Data Envelopment Analysis Methodology Research Articles

Investors' Decision-making Under Risk: Evidence from the Croatian Stock Market

Purpose: This article deals with the retail investors’ decision-making under risk, firstly addressing several theories of decision-making under risk. Following this theoretical framework, an analysis on investment strategies on the Croatian capital market has been conducted. Design/methodology/approach: In this paper a non-parametric Data Envelopment Analysis (DEA) methodology is used to estimate input-oriented efficiency (minimization of risk i.e. stock return volatility, standard deviation) in retrospect to monthly stock returns of 15 selected stocks (due to a liquidity criteria) and five stock indices on the Croatian stock market in the period from 2016 until 2021. Findings: Results show that just but a few stocks provide high efficiency levels on the Croatian stock exchange, while the general CROBEX stock index proves to be a viable investment option for retail investors whose financial knowledge, expertise and time are limited. Research limitations/implications: This study was conducted on a limited sample of 15 most liquid stocks and five stock indices on the Croatian stock market in the period from 2016 until 2021. Due to the limited number of liquid stocks through time, the shallowness and illiquidity of the Croatian stock market provides a major limitation of this study. Furthermore, the limited sample attained dictated the use of nonparametric static DEA methodology that is suboptimal. For future studies, it is recommended to internationally expand the sample and use dynamic nonparametric and parametric techniques in stock efficiency estimation. Originality/value: The main aim of the study was to provide a theoretical overview on the theories of decision-making under risk. These theories provide insight that investors (retail but institutional nonetheless) are more loss avoidant than return seeking (risk aversion) which in the end affects their optimal investment strategy. In addition, this study used DEA methodology in efficiency estimation of 15 stocks on the Zagreb Stock Exchange (ZSE). The results from this study suggest that for untrained and inexperienced retail investor the investment in the general stock index could be a viable investment strategy. This study builds upon several studies on investment strategies on the Croatian stock market by providing more insight on stock and stock indices returns and efficiency several years previously and during the COVID-19 pandemic. Future studies dealing with similar topics should expand to a multinational sample that would solve the two main limitations of this study. Therefore, by expanding the sample to neighbouring countries, and increasing the number of liquid stocks observed and the possibility of using dynamic nonparametric and stochastic models in efficiency estimation of stocks to determine adequate investment strategies.

Evaluation of the Allocation of Public Resources Destined to the Fight against COVID-19 in the Brazilian Regions Using Data Envelopment Analysis (DEA)

This work presents an exploratory analysis concerning the understand of which Brazilian states have proven efficient in combating the Covid-19 pandemic, based on the treasury provided to them by the federal government, along with the understand of the association between input and output variables. As mathematical modeling support, the Data Envelopment Analysis (DEA) methodology is used as aid in the exploratory analysis. In this scenario, the states were analyzing based on the data of the treasury provided in the portal transparency of the federal government as well as the data of contamination and deaths available in the site informing health also of the government. The results show that with the CCR model, seven states are efficient while eleven are exposed in the BCC model. After the reduction in the number of inputs and outputs, the BCC model showed a decrease in the number of efficient states, being seven the new number to demonstrate an increase in inefficiency aspects.

Comparative assessments of the effectiveness of health care and health saving institutions in Russian regions

The relevance of the study is related to the global controversy about the indicators of "impact on the determinants of health and reduction of health inequalities" proposed by the WHO European Committee in the framework of the policy "Health 2020". The aim of the work is to test the hypothesis that the level of development of formal and informal norms and rules, established in the spheres of health care and health saving and at their intersections, affects the quantitative and qualitative characteristics of health of an individual, groups of people, the population as a whole, and also significantly determines the regional differentiation of the analysed parameters. Based on the results of the evaluation of the effectiveness of the functioning of health care and health-saving institutions using the DEA (Data Envelopment Analysis) method, the assumption about the influence of the level of development of health care and health-saving institutions on the dynamics of preservation and accumulation of health capital of senior citizens was confirmed. The novelty of the study is the use of DEA methodology "at the input" - resource indicators characterising health care and health saving in the Russian Federation in the regional aspect, and at the output - subjective assessments of satisfaction of the elderly with the work of the analysed institutions. Proposals on transformations necessary to improve the effectiveness of health care and health-saving institutions as an important condition for reducing regional inequality in health for the elderly citizens are formulated.

