rostami Mal Khalife; Meysam Varzi
Abstract
Purpose: Efficiency is an economic concept which shows the performance of a wide range of economic activities in different areas of an economic sector. Most of studies using frontier technique Data Envelopment Analysis (DEA) do not test for the relationship of efficiency estimation with key performance ...
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Purpose: Efficiency is an economic concept which shows the performance of a wide range of economic activities in different areas of an economic sector. Most of studies using frontier technique Data Envelopment Analysis (DEA) do not test for the relationship of efficiency estimation with key performance indicators. This is despite the fact that DEA is one of the most effective tools for measuring and evaluating efficiency. Nevertheless, identifying the relationship between efficiency estimates and commonly accepted financial measures of performance could guide benchmarking activities, pricing decisions, and regulatory monitoring.Methodology: In this paper, the DEA super-efficiency formula is tested in two profitability models. Four ratios of net interest income to total assets, post-tax profit to total assets, owner’s equity returns and impaired loans to total assets, were calculated with a developed profitability model; besides, the growth rate of assets was calculated with main profitability model and all the aforementioned ratios addressed a significant association with efficiency estimates.Findings: In this study, the DEA super-efficiency formula is tested in two profitability models for 15 banks for two years. The correlation obtained is generally low. However, the four ratios of net interest income to total assets, post-tax profit to total assets, owner’s equity returns and impaired loans to total assets, in the EPM model and asset growth rate in the CPM model have a significant relationship with performance estimates. Finally, the results indicate poor credit quality in Iranian banks in 1397-1397.Originality/Value: In this study, for the first time, the nature of the relationship between performance and key performance indicators has been estimated. DEA technique has been used to purposefully identify criteria for analyzing financial ratios.