Data Envelopment Analysis Method Research Articles

Efficiency Of Sharia Commercial Banks In Indonesia (Two-Stage Analysis)

This research is motivated by the importance of efficiency in the banking industry, especially in the Islamic banking sector which has a vital role in the Indonesian economy. This study aims to analyze the efficiency of Islamic commercial banks in Indonesia using a two-stage analysis approach. The method used is divided into 2 stages, the first stage is to measure efficiency using the Data Envelopment Analysis (DEA) method to assess the operational performance of banks. The second stage is to analyze the factors that influence efficiency through panel regression. The results of the study indicate that although there are variations in the level of efficiency between banks, factors such as bank size, capitalization, and information technology have a significant influence on efficiency. These findings are expected to provide insight for stakeholders in improving the performance of Islamic banks in Indonesia

Quantitative evidence of the community of shared future for mankind as a driver of sustainable development in human society

In an era marked by global economic challenges, an increasing array of non-traditional security threats, and a proliferation of conflicts and issues, China has put forth the building of a community of shared future for mankind as a way to address this question of the times. The theory of the community of shared future for mankind offers a framework to address contemporary issues by promoting equality, mutual benefit, security, justice, openness, innovation, multicultural exchange, and green development. This paper innovatively quantifies the five core principles of the theory of the community of shared future for mankind using the entropy method. It calculates the proxy variable for sustainable development, green total factor productivity, using the super-efficiency Slack-Based Measure model in Data Envelopment Analysis. Baseline regression is conducted on this basis. The Principal Component Analysis method and another Data Envelopment Analysis method, the Malmquist index, are utilized to recalculate the indicators, followed by another round of regression analysis. The results are consistent with the baseline regression. Additionally, Ordinary Least Squares, Partial Least Squares, Maximum Likelihood Estimation, Ridge regression, and Lasso regression are employed to ensure the robustness of the results. The findings indicate a significant positive relationship between the community of a shared future for mankind and the sustainable development of human society, with consistent conclusions drawn from different calculation methods and regression techniques. Through value recognition, international cooperation based on benefit-sharing and mutual reciprocity can guide humanity towards a harmonious coexistence with nature, irrespective of regional and economic disparities. This study provides quantitative evidence of the impact of the community of a shared future for mankind on the sustainable development of human society, filling a gap in existing research. Based on these findings, feasible policy recommendations are proposed to promote sustainable development in human society.

Application of Non-Parametric and Forecasting Models for the Sustainable Development of Energy Resources in Brazil

To achieve Sustainable Development Goal 7 (SDG7) and improve energy management efficiency, it is essential to develop models and methods to forecast and enhance the process accurately. These tools are crucial in shaping the national policymakers’ strategies and planning decisions. This study utilizes data envelopment analysis (DEA) and bootstrap computational methods to evaluate Brazil’s energy efficiency from 2004 to 2023. Additionally, it compares seasonal autoregressive integrated moving average (SARIMA) models and autoregressive integrated moving average (ARIMA) forecasting models to predict the variables’ trends for 2030. One significant contribution of this study is the development of a methodology to assess Brazil’s energy efficiency, considering environmental and economic factors to formulate results. These results can help create policies to make SDG7 a reality and advance Brazil’s energy strategies. According to the study results, the annual energy consumption rate is projected to increase by an average of 2.1% by 2030, which is accompanied by a trend of GDP growth. By utilizing existing technologies in the country, it is possible to reduce electricity consumption costs by an average of 30.58% while still maintaining the same GDP value. This demonstrates that sustainable development and adopting alternatives to minimize the increase in energy consumption can substantially impact Brazil’s energy sector, improving process efficiency and the profitability of the Brazilian industry.