Analyzing efficiency of decision-making units in data envelopment analysis

A variety of irrigation management systems are evaluated using Data Envelopment Analysis (DEA) to see which one is the most cost-effective, environmentally friendly, and socially responsible. Accordingly, an irrigation management project report serves as the basis for the comparison of different ranks in MCDM and DEA. There are DEA approaches termed CCR, BCC, and RCCR that use criterion weights integrated with the inclusion of assurance areas to increase the analysis' discriminating power and reach the ranking of strategies. The findings show that DEA is a good alternative or supplement to MCDM, and including management preferences into the DEA methodology yields comparable outcomes to MCDM procedures.

Analysis of the efficiency of banks in Serbia and Montenegro using the DEA method

The banking sector of a country plays a crucial role in the overall economy of a nation. The efficiency of banks is a critical factor in assessing their financial performance and competitiveness. The aim of this paper is to measure the relative efficiency of the commercial banks in Serbia and Montenegro by using the non-parametric methodology Data Envelopment Analysis (DEA). The efficiency of banks will be measured using DEA for two models with different input and output variables. The sample consists of banks from Serbia (21) and banks from Montenegro (11) for the period 2017-2022. According to the obtained results, there are four banks that are relatively efficient every year, two from Serbia and two from Montenegro (AIK banka and 3M banka according to the first model and Crnogorska komercijalna banka and Hipotekarna banka according to the second model). The findings from the paper are valuable for further use by regulators, policy makers and bank management who are expected to identify a sustainable business strategy in line with the company's capabilities.

Financial Inclusion in West African Economic and Monetary Union’s Economies: Performance Analysis Using Data Envelopment Analysis

A data envelopment analysis (DEA) has yet to be chosen to assess countries’ financial inclusion levels. We introduce an application of the DEA methodology to compute aggregate performance measures regarding the financial inclusion of economies. We specifically explore composite scores based on relative efficiency, super-efficiency, and cross-efficiency approaches. We implement the proposed procedure to study the financial inclusion in nations from the West African Economic and Monetary Union (WAEMU). We use the Union’s Central Bank’s financial inclusion data from 2010 to 2017. We obtain robust financial inclusion level measures, showing that overall, in the Union, there have been steady improvements during the study period, but with heterogenous behavior at the level of each economy. A benchmarking analysis allowed us to determine the countries with the best practices. For the remaining nations, we find their reference countries. Finally, we identified which financial service sectors drive the financial inclusion in each country from the optimal weights of the DEA model.

Analysis of the Productivity Dynamics of Electricity Distribution Regions in Ghana

Electrical power distribution is the most important division in the power supply chain. However, its sustainability in terms of efficiency is very important for the growth of every country. This main objective of the paper is to assess the productivity dynamics of this process using the data envelopment analysis (DEA) methodology to analyse the effectiveness of the electricity distribution regions (EDRs) over a period of 7 years. The paper adapts the biennial Malmquist productivity index by infusing it with the slacks-based measure (SBM) to assess the productivity dynamics of EDRs in Ghana. Productivity dynamics were assessed by decomposing the SBM-BMPI productivity scores into the efficiency, technology, and scale change. It was discovered that the productivity of EDRs in Ghana progressed by 16.23% per annum over the sample period. Productivity was driven mainly by technological change and not the efficiency changes and scale changes.

