Input-oriented Data Envelopment Analysis Research Articles

Technical Efficiency of Maternal Health Services Provision in Public Hospitals of Northwest Ethiopia: A Two-Stage Data Envelopment Analysis.

IntroductionEthiopian health expenditure as a share of total government expenditure increased from 7.6% in 2013/14 to 8.1% in 2016/17. But it remained low even for the low-income country average expected share of 8.7%. It signifies the efficient use of scarce resources in the health sector is still critical to achieving sustainable development goals. But little evidence is available about public hospitals’ technical efficiency in providing maternal health services. Therefore, the aim of this study was to assess the technical efficiency of maternal health services provision of public hospitals in Northwest Ethiopia.MethodsFacility-based cross-sectional study was conducted among twelve randomly selected public hospitals. Input data (salary expenditure, non-salary expenditure, and the number of beds) and maternal health services output data (antenatal care, skilled delivery, and postnatal care) for a 2011 Ethiopian fiscal year (July 2018 to June 2019) were collected and entered into Epi-Data 3.1. We used both primary and secondary data collection procedures to determine independent variables and the dependent variable, respectively. We also used a two-stage input-oriented data envelopment analysis with variable returns to scale assumption.ResultsThe study showed that hospitals included in this study wasted US$ 6833.50 for salary and US$ 3886.8 for non-salary expenditures. The study also revealed that the mean pure technical efficiency of public hospitals for maternal health service provision was 0.92±0.142, and their scale efficiency was 0.795±0.24. The hospital manager’s experience year, the educational level of the manager, and the hospital service year associated positively with the technical efficiency. However, the catchment population and distance of another health facility associated negatively with technical efficiency.ConclusionThe public hospitals’ pure technical efficiency in the provision of maternal health services in Northwest Ethiopia was high. More than half of the public hospitals were technically efficient. The wasted amount of expenditures could be used for satisfying the unmet health services need of the population. Therefore, it is better to monitor the health facilities for the wise use of the existing resources for their best performance.

Oncology services efficiency in the age of pandemic: A jackknife and bootstrap sensitivity analysis for robustness check of DEA scores

BackgroundDeveloping countries face great challenges in health care because of changing disease dynamics and the increasing burden of chronic diseases such as cancers. Thus, effective operational design of health services is critical to better manage scarce health care resources. This study aimed to examine the spatial distribution of the efficiency of Turkey’s oncology services. MethodsData was collected from the 2017 Public Hospitals Statistical Yearbook, and a total of 55 provinces with advanced centers for cancer were analyzed. This study applied Charnes, Cooper, and Rhodes’s input-oriented data envelopment analysis (DEA) and performed jackknifing for robustness check of DEA scores. ResultsThe iteration procedure generated four models. The final model included 38 decision-making units (DMUs), and 50 % of provinces were found to have efficient oncology services. The final model’s average conventional efficiency score was 0.79. Next, bootstrapped DEA procedure was incorporated into the final model to gather bias-corrected efficiency scores. After applying the bootstrapping approach, efficiency scores are significantly improved and the difference between conventional and bias-corrected efficiency scores are statistically significant (U = 475; p < 0.05). ConclusionsGeographic planning of cancer care services is a relevant principle in health operations design that requires specific health service configurations for preparedness of health crisis such as pandemic. The results highlighted that health policymakers must be aware of regional imbalances and eliminate them to provide advanced oncology care services for population groups in poor areas of the country. Policy summaryHealth policy makers should prioritize a balanced geographical distribution of professional oncology services to provide vulnerable groups better access to critical care.

Evaluating technical efficiency of hair goat farms in Turkey: the case of Mersin Province.

This study aims to determine the efficiency levels of hair goat farms and to investigate the effect of socio-economic factors on efficiency. The data were collected from 110 hair goat farmers operating in Mersin province of Turkey, in the year 2019. An input-oriented data envelopment analysis (DEA) was used to estimate technical efficiency scores and Tobit regression was employed to determine effective factors on technical efficiency. DEA results showed under the constant and variable returns to scale assumptions that the mean efficiency scores were estimated as 0.67 and 0.76, respectively. The present results indicated that farmers were overusing inputs and they can reduce the inputs by 33% and 24% in order to produce the same level of output. The results further show that farmers' education (p < 0.05), the number of goats (p < 0.01), income (p < 0.05) and cooperative membership (p < 0.10) are statistically significant factors influencing the technical efficiency of hair goat farms. Technical efficiency of farms should be improved by focusing on the education and extension services for optimum input use, adopting new technologies by encouraging farmers to join cooperatives.