EFFICIENCY MEASUREMENT OF ARTIFICIAL INTELLIGENCE: A RESEARCH ON COMPANIES IN TÜRKİYE

The use of technology is increasing due to Industry 4.0. Both countries and organizations have had to invest in the field of artificial intelligence (AI) to compete with their rivals in global competitive conditions and to adapt to the ever-changing world. An organization or a country needs to evaluate its performance to ensure its sustainability constantly. The Data Envelopment Analysis (DEA) method is widely used in performance evaluation. This study aimed to evaluate Türkiye AI performance for the nine years between 2014 and 2022. In the research, years were included in the analysis as the decision-making unit. Two input and two output variables were used in the analyses. The study was carried out by using the input-oriented CCR DEA model and its super-efficiency model. According to the results of the analysis, efficient/inefficient decision-making units were determined. Several potential improvement suggestions have been put forward for inefficient decision-making units.

Using super-efficiency slack-based measure data envelopment analysis with enhanced neural network frontier to evaluate the operating efficiency of Chinese-listed real estate companies

China's real estate industry has faced significant changes and challenges in the aftermath of the COVID-19 pandemic and recent years, and has been unable to maintain its former prosperity. Facing a rapidly changing market environment and new loan restriction policies, real estate companies are encountering unprecedented challenges. Efficiency evaluation and analysis of real estate companies are essential to guide them in improving operational efficiency and adapting to new development models. This paper examines 87 real estate development companies listed on the Shenzhen and Shanghai markets, first evaluating and analyzing their operational efficiency in 2023 using the output-oriented super-efficiency slack-based measure data envelopment analysis (SBM-DEA) method. To address the issue of overestimated operational efficiency in the original model, this paper integrates it with the backpropagation neural network (BPNN) algorithm to obtain more robust re-evaluated efficiency scores. The results align with expectations, showing an overall decline in efficiency scores, and more significant decreases for companies with smaller output shortfalls in the original evaluation. The re-evaluated efficiency scores do not excessively underestimate efficiency and can serve as a reliable proxy for the original scores. The enhanced model combining BPNN with super-efficiency SBM DEA provides reliable and robust efficiency evaluations for these 87 listed real estate companies.

A novel two-stage network data envelopment analysis model for kidney allocation problem under medical and logistical uncertainty: a real case study.

Organ transplantation is one of the most complicated and challenging treatments in healthcare systems. Despite the significant medical advancements, many patients die while waiting for organ transplants because of the noticeable differences between organ supply and demand. In the organ transplantation supply chain, organ allocation is the most significant decision during the organ transplantation procedure, and kidney is the most widely transplanted organ. This research presents a novel method for assessing the efficiency and ranking of qualified organ-patient pairs as decision-making units (DMUs) for kidney allocation problem in the existence of COVID-19 pandemic and uncertain medical and logistical data. To achieve this goal, two-stage network data envelopment analysis (DEA) and credibility-based chance constraint programming (CCP) are utilized to develop a novel two-stage fuzzy network data envelopment analysis (TSFNDEA) method. The main benefits of the developed method can be summarized as follows: considering internal structures in kidney allocation system, investigating both medical and logistical aspects of the problem, the capability of expanding to other network structures, and unique efficiency decomposition under uncertainty. Moreover, in order to evaluate the validity and applicability of the proposed approach, a validation algorithm utilizing a real case study and different confidence levels is used. Finally, the numerical results indicate that the developed approach outperforms the existing kidney allocation system.

Analysis of China’s carbon financial Development’s impact on reducing emissions using the BCC and Malmquist models

This study evaluates the impact of China’s carbon finance development on carbon emission reduction and its role in promoting low-carbon economic growth. We construct an evaluation index system and employ Systematic Cluster Analysis (SCA) and Data Envelopment Analysis (DEA) methods to analyze the carbon finance markets in five representative Chinese provinces (autonomous regions). Utilizing the DEA-BCC model and DEA-Malmquist index, we conducted an in-depth analysis of the carbon emission reduction effects between 2022 and 2023. Our findings reveal that while China’s carbon finance development significantly contributes to carbon emission reduction, there are considerable regional disparities in effectiveness. Beijing and Guangdong achieved DEA efficiency, whereas Jilin, Ningxia, and Xinjiang experienced efficiency losses, suggesting a need for structural optimization. The study provides insights into challenges and potential improvements in China’s carbon finance sector and offers policy recommendations for enhancing market mechanisms, technological innovation, and social engagement to support China’s carbon peak and neutrality goals.

