Impact assessment of construction waste policy intensity on environmental efficiency based on system generalized method of moments

With the acceleration of urbanization in recent years, China has witnessed large-scale construction across its provinces, generating massive amounts of construction waste that pose challenges to environmental protection and sustainable development. This study evaluated the impact of construction waste policy intensity on its environmental efficiency. Firstly, the content analysis method was used to analyze the construction waste policy text quantitatively. Second, this study constructed a slack-based measure (SBM) model based on data envelopment analysis (DEA), considering resource input and construction waste output to measure environmental efficiency. Finally, we built and tested an econometric model of how policies affect environmental efficiency using the system generalized method of moments (SYS-GMM). The findings indicate a non-linear U-shaped link between policy intensity and environmental efficiency. Among all five control variables, population density, urbanization level, and technological innovation enhance environmental efficiency, while economic development and highway density will lower it. This study advances the research on construction waste policies and offers some insights for the construction industry to pursue sustainable development.

Carbon emission efficiency evaluation of wastewater treatment plants: evidence from China

A scientific evaluation of the carbon emission efficiency is crucial for ensuring the sustainable development of wastewater treatment plants (WWTPs). In this paper, we applied a non-radial data envelopment analysis (DEA) model to calculate the carbon emission efficiency of 225 WWTPs located in China. The results showed that the average carbon emission efficiency of China's WWTPs was 0.59, indicating that the efficiencies of most samples still require improvement. The carbon emission efficiency of WWTPs from 2015 to 2017 decreased because of the decrease in technology efficiency. Among the influencing factors, different treating scales had positive impact on carbon emission efficiency improvement. WWTPs with anaerobic oxic process and the first-class A standard were likely to have higher carbon emission efficiency in the 225 WWTPs. By incorporating direct and indirect carbon emissions into WWTP efficiency evaluation, this study helped decision-makers and related water authorities to better understand the contribution of WWTPs to the aquatic and atmospheric environments.

Assessment of equity and efficiency of magnetic resonance imaging services in Henan Province, China

BACKGROUND

By evaluating equity and effectiveness, this study provides evidence-based knowledge for scientific decision-making and the optimization of magnetic resonance imaging (MRI) configuration and utilization at the provincial level.

METHODS

Using data from 2017, we applied a Gini coefficient to analyze the equity of MRI services in 11 sample cities in Henan province. An agglomeration degree was then applied to measure equity from the perspective of population and geography, and a data envelopment analysis was used to evaluate MRI efficiency.

RESULTS

The overall Gini coefficient of MRI allocation by population in the 11 sample cities is 0.117; however, equity varies considerably among the sample cities. The sample's comprehensive efficiency is only 0.732, indicating the overall ineffectiveness of provincial MRI utilization. The pure technical and scale efficiencies of four sample cities are below 1, indicating lower MRI effectiveness than the rest.

CONCLUSIONS

Although the overall equity of configuration at the provincial level is relatively good, equity varies at the municipal level. Our results demonstrate a low MRI utilization efficiency; accordingly, policymakers should dynamically adjust the policy based on equity and efficiency.

How has China's industrial eco-efficiency been improved? Evidence from multi-scale countrywide study

The process of industrialization often causes resource depletion and environmental pollution. To shed light on China's resource use and pollution trends in the context of the country's rapid industrial growth, this study analyzes the eco-efficiency of China's industry from 2000 to 2015. We quantify industrial eco-efficiency (IEE) for China and its provinces using data envelopment analysis (DEA) and analyze potential influencing factors at national and regional levels using Tobit regression. IEE in China and in most provinces shows a clear upward trend with some fluctuations, with national scores increasing from 0.394 to 0.704. There is strong regional disparity, with average IEE scores in eastern provinces (0.840) higher than those in central provinces (0.625), which are in turn higher than those in the northeast (0.537) and west (0.438). We next consider potential drivers. Economic development and foreign direct investment (FDI) are positively associated with IEE but appear to show diminishing returns. Environmental enforcement and market for technology are also positively associated with IEE, as expected. The impact of economic development, industrial sector structure, and investment in research and development (R&D) are modified by the stage of industrialization in each region. Targeted measures that can adjust industry structure, enhance environmental enforcement, attract FDI, and increase R&D investment may help further improve IEE in China.

