Two-stage Data Envelopment Analysis Method Research Articles

Estimation of Technical, Allocative, and Economic Efficiencies for Smallholder Broiler Producers in South Africa

The prevailing economic conditions as a result of COVID-19, climate change, and the Russia–Ukraine conflict, have led to renewed global interest in the efficiency of the agricultural sector. As a result of this, we investigated the efficiencies of 64 broiler producers in three districts covering the North West and Limpopo provinces in South Africa from 2019 to 2022, using a two-stage data envelopment analysis method with input orientation. The results show that producers operate on the upper bounds toward efficiency, but room for improvement still exists at 10%, 20%, and 28% on technical, allocative, and cost efficiencies. This indicates that inputs can still be reduced without changing the level of output and that the input combination is incompatible with cost minimization. Consequently, only 13%, 8%, and 4% of the sampled broiler producers exhibited technical, allocative, and cost efficiencies, respectively; the majority were women. The Vhembe, Capricorn, and Dr. Kenneth Kaunda (DRKK) districts had vastly different scores for each efficiency type, indicating that their differences in resource endowments, technology, and climate, necessitate the formulation of district-specific policies. The mortality rate, heating costs, and investments in health emerged as significant efficiency determinants. Overall, the findings provide insights into refocusing the country’s poultry sector in light of current shocks and the notable aspirations of the poultry master plan.

Who Is the Most Effective Country in Anti-Corruption? From the Perspective of Open Government Data and Gross Domestic Product

Corruption represents the misuse of public power by government departments for personal gain, hindering a country’s economic growth. Corruption cannot be eliminated by implementing the national democratic system, and mature democratic countries also exist with varying degrees of corruption. Corruption affects people’s trust in the public sector and the country’s economic development. Open government data can help people understand the governance performance of the government to reduce corruption in the public sector. Citizens can use open government data to generate innovative applications and economic value. This study uses a two-stage data envelopment analysis method to assess the anti-corruption efficiency of 21 countries from 2013 to 2017 through open government data, the corruption perception index, and GDP data. Then, the efficiency analyzed is introduced into the BCG (Boston Consulting Group) matrix to observe the distribution of these 21 countries. Analyzing the results showed that Uruguay and Costa Rica in Central and South America are the two most influential countries in fighting corruption. Turkey is at the bottom in the evaluation of anti-corruption efficiency. In addition, discussions of the included countries for their possible improvement in anti-corruption are also provided by using the association rule’s analysis. The study results will provide a reference for governments to effectively carry out anti-corruption work in the future.

Determinants of efficiency of Indonesian Islamic rural banks

The purpose of the study is to evaluate the efficiency of Islamic Rural Banks (BPRS) and analyze the factors that determine them using a two-stage approach to Data Envelopment Analysis (DEA). DEA in this study focuses on the production, intermediation, and inefficiency causes. This research was done on BPRS across Indonesia. The data were taken from a financial report for the 2013-2021 period. The source of the data was a publication from the Financial Services Authority of Indonesia. The data were analyzed using the non-parametric approach with a two-stage DEA method. The input variables were personnel costs, fixed assets, and third-party funds. The result shows that Revenue Sharing, ROA, and Growth have a significant positive effect on DEA. BOPO and inflation have a positive but insignificant effect on DEA. While NPF and FDR have negative but insignificant effects on DEA. Then CAR has a negative and not significant effect on DEA. It also shows that the variables of Revenue Sharing, NPF, ROA, CAR, FDR, BOPO growth, and inflation have a simultaneous effect on DEA.

Investigation of factors affecting efficiency of primary healthcare in Turkey with two-stage data envelopment analysis

ABSTRACT This study had two aims, one of which was to reflect the efficiencies of all institutions providing primary healthcare in Turkey between the years of 2012–2014 at the level of provinces. The second aim was to identify the factors that affect the efficiency scores. Two-stage data envelopment analysis method was utilized accordingly. The findings of the study showed that the number of provinces providing primary healthcare efficiently was found as 20 for 2012, 17 for 2013 and 24 for 2014. The study also showed that the efficiency scores of the provinces in primary healthcare changed according to income, apart from the input and output variables. According to the results of the study, it was found that most of the provinces are inefficient. In order to improve this, attention should be paid to decreasing inputs and infant mortality rate and increasing the average number of follow-up per infant, especially in provinces where income per capita is low. In addition, it is thought that the results of this study will provide important information to healthcare administrators and policy makers regarding primary care, which has an important role in preventing outbreaks (for example COVID-19), monitoring diseases, protecting and promoting health.

