DEA Technique Research Articles

Retraction Note: Does financial institutions assure financial support in a digital economy for energy transition? Empirical evidences from Markov chain and DEA technique.

Retraction Note: Does financial institutions assure financial support in a digital economy for energy transition? Empirical evidences from Markov chain and DEA technique.

Analyzing commercial grape farm efficiency in Armavir region (Armenia) by using two-stage empirical approach

The purpose of this paper is to provide an empirical assessment of the economic efficiency of grape-producing farms in Armenia. Upon reviewing various field-related studies the frontier analysis was singled out as a methodological base of this study. More specifically two-stage empirical analysis was performed, which includes the measurement of efficiency levels of grape farms by implementing the DEA technique and then assessing the determinants of obtained efficiency scores by performing Tobit modeling. To obtain necessary data, 365 grape farms from the Armavir region were surveyed. The main findings of this paper suggest that the average efficiency score for grape farms is 0.72, and there is room for improvement in the economic performance of farms with 28%. The main determinants of farm efficiency were cultivated grape varieties, farm size, and selling prices of grapes. The obtained results mainly support the findings of similar studies carried out for various viticulture regions across the world. This study provides some methodology bases for further expansion of similar studies both in terms of including the other Armenian viticulture regions and different years to explore the changes in the efficiency of grape farms over time. This article provides a base of knowledge for policymakers, scholars, researchers, investors, and credit companies for their decision-making processes and other purposes.

Measuring performance of farmer producer organisations using data envelopment analysis

PurposeFarmers producer organisations (FPOs) play the most crucial role in the agriculture supply chain system, aiming to redress the balance between farming and marketing activities of agricultural produce. The purpose of this study is to assess the performance of FPOs using data envelopment analysis (usually referred to as DEA) on 34 FPO units selected from the state of Rajasthan.Design/methodology/approachOne of the most commonly used techniques to examine business performance is the application of DEA. The application of DEA requires the selection of inputs and outputs. This study takes three inputs and three outputs based on the insights drawn from the field survey. While the input variables consist of total assets, paid-up capital and the number of economic activities, the three output variables are turnover, net profit and number of members benefitted. Broadly, these variables encapsulate the operational performance of the business units.FindingsThis study’s findings reveal that the estimated relative efficiency score of the input-oriented CCR (Charnes, Cooper, and Rhodes) model ranges from 0.06 to 1. Interestingly, only one FPO has reported a relative efficiency (RE) score of one, whereas the remaining FPOs fall below the efficiency frontier. However, 15 FPOs report an RE score of one in the output-oriented CCR approach. Considering the estimates obtained in the input- and output-oriented BCC (Banker, Charnes and Cooper) models, this study found that about 20% of the FPOs report an efficiency score greater than 0.80. Moreover, three FPOs are on the frontier line. An examination of the scale efficiency score in the input-oriented model, 45% of the FPOs have an efficiency score greater than 0.80, whereas almost all FPOs achieve a scale efficiency score greater than 0.80 in the output-oriented model. Overall, the results imply that the FPOs should place greater emphasis on the efficient utilisation of the inputs to enhance the overall business performance and productivity.Research limitations/implicationsThe findings of this study provide vital insights into the specific inputs and outputs that determine the performance efficiency of FPOs and identify the potential areas for improving the existing inefficient FPOs.Originality/valueThis study contributes to the repository of the existing empirical studies in three distinct ways. First, the authors hardly found any previous studies that quantitatively assess the business performance of FPOs using the DEA technique. Second, the effort to identify the slacks associated with each input and output variable in input- and output-oriented models gives insights on improvable areas for inefficient FPOs. Third, the authors attempt to demystify the empirical obfuscations by highlighting the major challenges FPOs face in the state of Rajasthan.

