Data Envelopment Analysis Method Research Articles

Competition and evaluation of two-stage systems with fixed-sum outputs

Fixed-sum outputs are widely found in fields and lead to fierce competition among individuals or organizations. While competition strategy and efficiency evaluation for single-stage or black-box systems with fixed-sum outputs are discussed, few concerns the network systems with fixed-sum outputs that prevail in practical production and should not be neglected. In this study we analyze the competition and evaluation of network systems with fixed-sum outputs. First, we propose a data envelopment analysis (DEA) method searching a competition equilibrium that all basic two-stage systems are relatively efficient, by simultaneous adjustment of their intermediate outputs and fixed-sum outputs simultaneously, rather than only adjusting fixed-sum outputs, then proposing models for evaluating system competition efficiency and intervals of stage efficiencies based on the equilibrium frontier. Second, we focus on the normal case in which systems’ intermediate outputs may be excessive or inadequate for the uncertain capacity of final outputs, which are determined by competition instead of personal preference in the condition of fixed-sum outputs. To balance the excess and shortage in achieving the competition equilibrium, a method that allows external transfer of intermediate outputs is developed. An illustrative example indicates that the competition equilibrium can be achieved with less adjustments in some situations, when intermediate outputs are allowed to be externally transferred.

Efficiency of Bank Aceh Syariah and Bank NTB Syariah After Conversion

This study aims to compare the efficiency levels of Islamic commercial banks using the Data Envelopment Analysis (DEA) and Hahslm Reflexivity Dynamics (HEFDYN) methods before and after the spin-off period from 2008 to 2021. The implementation of Law (UU) No. 21 of 2008 concerning Sharia banking requires conventional commercial banks (BUK) to separate their Sharia business units (UUS) and establish Sharia commercial banks (BUS) when the assets of the UUS reach at least 50% of the total assets of the parent bank or after 15 years from the enactment of the Law. This research adopts a quantitative approach and focuses on a case study of two converted banks, namely Bank Aceh Syariah and NTB Syariah. The research methodology involves employing the data envelopment analysis with the VRS approach and the Hahslm Reflexivity Dynamics (HEFDYN) method. Based on the results of the DEA analysis, Bank Aceh Syariah successfully achieved a perfect efficiency value after undergoing conversion, demonstrating effective resource utilization and optimal operational performance. Conversely, Bank NTB Syariah experienced a slight decline in efficiency values, primarily attributable to decreased income variables and financing output in 2019. The HEFDYN analysis also revealed that although Bank Aceh Syariah attained perfect efficiency post-conversion, there is still potential for improvement, particularly in terms of financing growth. Similarly, Bank NTB Syariah, despite the decrease in efficiency values, has the opportunity to enhance its financial performance through targeted improvement efforts. Keywords: efficiency, conversion, DEA, HEFDYN

A simulation-based DEA approach for multiple criterion decision-making problems with uncertain mixed-criteria values

In ex-ante decision scenarios, predicting criterion values accurately is difficult for decision makers (DMs). Inconsiderable work is normally required for measuring criteria by uncertain random values or ordinal values. However, in the classical data envelopment analysis (DEA) model, criterion values are the constants that limit the application of the classical DEA model in ex-ante decision scenarios. This paper presents a simulation-based DEA approach, which captures random and ordinal criterion values by a simple and direct simulation-based approach. The approach includes three steps. In the first step, Monte Carlo simulation methods are used to convert uncertain random values or ordinal values into cardinal data. In the second step, we use traditional DEA methods to compute the efficiency score of decision-making units (DMUs). In the third step, we ranked all DMUs by calculating the DEA-efficient acceptability of each DMU in multiple simulations and then selected the optimal DMU. The proposed approach is illustrated by experimental examples and a case study of a municipal wastewater treatment system.

How can open public data promote efficient and equitable green production? Evidence from eco-efficiency in China.