The determinant factors of efficiency on Islamic banking and conventional banking in Indonesia

As intermediary institutions, conventional banks have larger amount of loans to third party funds than of Sharia banks. Thus, the bank needs a performance appraisal to measure banking operations through efficiency. We examine the efficiency of Islamic banks and conventional banks in Indonesia and analyzes the factors that influence the level of efficiency known as the Two-Stage Data Envelopment Analysis method. We found that there are significant efficiency differences between Islamic banking and conventional banking in the 1 st quarter 2014- 4 th quarter 2017. On the other hand, NPF and NPL results affected negatively towards Islamic and conventional banks efficiency. Asset and CAR affected positively significant toward Islamic banks efficiency. Asset and ROA had affected positively significantly toward conventional banks efficiency but CAR had affected positively insignificantly toward conventional banks. Lastly, ROA had affected positively insignificantly toward Islamic banks efficiency. JEL Classification: G31, G32, G33 DOI : https://doi.org/10.26905/jkdp.v23i3.3157

Measuring the efficiency of Palestinian public hospitals during 2010\u20132015: an application of a two-stage DEA method

BackgroundWhile health needs and expenditure in the Occupied Palestinian Territories (OPT) are growing, the international donations are declining and the economic situation is worsening. The purpose of this paper is twofold, to evaluate the productive efficiency of public hospitals in West Bank and to study contextual factors contributing to efficiency differences.MethodsThis study examined technical efficiency among 11 public hospitals in West Bank from 2010 through 2015 targeting a total of 66 observations. Nationally representative data were extracted from the official annual health reports. We applied input-oriented Data Envelopment Analysis (DEA) models to estimate efficiency scores. To elaborate further on performance, we used Tobit regression to identify contextual factors whose impact on inefficient performance is statistically significant.ResultsDespite the increase in efficiency mean scores by 4% from 2010 to 2015, findings show potential savings of 14.5% of resource consumption without reducing the volume of the provided services. The significant Tobit model showed four predictors explaining the inefficient performance of a hospital (p < 0.01) are: bed occupancy rate (BOR); the outpatient-inpatient ratio (OPIPR); hospital’s size (SIZE); and the availability of primary healthcare centers within the hospital’s catchment area (PRC). There is a strong effect of OPIPR on efficiency differences between hospitals: A one unit increase in OPIPR will lead a decrease of 19.7% in the predicted inefficiency level holding all other factors constant.ConclusionTo date, no previous studies have examined the efficiency of public hospitals in the OPT. Our work identified their efficiency levels for potential improvements and the determinants of efficient performance. Based on the measurement of efficiency, the generated information may guide hospitals’ managers, policymakers, and international donors improving the performance of the main national healthcare provider. The scope of this study is limited to public hospitals in West Bank. For a better understanding of the Palestinian market, further research on private hospitals and hospitals in Gaza Strip will be useful.

A novel two-stage DEA production model with freely distributed initial inputs and shared intermediate outputs

Conventional data envelopment analysis (DEA) models treat the decision-making units (DMUs) as black-boxes: inputs enter the system and outputs exit the system, with no consideration for the intermediate steps characterizing the DMUs. As a result, intermediate measures are lost in the process of changing the inputs to outputs and it becomes difficult, if not impossible, to provide individual DMU managers with specific information on what part of a DMU is responsible for the overall inefficiency. This study defines a two-stage DEA model, where each DMU is composed of two sub-DMUs in series, the intermediate products by the sub-DMU in Stage 1 are partly consumed by the sub-DMU in Stage 2, and the initial inputs of the DMU can be freely allocated in both stages. Also, there are additional inputs directly consumed in Stage 2 while part of the outputs of Stage 1 are final outputs. We develop four new linear models to determine the upper and lower bounds of the efficiencies of the two sub-DMUs in a non-cooperative setting and a linear model to calculate the overall efficiency of DMU in a cooperative setting. That is, the overall efficiency of a DMU is modelled in a cooperative setting via upper and lower bounds obtained in the non-cooperative one. The proposed two-stage DEA method allows for important applications to several management areas. A case study in the banking industry is presented to demonstrate the applicability and exhibit the efficacy of the proposed models.