Research on the mechanism of digital economy to enhance the innovation efficiency of high-tech industry in the context of big data

Abstract Investigating how the digital economy can improve the innovation efficiency of the high-tech industry in the context of big data. This study uses a three-stage DEA technique to measure the innovation efficiency of high-tech businesses. The index system is created by selecting innovation inputs and outputs and adjusting them with exogenous environmental factors. A thorough and organized method for evaluating digital economy indices has been developed, and weights are allocated to the indexes based on spatial autocorrelation. In the end, the Tobit model is utilized to investigate the impact of the digital economy’s growth on the innovation capacity of high-tech industries. The innovation efficiency of high-tech sectors is positively influenced by the digital economy index, increasing by 0.2102% for every 1% increase. The digital infrastructure regression coefficients for the eastern, central, and western areas are 0.00045, -0.0015, and 0.00076, respectively.

A fully Fermatean fuzzy multi-objective transportation model using an extended DEA technique

A fully Fermatean fuzzy multi-objective transportation model using an extended DEA technique

Does financial institutions assure financial support in a digital economy for energy transition? Empirical evidences from Markov chain and DEA technique.

Enhancing the energy transition of the Chinese economy toward digitalization gained high importance in realizing SDG-7 and SDG-17. For this, the role of modern financial institutions in China and their efficient financial support is highly needed. While the rise of the digital economy is a promising new trend, its potential impact on financial institutions and financial support is unproven. For this, this research intended to study how financial institutions assure financial support for China's energy transition toward digitalization. To attain this purpose, DEA analysis and Markov chain techniques are applied to the Chinese data from 2011 to 2021. The results estimated that the transition of the Chinese economy toward digitalization significantly depends upon the digital services of financial institutions and extended digital financial support. The extent of the digital energy transition in China can enhance economic sustainability. The role of Chinese financial institutions accounted for 29.86% of the total effect in transiting China's digital economy. In comparison, the part of digital financial services is found to be significant, with a score of 19.77%. The Markov chain estimates revealed that the digitalization of financial institutions is 86.1%, and financial support is 28.6% important for the digital energy transition of China. The Markov chain result caused a digital energy transition of 28.2% in China from 2011 to 2021. The findings highlighted that China still warrants more prudent and active efforts for financial and economic digitalization, for which the primary research also presents multiple policy recommendations.

An environmental, energy, and economic efficiency analysis for the energy market in European Union

AbstractEnergy and environmental issues have been high on agendas of European Union members since they are intertwined with efforts to mitigate climate change and expand the economy. We intend to analyze the energy and environmental efficiency of EU countries using enhanced data envelopment analysis techniques. First, our study investigates energy efficiencies using the bootstrap DEA technique, which addresses the problem of statistical noise. Further, we examine the environmental and eco‐innovation efficiency of EU countries by employing the two‐stage super‐slack‐based DEA technique, which is one of the most suitable approaches for modeling undesired output. According to the environmental efficiency findings, the Nordic countries are primarily more efficient whereas, in terms of eco‐innovation efficiency, Germany is ranked as the top‐performing country. In addition, substantial prospects for improvements exist in the efficiency of the EU countries We may conclude that this research will help policymakers in this area.

Analysis of the Path Optimization of the Sustainable Development of Coal-Energy Cities Based on TOPSIS Evaluation Model

At present, various contradictions in most coal-energy cities have become increasingly prominent, which has become a disharmonious factor restricting the optimization and upgrading of coal-energy cities. Since the turn of the century, taking effective improvement and protection measures and promoting the economic transformation of cities reliant on coal as an energy source has been the primary job of departments at all levels in order to secure the sustainable growth of cities. In this paper, the economic transformation and sustainable growth of coal-energy cities are included in the enhanced TOPSIS economic transformation evaluation model based on the proposed entropy weight. This study examines the industrialization of cities that rely on coal energy resources, assesses the industrial efficacy of coal energy using the DEA technique, and proposes a plan for the industrialization of cities that rely on coal energy resources. This paper summarizes the industrial transformation process of coal-energy cities and designs an evaluation method for the industrial economic transformation of coal-energy cities. This paper determines a set of evaluation index systems suitable for the economic transformation of coal-based energy cities; constructs an evaluation model for the economic transformation of improved TOPSIS coal-based energy cities based on entropy weight; and, finally, calculates and analyzes the industrial economic statistics of a city over the years. It is found that, at the economic structure level, the transformation score of driving forces increases from 0.606 to 0.871; at the level of social economic structures, the transition score of the pressure system increases from 0.476 to 0.779, and the transition score of the state system increases from 0.401 to 0.699; at the level of urban construction structures, the transformation score of the pressure system increases from 0.467 to 0.568; and at the level of comprehensive transformation structures, the transformation score affecting the system increases from 0.611 to 0.716. This shows that, in the process of transformation, the driving force of industrial and economic development in coal-energy-based cities is sufficient, while the pressure of social and economic transformation is great. In the process of transformation, we should strengthen infrastructure construction and protect the urban environment.