Nowadays, concurrent attention to economic development and ecological issues is becoming an important trend. In this paper, we measure the eco-efficiency of 285 Chinese cities from 2003 to 2019 using a non-radial directional distance function and the data envelopment analysis method, based on which we analyze the club convergence of cities' eco-efficiency using the logt test; we estimate the impact of open public data platforms on eco-efficiency and its convergence using a multi-period difference in difference model and panel-ordered logit model, respectively. We find that, first, open public data platforms improve cities' eco-efficiency by about 6.5%, and the impact mechanisms include scale efficiency, technical efficiency, and total factor productivity, or, at the micro level, increasing the economic agglomeration degree, boosting the amount of foreign investment used, and increasing green innovation level. Second, there are three convergence clubs of eco-efficiency in China's cities, whose average eco-efficiency trends are above, close to, and below average, respectively. Third, public data platforms significantly increase the probability of cities belonging to the convergence clubs of high and medium eco-efficiency (Clubs 1 and 2) and decrease the probability of belonging to the low one (Club 3). However, the mechanisms only include technical efficiency and total factor productivity, or the amount of foreign investment used and the green innovation level at the micro level.

Non-farm income and environmental efficiency of the farmers: Evidence from India

In the face of various agro-climatic shocks when agricultural income becomes highly volatile, farmers often undertake multiple jobholding and engage in non-farm activities for income smoothing. The earnings from these activities are often used to purchase productivity enhancing agricultural inputs. In this context, the impact of non-farm income on intensification of agricultural inputs and the consequent impact on over-all farm efficiency is well documented in the literature. However, with a rapid rise in usage of agricultural inputs with environmentally detrimental impact, very little is known about whether non-farm income has any impact on farmers’ environmental efficiency-ability to reduce the amount of polluting inputs to the largest extent possible without reducing the amount of agricultural production. Our study fills the gap in the literature by analysing the impact of non-farm income on environmental efficiency of the farmers. We first estimate the environmental efficiency scores adopting the non-parametric data envelopment analysis (DEA) method and using a household level panel data from Village Dynamics of South Asia project on Indian states for a span of five years (2010–2014). We then estimate the impact of non-farm income on environmental efficiency using Instrumental Variable Tobit Model. Our results show that average environmental efficiency of the Indian farmers was 46 % during the study period indicating the fact that a reduction in polluting agricultural inputs by 54 % was possible without compromising the level of farm production. We also find that for 1 % increase in non-farm income, environmental efficiency of farmers rises by around 4 %. This reflects the environment friendly behaviour of farmers as a channel through which non-farm activities affect usage of environmentally linked inputs. These results provide vital policy insights in terms of how non-farm activities could be integrated with policies related to farming, in order to ensure sustainable agricultural practices.

A novel improved FMEA method using data envelopment analysis method and 2-tuple fuzzy linguistic model

A novel improved FMEA method using data envelopment analysis method and 2-tuple fuzzy linguistic model

Operational efficiency in the presence of undesirable byproducts: an analysis of Indian banking sector under traditional and market-based banking framework

Purpose In the backdrop of an increase in market-based banking activities, this paper aims to study operational efficiency of Indian banking sector during 2009–2010 through 2017–2018 considering Capital Gain and Gain from Forex Market (as desirable outputs) and Slippage (as undesirable byproducts) simultaneously, along with Advances – a desirable output considered in the traditional banking performance assessment literature. This enables to have an assessment of performance (as captured by the measured efficiency scores) of Indian Banks following an alternative viewpoint about the banking activities. The authors also explain such efficiency scores in terms of bank-specific factors, banking industry competition scenario and interest rate channel. Design/methodology/approach Using data envelopment analysis (DEA) method, the authors estimate six alternatives but interlinked operational efficiency scores (TES) of the Indian domestic commercial banks. In the second stage, they explain such TES in terms of bank-specific factors, banking industry competition scenario and interest rate channel. Findings The authors observe that the private sector banks as a group outperform those under public ownership. Moreover, although the private sector banks could maintain somewhat consistency in their operational efficiency performance over the sample period, public sector banks clearly show a declining tendency. The second stage econometric estimation results show that the priority sector lending has a negative effect on efficiency. Interestingly, the authors get varying results for the relationship between maturity and efficiency score depending on banks’ strategies on stressed assets management. Furthermore, the analyses result that banks are not so efficient in managing relatively larger-volume loans. It is also observed that banks’ efficiency positively depends on the Credit-to-Deposit (CD) ratio. It is found that the overall operational efficiency of the banks to manage their credit risk portfolio improves with a reduction in the lending rate (LR). However, the interaction of lending activities and capital market shows that with the increase in LR, corporate borrowers may switch to capital market to explore for desired funds, which may induce the banking sector to investment in capital markets and create a positive market sentiment. Originality/value Literature, although scanty, is there dealing stressed assets of a bank as some undesirable byproducts of its operational and business activities. However, such literature mostly done within the traditional framework of banking business activities and modern market-based business activities are almost absent in the literature. The authors have done it in the present study.

