Two-stage Data Envelopment Analysis Model Research Articles

Efficiency of Public Spending in Solid Waste Management: Analyzing Distinct Aspects of How Municipalities Operate and Optimize Resources

This study aims to analyze the endogenous variables that influence the solid waste management in Brazil. Applying a two-stage data envelopment analysis model, the study encourages discussion on the management of municipal solid waste in developing countries. In addition, this research contributes to the evaluation of efficient public resources, analyzes the efficiency of public spending and distinct aspects regarding how municipalities operate and optimize resources. Results show that the coefficients provide strong evidence that efficiency is affected by the form of waste management and corroborates the literature that highlights this relationship. The results provide insight into the structure of the solid waste collection function, and that preliminarily provides the possibility of analyzing the benchmark identification.

Two-stage DEA models with fairness concern: Modelling and computational aspects

In a two-stage series system with two sub-stages connected, fairness concern between two sub-stages is critical. In order to evaluate system performance fairly and objectively, data envelopment analysis (DEA) has been widely applied for evaluating multi-input and multi-output two-stage series systems. Traditional two-stage evaluation DEA models ignore the behavioral factors between two sub-stages. This paper studies how one behavioral factor, fairness concern, impacts decision making unit (DMU) by proposing new utility-based two-stage DEA models to analyse the non-cooperative and cooperative modes. Two simple algorithms are proposed to solve our nonlinear models and one simple algorithm is proposed to determine the parameters of fairness concern. Further, theorems are proposed to better understand the impacts of fairness concern on DMUs. Finally, a numerical example and an application of fairness concern between sub-stages in non-life insurance companies are given to illustrate the proposed approach and to compare it in different scenarios, respectively. The results from two examples show that acknowledging fairness concern in two-stage system is imperative to achieve its best performance.

Evaluate the economic and environmental efficiency of land use from the perspective of decision-makers’ subjective preferences

Land resources are not only the spatial carriers of social and economic development, but also the carriers of environmental and ecological services. With the accelerated urbanization, the non-coordinated development of land resources and environmental protection will restrict economic growth and the benefits of land use changes. Moreover, the economic efficiency and environmental efficiency of land use largely depend on the value judgment of the decision makers on the future human environment. Therefore, it is extremely important to achieve a win–win outcome of land development and ecological protection. In this research, a new analysis framework for land use efficiency was proposed from the perspective of decision makers' different benefit preferences. This framework uses the unexpected output of environmental pollution as a bridge to build a two-stage data envelopment analysis (DEA) model to evaluate the economic efficiency, environmental efficiency and overall efficiency of land development, and weight parameters were constructed to express decision-makers' preferences. The model not only considers the objectivity of the scores of land use efficiency, but also guarantees the subjectivity of decision-makers in land use management. This is also the biggest difference between previous studies in this study. The specific conclusions are: (I) as decision makers tend to focus on economic benefits, economic efficiency first rises and then declines. It can be seen that ignoring the problem of environmental pollution will reduce economic efficiency. (II) Generally speaking, the efficiency of compact land development (0.883) in various counties and cities in Taiwan is greater than the efficiency of expanded land development (0.737). This research can provide guidance on the distribution of land resources and the development of land space on a macro-regional scale.

The policy effects of innovative city pilot on the dual efficiency of industry–university–research knowledge flow

The implementation of the innovative city pilot policy (ICPP) is conducive to promoting the urban industry–university–research collaborative innovation, but there is no clear answer to how industry–university–research knowledge flow is affected by the policy. Based on the knowledge flow process divided into the knowledge creation stage and knowledge transfer stage, this paper uses the two-stage Data Envelopment Analysis (DEA) model to measure the dual efficiency of urban industry–university–research knowledge creation and knowledge transfer. And the paper also adopts the spatial difference-in-difference (SDID) model to study the impact mechanism of ICPP on the knowledge flow dual efficiency. The results show that there are positive spatial spillover effect of the knowledge creation efficiency (KCE) and knowledge transfer efficiency (KTE). And the effects of ICPP on industry–university–research KCE and KTE are both manifested as the promoting impact. Furthermore, ICPP has a significantly positive impact on the urban innovation atmosphere (UIA), and UIA plays a partial mediating role in the impact mechanism of ICPP on KCE and complete mediating role in the relationship of ICPP and KTE.