Efficiency and Productivity Analysis of the Indian Agriculture Sector Based on the Malmquist-DEA Technique

This article evaluated the agricultural performance of 31 states and union territories (UTs) in India from 2012 to 2017. The best agricultural productivity states and UTs in India were obtained using Malmquist based DEA technique and the efficiency score for each year was found using CCR model. The input parameter is taken as annual rainfall, total population, GDP, Workers, and net cultivated area, and the output parameter is taken as production of rice, wheat, coarse cereals, pulses, oil seeds, and sugarcane. The productivity of the states and UTs are compared, as well as the increase or decrease in productivity is calculated. Total productivity change was calculated using cumulative Malmquist index (CMI). As a result, Punjab, Rajasthan, Sikkim, and Uttar Pradesh are the most efficient states throughout the year, while Kerala and Goa are the least efficient. Maximum states and UTs advanced 61.25% in 2015-16, whereas maximum states and UTs declined 62.52% in 2012-13. The overall productivity change in Madhya Pradesh increases perfectly while Nagaland's is almost decreasing. Other factors that may have an influence on state and UTs agriculture productivity include capital investment and fertiliser use. Additional social and environmental performance criteria, such as contribution to local community development and harmful emission measurement, can be integrated as output criteria for sustainability performance analysis.

Examining the determinants of bank efficiency in transition: empirical evidence from Ghana

This paper measures and evaluates the relative pure technical efficiency and cost-efficiency of Ghanaian banks over the period 2008–2019 using a nonparametric DEA technique. The study also examines the factors that determines bank efficiency in Ghana using both static panel and dynamic panel regression estimators. The results show that the overall average bank efficiency (pure-technical and cost) levels in Ghana are relatively low compared to the benchmark “best-practice” efficiency level of 1. However, the results indicate that there are remarkable improvements in both the pure technical efficiency and cost-efficiency levels since the coming into effect of the new banking Act in 2016. Further, the study depicts bank size, GDP growth rate and inflation to be the most important factors that must be considered in the determination of bank efficiency in Ghana. Also, bank capitalization is depicted to have a significant impact on bank cost-efficiency. In contrast, the findings reveal that return on assets (ROA), liquidity and loan loss provision are, however, not important factors in the determination of both banks pure technical and cost-efficiency. Bank capital is further depicted to have insignificant impact in the determination of bank pure technical efficiency in Ghana.

Do green financing and industrial structure matter for green economic recovery? Fresh empirical insights from Vietnam

This study used a systematic empirical method, the DEA, to examine the effect of green finance on the industrial structure of Vietnam holistically to present the way forward for the improvement of green economic recovery. The empirical findings indicate that the effect of green finance on the industrial structure is 0.29, 0.37, and 1.98 on green economic recovery correspondingly. The green finance and the industrial structure present in Vietnam lead to significant economic benefits for the green economic recovery in the country as a whole. Additionally, we included other factors such as the urbanization, industrialization, and population growth to predict the green economic recovery better. The DEA technique was applied in the analysis, and the findings were robust. In addition, four hypothetical time-dependent cases showed that Vietnam’s anticipated green finance and industrial structure nexus for the year 2001 to 2019. Empirical forecast findings indicate that the percentage of industrial structure is declining, and as a consequence, green finance has risen by 11.9% on average during the period. Reductions in industrial structure will cause Vietnam’s green funding to decline significantly. Such findings thus proposed several policy implications for essential stakeholders.