EFISIENSI PERBANKAN DI INDONESIA DENGAN METODE DATA ENVELOPMENT ANALYSIS (DEA) SEBAGAI PERTIMBANGAN KINERJA PERBANKAN

<p align="justify">To implement sound banking principles, the assessment of bank efficiency is very important. This is because efficiency is a picture of a bank's performance as well as a factor that must be considered by the bank to act rationally in minimizing the level of risk faced in dealing with its operational activities. This study aims to measure the relative efficiency of banks in Indonesia using the Data Envelopment Analysis (DEA) methodology based on the intermediation approach. The research samples are Mandiri, BRI, BNI, BCA, and BTN. DEA is a methodology with a non-parametric-deterministic approach that aims to determine the relative efficiency and managerial performance, based on empirical data by determining the input and output of a UPK (Decision Making Unit). The results showed that BNI was relatively inefficient during the study years. Bank Mandiri was efficient in 2013. BCA was relatively inefficient during the study years. BRI experienced perfect efficiency level in 2013. BTN experienced perfect efficiency level from year to year. Overall, the commercial banks that are widely referenced by other commercial banks are BRI in 2011, BTN, BNI, and Bank Mandiri in 2013. The summary of potential improvement shows that the combined sources of inefficiency in banks are revenue needs to be increased by 35.58% and credit needs to be increased by 31.83%. While deposits need to be reduced by 9.49%, total assets need to be reduced by 1.51%, and interest expenses reduced by 21.48%.</p><p><strong>Key words:</strong> Banking, Efficiency, DEA Methodology Approach.</p>

The Macroeconomic Implications of the Transition of the Forestry Industry towards Bioeconomy

In a global economic system where essential resources are limited, demand is increasing and environmental degradation is more pronounced, the only viable option to ensure sustainable development is to create an environmentally friendly and efficient economy in order to produce more economic value with the same or fewer resources. The aim of this paper is to provide insight into the macroeconomic implications determined by the transition to a forest bioeconomy, with a focus on the impact on the national gross value added. More specifically, this analysis assesses the relationship between the potential of the macroeconomic value creation on the forestry industry and the measures of progress on the transition towards sustainable forest management and long-term economic growth. The analysis refers to a period between 2013 and 2019, summing-up 133 observations, data that were reported by Eurostat for 23 European Union members. We propose a model that describes a construct of the potential of the value creation that can be generated by each country included in our sample, translated into an efficiency score determined using the Data Envelopment Analysis(DEA)methodology. The results highlighted that the evolution of economic, social, and environmental (ESG) context positively impacted the efficiency score. This positive evolution in time was mainly driven by the higher awareness of governments, companies, and people on the need for a transition to sustainable economic growth and sustainable forest management. Furthermore, this study highlights that the transition to sustainable economic growth implies negative changes to the cost structure of the economies, which lead to higher operational costs and lower gross value added. Moreover, our study provides more insight, from an econometric methodology perspective, regarding the synergy effect as determined by the transformation of business models in the forestry sector towards sustainable forest management.

Efficiency Assessment of General Insurers in Malaysia Through Data Envelopment Analysis

This study aims to get an overview about the efficiencies of the general insurance companies operating in Malaysia. Data Envelopment Analysis (DEA) approach is used to evaluate the management efficiency and profitability of general insurers either local or foreign insurance companies for the period 2015-2018. Indeed, a two-stage approach to data envelopment analysis (2S-DEA) methodology is used to decompose the typical two-stage operating process of general insurance undertakings in a single intermediate operation. Based on the result, the companies seen not very efficient from the past four years. In addition, the general insurance companies in Malaysia shows a declining trend in their efficiencies. However, in between local and foreign insurance companies, it seen that the foreign companies are more efficient than the local companies since it has the large range of efficient value. These findings would benefit consumers and Malaysia 's insurance societies such as insurers and policy makers

Evaluation of the Efficiency of Regional Airports Using Data Envelopment Analysis