Developing a linear stochastic two-stage data envelopment analysis model for evaluating sustainability of supply chains: a case study in welding industry

Developing a linear stochastic two-stage data envelopment analysis model for evaluating sustainability of supply chains: a case study in welding industry

Alternative Secondary Goals in Multiplicative Two-Stage Data Envelopment Analysis

Data envelopment analysis (DEA) is a nonparametric method for evaluating the relative efficiency of a set of decision-making units (DMUs) with multiple inputs and outputs. As an extension of the DEA, a multiplicative two-stage DEA model has been widely used to measure the efficiencies of two-stage systems, where the first stage uses inputs to produce the outputs, and the second stage then uses the first-stage outputs as inputs to generate its own outputs. The main deficiency of the multiplicative two-stage DEA model is that the decomposition of the overall efficiency may not be unique because of the presence of alternate optima. To remove the problem of the flexible decomposition, in this paper, we maximize the sum of the two-stage efficiencies and simultaneously maximize the two-stage efficiencies as secondary goals in the multiplicative two-stage DEA model to select the decomposition of the overall efficiency from the flexible decompositions, respectively. The proposed models are applied to evaluate the performance of 10 branches of China Construction Bank, and the results are compared with the results of the existing models.

Green technology innovation efficiency of energy-intensive industries in China from the perspective of shared resources: Dynamic change and improvement path

Energy-intensive industries are high-energy-consumption and high-pollution industries, and their green technology innovation efficiency deserves in-depth investigation. This paper explores the efficiency of green technology innovation and its combinatorial improvement path in energy-intensive industries from 2005-2015 with a two-stage data envelopment analysis model based on shared and additional input resources and fuzzy-set qualitative comparative analysis. The results indicate that (1) the overall efficiency of green technology innovation in energy-intensive industries as a whole showed a fluctuating upward trend from 2005 to 2015, benefiting from the improvement of technology R&D efficiency and achievement conversion efficiency; (2) there is high industry heterogeneity in the green technology innovation capacity of energy-intensive industries, and the difference in the average efficiency in green technology innovation between the industries with the strongest innovation strength and that with the weakest is as high as 0.615; (3) small-scale enterprises’ strategies should be based on foreign scientific research support or environmental regulations, supplemented by a small amount of industry-university-research cooperation. Large-scale enterprises’ strategies should be based on foreign scientific research support and industry-university-research cooperation, supplemented by appropriate environmental regulations and government investment. This study provides a reference for the formulation of green technology innovation development strategies for energy-intensive industries.

Innovation Efficiency Evaluation Based on a Two-Stage DEA Model With Shared-Input: A Case of Patent-Intensive Industry in China

The patent-intensive industries play a leading and exemplary role in innovation driven, it is crucial to research evaluation methods to draw their levels and difference of innovation efficiency. This article proposes a new definition method for the patent-intensive industry with the ratio of inventions in force and research and development (R&D) personnel's full-time equivalent, divides the innovation process into technology R&D stage and scientific & technological (S&T) achievement transformation stage. The basic work includes three aspects: selecting the two-stage data envelopment analysis model with shared-inputs as evaluation method by comparison with others; constructing evaluation index system by comprehensive analysis of previous researches and objective judgment; extracting evaluation data. It evaluates the innovation efficiency of patent-intensive industries, demonstrates the corresponding characteristics: 1) the overall level of innovation efficiency is not high; 2) the R&D capability is stronger than the transformation capability of S&T achievement; and 3) the industry with better overall innovation efficiency has better transformation capability. It also provides the targeted industrial policy suggestions by dividing the patent-intensive industries into four categories. The research result shows that the proposed method is suitable for the innovation efficiency evaluation for the patent-intensive industries, and its research framework could be applied to the evaluation of other industries.

A comprehensive analysis of China’s regional energy and environment efficiency from supply chain perspective

ABSTRACT With the rapid development of China’s economy, the problems of China’s energy shortage and environmental pollution have become increasingly prominent. However, few studies have evaluated energy and environment efficiency from the perspective of energy production and energy utilisation. From supply chain perspective, this paper uses a two-stage data envelopment analysis (DEA) model to measure the efficiency of China’s regional energy and environment by considering both energy production and utilisation systems. Specifically, the production in each region is regarded as a two-stage network structure. The first stage is the energy production system, and the second stage is the energy utilisation system. Then, an efficiency decomposition programme is proposed to obtain the highest subsystem efficiency. Our empirical study on 30 main province-level regions of Chinese mainland shows that most of these regions are inefficient in both stages of energy production and utilisation. The energy production system has a negative impact on overall efficiency. In addition, China’s three major areas have unbalanced development. The eastern has the highest efficiency, followed by the central, and then the western part. Our empirical results provide effective measures in improving energy and environment efficiency.