Two-Stage DEA Analysis of Water Resource Use Efficiency

This paper presents an extended two-stage data envelopment analysis (DEA) method for analyzing water resource use efficiency (WRUE) and related WRUE issues, which was developed by introducing regional water resource metabolic theory into the two-stage DEA method. It has the following advantages: (1) it has the ability to reflect the inner difference and connection of the regional water resource consumption process, which developed the corresponding physical model instead of making it a “black box”; (2) the built physical model for WRUE divided the main body of water resource consumption into social and economic subsystems, which can thus elaborate WRUE; (3) it can analyze not only WRUE but also related WRUE issues. The proposed method was applied to a real-case study in Gansu Province, China. Results show that decision makers can determine the comprehensive and accurate WRUE and negative factors of WRUE in Gansu Province. Moreover, the results offer recommendations for decision makers to plan for efficient use of water resources in different cities.

PERFORMANCE EVALUATION OF CZECH INNOVATIVE COMPANIES: DATA ENVELOPMENT ANALYSIS APPROACH

The article deals with the verification of a performance evaluation model of innovative companies in the Czech Republic and the evaluation of the impact of a branch on their performance in terms of effectiveness and efficiency. From a methodological point of view, the article is based on the use of Data envelopment analysis (DEA) to evaluate the performance of the selected companies. To evaluate their performance, a two-stage DEA method, BCC model orientated at inputs is used. In the first stage, the effectiveness of resources spent on protecting industrial property rights is evaluated. In the second stage, it is assessed how the companies managed to evaluate registered property rights in terms of added value. The research results show that among branches, there are significant differences in both the overall level of performance, and in its pillars – effectiveness and efficiency. In the conclusion, other potential factors that could affect the company’s performance in terms of effectiveness and efficiency are discussed.

Profitability performance assessment in the Australian construction industry: a global relational two-stage DEA method

Effective performance measurement drives performance and supports the development of construction. Only minimal literature measuring construction performance, efficiency and effectiveness simultaneously can be identified. A global relational two-stage data envelopment analysis (DEA) method is here proposed in order to produce effective and informative performance results. A relational two-stage DEA method systematically measures overall efficiency for a whole construction system and also yields scores for the individual stages of construction. The DEA results can be directly compared through global benchmark technology. The Australian construction industry is employed in order to implement the new method, in which profitability performance as a vital indicator of business survival, and its two dimensions of efficiency and effectiveness, are measured. The construction profitability performance and efficiency measures obtained provide evidence of underperformance and a slight imbalance in Australia between 1991 and 2012, while the measures obtained for the effectiveness factor indicate better achievement. The approach here developed promotes progress in modelling two-stage performance measurement and it can be replicated worldwide by construction projects, organizations or industries in order to quantify their performance, identify internal inefficiency components and recognize competitive advantages for promoting sustainable development.

A two-stage data envelopment analysis model for measuring performance in three-level supply chains

Data Envelopment Analysis (DEA) has been widely used to evaluate supply chain performances. In conventional DEA, supply chains are represented as black boxes where only the initial inputs and final outputs are considered to measure their efficiency. However, an integrated model measuring both the efficiency of the entire supply chain and that of all its components at all levels is essential for a comprehensive evaluation. This study presents a two-stage DEA method to evaluate the performance of a three-level supply chain including suppliers, manufacturers and distributors. The proposed model can be used both under the constant returns to scale and the variable returns to scale assumptions and can be easily implemented for comprehensive analysis of multi-level supply chains. We present a numerical example to demonstrate applicability of the proposed model and exhibit the efficacy and effectiveness of the proposed algorithms and procedures. In particular, the numerical results demonstrate that the entire supply chain is “comprehensively” efficient only if efficient supplier–manufacturer and manufacturer–distributor relationships are established.