Background: Small regional airports provide the necessary assistance to enable mobility in isolated areas where access is critical and costly due to poor road infrastructure and geographic constraints. Colombia’s air transportation industry has grown astonishingly quickly and dynamically over the past fifteen years. This period was coincident with the establishment and continued implementation of a public policy intended exclusively for the aviation industry and airports. However, there are currently no methods available to measure the efficiency of airports in Colombia, especially small regional airports. Methods: The research presented in this article aims to evaluate the technical efficiency of small regional airports in Colombia, using data envelopment analysis. This efficiency is achieved by considering the minimum infrastructure required to provide services and the administrative forms or properties that provide appropriate levels of this. Results: The study’s input and output data are identified, a non-parametric data envelopment analysis methodology is used, and the findings are assessed. Conclusions: The factors directly identified in the research affect the airport administration and, in the options, are available to help citizens transport optimally.

Planning feasible and efficient operational scenarios for a university hospital through multimethodology

The COVID-19 pandemic required managerial and structural changes inside hospitals to address new admission demands, frequently reducing their care capacity for other diseases. In this regard, this study aims to support the recovery of hospital productivity in the post-pandemic context. The major challenge will be to make use of all the resources the institution has obtained (equipment, beds, temporarily hired human resources) and to increase production to meet the existing repressed demand. To support evidence-based decision-making at a major university hospital in Rio de Janeiro, hospital managers and operations research analysts designed an approach based on multiple methodologies. Besides multimethodology, one important novelty of this study is the application of a productivity frontier function to future scenario planning through the quantitative DEA methodology. Concept maps were used to structure the problem and emphasize stakeholders’ perspectives. In sequence, data envelopment analysis (DEA) was applied, as it combines benchmarking best practices and assigns weights to inputs and outputs. To guarantee that the efficiency measurement considers all inputs and outputs before any inclusion of expert judgment, the scope was redirected to full dimensional efficient facet, if any, or to maximum efficient faces. The results indicate that production scenarios proposed by stakeholders based on the Ministry of Health parameters overestimate the viable production framework and that the scenario that maintains temporary human resource contracts is more compatible with quality in health provision, teaching, and research. These findings will serve as a basis for decision-making by the governmental agency that provided temporary contracts. The present methodology can be applied in different settings and scales.

The interplay between technological innovation, energy efficiency, and economic growth: Evidence from 30 European countries

It is assumed that technological progress plays a vital role in energy efficiency improvements when the effects of industrial restructuring, infrastructure, environmental challenges, and economic shocks seem more dubious. However, a limited number of studies have been conducted to examine the impact of technological innovation on countries’ energy efficiency levels. This study aims to explore the relationship between energy efficiency, technological innovation, and economic growth in 30 European countries by utilizing data from 2012 to 2020. To this end, a two-stage analysis is carried out. The first step involves estimating the total factor energy efficiency (TFEE) by the countries to illustrate the effects of energy parameters on economic growth and the environment, and technological innovation (TI) to estimate the innovation capability of each country by using data envelopment analysis (DEA) methodology. The second step includes a panel regression model to explore how technological innovation affects energy efficiency, considering the degree of government intervention, industrial structure, infrastructure, and economic openness.The results indicate that the bottom-15 countries, whose TFEE scores were the lowest, are mainly countries of Central and Eastern Europe. Regarding the countries’ technological capability, the results were similar, but the score was lower than the TFEE. Moreover, the regression analysis shows that a one percent increase in innovation activity contributes to an increase in energy efficiency by 0.27 percent. Hence, it confirms the notion of a positive impact of new technology on energy efficiency. AcknowledgmentsThe study is supported by the grant from the Research Based Innovation “SFI Marine Operation in Virtual Environment (SFI-MOVE)” (Project No. 237929) in Norway.