Background of Data Envelopment Analysis Implementation in Moscow Healthcare System: International and Russian Experience

Background. The efficiency of healthcare organization activity should be improved and measured using new techniques, as the healthcare system has widely applied advanced technologies and optimized the workflow of all medical facilities. The methodology of data envelopment analysis (DEA) is one of the fast-evolving approaches to assessing the performance of healthcare organizations. The article examines Russian and international experience in applying the DEA method, which can be used for assessing the performance of Moscow public healthcare organizations. Purpose. To study the basics of DEA and the experience of its use for assessing the efficiency of healthcare organizations in Russia and abroad, and to consider its potential implementation in the Moscow healthcare system. Materials and methods. The publications were selected using the PRISMA guidelines. A complex of modern general scientific methods of cognition was also used: system and structural approach, analytical method, comparison, and generalization. Results. The practice of using the DEA method in Russian regions and abroad was analyzed. The main advantages and disadvantages of DEA, as well as the main parameters used in constructing the model of efficiency measurement for healthcare organizations, were categorized. The prerequisites for using the DEA method to assess the efficiency of Moscow healthcare organizations were identified.

Cross-Efficiency Evaluation Method with Performance Level as a Management Objective in Consideration of Bounded Rationality

According to management by objectives (MBO) theory, the significance of management objectives must be considered as a reference point in a performance evaluation. Cross efficiency evaluation has always been considered to be one of the important performance evaluation methods. However, few studies to date have considered the impact of management objectives on cross efficiency. According to prospect theory, the choice of reference point will cause irrational psychology in decision makers. A management objective is a natural reference point, which will cause a ‘gain and loss’ psychology in enterprises and may create irrational psychology. Performance level is an important index by which to evaluate resource allocation, which in turn can be regarded as an important enterprise management objective. This paper proposes a cross efficiency evaluation method based on performance level. Cross efficiency evaluation models are constructed, based on the irrational psychology that occurs under organization objectives, personal objectives and composite objectives. This method not only considers the bounded rational behavior of enterprises, but is also more flexible. A numerical example is given to illustrate the application of the bounded rational cross efficiency evaluation method in data envelopment analysis (DEA) ranking.

The Evaluation of Climate Change Competitiveness via DEA Models and Shannon Entropy: EU Regions.

The purpose of this paper is to assess the efficiency of climate change competitiveness via a case study on EU regions by using the data envelopment analysis (DEA) model and Shannon entropy. First, on the same premise as similar composite indicators, we develop a DEA model to assess the relative performance of the regions in climate change competitiveness. Then, we extend our calculations with a DEA-like model and Shannon entropy to derive global estimates of a new competitiveness index by using common weights. Results show that the proposed DEA-Entropy model enables the construction of a regional climate change competitiveness index among all regions via a set of common weights. The proposed model's common weight structure demonstrates more discriminative power compared to the weights obtained through pure DEA or DEA-like methods. In order to validate the proposed DEA-Entropy model, it was applied to 120 EU regions. The results are meaningful for the regions to improve their competitiveness.

Evaluation of Cognitive Load Differences between Elderly and Young Pedestrians at the Signalised Intersection