Levels, trends and determinants of technical efficiency of general hospitals in Uganda: data envelopment analysis and Tobit regression analysis

BackgroundGeneral hospitals provide a wide range of primary and secondary healthcare services. They accounted for 38% of government funding to health facilities, 8.8% of outpatient department visits and 28% of admissions in Uganda in the financial year 2016/17. We assessed the levels, trends and determinants of technical efficiency of general hospitals in Uganda from 2012/13 to 2016/17.MethodsWe undertook input-oriented data envelopment analysis to estimate technical efficiency of 78 general hospitals using data abstracted from the Annual Health Sector Performance Reports for 2012/13, 2014/15 and 2016/17. Trends in technical efficiency was analysed using Excel while determinants of technical efficiency were analysed using Tobit Regression Model in STATA 15.1.ResultsThe average constant returns to scale, variable returns to scale and scale efficiency of general hospitals for 2016/17 were 49% (95% CI, 44–54%), 69% (95% CI, 65–74%) and 70% (95% CI, 65–75%) respectively. There was no statistically significant difference in the efficiency scores of public and private hospitals. Technical efficiency generally increased from 2012/13 to 2014/15, and dropped by 2016/17. Some hospitals were persistently efficient while others were inefficient over this period. Hospital size, geographical location, training status and average length of stay were statistically significant determinants of efficiency at 5% level of significance.ConclusionThe 69% average variable returns to scale technical efficiency indicates that the hospitals could generate the same volume of outputs using 31% (3439) less staff and 31% (3539) less beds. Benchmarking performance of the efficient hospitals would help to guide performance improvement in the inefficient ones. There is need to incorporate hospital size, geographical location, training status and average length of stay in the resource allocation formula and adopt annual hospital efficiency assessments.

Supply Chain Performance Analysis With Data Envelopment Analysis in TBBM PT. Pertamina Boyolali

PT. PERTAMINA TBBM Boyolali is a supplier of fuel oil in the form of premium, pertamax and diesel. The company should distribute fuel products using tank cars with operating areas covering Boyolali, Surakarta, Karanganyar, Sukoharjo, Sragen, Klaten, Wonogiri, Ngawi, Pacitan, Magetan, Ungaran, Semarang, Salatiga, Purwodadi, and Blora. An efficient supply chain is needed to provide the right products and services, with the specifications needed, in the right place and to the right customers. This article aims to find out and analyze the efficiency that occurs at operational TBBM Pertamina Boyolali and to find out the variables that most influence supply chain performance to be analyzed and improved so that improvements in supply chain performance can be more focus and optimal. The Decision-Making Units (DMUs) stated in this article are the period of supply chain activities from January 2018 to November 2018 at TBBM Pertamina Boyolali, the number of DMU is 11 DMUs. Supply Chain Operation Reference (SCOR) method with responsiveness, flexibility, and reliability attributes is used to measure Supply chain performance. To analyze supply chains efficiency, this article applies input-oriented DEA CCR (Charnes, Cooper, and Rhodes) model which considers linear relationships in its input and output. Data Envelopment Analysis (DEA) is a strong tool for measuring the efficiency of the DMUs and does not need to normalize indicator values that have different dimensions. The software used for processing data in this article is Banxia Frontier Analyst 4.2. This article provides suggestions for improving cash-to-cash cycle time, lead time, and flexibility for more efficient fuel distribution.