Resource use efficiency level of public organizations. The case of Spanish health systems

Objectives: This paper seeks to detect, in the Spanish health system, which health services are efficient, and which are not, as well as propose corrective measures that allow inefficient health services to achieve efficiency. Methods: This paper applies the Data Envelopment Analysis (DEA) methodology, which allows obtaining natural and managerial efficiencies, as well as deviations from inefficient units in relation to efficient ones and proposing corrective measures that imply only budgetary (natural) modifications or changes in the policies of resource management (management). Results: Through the efficiencies, or the lack of them, the health services of the 17 Spanish autonomous communities are classified into four groups: With high, medium-high, medium-low or low natural or managerial efficiency. Conclusions: The lack of natural efficiency can be corrected with a greater budgetary endowment and the lack of managerial efficiency with a budget cut and changes in resource management policies. This tendency contrary to the adjustments is precisely what gives this work of interest and novelty with respect to others that apply the DEA in different sectors such as those that study the impact on the environment of resource consumption. Another important aspect of this study is the possibility of applying it to other countries with similar political structures.

A novel inverse DEA-R model with application in hospital efficiency

The inverse Data Envelopment Analysis (DEA) method is primarily used to analyze the changing relationship between the inputs and outputs of production units while preserving efficiency levels. This paper aims to perform an efficiency and post-efficiency analysis of 130 public hospitals in Iran. However, we faced with some hospital data that are only available in form of ratios. This motivates us to develop a novel and proper inverse DEA methodology capable of dealing with such cases. We develop the theoretical foundation of the inverse DEA-R model as a post-efficiency analysis approach. Both input-oriented and output-oriented inverse models are developed. In the end, we apply the proposed models for efficiency assessment and moreover inverse analysis of 130 public hospitals in Iran.

The drivers of energy efficiency improvement among nine selected West African countries: A two-stage DEA methodology

There has been a general outcry globally to ensure sustainable environmental practices by minimizing CO2 while increasing economic growth. In general, most African countries have had the lowest energy efficiency levels over the past decades. This is because of higher inefficiency due to mismatches between efficiency inputs and outputs. Previous studies have only focused on measuring the energy efficiency of African countries without determining the drivers of such efficiency. Hence, the current study adopted the two-stage Data Envelopment Analysis (DEA) methodology to measure energy efficiency among nine selected West African states and their influencing factors. The focus of the first-stage DEA was to measure the energy efficiency among the nine selected countries using the Dynamic Slack Based Measure (SBM) DEA model with and without the inclusion of CO2 emissions and the Malmquist Productivity Index (MPI) to estimate the technology efficiency improvement. Panel data from 2007 to 2020 was used for the study. The study found that energy efficiency without the inclusion of CO2 emissions in West Africa has improved during the period ranging from 2007 to 2020. Of the nine countries involved in the study, four of them, including Ghana, Nigeria, Côte d'Ivoire and Senegal, had an efficiency level above 100% with an average economic growth of 6% during the sampled period of the study. The efficiency level increased with an 6% increase in economic growth and a reduction in CO2 emissions. The Tobit regression model was adopted in stage two to analyze the factors that may affect energy efficiency in West Africa. The study results revealed a significant and positive association between population and energy efficiency in West Africa. At the same time, gross national income and urbanization negatively influence West Africa's energy efficiency. The findings were in line with the results from the fixed effect estimates. The study concludes that despite the improvement in energy efficiency in West Africa, there is a need to further boost their efficiency by reducing carbon dioxide emissions and other harmful pollutants. According to the study, West African leaders should adapt global benchmarks of sustainable environmental practices for sustainable energy implementation for the sustainable energy sector.