Unified AHP-TOPSIS and DEA technique for the adoption and performance evaluation of green transportation alternatives in India

The use of electric vehicles can shift India towards sustainable transportation or eco-friendly transportation. EVs are different as compared to petrol vehicles on distinct properties. Electric vehicles have zero tail-pipe outflows, noise, and low running expense contrasted with the internal ignition engines. This paper adds to the existing information by undertaking a multi-criteria analysis for electric vehicles' ranking and performance measures based on the rating by two stakeholder groups, "electric vehicle dealers" and "electric vehicle users". In this paper, the criteria for selecting electric vehicles are identified from the literature and personal interview. This paper utilises the combination of analytical hierarchical processes, technique for order of preference by similarity to ideal solution, and data envelopment analysis techniques to rank the various types of electric vehicles and measuring the performance of 16 electric and hybrid electric cars that exist in India.

Unified AHP-TOPSIS and DEA technique for the adoption and performance evaluation of green transportation alternatives in India

Unified AHP-TOPSIS and DEA technique for the adoption and performance evaluation of green transportation alternatives in India

Predicting Banks' Financial Distress by Data Envelopment Analysis Model and CAMELS Indicators

Due to their inherent nature in the economy, banks have a fundamental and significant responsibility for capital formation. Therefore, evaluating their performance can help decision makers find the optimal solution and prevent financial distress. The purpose of this study is to evaluate the performance and forecast financial distress of banks listed on the Tehran Stock Exchange, based on CAMELS indicators and Data Envelopment Analysis model. First, using the data of 17 banks in the fiscal year 2018, 5 levels of determining the health of banks, in the form of differences between the performance of these banks in terms of capital adequacy, quality of assets, quality of management, Earning and liquidity and sensitivity to market risk, It was found. And the studied banks were divided into two groups: healthy and helpless, based on CAMELS indices. Then, according to the effects of financial distress on banks, financial distress was predicted by Data Envelopment Analysis model slacks-based on measure of efficiency (SBM) and with a different approach. The results show that 61% of the predictions were correct by DEA technique and 39% of them were incorrect. Also, the results of this study showed that CAMELS financial ratios can be a good assessor for banks' financial distress.

A novel fuzzy non-radial data envelopment analysis: An application in transportation

The slack-based measure (SBM) DEA model is a non-radial model used to calculate the relative efficiency, input, and output targets of the different decision-making units (DMUs) based on their best peers or efficient frontier. The conventional SBM DEA model used crisp inputs and outputs. But, it can be observed in real-life problems that sometimes the available data is in linguistic forms such as “few”, “many”, “small”, or missing data. The DEA technique is frontier based, and therefore, imprecise data may lead to untenable results. Fuzzy theory, which is already established to handle uncertain data, can overcome this problem. Furthermore, the sensitivity and stability analysis have been checked the robustness of fuzzy DEA models. In this study, sensitivity and stability analysis of the fuzzy SBM DEA has been performed. The lower and upper sensitive bounds for inputs and outputs variables have been obtained for both the inefficient and efficient DMUs to calculate the input and output targets. Finally, a real-life transportation problem for the validity of the study is presented for its depiction.

Indirect Effect on Port and Freight Railroad Relations: Some Empirical Evidence for Reciprocal Efficiency

To address the need for a better understanding of cooperation, coordination and competition among transportation modes identified by various research studies, this paper sets out to analyze port-railroad relations of cooperation and coordination in the Brazilian case and the possible existence of a cross-side effect between port and railroad efficiencies. To that end it tests returns to scale and efficiency discretionary factor hypotheses. DEA technique and the Malmquist index were used to compute efficiencies and their dynamics. There is a discrepancy between the port and railroad databases, so they are subjected to sensitivity tests and descriptive statistics treatment. The analyzed ports and railroads present temporal variances in efficiency requiring adjustment of the variable returns models. There are notable technological variations for both transportation modes and the econometric techniques used to assess the cross-relations after the efficiency’s measurement stage prove to be promising. The conclusion indicates the existence of a to-and-fro cross-side effect between railroads and ports.