Performance Assessment Based on the Relative Efficiency of Indian Opencast Coal Mines Using Data Envelopment Analysis and Malmquist Productivity Index

Coal is the primary source of energy in India. Despite being the second-largest coal-producingcountry, there exists a significant difference in demand and production in India. In this study, the relativeefficiency of twenty-eight selected opencast mines from a large public sector undertaking coal companyin India for 2018–2019 was assessed and ranked by using data envelopment analysis (DEA). This studyused input-oriented DEA with efficiency decomposition to pure technical efficiency, technical efficiency,and scale efficiency. The result showed that 25% and 36% of mines were efficient in technical efficiencyand pure technical efficiency, respectively, whereas the eight mines scale efficiency was inefficient witha decreasing return to scale. Further, in this study, theMalmquist Productivity Index (MPI)was employedto measure the efficiency of the selected mines for three consecutive years (2016–2017 to 2018–2019).The result shows that in only three mines the efficiency is continuously improving from 2016–2017 to2018–2019, whereas in more than 20% of mines the efficiency score is decreasing. Comparing theMPIefficiency and productivity assessment throughout the years, changes in innovation and technology areincreasing from 2017–2018 to 2018–2019. Finally, the study concluded with a comprehensive evaluationof each variable with mines performance. The author formulated the strategies, which in turn help coalprofessionals to improve the efficiency of the mine.

Benchmarking the efficiency model for working capital management: data envelopment analysis approach

PurposeThis paper evaluates the working capital management (WCM) efficiency of the Indian manufacturing industries through data envelopment analysis (DEA) and empirically investigates the influence of several exogenous variables on the WCM efficiency.Design/methodology/approachWCM efficiency was calculated using BCC input-oriented DEA model. Further, the panel data fixed effect model was used on a sample of 1391 Indian manufacturing firms spread across nine industries, covering the period from 2008 to 2019.FindingsFirstly, the WCM efficiency of Indian manufacturing industries has been stable over the analysis period. Secondly, the capacity to generate internal resources, size, age, productivity, gross domestic product and interest rate significantly influence WCM efficiency.Research limitations/implicationsFirst, the selected study period has observed various economic uncertainties including demonetization and recession, so the scenario might differ in normal conditions or country-wise. Second, the findings might not be generalizable to the developed economies, since the current study sample belongs to a developing economy, which further provides scope for comparative study.Practical implicationsAn efficient model for managing the working capital comprising most vital determinants could enhance the firms' valuation and goodwill. Also, this study would be helpful for financial executives, manufacturers, policymakers, investors, researchers and other stakeholders.Originality/valueThis study estimates the industry-wise WCM efficiency of the Indian manufacturing sector and suggests measures to the concerned parties on areas to focus on and provide evidence on the estimated relationships of firm-level and macroeconomic determinants with WCM efficiency.

Health systems efficiency in Eastern Mediterranean Region: a data envelopment analysis

BackgroundOne of the most important issues in public policy and welfare state is health care. Poor management leads to the waste of resources, including money, human resources, facilities, and equipment.AimsThis paper seeks to answer the question of which eastern Mediterranean countries are more effective in allocating their health resources, and does Iran, in relation to those countries, have an effective health system.MethodsThis study examined technical efficiency among eastern Mediterranean countries in 2018. Data were extracted from Global Health Observatory data World Health Organization. We applied input-oriented Data Envelopment Analysis (DEA) models to estimate efficiency scores. Inputs are Physicians density per 10,000 populations, Total hospital beds per 10,000 populations, Current expenditure on health, % of gross domestic product and outputs are infant survival rate and Life expectancy.ResultsThe most efficient health systems in the eastern Mediterranean were Bahrain, Egypt, Iran, Lebanon, Morocco, Oman, Pakistan, Qatar, Tunisia and the United Arab Emirates. The inefficient countries are Iraq, Jordan, Kuwait, Libya, Palestine and Saudi Arabia.ConclusionsAmong the efficient countries, one category of high-entry countries such as Bahrain and Qatar with high input especially in health expenditure had higher output. The second group of countries with lower inputs such as Iran and Morocco has been able to produce similar output with other countries. Also, inefficiency in countries such as Saudi Arabia can be attributed to this with higher input such as health expenditure has lower output such life expectancy and infant survival rate.

Ağız ve Diş Sağlığı Merkezlerinin Verimlilik Analizi: Marmara Bölgesi Örneği

The aim of this research is to determine the technical, allocative and scale efficiency of Oral and Dental Health Centers in Marmara region under the Turkish Ministry of Health in 2014 and 2017. Input-oriented Data Envelopment Analysis (DEA) method was used for efficiency measurement. Two inputs and six output variables were used in the study. Super efficiency analysis was performed to rank the advantages among the centers found to be efficient as a result of DEA, and regression analysis was performed to determine the correlation between the efficiency results and the input/output variables. As a result of the research, the average technical efficiency of 33 centers in 2014 was 0,909, allocative efficiency 0,945 and scale efficiency 0,960. In 2017, the centers had an average technical efficiency of 0,916, allocative efficiency of 0,954 and scale efficiency of 0,960. Inefficient centers must make the necessary potential improvements based on the reference set in order to achieve technical, allocative and scale efficiency.