Effectiveness of Public-Private Partnership Projects During the COVID-19 Pandemic

The purpose of the study is to assess the effectiveness of public-private partnership (PPP) projects during the COVID-19 pandemic, taking into account the specificities of the industry. The empirical research base included the main characteristics (contract price, federal district of the project, customer, general contractor, project start period, project start year, project deadlines, price reduction during project implementation, application security, contract security and type of activity) of 144 regional investment projects. The research methodology included mathematical modeling using the DEA (Data Envelopment Analysis) data convolution method, on the basis of which an efficiency index was assigned to each PPP project from 0 to 1. The study concluded that prior to the COVID-19 pandemic, regional investment projects received more funding; after the start of the COVID-19 pandemic, the implementation time of regional investment projects has increased, the contract value more often changes downwards during the project implementation; and the average support for a project application has increased. The efficiency of implementation of regional investment projects, calculated using the DEA method, was reduced. The results obtained will be useful to private investors and government authorities when implementing joint projects to improve their efficiency.

Aeronautical Infrastructure Optimization to Enhance the Strategic and Operational Business Performance of Small Airports

Airport business management literature commonly evaluates the performance of these organizations based on the number of passengers and cargo processed, aircraft movements, number of runways, number of employees, and passengers’ terminal dimension, among other factors concerning commercial aviation, commonly applied to large structures, with gaps being identified in the literature of small airports. The identification and analysis of the main factors that interfere with the performance of airport business, and the strategic and operational management of small public airports have been analyzed from 24 small Brazilian airports. The study employed the Data Envelopment Analysis method based on the Charnes, Cooper, and Rhodes model, as well as the Banker, Charnes, and Cooper model, adapted for Visual Basic Analysis. The main results demonstrate that infrastructural characteristics, such as runway width, pavement classification number, runway length, buldings' age, maximum take-off weight of the critical aircraft, passenger terminal size, and air cargo and passengers processed, show significant relevance to the operational performance of small airports. The main theoretical implications of the study are the definition of strategic and operational parameters that impact the performance of small airports, which can be used as a reference by air transport decision-makers.

Estimating the eco‐efficiency of urban waste services towards sustainable waste management

AbstractAssessing the eco‐efficiency of municipalities regarding the provision of solid waste services is a useful tool for improving its sustainability. However, robust, and reliable methods are needed to benchmark the performance of municipalities. Data envelopment analysis (DEA) methods typically used to assess the eco‐efficiency of municipal solid waste (MSW) service providers. However, the variables used in the eco‐efficiency assessment bear distinct weights for each individual unit, limiting thus interpretation. Therefore, benchmarking the performance of MSW service providers becomes challenging because different conditions are applied. Thus, this study uses a common set weights DEA (DEA‐CSW) model assess the eco‐efficiency of different municipalities in providing MSW services. Eco‐efficiency scores were estimated by integrating total costs, recycled waste and unsorted waste as input, desirable outputs and undesirable outputs, respectively. The empirical application of the model demonstrated that when using DEA‐CSW, only one municipality (out of 36) was eco‐efficient in managing MSW. The weightings for inputs and outputs were allocated based on the degree of satisfaction estimated for each municipality. Satisfaction ranged from 0.829 to 1.000 indicating that none of the municipalities were heavily penalized based on the eco‐efficiency scores estimation when allocating common weights. In conclusion, this study demonstrates that compared to traditional DEA models, the DEA‐CSW approach is more adequate at benchmarking the performance of municipalities regarding the provision of MSW services.