Assessment of airline industry using a new double-frontier cross-efficiency method based on prospect theory

Cross-efficiency method (CEM) is a well-known technique based on data envelopment analysis that provides policymakers with a powerful tool to measure the efficiency of decision-making units. However, there are two main gaps in the traditional CEM. First, it neglects the subjective preferences of decision-makers (DMs), and therefore, cannot reflect the importance of self-evaluation compared to peer-evaluations. Second, it ignores the importance of anti-efficient frontier in the overall evaluation. The present study aims to incorporate the prospect theory into the double-frontier CEM to deal with these drawbacks while considering the preferences of DMs towards gains and losses. To address these drawbacks, this paper utilizes an aggregation method based on the prospect theory and consensus degree (APC) to reflect the subjective preferences of DMs. The second issue is also addressed by incorporating APC into the optimistic and pessimistic CEMs. Finally, the double-frontier CEM aggregated using APC (DAPC) is obtained by aggregating two viewpoints. As a real case study, DAPC is applied to evaluate the performance of 17 Iranian airlines based on three inputs and four outputs. The findings demonstrate that both viewpoints are influenced by DMs' preferences. The ranking results achieved for more than half of the airlines based on the two viewpoints are significantly different. The findings confirm that DAPC deals with these differences and leads to more comprehensive ranking results by considering both subjective viewpoints simultaneously. The results also show that to what extent DAPC efficiency for each airline is influenced by each viewpoint. In this regard, the efficiency of IRA is most influenced by the optimistic point of view (80.92%), and on the other hand, the efficiency of IRZ is most influenced by the pessimistic viewpoint (73.45%). KIS is the most efficient airline, followed by PYA. On the other hand, IRA is the least efficient airline, followed by IRC.

How to improve the future efficiency of Covid-19 treatment centers? A hybrid framework combining artificial neural network and congestion approach of data envelopment analysis

Covid-19 virus (severe acute respiratory syndrome coronavirus 2, SARS-CoV-2) threatens the health of human beings worldwide, imposing a concern for the world and prompting governments to control the contagion. Although vaccination is a proper tool to control the transmission, the efficient allocation of limited health-care resources to massive patients can improve the effectiveness of medical services. Relying on the Artificial Neural Network (ANN), the aim of this research is to enhance the future efficiency of Covid-19 treatment centers by forecasting their efficiency and providing benchmarks. To do this, we use the congestion approach of data envelopment analysis (DEA) based on the theory of economies of scale principles. In the traditional input-oriented DEA, inefficient decision-making units (DMUs) can become efficient merely by reducing the inputs. However, this may not always be true in real-world applications such as improving the efficiency of COVID-19 treatment centers (DMUs). Meaning that the treatment centers with less congested inputs (e.g., ventilators, test equipment, pulmonologists, and nurses, etc.) normally have higher mortality rates. For this reason, in this study, we take the congested inputs approach into account to provide proper benchmarks for the inefficient treatment centers. According to the congestion approach of DEA, an optimum increase in congested inputs can lead to a greater than a proportional increment in outputs. In other words, if more respiratory equipment, pulmonologists, patient rooms, nurses and beds, etc. are allocated to Covid-19 treatment centers, not only the number of deaths (undesirable outputs) are decreased, but also the number of recoveries (desirable outputs) are increased. Such an optimal rise in the congested inputs is determined in pairwise comparisons derived from the model. Accordingly, in this study, first, considering the congestion approach of DEA and historical data of five periods, we identify the initial efficiency of Iranian Covid-19 treatment centers. Then, by running ANN, we forecast the future inputs and outputs, the overall efficiency, and rank of the treatment centers. By doing this, the prospective efficient and inefficient DMUs are identified, and appropriate benchmarks are determined.