EFISIENSI BANK UMUM SYARIAH MENGGUNAKAN PENDEKATAN TWO-STAGE DATA ENVELOPMENT ANALYSIS

The aim of this study is to measure the efficiency of Islamic Bank in Indonesia, to analyze the factors that affect the level of efficiency which is known as Two-Stage Data Envelopment Analysis method and to propose measurement of Bank Soundness with modified CAMELS. The objects of this study are 10 (ten) Islamic Bank (BUS) in Indonesia which analyzes from the second Quarter of 2010 until the fourth Quarter of 2012. There are 2 (two) methods which are used in this study, namely non-parametric method of Data Envelopment Analysis (DEA) on the first stage and Tobit model on the second stage. In addition, this study will illustrate the formulation of the financial factors of CAELS instead of CAMEL by integrating the results of efficiency level measurement using DEA in CAELS formulation. Overall, the results, show that the efficiency level of Islamic banks in Indonesia during the time period in this study, have not yet reach the optimum level of efficiency. In addition, modification of CAELS for the bank performance level method by integrating the result of DEA shows that the modification of CAELS could be more accurate in describing the bank performance level, particularly for Islamic Bank in Indonesia. Keywords: Efficiency, Data Envelopment Analysis (DEA), Tobit Model, CAELS + DEAJEL Classification: C02, C14, C54,G21

Efficiency of Islamic Banks Using Two Stage Approach of Data Envelopment Analysis

The aim of this study is to measure the efficiency of Islamic Bank in Indonesia, to analyze the factors that affect the level of efficiency which is known as Two-Stage Data Envelopment Analysis method and to propose measurement of Bank Soundness with modified CAMELS. The objects of this study are 10 (ten) Islamic Bank (BUS) in Indonesia which analyzes from the second Quarter of 2010 until the fourth Quarter of 2012. There are 2 (two) methods which are used in this study, namely non-parametric method of Data Envelopment Analysis (DEA) on the first stage and Tobit model on the second stage. In addition, this study will illustrate the formulation of the financial factors of CAELS instead of CAMEL by integrating the results of efficiency level measurement using DEA in CAELS formulation. Overall, the results, show that the efficiency level of Islamic banks in Indonesia during the time period in this study, have not yet reach the optimum level of efficiency. In addition, modification of CAELS for the bank performance level method by integrating the result of DEA shows that the modification of CAELS could be more accurate in describing the bank performance level, particularly for Islamic Bank in Indonesia. Keywords: Efficiency, Data Envelopment Analysis (DEA), Tobit Model, CAELS + DEAJEL Classification: C02, C14, C54,G21

Analysis of relationship between efficiency of justice services and salaries of judges with two-stage DEA method

In this study it’s aimed to determine the relationship between efficiency of justice service and salaries of judges in European countries with two-stage Data Envelopment Analysis (DEA). Data used in this study are taken from European Judicial System report published by The European Commission for the Efficiency of Justice. In this study two stage DEA is used. In the first stage, the efficiency of justice service is measured by data envelopment analysis. In the second stage, the results obtained from DEA are regressed with variables affecting the courts by Tobit regression model. In the DEA analysis while number of judges and office staff are used as inputs, resolved cases are used as outputs. In the Tobit regression model while the results obtained from DEA are used as dependent variable, judge salaries, judges’ basic education and number of courts are used as explanatory variables. According to Tobit regression model, it’s found that there is a positive and significant relation between efficiency of justice service and salaries of judges in European countries. The increase in judge salaries is significant for the efficiency of courts, but it certainly is not only solution for the efficiency of justice services.

A cause and effect two-stage BSC-DEA method for measuring the relative efficiency of organizations

This paper presents an integration of balanced score card (BSE) with two-stage data envelopment analysis (DEA). The proposed model of this paper uses different financial and non-financial perspectives to evaluate the performance of decision making units in different BSC stages. At each stage, a two-stage DEA method is implemented to measure the relative efficiency of decision making units and the results are monitored using the cause and effect relationships. An empirical study for a banking sector is also performed using the method developed in this paper and the results are briefly analyzed.