The pedestrian cognitive load has an important effect on the pedestrian crossing decision making. Compared with young adults, old people are characterised by declining physical function and slower reaction ability, which makes them prone to traffic accidents when crossing the street. This study aims to compare the visual information-mental load correlation between elderly and young adults waiting at the signalised intersections and evaluate their cognitive load conditions. Therefore, two signalised intersections with different traffic scenes in the Nan’an District, Chongqing, China were selected. The eye-tracking, electrocardiographic and electrodermal activity data of young and old pedestrians were collected using eye-tracking and physiological instruments. The visual indexes (the total duration of fixations, the number of fixations, the average pupil diameter changing rate, the number of saccades, the average peak speed of saccades, the average amplitude of saccades and the total amplitude of saccades) and physiological indicators (the average growth rate of heart rate, the time-domain analysis indicator of HRV and HRV frequency domain analysis indicators, electrodermal response amplitude and rise time of the EDR amp.) were taken as inputs and outputs parameters, respectively. Then, the comprehensive cognitive load evaluation model for pedestrians was constructed when waiting to cross the street based on the data envelopment analysis method. And the cognitive load characteristic differences between the young adults and the elderly were compared. The results show that in the same crossing scene, compared with the young pedestrian, the elder pedestrian exhibited lower overall perceptual efficiency, lower fixation durations and higher cognitive loads. These results can provide certain references on improving the street crossing safety for the elderly pedestrian.

Efficiency of financial support and factors influencing strategic emerging industries: Based on an empirical analysis of listed companies in China

This paper analyzes the characteristics and influence mechanisms of financial support for China’s strategic emerging industries. Using a sample of 356 listed companies across nine major industries, we conduct an in-depth analysis of the efficiency of financial support and its influencing factors. In addition, this paper analyzes the influence mechanism of financial support for strategic emerging industries based on the relevant theory of financial support for industry development. It clarifies the internal and external influencing factors. Based on the theoretical analysis, a two-stage empirical investigation was conducted: The data of 356 listed companies in strategic emerging industries from 2010 to 2022 were selected as a sample, and the data envelopment analysis (DEA) method was applied to measure efficiency. The influencing factors were then analyzed using a Tobit regression and an intermediate effects test.

Analysis of The Efficiency of Public Expenditure on Education in Elementary Education in The State of Alagoas

Objective: This article analyzes the efficiency of public spending on education in the municipal public network in elementary education, in all cities in Alagoas, using the data envelopment analysis method, DEA. Theoretical Framework: The present work used the variable return to scale (BCC) model, since we would be dealing with municipalities with varied realities. There are two basic ways for a unit that is inefficient to become efficient. The first would be to reduce resources (inputs) and keep products constant, which would be an input-oriented orientation; the second would be doing the opposite, increasing the result (products) from the same amount of inputs, an orientation focused on outputs. Method: The data envelopment analysis method - DEA is used to estimate efficiency with traditional inputs such as school infrastructure, capital, labor and municipal wealth. As output, the Portuguese and mathematics grades in the 9th grade, in the Saeb 2019 test, are considered, multiplied by the students enrolled in this year of education; as well as the inverse of per capita expenditure on elementary education. Results and Discussion: It was concluded that most of the benchmarkings are represented by municipalities with smaller inhabitants, indicating that the population increase in municipalities increases the demand for education. Research Implications: Thus, based on technical efficiency analyses, public policies can be proposed that mitigate the deficiencies presented in elementary education. Originality/Value: This study contributes to the literature by estimating the efficiency of municipalities in terms of public spending on education and the efficiency results are the grades of public school students. The research introduces a new output to measure efficiency, and points to new evidence for public educational policies.

Integrating the water-energy-food nexus and LCA + DEA methodology for sustainable fisheries management: A case study of Cantabrian fishing fleets

The fishing sector constitutes an important source of economic revenue in northern Spain. In this context, various research studies have focused on the application of the five-step Life Cycle Assessment (LCA) and Data Envelopment Analysis (DEA) methodology to quantify environmental impacts of fishing systems. However, some of them have used environmental indicators that focus on individual environmental issues, hindering the goal of achieving integrated resource management. Therefore, in this study, the Water-Energy-Food (WEF) Nexus is employed as an integrative perspective that considers the synergies and trade-offs between carbon footprint, energy requirements, and water demand.The main objective of this study is to evaluate the operational efficiency and environmental impacts of Cantabrian fishing fleets. To this end, the combined use of LCA and DEA, along with the WEF Nexus, was applied to the Cantabrian purse seine fleet. DEA matrices were generated using the LCA-derived WEF nexus values as inputs to calculate efficiency scores for each vessel. Subsequently, based on the efficiency projections provided by the DEA model, a new impact assessment was performed to understand the eco-efficiency and potential environmental benefits of operating at higher levels of efficiency within this fleet.The average efficiency of the fleet was above 60 %. Inefficient units demonstrated a greater potential to reduce their environmental impacts (up to 65 %) by operating according to efficiency projections. Furthermore, the results revealed a strong dependence of environmental impacts on one of the operational inputs, i.e., fuel consumption. These findings highlight the significance of embracing holistic approaches that combine technical, economic, and social factors to achieve a sustainable balance in fisheries systems. In this regard, the five-step LCA + DEA method applied in conjunction with the WEF Nexus emerged as a suitable tool for measuring operational and environmental objectives.