Determinants of Human Capital Development and Macroeconomic Freedoms: DEA Modelling

The purpose of the study is to identify countries with mechanisms to most effectively ensure that human capital losses do not become an obstacle to strengthening macroeconomic freedoms. The study is based on the hypothesis that a decrease in absence from work due to personal health problems, unemployment, and mortality leads to an increase in the level of six basic macroeconomic freedoms: business, labour, trade, investment, monetary, and financial freedoms. In this case, absence from work due to personal health problems, unemployment, and mortality serve as discouragers/inhibitors of human capital development, the growth of which reduces the chances of an employee obtaining the necessary knowledge and skills to effectively transform this employee’s labour into an economic asset. To generalise the scientific opinion on the studied issue, a bibliometric analysis of the relationship between each of these factors and the totality of all macroeconomic freedoms was carried out using the R Bibliometrix package in RStudio software. The basis of this analysis was formed by the databases of publications indexed by Scopus for 1937–2024, consisting of 1618, 1578, and 1517 literature sources for each factor-destimulator. This analysis allowed us to form clouds of the most used keywords and analyse the dynamics of their use, see how the relevant research areas and the keywords used have evolved, build a topic map of the research interface, etc. The information base of the study is the statistical data of Europa and the Heritage Foundation; the object is 30 European countries; the time horizon is 2021; the main method is the non-parametric method of Data Envelopment Analysis (CCR and BCC models); the software package is the rDEA and Benchmarking package in the R programming language. Frontier graphs were constructed that clearly show the efficiency frontier in the CCR and BCC orientations. Six iterations of DEA modelling were carried out, each using only one of the 6 indicators of macroeconomic freedom as an output and three indicators of human capital as inputs. The countries with the most effective national mechanisms to ensure that human capital losses do not become an obstacle to strengthening macroeconomic freedoms are Cyprus, Czech Republic, Iceland, Ireland, Malta, and Romania. These countries demonstrate “benchmark” efficiency in 6 cases out of 6 calculated. There is also a group of countries that have never been included in the list of “benchmark” countries: Austria, Belgium, Croatia, Estonia, France, Hungary, Greece, Italy, Lithuania, Latvia, Portugal, Serbia, Slovakia, and Spain. We have also identified countries that are “benchmark” not by all parameters, but only by certain ones: Bulgaria – only in terms of the impact of the studied human capital determinants on monetary freedom; Luxembourg – only on investment freedom and financial freedom; Poland – only on investment freedom.

Study on the Spatiotemporal Evolution of Urban Land Use Efficiency in the Beijing–Tianjin–Hebei Region

The Beijing–Tianjin–Hebei region (BTH) is one of the crucial areas for economic development in China. However, rapid urban expansion and industrial development in this region have severely impacted the surrounding ecological environment. The air quality, water, and soil resources face significant pressure. Due to the close relationship between land utilization, population, investment, and industry, effective land use is a key factor in the coordinated development of the region. Therefore, clarifying the patterns of urban land use change and revealing its influencing factors can provide important scientific evidence for the coordinated development of the BTH region. This study aims to improve urban land use efficiency (ULUE) in the BTH region. Firstly, based on the input and output data of land elements for the 13 cities in the BTH region, the Data Envelopment Analysis (DEA) method is used to quantify the ULUE of the BTH urban agglomeration and analyze the spatiotemporal characteristics of ULUE. Input indicators includes capital, labor, and land. Output indicators includes economy, society, and environment. The results show that the overall ULUE in the BTH region has increased, albeit with notable fluctuations. Between 2000 and 2010, ULUE rose swiftly across all cities except Beijing and Tianjin, where changes were minimal. Post-2010, cities exhibited varied trends: steady growth, slow growth, sustained growth, step-wise growth, and initial growth followed by decline. Spatially, before 2010, the BTH showed a “high in the northeast and low in the southwest” pattern, transitioning post-2010 to a smoother “core-periphery” pattern. Mid-epidemic, high ULUE values reverted to the core area, shifting southward post-epidemic. Secondly, panel data analysis is conducted to explore the factors influencing ULUE. The results indicate that fiscal balance, the level of openness, the level of digitalization, industrial structure, and the level of green development are significant factors affecting ULUE. Finally, strategies are proposed to improve ULUE in the BTH region, including national spatial planning, industrial layout, existing land use, infrastructure construction, optimization of local fiscal revenue, and improvement in the business environment, aiming to enhance ULUE and promote the coordinated development of industries in the BTH region.