The Extent, Dynamics, and Potential Predictors of Technical Efficiency and Capacity Utilisation in Small-Scale Fisheries in Oman

This paper investigates the extent, dynamics, and factors influencing technical efficiency (TE) and capacity utilisation (CU) in small-scale fisheries (SSF) using a two-stage data envelopment analysis (DEA) approach covering the period 2010–2012. A considerable extent of boat-level technical inefficiency, capacity underutilisation and scale inefficiency were evident. On average, TE and CU levels under the constant returns to scale (CRS) and variable returns to scale (VRS) models declined over time. The TE and CU scores of 2010 remained unaltered with the addition of ‘fishing time’ as an input to the model. The proportion of boats with unitary scale efficiency (SE) decreased from 26 % in 2010 to 12 % in 2012. The underutilisation rates of the inputs ‘crew’ and ‘fishing time’ ranged from 15.5 % to 31.6 % and 15.8 % to 28.6 %, respectively. Among the species category, the extent of excess capacity was 70 % to 156 % and 47 % to 119 % under the CRS and VRS models, respectively. The second-stage DEA results indicated that the explanatory variables ‘fishing location’, ‘catch per unit of effort’ (CPUE), ‘fuel costs’ and ‘crew share’ significantly influenced CU under the CRS model. In contrast, the significant influence of subsidies and other operating costs were noted under the VRS model. For the TE case, ‘age’, ‘education’, ‘subsidy’ and ‘CPUE’ were found to be significant under the CRS and VRS models. Other significant variables were found in the study under CRS and VRS models. Finally, the results from the descriptive and empirical analysis under the two-stage DEA model are discussed together with policy implications.

A Two-Stage DEA Model to Evaluate the Technical Eco-Efficiency Indicator in the EU Countries.

This paper evaluates the evolution of eco-efficiency for the 27 European Union (EU) countries over the period 2008–2018, provided the traditional high concerns of the EU concerning the economic growth-environmental performance relationship. The EU has triggered several initiatives and regulations regarding environmental protection over the years, but as well the Sustainable Development Goals demand it. Under this setting, we conduct a two-stage analysis, which computes eco-efficiency scores in the first stage for each of the pairs EU 27-year, through the nonparametric method data envelopment analysis (DEA), considering the ratio GDP per capita and greenhouse gas emissions (GHG). In the second stage, scores are used as a dependent variable in the proposed fractional regression model (FRM), whose determinants considered were eight pollutants (three greenhouse gases and five atmospheric pollutants). CO2/area and N2O/area effects are negative and significant, improving the eco-efficiency of the EU 27 countries. When the efficient European countries are excluded from the estimations, the results evidence that CO2/area and CH4/area decrease the DEA score. The country with the lowest GHG emissions and pollutant gases was Ireland, being the country within the considered period that mostly reduced emissions, particularly SOx and PM10, increasing its score.

Designing an Intuitionistic Fuzzy Network Data Envelopment Analysis Model for Efficiency Evaluation of Decision-Making Units with Two-Stage Structures

Data envelopment analysis (DEA) is a powerful tool for evaluating the efficiency of decision-making units for ranking and comparison purposes and to differentiate efficient and inefficient units. Classic DEA models are ill-suited for the problems where decision-making units consist of multiple stages with intermediate products and those where inputs and outputs are imprecise or nondeterministic, which is not uncommon in the real world. This paper presents a new DEA model for evaluating the efficiency of decision-making units with two-stage structures and triangular intuitionistic fuzzy data. The paper first introduces two-stage DEA models, then explains how these models can be modified with intuitionistic fuzzy coefficients, and finally describes how arithmetic operators for intuitionistic fuzzy numbers can be used for a conversion into crisp two-stage structures. In the end, the proposed method is used to solve an illustrative numerical example.