Comparative Analysis of the Level of Financial Efficiency in the National Construction Services Industry Before and After the Implementation of PSAK 72 with a Two-Stage Data Envelopment Analysis Approach

This study analyzes the financial efficiency of Indonesia's national construction services industry before and after the implementation of PSAK 72 using the Data Envelopment Analysis (DEA) method. It aims to address the poor performance of contractor companies, which have negative operating cash flows and high Debt to Equity Ratios (DER). Input variables include Net Fixed Assets, Operating Expenses, and Total Employees, while output variables are Revenue and Profit Before Tax. Efficiency scores range from 0 to 1, with scores close to 1 indicating high efficiency. Prior to PSAK 72, PP Presisi Tbk and Wijaya Karya Bangunan Gedung Tbk were the most efficient companies, consistently achieving perfect efficiency scores. Total Bangun Persada Tbk was the least efficient. After PSAK 72, Bukaka Teknik Utama Tbk reached maximum efficiency in 2021, while Brantas Abipraya (Persero) was the least efficient in 2020. A Kolmogorov-Smirnov normality test showed the data was not normally distributed, leading to a non-parametric Wilcoxon signed rank test. The test indicated a significant difference in financial efficiency before and after PSAK 72, with a p-value of 0.04. This suggests a notable impact of PSAK 72 on the efficiency of construction companies.

The impact of border reorganization within cities on misallocation: Empirical evidence from firm-level data

The government of China merged or disintegrated several municipal districts on a large scale during 2000s. Employing a difference-in-difference approach and the benchmarking data envelopment analysis method, we show that border reorganization within cities significantly improves enterprise resource allocation efficiency. The primary mechanism is that modifying internal city boundaries enables geographically clustered enterprises to achieve agglomeration and specialization within administrative units and help mitigate market segmentation. This implies that borders within cities are important and enable use of border reorganizations as an effective tool in optimizing the quality of urban development.

A Hybrid Data Envelopment Analysis–Random Forest Methodology for Evaluating Green Innovation Efficiency in an Asymmetric Environment

The accurate evaluation of green innovation efficiency is a critical prerequisite for enterprises to achieve sustainable development goals and improve environmental performance and economic efficiency. This paper evaluates the green innovation efficiency of 72 new-energy enterprises by using a hybrid method of Data Envelopment Analysis (DEA) and a random forest model. The non-parametric DEA model is combined with the parametric SFA model to analyze the real green innovation efficiency on the basis of removing environmental factors and random factors. Then, the random forest model based on a nonlinear relationship is used to evaluate factors impacting green innovation efficiency. This paper proposes a comprehensive evaluation method designed to assess the green innovation efficiency of new-energy enterprises. By applying this method, companies can gain a comprehensive understanding of the current performance in green innovation, facilitating informed decision-making and accelerating sustainable development.