Comparison of Technical Efficiency of Hospitals Affiliated to Shahid Sadoughi University of Medical Sciences before and after Executing Health Reform Plan

Background: Hospitals are one of the greatest and most costly operational units of the health system and a study on its performance may be a criterion for operation and efficiency assessment of its resource consumption. The present study was done in 2017 with the purpose of assessing technical efficiency of the selected hospital under the coverage of Yazd University of Medical Sciences using Data Envelopment Analysis (DEA) in context of Health Reform Plan. Methods: This research is a descriptive-analytical study was done in 2017. In this research in order to determine assessing the efficiency of Yazd University of Medical Sciences hospitals, 10 hospitals affiliated with this university were chosen. To collect data the information collection form including specifications of hospital as well as input and output index is used and the data before and after executing Health Reform Plan were collected and compared. The input-oriented DEA method is used for estimating technical efficiency of hospitals and data analysis is done by DEAP software and two-sample paired-t test SPSS21. Results: The average of hospitals that have been studied before and after the reform plan is 0.985 and 0.990 respectively. In management efficiency, it is respectively 0.986 and 0.992 before and after the reform plan and the efficiency average of the hospital's scale before and after executing the health reform plan is respectively 0.999 and 0.997. There is no meaningful relationship observed between hospitals' efficiency grades before and after the reform plan in these three technical, management and scale types of efficiency (P-value &gt; 0.05). Conclusion: According to results we could say the efficiency of the hospitals was not so affected by reform plan. It is recommended to assess the efficiency of the Stochastic Frontier Analysis (SFA) method on a linear basis in addition to identifying indexes that are effective in efficiency of hospitals.

The Efficiency of Primary Health Care Institutions in the Counties of Hunan Province, China: Data from 2009 to 2017.

This study aimed to estimate the efficiency and its influencing factors of Primary Health Care Institutions (PHCIs) in counties in Hunan Province, China, and put forward feasible suggestions for improving the efficiency of PHCIs in Hunan Province. We applied the Input-Oriented Data Envelopment Analysis (DEA) method and the Malmquist Index Model to estimate the efficiency of PHCIs in 86 counties in Hunan Province from 2009 to 2017. Then, the Tobit model was used to estimate the factors that influence the efficiency of PHCIs. Since the implementation of the new health-care reform in 2009, the number of health resources in PHCIs in Hunan Province has increased significantly, but most counties’ PHCIs remain inefficient. The efficiency of PHCIs is mainly affected by the total population, city level, the proportion of health technicians and the proportion of beds, but the changes in per capita GDP have not yet played a significant role in influencing efficiency. In the future, the efficiency of PHCIs should be improved by increasing medical technology skills and enthusiasm of health technicians and by improving the payment policies of medical insurance funds.

Determinants of soft budget constraints: How public debt affects hospital performance in Austria.

Soft budget constraints (SBCs) undermine reforms to increase hospital service efficiency when hospital management can count on being bailed out by (subnational) governments in case of deficits. Using cost accounting data on publicly financed, non-profit hospitals in Austria from 2002 to 2015, we analyse the association between SBCs and hospital efficiency change in a setting with negligible risk of hospital closure in a two-stage study design based on bias-corrected non-radial input-oriented data envelopment analysis and ordinary least squares regression. We find that the European debt crisis altered the pattern of hospital efficiency development: after the economic crisis, hospitals in low-debt states had a 1.1 percentage point lower annual efficiency change compared to hospitals in high-debt states. No such systematic difference is found before the economic crisis. The results suggest that sudden exogenous shocks to public finances can increase the budgetary pressure on publicly financed institutions, thereby counteracting a pre-existing SBC.