An optimistic-pessimistic game cross-efficiency method based on a Gibbs entropy model for ranking decision making units

The game cross-efficiency method, a commonly utilized approach for ranking decision-making units in tie-breaking scenarios, is based on secondary goals. However, in certain data envelopment analysis ranking problems, the classical game cross-efficiency method may fail to differentiate all decision-making units effectively. To address this limitation, it is prudent to explore the development of a new method that can enhance the ranking performance of the classical game cross-efficiency approach. In this study, we propose a novel Gibbs entropy linear programming model that integrates both optimistic and pessimistic perspectives of the classical game cross-efficiency method for data envelopment analysis ranking problems. To validate the reliability and utility of our proposed method, we present three examples: the six nursing homes problem, numerical example 2, and an application involving twenty Thai provinces with cash crop data. The reliability of the proposed method is assessed using Spearman’s correlation coefficient (rs) on the numerical examples. The results demonstrate that the rs values for both the proposed method and the classical game crossefficiency method, specifically for the six nursing homes problem, numerical example 2, and the application involving twenty Thai provinces, are determined to be rs=0.998, 0.998, and 0.986 respectively.

Measuring the efficiency of health services financing in Algeria using the data envelopment analysis method (DEA) an applied study of a sample of hospital institutions in the Algerian East (2019-2020)

Measuring the efficiency of health services financing in Algeria using the data envelopment analysis method (DEA) an applied study of a sample of hospital institutions in the Algerian East (2019-2020)

A Novel Data-Envelopment Analysis Interval-Valued Fuzzy-Rough-Number Multi-Criteria Decision-Making (DEA-IFRN MCDM) Model for Determining the Efficiency of Road Sections Based on Headway Analysis

The capacity of transport infrastructure is one of the very important tasks in transport engineering, which depends mostly on the geometric characteristics of road and headway analysis. In this paper, we have considered 14 road sections and determined their efficiency based on headway analysis. We have developed a novel interval fuzzy-rough-number decision-making model consisting of DEA (data envelopment analysis), IFRN SWARA (interval-valued fuzzy-rough-number stepwise weight-assessment-ratio analysis), and IFRN WASPAS (interval-valued fuzzy-rough-number weighted-aggregate sum–product assessment) methods. The main contribution of this study is a new extension of WASPAS method with interval fuzzy rough numbers. Firstly, the DEA model was applied to determine the efficiency of 14 road sections according to seven input–output parameters. Seven out of the fourteen alternatives showed full efficiency and were implemented further in the model. After that, the IFRN SWARA method was used for the calculation of the final weights, while IFRN WASPAS was applied for ranking seven of the road sections. The results show that two sections are very similar and have almost equal efficiency, while the other results are very stable. According to the results obtained, the best-ranked is a measuring segment of the Ivanjska–Šargovac section, with a road gradient = −5.5%, which has low deviating values of headways according to the measurement classes from PC-PC to AT-PC, which shows balanced and continuous traffic flow. Finally, verification tests such as changing the criteria weights, comparative analysis, changing the λ parameter, and reverse rank analysis have been performed.

A Study on Risk and Return Analysis and Data Envelopment Analysis of Public and Private Sectors Banks: A Five -Year Study (2018-2022)

Risk and returns are like two faces of the same coin, if an investor wants to gain higher returns, he must also accept the fact that this would also increase the amount of risk involved. Most of the times, individual decision process is influenced by risk and return analysis. The study is focused on analysing the performance of those nationalized banks listed in the NSE with respect to return, risk and beta for the period 1st January 2017 to 31st December 2017. The term risk is a situation in which the possibility of the consequence can be predicted, but uncertainty is the situation where the possibility cannot be predicted. Risk and uncertainty are part and parcel of investment The possibility of risk is a loss for the investors. The methodology adopted includes analysis of the performance of banking sector considering Bank Nifty Index as benchmark. Risk and return of banking stocks as well as Data Envelopment analysis method is used for analysing the efficiency of banks. The entire study is based on secondary data collected from the NSE. The data collected was based on the monthly prices of the bank stocks listed in Bank Nifty. The reason for selecting monthly prices is to measure the shortterm variations in the banking stocks due to various other internal and external factors. The findings of the study revealed that if the investors are ready to take high risk for more returns, the investors are suggested to invest in stocks like Bank of India and Punjab National Bank in which risk and return are high. The investors who prefer low risk and return are suggested to invest in Axis Bank stock.