About job market outcomes: Assessing the performance of Colombian higher education institutions

AbstractOne method for evaluating higher education performance is to conceptualize it as a production function represented as an input/output process. This paper proposes a performance evaluation of higher education institutions from the perspective of recent graduates taking as inputs students' cognitive abilities and tuition, and as outputs three we contend are relevant for recent graduates: starting salary, sectoral distinctiveness, and sectoral variety. Using a sample of recent Colombian higher‐education graduates, we apply the DEA technique to analyze efficiency at the institutional level in the formal labor market. Our results highlight the importance of focusing on the student as the protagonist of the educational process and contribute to the debate about the selection of relevant inputs and outputs when measuring institution's efficiency.

STUDY OF THE EFFICIENCY OF SPANISH AIRLINES: A NON-PARAMETRIC DATA ENVELOPMENT ANALYSIS

Spain is an eminently tourist country, which allows the creation of countless jobs and contributes greatly to GDP growth. Millions of people visit this country every year, and more than 80% do so through air transport. This paper studies whether the 13 Spanish airlines with the highest revenues in 2018 were efficient in that year, thus filling a gap in the tourism literature. For this purpose, the non-parametric DEA technique has been used, using as inputs the total number of workers in the company and the total number of seats available (airline capacity). Total revenue and number of passengers have been used as outputs. The results obtained show that all the airlines studied within the IAG group (Iberia, Vueling, Air Nostrum, Iberia Express) are efficient, in addition to the Canary Islands airlines (Binter Canarias, Canarias Airlines and Canary Fly) and Air Europa. Likewise, the reference airlines for the inefficient ones have been determined, which will have to reduce the number of workers or make changes in capacity in order to achieve greater income and be efficient.

The efficiency of Islamic Banks in the Southeast Asia (SEA) Region

The Islamic banking sector has become a crucial part of the global banking industry. Despite the Islamic banking industry’s encouraging growth in the Southeast Asia (SEA) region, prior studies mostly focused on Islamic banks’ efficiency in the individual country. To fill the literature gap, this study aims to measure the efficiency and productivity growth of Islamic banks in the SEA region. This study adopted the DEA technique and the Malmquist productivity index to evaluate 31 Islamic banks’ performance in SEA from 2014 to 2019. The results evidenced an improvement in efficiency and progress in productivity for the banks in the region. The findings documented better efficiency and gradual progress in productivity for Islamic banks in Indonesia, consistent efficiency for Malaysia, a significant improvement for Brunei; hence, both Thailand and the Philippines Islamic bank depicted a drop-in efficiency for 2019. The findings trigger bank managers to acknowledge the inefficiencies and their sources. Investors and policymakers may find the findings useful in observing the banks’ performance; thus, taking effective mechanism and policies to promote competent and sustainable SEA Islamic banks in the long run.

DATA ENVELOPMENT ANALYSIS (DEA) APPROACH FOR ASSESSING TECHNICAL, ECONOMIC AND SCALE EFFICIENCY OF BROILER FARMS

This study was surveyed and evaluated technical, economic and scale efficiency of broiler farms in Egypt using DEA technique. So as to accomplish the specified aim, stratified random sampling technique was utilized to gather information from 150 broiler farms. The results showed that mean technical efficiencies of broiler farms were 0.915 and 0.985 under constant returns to scale (CRS) and variable returns to scale (VRS) respectively, implying that on average the farms could reduce input utilization by 8.5% and 1.5% for production level of output to be technically efficient. Notably, 48.7% of the farms were estimated fully technical efficient under VRS-model. The mean allocative and economic efficiency of the farms were assessed as 0.941 and 0.918 respectively, with only 2% of the farms were fully allocative and economic efficient. Furthermore, the average scale efficiency was 0.929 with the majority of broiler farms (82%) were operating with increasing returns to scale. The estimated Tobit regression showed that farmer's age, education, experience, access to extension services, and level of training were the most significant variables contributing to the disparities in efficiency of broiler farms. Such results are useful for extension workers and policy makers so as to guide policies towards expanding efficiency.