Operational Efficiency of Mexican Water Utilities: Results of a Double-Bootstrap Data Envelopment Analysis

The objective of this paper is to estimate the operational efficiency of Mexican water utilities and identify the context variables that impact their efficiency. In particular, a bootstrap data envelopment analysis (DEA) and a bootstrap truncated regression analysis are combined in a two-stage research method. In the first stage, an input-oriented DEA model is used to determine bootstrap efficiency scores. Then, the corrected distribution function of the efficiency scores is used to estimate a truncated regression which is aimed to identify the significant influential context variables. Three categorical and two continuous context variables are considered in the analysis. Results show that only one context variable has a significant impact on the water utilities efficiency scores. Managerial recommendations are drawn from the analysis. It is suggested that water utilities continue or implement wastewater treatment, persist in decreasing and controlling leakage across the distribution network, and maximizing sewer coverage.

Determinants of Public Health Care, Education and Administration Efficiency in Central, Eastern and South Eastern Europe

This paper analyses determinants of public sector efficiency in 15 Central Eastern and South Eastern European (CESEE) countries. Using Data Envelopment Analysis (DEA) and panel Tobit regressions we analyse the efficiency of public expenditure on health care, education, and public administration. This paper represents the first analysis of public expenditure efficiency for this region. The countries in the sample share a similar economic transition background and transition related challenges in terms of government size and efficiency. In this paper we use input-oriented DEA to calculate efficiency scores and apply Tobit regressions to identify the determinants of public expenditure efficiency for each category. According to our results, the health care sector shows the most room for improvement. With an average input efficiency score of 0.87, the analysed countries could attain the same output with an average 13% fewer resources. The results show that Bulgaria, Estonia, and Slovenia are the most efficient, whilst Serbia, Croatia, and Bosnia and Herzegovina are the worst performers. GDP per capita has a positive effect on efficiency in the health care sector, the rising share of the elderly population reduces the efficiency coefficient, whilst a higher level of education has a positive effect on the efficiency score, as recorded in earlier studies. In education, our results suggest that countries waste an average 10% of their resources. The Czech Republic, Estonia, Poland, Romania, and the Slovak Republic represent the frontier, while the worst performers are Slovenia, Lithuania, and Latvia. The results show that GDP per capita has a positive effect on efficiency in the education sector, whilst a higher unemployment rate leads to lower efficiency scores. Regarding public administration, the average efficiency score of the analysed countries is 0.9, which indicates that countries are wasting an average 10% of their resources. Estonia and Romania are fully efficient, whilst Montenegro, Bosnia and Herzegovina, and Hungary are the most inefficient countries in the sample. As expected, GDP per capita and institutional quality have positive effects on the efficiency of public administration.

The Impact of Bank-Specific Factors on the Efficiency of Pakistan's Commercial Banks: Data Envelopment Analysis and Tobit Regression Model Framework

This study aims to measure the effects of bank-specific factors on the efficiency of Pakistan's twenty-seven (27) commercial banks. Efficiency was computed by input-oriented data envelopment analysis approach under CRS (constant return to scale) and VRS (variable return to scale) assumptions. The results revealed that overall inefficiency in commercial banks was to tune of 10 percent and was caused by both managerial incompetence and uneconomical bank's size. However, the uneconomic scale size remained the dominant source of inefficiency at individual banks level, and most of the banks exhibited a decreasing return to scale (DRS) behaviour. Furthermore, efficiency scores were regressed by bank-specific factors using the Tobit regression model. Among the bank-specific factors, Profitability, liquidity, bank size had a significant and positive impact, while market share and Asset quality had a negative and substantial effect on all the efficiency parameters.

Assessment of public sector performance in the MENA region: data envelopment approach

ABSTRACTThis paper aims to measure the performance and efficiency of the public sector in the MENA region over the 2004–2015 period. To do so, two approaches are used: composite indicator approach and Data Envelopment Analysis (DEA). Fourteen, relatively stable, countries from the MENA region were chosen to construct the study sample. The findings of the input-oriented DEA indicate that the United Arab Emirates is the only efficient country according to constant return to scale model, and that the United Arab Emirates, Qatar, and Iran are the most efficient countries with respect to variable return to scale model. Moreover, a comparison of the efficiency of the MENA countries in question to the efficiency of a number of emergent countries in Europe and South America shows that the emerging countries of Europe are the most efficient, followed by South American countries and finally those of the MENA region.