Analysis of relative efficiency of vessels of passenger transportation in the Brazilian Amazon: an AHP-DEA approach

Waterway transport is of great importance for the population of the Amazon Region. It is responsible for moving, according to Agência Nacional de Transportes Aquaviários (Antaq, 2018), approximately 9.8 million passengers and 3.4 million tons of cargo distributed by state, interstate longitudinal transport interstate and crossing. However, despite the great importance, there are several blockages related to the conditions of the roads and vessels in certain routes. The study in question proposes the use of a mathematical tool to analyze vessels from the relative efficiency involving parameters of input and output for two analysis scenarios: Energy Efficiency Analysis and Modality Analysis, being analyzed variables such as power, consumption, total time of the trip, total distance of the line of action, passenger capacity and ticket price. For that, the data of 652 vessels used in the Amazon region registered in the Brazilian states (Pará, Amazonas, Amapá and Rondônia) were verified, and from these data, a sample space of 148 vessels from the same utilization level was selected. With these data, a model was developed using the Data Envelopment Analysis (DEA) methodology, with the aid of the DEA-Solver software. After the use of the solver, the relative efficiency indexes of each vessel were obtained, allowing to rank and measure the efficient and inefficient Decision Units (DMU'S). Lastly, analysis of the general characteristics of efficient vessels were made in order to stratify the parameters that may have transformed them into efficient DMU`s, making it possible to trace a profile of the type of vessel employed in each type of line, thus helping in decision making of new projects.

A comprehensive review of data envelopment analysis (DEA) methodology in port efficiency evaluation

A comprehensive review of data envelopment analysis (DEA) methodology in port efficiency evaluation

A sustainable lean production framework based on inverse DEA for mitigating gas flaring

The gas flaring process remains a significant contributor to climate change due to the release of greenhouse gases. Additionally, it denies oil-producing nations access to affordable energy sources. With climate change gaining momentum and in accordance with the global gas flaring reduction partnership (GGFR), oil and gas production managers must adopt an approach that can be both environmentally and economically beneficial. As such, this study proposes a novel application of the inverse data envelopment analysis (DEA) model for implementing lean production practices in the petroleum industry. Using inverse DEA methodology, a three-stage inverse problem involving selected oil-producing nations during the 2015 production year was solved. Stage one found that by incorporating lean practices, all the efficient producers were able to increase oil production by 50,000 barrels without increasing their current levels of flared gas. For the second stage, a reduction in gas flaring was imposed on the efficient producers to achieve the same production targets as stage one. Gas flaring reductions for Angola, Iraq, Libya, and Nigeria were computed to be 13.75%, 4.59%, 25.24%, and 54.93 %, respectively. A simple cycle gas turbine, such as the GT13E2, was used for all four nations to convert these reductions into gross power outputs of 300 MW, 150 MW, 450 MW, and 2250 MW, respectively, with Nigeria clearly benefiting the most. In the third stage, the concept of lean potential growth was integrated into an improved model to rank efficient oil producers. Saudi Arabia was found to be the most efficient producer, partly explaining why no reductions in gas flaring were obtainable for the nation in stage two. Based on our findings, we recommend the proposed models and new concepts for improving operational sustainability in the petroleum industry.

Social network analysis for cross‐evaluation in data envelopment analysis

AbstractAs one of the important extensions of data envelopment analysis (DEA) methodology, cross‐evaluation combines self‐evaluation and peer‐evaluation processes for each decision making unit (DMU) to effectively eliminate unrealistic weight schemes and differentiate all the units for ranking. Differing from previous research, which mainly pays attention to either secondary goals for generating weights for peer evaluation or aggregation of self and peer‐evaluation efficiencies, our study focuses on evaluating the relationships among all DMUs. If we view each unit as a node to be evaluated, then peer‐evaluation among pairs of DMUs forms a bidirectional network among all the DMUs. Based on this idea, we introduce a data‐driven tool combining social network analysis and cross‐evaluation to examine self‐evaluated and peer‐evaluated scores in the network. Using the hyperlink‐induced topic search algorithm, we develop the concepts of self‐evaluation and peer‐evaluation objectivity coefficients based on how well DMUs accept the analysis results. The rankings based on our self‐evaluation and peer‐evaluation scores adjusted with objectivity coefficients are shown to be consistent. Our study provides a novel perspective for cross‐evaluation and DEA research. An application case study illustrates our new method.