Farm efficiency related to animal welfare performance and management of sheep farms in marginal areas of Central Italy: a two-stage DEA model

The development of specific actions to increase animal health and welfare is indicated as a strategy to improve the efficiency and sustainability of many livestock systems, including sheep farming. In this paper, efficiency measures are provided to confirm the hypothesis that farms that are higher-performing in terms of animal welfare and management are also more technically efficient. A two-stage Data Envelopment Analysis (DEA) approach was adopted with the following twofold objectives: 1) to evaluate the efficiency and super-efficiency of 76 meat-producing sheep farms situated in marginal lands in central Italy, through DEA and Super-DEA (S-DEA) models; and 2) to assess the influence of animal welfare and management indicators on technical efficiency values through the application of a Tobit regression model. An overall efficiency performance varying within a range of 0.44–1 was estimated, with an average value of 0.80, implying a potential increase of 20% in terms of output production from both management and scale improvements. The ‘pure’ technical inefficiency was found to contribute three times more than scale inefficiency in determining the overall technical inefficiency. Adopting a more extensive farming system and increasing replacement rate were found to affect negatively the efficiency scores. On the other hand, having less than 5% of animals with body condition score beyond acceptable limits, presence of access control structures, well managed lambing pens, and dedicated feed stocking areas resulted in a positive influence on efficiency. Improvements in animal welfare aspects did not appear to be farm-scale-dependent. Highlights DEA and Super-DEA models were applied to assess sheep farm technical efficiency in Central Italy. An overall potential 20% increase in output production was estimated. Animal welfare factors were found to significantly affect efficiency performance.

Optimal capital adequacy ratio: An investigation of Vietnamese commercial banks using two-stage DEA

Over the last years the Vietnamese banking system has been struggling to restructure, reform governance, consolidate financial statements and build up merge and acquisition, in line with international standards. The Bank for International Settlements (BIS) proposed BASEL III in 2010, whereby banks must increase their minimum Capital Adequacy Ratios (CAR) year by year with a goal of 10.5% by 2019. The objective of this paper is to address the questions: (1) what are the optimal CAR levels for Vietnamese Commercial Banks (2) whether the minimum required CARs stipulated in the Basel II and III are reasonable for Vietnam banking system? The data set consists of a sample of Vietnamese commercial banks over the six-year period from 2010 to 2015. The optimal CARs of banks are calculated using the nonparametric two-stage Data Envelopment Analysis (DEA) model, with two inputs: fixed assets, employee expense and two outputs: interest income, non-interest income. The findings indicate that 92.4% of the banks have the optimal CAR higher than the minimum ratio 10.5% defined in BASEL III. Moreover, 57.98% of the banks should raise their current level of CAR to reach their optimal ones. To conclude, this paper will provide a guideline for Vietnamese banks to decide their optimal CAR to reach the efficiency frontier.

Determinants of Productive Efficiency of Public Service: What Effect of the Interaction of Corruption Control and Average Wage?

This paper seeks to analyze the determinants of the civil service productive efficiency in West African Economic Monetary Union (WAEMU) countries over the period 2003-2017. Using the two-stage Data Envelopment Analysis (DEA) model, our results show that the average productive efficiency of the public services studied is 87.4%. This suggests that there is room for improvement in the level of output of the public services, all other things being equal. We also found that the average wage, the square of corruption control, and the interaction term between corruption control and the average wage have a positive effect on productive efficiency. These findings suggest that before getting improvement in the productive efficiency of public service in the WAEMU region, countries should reach a higher level of corruption control and a substantial level of the average wage.

A two-stage parallel network DEA model for analyzing the operational capability of container terminals

ABSTRACT This study proposes a systematical approach to evaluate the operational capability of container terminals and discusses the effect of resource usages on operational performances. Two inter-dependent processes (i.e. the loading-discharging (L&D) and the delivery-receiving (D&R) operational processes) with shared/non-shared resources and common/separate productions are examined and characterized as a two-stage parallel network. An evaluation model is developed upon the principles of data envelopment analysis (DEA) to assess the operational capability of the terminals. Using the real-world dataset of 9 container terminals at Port of Busan, comparative performance results are obtained for 5 years spanning across 2014–2018. The proposed model demonstrates a much stronger discriminative power compared to the traditional CCR model in its estimations of performance in the decision-making units (DMUs). It can also be inferred from the results that efficiency in operations is a key qualifier for container volume while the market aggressiveness lends a competitive edge and reinforces a positive outcome on the performance of a container terminal. The study further examines the influence of management directive on a terminal performance and confirms that alignment of management directive with the operational capability of L&D and D&R processes is important in maximizing terminal throughout.

