A novel method for computing single output for DEA with application in hospital efficiency

Yeşilyurt, M. Ensar; Sahin, Emre; Elbi, Mehmet Dogan; Kızılkaya, Aydın; Koyuncuoğlu, Mehmet Ulaş; Akbaş-Yeşilyurt, Filiz

doi:10.1016/j.seps.2020.100995

Cited by 20 publications

(8 citation statements)

References 41 publications

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“…It also leads to training specialists in the health treatment section, performing medical research, and improving the health of society. Therefore, this organization has a particular sensitivity and importance regarding economic infrastructures and its severe vulnerability against currency rate fluctuations and commodity markets, particularly in developing countries [ 5 ]. This institution is the most extensive and most costly operating unit of the health treatment system in Iran [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

Hospital efficiency measurement in the west of Iran: data envelopment analysis and econometric approach

Nayer

Fazaeli

Hamidi

2022

Cost Eff Resour Alloc

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Objective Measuring hospital efficiency is one of the way how to use resources.The optimal hospital performance is the goals of healthcare policymakers. This study aimed to the current study was conducted to evaluate the efficiency the current study was conducted to evaluate the efficiency and assess the association between hospital size and hospital area population with technical efficiency in public hospitals. Methods In this descriptive-analytical study, the statistical population consisted of 15 public hospitals in the west of Iran. First, the data envelopment analysis (DEA) method was used to evaluate technical efficiency. inputs included staff and beds, and outputs consisted of the number of surgeries, the number of patients, and the average length of stay. Then, according to the public ownership of all hospitals, their educational and therapeutic activities, as well as their size and population were considered as the environmental factor affecting efficiency. Thus, regression was applied to measure their effects on efficiency. Results The average technical efficiency of the studied hospitals, the average management efficiency, and the average efficiency of the scale were 0.935, 0.961, and 0.987, respectively. Out of the total evaluated hospitals, six and nine hospitals had an efficiency of less than one and one, respectively. Moreover, the size of the hospital and the population as the environment variable were significant in the Tobit model. Our regression demonstrated that although the size of the hospital is positively associated with its technical efficiency, the hospital population negatively affects hospital efficiency. Conclusion According to the size and area population of the hospitals, they decrease their inputs to maximize their efficacy by optimizing their surplus amounts. Tobit regression analysis concludes that hospital size and population covered by the hospital significant effect on hospitals' efficiency.

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Section: Introductionmentioning

confidence: 99%

Hospital efficiency measurement in the west of Iran: data envelopment analysis and econometric approach

Nayer

Fazaeli

Hamidi

2022

Cost Eff Resour Alloc

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“…The VRS models reflect the fact that production system may exhibit increasing, constant and decreasing returns to scale (Soheilirad et al, 2018 ). Because it does not require any assumptions and can be used to measure the efficiency of DMUs with multiple inputs and multiple outputs, DEA is more popular in the literature (Yeşilyurt et al, 2021 ). Standard linear programming (LP) techniques can be used to solve the majority of popular DEA models (Chen & Cho, 2009 ).…”

Section: Methods and Applicationmentioning

confidence: 99%

An Application of Machine Learning to Logistics Performance Prediction: An Economics Attribute-Based of Collective Instance

2023

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In this work, a machine learning application was constructed to predict the logistics performance index based on economic attributes. The prediction procedure employs both linear and non-linear machine learning algorithms. The macroeconomic panel dataset is used in this investigation. Furthermore, it was combined with the microeconomic panel dataset obtained through the data envelopment analysis method for evaluating financial efficiency. The procedure was implemented in six ASEAN member countries. The non-linear algorithm of an artificial neural network performed best on the complex pattern of a collective instance of these six countries, followed by the penalized linear of the Ridge regression method. Due to the limited amount of training data for each country, the artificial neural network prediction procedure is only applicable to the datasets of Singapore, Malaysia, and the Philippines. Ridge regression fits the Indonesia, Thailand and Vietnam datasets. The results provide precise trend forecasting. Macroeconomic factors are driving up the logistics performance index in Vietnam in 2020. Malaysia logistics performance is influenced by the logistics business's financial efficiency. The results at the country level can be used to track, improve, and reform the country's short-term logistics and supply chain policies. This can bring significant gains in national logistics and supply chain capabilities, as well as support for global trade collaboration, all for the long-term development of the region.

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“…Second, previous research ignored the link between environmental regulation and energy efficiency in various types of environmental decentralization, such as environmental management, environmental regulation, and environmental surveillance. Ultimately, in terms of research approaches, the majority of earlier studies used static research and linear analysis ( 63 ). Endogeneity issues arising from a mutual usual association between variables cannot be effectively addressed.…”

Section: Methodsmentioning

confidence: 99%

Does Green Governance Efficiency and Green Finance Polices Matters in Sustainable Environment: Implications for Public Health

Zhu

2022

Front. Public Health

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Rapid and widespread changes in the environment and climate, such as rising temperatures, water and air pollution, floods, and droughts, disease vector migration are putting human health at risk. In this case, green governance is an essential driver for the restructuring of economic development and realizing a green technological revolution for sustainable development and its implications for public health. This article aims to explore the effects and interrelationships of green governance and green finance policies on sustainable development in various regions of China's from 2008 to 2018 using panel data estimation technique. The findings show that China's overall green governance index and green finance policies resulted in a substantial decrease in environmental pollution during the study time. Financial inclusion also be a factor to the reduction of CO2 emissions and has a positive influence on environmental security investment projects, according to our findings. China is on track to become a world leader in an enactment of green finance concept, and controllers must speed up the development of green finance products and strengthen financial institutions' ability to provide green credit. Policymakers should promote green governance and green fiancé to keenly play a part in environmental security projects that boost green spending while minimizing the procedural risk.

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A novel method for computing single output for DEA with application in hospital efficiency

Cited by 20 publications

References 41 publications

Hospital efficiency measurement in the west of Iran: data envelopment analysis and econometric approach

Hospital efficiency measurement in the west of Iran: data envelopment analysis and econometric approach

An Application of Machine Learning to Logistics Performance Prediction: An Economics Attribute-Based of Collective Instance

Does Green Governance Efficiency and Green Finance Polices Matters in Sustainable Environment: Implications for Public Health

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