Principles and Optimization of China’s Unconventional Water Management: From a Brand-New Perspective of Responsibility Allocation

Unconventional water includes reclaimed water, harvested rainwater, desalinated seawater, and mine water. Unconventional water use is considered more of a “mandatory responsibility” in China. The initial allocation of unconventional water emphasizes quantity-centered responsibility allocation while the minimum utilization reflects this responsibility. The unconventional water use responsibility (UWUR) should be tailored to the characteristics of each area, moving away from a ‘more is better’ mindset. However, there is a large research gap in this field. This paper first presented six fundamental principles for unconventional water allocation. Ensuring fairness in allocation involves aligning the allocated amount with urban water usage characteristics. Hence, based on four key features, this paper integrated various socioeconomic and environmental factors to build an initial allocation model. To enhance efficiency, an optimal allocation model was constructed using the zero-sum gains–data envelopment analysis (ZSG-DEA) method. The models were then applied to Jiangsu Province, China, to verify their applicability. The results showed that the projected minimum UWUR allocation (unit: 100 million m3) for each city in 2025 is 1.482 (Nanjing), 1.501 (Wuxi), 0.919 (Xuzhou), 1.029 (Changzhou), 2.977 (Suzhou), 1.497 (Nantong), 0.818 (Lianyungang), 0.766 (Huai’an), 0.875 (Yancheng), 0.920 (Yangzhou), 0.790 (Zhenjiang), 0.858 (Taizhou), and 0.766 (Suqian). The rational and feasible results indicated that the allocation framework proposed in this paper has a certain practicability. Lastly, this paper considered the differences in unconventional water utilization conditions across 13 cities and proposed corresponding measures to improve the utilization. This paper represents a tentative exploration of unconventional water allocation in China and offers theoretical and practical insights for policy-makers to improve territorial spatial planning and sustainable water management.

Rice Supply Chain Performance Measurement Model Using Supply Chain Operational Reference and Data Envelopment Analysis Methods at PT XYZ

During the covid-19 pandemic, consumer demand for product quality on production accuracy and product availability at PT XYZ has increased. Because demand from consumers is fluctuating but the company cannot meet this demand. One way to maximize supply chain performance assessment is to evaluate the performance measurement of supply chain management using the SCOR and DEA methods and assisted by LINDO 6.1 software. The results of the research, risk identification carried out using the SCOR method with five activities, namely plan, source, make, deliver, and return, obtained 22 risks that occur in the company's supply chain, each of which is divided into: 4 risks that occur in the plan activity, 9 risks that occur in the source activity, 4 risks that occur in the make activity, 3 risks that occur in the deliver activity, and 2 risks that occur in the return activity. And from data processing with the DEA method shows that the rice product that is the target of improvement is FSN Setra Wangi 5 kg (FPW017) obtained 0.8348271 or < 1 with the variable that is the target of improvement is plan. Further research is recommended to be developed by adding benchmarking so that the application of the SCOR model can be carried out more completely. Then DEA calculations with more specific parameters so as to produce better data on each supply chain process.

Efficiency of Professional Polish Volleyball Clubs PlusLiga, Poland: Data Envelopment Analysis Approach

The aim of the article is to assess the degree of variation in the efficiency of professional men’s volleyball clubs playing matches at the highest level of competition in Poland PlusLiga in the 2020/2021 season. The non-parametric Data Envelopment Analysis (DEA) method was used to measure efficiency. The research is supported by the fact that the literature evaluates the efficiency of mainly football clubs. Therefor, the research extends the efficiency analysis to include volleyball clubs on the example of Poland, where in recent times both clubs and the national team have been highly successful on the world stage. The results of the research indicate that the efficiency of PlusLiga clubs varies. More than half of the (inefficient) clubs have too high expenses (operating costs) in relation to the actual financial and sporting results. The study shows that the technology of efficient clubs is mainly based on generating significantly higher revenues than operating costs. This allows efficient clubs to convert expenses into results more efficiently than inefficient clubs. Inefficiencies have been observed mainly in clubs where local governments are the majority shareholder. They generate negative financial results and use budget funds from their owners to cover losses and maintain economic stability. They operate under soft budget constraints and are favoured by local governments to prevent their bankruptcy. By identifying differences in efficiency using established benchmarking coefficients, the optimal amount of expenditure for inefficient clubs was determined and what measures should be taken to improve their efficiency.