Improve the efficiency of the energy services at national electricity company (PLN) using data envelopment analysis (DEA)

The indicators of economic improvement in energy efficiency have been measured and evaluated globally, one of them was the consumption of energy. However, in Indonesia, the increase in energy efficiency has not been optimally improved in terms of energy consumption, especially for fossil fuel energy consumption and GHG emission. This was caused by the energy resources which was heavily relied on coal-fired power generation and imported crude oil. This paper proposed a solution by providing a good energy efficiency measurement based on the well-developed DEA technique. This study was aimed to provide acceptable energy efficiency, especially any single rupiah of the GRDP produced the people had to consume energy in Indonesia. Thus, optimizing energy efficiency was a key to reduce import dependency, support the green economy, and bring down costs for consumers. This research used input-oriented DEA based on the Charnes, Cooper, and Rhodes (CCR) model to assess the efficiency scores of PLN in Indonesia implemented in the period 2017. The result revealed that the consumption of energy that any single rupiah of GRDP produced, the provinces at Jawa, Bali, Sumatra, Papua, Maluku, and Nusa Tenggara had to consume energy more than one at Kalimantan and Sulawesi. Based on this study, fossil fuel energy consumption and GHG emissions performance in PLN were very crucial for the future of energy assessment in Indonesia.

Public Sector Performance and Efficiency Assessment of Indian States

The purpose of this paper to analyze public spending of 19 Indian states on the basis of their performance. We have computed Public Sector Performance (PSP) scores with their representative sub-indicators for the period of 2006-2015. Total 10 years of data have taken of these sub-indicators to capture the structural changes in the economy. This PSP score is divided into two parts namely, PSP Opportunity and PSP Musgravian. Both the PSPs have their own representative variables and the total PSP scores are the composite average of these indicators. Based on these PSPs scores we have computed states efficiency using Data Envelopment Analysis (DEA) and ranked the states according to their efficiency. We applied three DEA models with consideration of State Total Revenue Expenditure (TRE) as an input variable, further we have considered PSP Opportunity, PSP Musgravian and Total PSP scores as output variables in these models. The input-oriented DEA analysis reveals that states should have decreased public spending by 57.88%. The output-oriented DEA models conclude that state governments would have potential to increase the efficiency by 14.16% without compromising public spending. Various policy suggestions also discussed by incorporating empirical findings at last section of this paper.

Data Envelopment Analysis for Simplified Neutrosophic Sets

In recent years, therehas been a growing interest in neutrosophic theory, and there are several methods for solving various problems under neutrosophic environment. However, a few papers have discussed the Data envelopment analysis (DEA) with neutrosophic sets. So, in this paper, we propose an input-oriented DEA model with simplified neutrosophic numbers and present a new strategy to solve it. The proposed method is based on the weighted arithmetic average operator and has a simple structure. Finally, the new approach is illustrated with the help of a numerical example.

THE EFFECTIVENESS OF FACEBOOK PROMOTING THE BRANDS OF SLOVAK WELLNESS HOTELS BASED ON THE DEA METHODOLOGY

This contribution presents an evaluation of the effectiveness of the Facebook social network promoting the brands of a number of selected Slovak wellness hotels based on the DEA (Data Envelopment Analysis) methodology and its selected models.&#x0D; The research question is that hotel guests use the funpages of the Slovak wellness hotels on the Facebook social network to learn more about its services and also how the Slovak wellness hotels use their funpages to promote their brand and communicate with their consumers.&#x0D; During the four months in 2018 (September – December), data on input and output variables was collected, with data from photos, videos and links to "funpage" hotels on Facebook and output to "Likes" and "Comments". The measurement of the efficiency of these input and output variables in order to assess the effectiveness of 16 wellness hotel brands operating in the Slovak Republic was based on an input-oriented CCR DEA model with weight adjustment via the Assurance Region.&#x0D; The number of Likes and comments on the Facebook pages of the 16 Slovak wellness hotels suggests that hotel guests use Facebook to learn more about the services and events they provide. The DEA model is therefore an effective tool to help evaluate the effectiveness of a business in a hotel sector on a social network, such as Facebook, in promoting its brands, as it uses multiple variables and does not necessarily require an input-output relationship. The results of using this method confirmed the research question.