Evaluation and Innovation of Methods for Measuring the Development Level of Urban Digital Economy

With the continuous development of Internet technology, the digital economy has become a new engine of contemporary economic development. In particular, on March 12, 2021, China released the "14th Five Year Plan" and the Outline of Vision Goals for 2035, clearly proposing to "create new advantages of the digital economy". Based on this background, this article first analyzes and evaluates the mainstream methods for measuring the development level of the digital economy in China and foreign countries. It is found that the current measurement methods and indicator selection vary greatly, and the accuracy and credibility of the measurement are questionable. Therefore, this article proposes to use Data Envelopment Analysis (DEA) method to measure the level of digital economy development in Chinese cities, and elaborates on its rationality.

Measuring the Productivity of SDG-3 Output in OIC Countries

Sustainable Development Goal 3 (SDG 3) focuses on ensuring healthy lives and promoting well-being for all at all ages. It aims to address various aspects of health and well-being, with specific targets to achieve by 2030. This study aims to calculate the efficiency and productivity based on SDG-3 output, 'Good Health and Wellbeing' in 50 countries that are members of the OIC over an 8-year period, from 2010 to 2017. Efficiency measurement was conducted using the Data Envelopment Analysis (DEA) method. Meanwhile, to measure the productivity score, this study using Malmquist Productivity Index (MPI). The result shows that the average efficiency value of OIC countries as a whole is 0.54. The country with the highest efficient value is Brunei with an efficiency value of 0.998, and the lowest country with an efficiency value of 0.35 is Indonesia. On the other hand, the country that experienced the most increase in productivity was Turkey with a TFP value of 1.357 and the country that experienced the largest decrease in productivity was Cameroon with a TFP value of 0.746.

Assessment of The Efficiency of The Territorial Administrative Reorganization of The Parishes of The District of Braga

Purpose: The objective of this study was to identify whether the reorganization of parishes carried out in Portugal, in the District of Braga, in 2013, is the one that enhances the greatest efficiency gains. Theoretical framework: The study is based on the relationship between financial sustainability, efficiency, and territory, seeking the optimal dimension of the local power unit. Methodology: The study is based on the Data Envelopment Analysis method, using data from the parishes of the district of Braga in two moments, the year 2012 and the year 2015. For this year, a new territorial reorganization was also proposed and analysed. Results and Conclusions: The reform increased efficiency in 10 of the 14 municipalities. However, it was possible to observe that a reorganization that gives the parishes a larger size, that is, closer to the average seen in the European Union, would bring average efficiency gains in all municipalities. Thus, it is concluded that the reform of the parishes carried out in 2013 in the district of Braga is not the one that allows greater efficiency, since this can be enhanced if they benefit from a larger geographical scale. Research implications: The research contributes to the knowledge of the efficiency of territorial reforms, namely, regarding the impact of the dimension in this context, as well as to the evaluation of the public policy adopted, allowing the public decision-maker to make a sound and sustained decision. Originality/value: This study is original because it studies smaller units of local government, the parishes, on which research is very incipient, namely in Portugal.

An innovative environmental regulation tool for regional air pollution based on DEA-RFR

Environmental regulation tools are one of the conventional means for pollution control in various countries. For large-scale urbanization regions, reasonable pre-allocation of pollutant emission amount for each area is an effective regulation to improve air quality. Treating pollutant emission quota as a resource element, a comprehensive input-output model has been established based on Data Envelopment Analysis (DEA) method, to evaluate the rationality of pollutant emission allocation and provide adjustment scheme, thus developing an environmental regulation tool. The index system includes factors of economy, environment, energy consumption, demographic and land-use as input indicators, regional GDP and environmental air quality index as output indicators. The regulation tool is applied to the current air pollutant emission management in Henan Province, China. The results show that 7 cities need to further adjust the allocation scheme, among which, Anyang, Xinxiang, Nanyang and Shangqiu are suggested to reduce the emission allocation quotas; Puyang and Zhumadian are suggested to increase the emission allocation quotas; Pingdingshan shall seek optimization paths through collaborative improvement. Further, to verify the effectiveness of the tool, by joint using Random Forest Regression (RFR), a DEA efficiency reassessment is conducted on the obtained new allocation scheme of Nanyang City. The results show that the efficiency of the new allocation scheme has reached optimal. This study provides a practical and effective regulation tool for regional management of pollutant emission, to balance economic growth and environmental protection.