Performance of China's rural supply chain finance: from the perspective of maximization of intermediate output

PurposeTo dilute the financial difficulties in agricultural production and operation, the Chinese government has actively explored and developed rural supply chain finance (RSCF) service systems. The purpose of this study is to evaluate and analyze the performance of RSCF systems in China.Design/methodology/approachTo evaluate the performance of RSCF systems in China, this study proposes a two-stage data envelopment analysis model. Compared with other models, the model proposed in this study considers not only the technical gap between RSCF systems but also the maximization of intermediate output to conform to the practice of RSCF.FindingsBased on the empirical analysis, this study draws the following four conclusions. First, the overall efficiency of China's RSCF systems is low, and there remains great potential for improvement. Second, the technology gap ratio index score and meta-frontier efficiency of RSCF systems in Central China are the lowest in all regions, indicating that the technical level of RSCF systems in Central China is the lowest. Third, the relationship between rural residents' disposable income and the efficiency of RSCF systems is U-shaped, and the efficiency of RSCF systems in the high-income group is far greater than that of other income groups. Finally, the main reason for the lack of efficiency in RSCF seems to lie in management and technology.Originality/valueThis study divides all RSCF systems into four types according to management potential and technical potential, and recommend corresponding improvement suggestions for different kinds of RSCF systems.

Shared and unsplittable performance links in network DEA

Data envelopment analysis (DEA) is a broadly used non-parametric technique for performance evaluation and data analytics. While conventional single-stage DEA models overlook the internal interactions of decision making units (DMUs), network DEA opens this black box to investigate the internal structure of DMUs. Practically, many network DEA models involve shared performance measures that are not easily divisible among individual components of a network. Based upon a two-stage network DEA model, the current study treats such performance measures as inseparable links, implying that no proportions are optimized and allocated to the two stages of the network. The shared and unsplittable links in the proposed two-stage DEA model manifest integrality while both ends of the link are maximized or minimized simultaneously, and this setting has not been modeled in any existing DEA studies. The shared and unsplittable links in our model can be considered intermediate measures, but they are different from the two existing types of dual-role intermediate measures, which are traditional intermediate measures and feedback measures. Our performance link is a new type of intermediate measure that is minimized or maximized in both stages of the network. The resulting network DEA model is highly non-linear. To address the non-linearity, a parametric linear model is adopted. The proposed approach is construed in four variants, and then illustrated using a set of 100 banks in the United States.

Research on the evaluation of comprehensive efficiency of technological innovation and eco-environment in China

To investigate the contribution of technology innovation to eco-environment, this paper sets up a comprehensive efficiency evaluation index system of technology innovation and eco-environment. A relational two-stage data envelopment analysis model with output orientation has been built to evaluate the comprehensive efficiency of technology innovation and eco-environment of 28 provinces of China for 2015. The efficiencies of two-sub-stages, technology innovation efficiency, and eco-environment efficiency have been evaluated and analyzed. The result shows that: first, the average of comprehensive efficiency of technology innovation and eco-environment is 0.1535, which indicates a low level. Second, the results of sub-stages show that the average value of technology innovation efficiency is higher than that of eco-environment efficiency. Third, the comprehensive efficiencies of technology innovation and eco-environment of 28 provinces are mostly influenced by their eco-environment efficiencies. Based on these results, corresponding countermeasures are suggested to improve the comprehensive efficiency of technology innovation and eco-environment of China.

Towards greener petrochemical production: Two-stage network data envelopment analysis in a fully fuzzy environment in the presence of undesirable outputs

Traditional Data Envelopment Analysis (DEA) models usually consider decision-making units (DMU) as black boxes that consume a set of inputs to produce a set of outputs and ignore the units’ internal structure. In literature, two-stage DEA models have been introduced and developed to deal with the inner workings of such DMUs; however, models in the extant literature can only be used to assess technologies with precise inputs and outputs. In this study we present an innovative two-stage DEA model for DMU evaluation in the presence of imprecise data, which are modeled using triangular fuzzy values in this study. We also innovate by including the treatment of undesirable outputs. We propose some alternative two-stage DEA network models with undesirable outputs in a full-fuzzy mode that are either directional or radial and are embedded within a multi-objective linear planning structure based on fuzzy triangular numbers. We also propose a method to solve fuzzy programming models in the presence of undesirable pollutant outputs from production processes such as greenhouse gas emissions, harmful effluents, among others. Our proposed model is then applied to a real case of 15 ammonia-manufacturing units in the Iranian petrochemical sector. The promising results that we obtained in our research and their implications for theory and practice are then presented and discussed.