'Cyclic syndrome' of arrears and efficiency of Indian judiciary

One of the four pillars of democracy in India is the judiciary, which in the recent past has experienced the 'cyclic syndrome' of arrears. There are 3.5 crore cases pending in the Indian judicial system that has a bearing on contract enforcement. A burgeoning stream of literature has reported the role of the judiciary in economic growth and development. In the wake of a given potential economic multiplier of the judicial system, examining the factors affecting the performance of the judiciary should merit attention. The present study juxtaposes jurisprudence and production theory, not frequently examined in the same gust by employing Data Envelopment Analysis (DEA), Malmquist Productivity Index (MPI), Stochastic Frontier Analysis (SFA), and regression for High Courts and Subordinate Courts. Employing the dataset for the years 2014-19, we investigate the technical efficiency and productivity of the High Courts and their Subordinate Courts and examine the factors influencing the dissolved cases. Furthermore, we examine the impact of COVID-19 on the cases instituted and cases disposed of. To sum up, the paper, thus, touches upon two basic dimensions of justice for High Courts and Subordinate Courts in India: Timeliness in the disposal of cases and the proportionate use of the state's resources. The study confirms the role of judges, judicial staff, and demand for justice on the supply of justice. Shreds of evidence point toward the need to introduce a "cocktail-based" approach instead of a "one-size-fits-all".

Supplementary Information

The online version contains supplementary material available at 10.1007/s43546-022-00377-1.

Evaluation of technical efficiency of some rain-fed cereal and legume crops production in Syria: does crisis matter?

BACKGROUND

Syria is a developing country whose economy is still dominated by the agricultural sector. The agricultural sector is considered as the main source of food in Syria and a major source of employment and income generation. Food and agricultural policies in Syria focus heavily on achieving food security and improving its four pillars (availability, accessibility, stability and utilization). As a result, until 2011, a good progress has been attained in food availability. The food security situation deteriorated in Syria after 2011 crisis, with the number of people facing acute food insecurity rising from 7.9 million in 2020 to a staggering 12.4 million in 2021. This is the result of many shocks that the agricultural sector has been exposed to, such as the relative decrease in cultivated areas, high costs of production, reduced input availability including labour, prevailing violence, related damage to farm equipment, and abandoned land. In view of the changes that the agricultural sector has been exposed to in Syria as a result of the crisis, the study concerns measuring the technical efficiency of production of some rain-fed cereal and legume crops in Syria and comparing it in the pre and post-crisis period, which has started in 2011. A non-parametric (DEA) method is applied for measuring technical efficiency during the time period 2003-2010 (pre-crisis) and the period 2011-2018 (post-crisis) with censored regression (the tobit model) to investigate the determinants of technical efficiency. A t test is used to test the null hypothesis (H₀) that there was no difference in technical efficiency of the production of studied crops before and after the crisis in Syria and the alternative hypothesis (H_a) that there was a significant difference in technical efficiency.

RESULTS

The findings show low level of technical efficiency in the post-crisis period. The results verified differences in the technical efficiency of pre- and post-crisis period. The use of censored regression with dummy for crisis has shown negative and significant effect on technical efficiency of each of the durum wheat and lentil crops, while it had no significant effect on the other studied crops.

CONCLUSIONS

This study can provide important information to the government to pursue a new policy for recovery and improving the agricultural production and productivity. There is an urgent need to adopt new policies that focus on providing production requirements in the form of low-interest loans, sustainable use of resources, providing support for the marketing process, and focusing on the export markets of some study crops (chickpeas and lentils). Government should improve agricultural extension services for farmers and encouraging them to adopt new technologies.

The impact of human resources for health on the health outcomes of Chinese people

Human resources for health (HRH) is a cornerstone in the medical system. This paper combined data envelopment analysis (DEA) with Tobit regression analysis to evaluate the efficiency of health care services in China over the years between 2007 and 2019. Efficiency was first estimated by using DEA with the choice of inputs and outputs being specific to health care services and residents' health status. Malmquist index model was selected for estimating the changes in total factor productivity of provinces and exploring whether their performance had improved over the years. Tobit regression model was then employed in which the efficiency score obtained from the DEA computations used as the dependent variable, and HRH was chosen as the independent variables. The results showed that all kinds of health personnel had a significantly positive impact on the efficiency, and more importantly, pharmacists played a critical role in affecting both the provincial and national efficiency. Therefore, the health sector should pay more attention to optimizing allocation of HRH and focusing on professional training of clinical pharmacists.

An eco-environmental efficiency analysis of Malaysia sewage treatment plants: an incorporated window-based data envelopment analysis and ordinary least square regression

Most human activities that use water produced sewage. As urbanization grows, the overall demand for water grows. Correspondingly, the amount of produced sewage and pollution-induced water shortage is continuously increasing worldwide. Ensuring there are sufficient and safe water supplies for everyone is becoming increasingly challenging. Sewage treatment is an essential prerequisite for water reclamation and reuse. Sewage treatment plants' (STPs) performance in terms of economic and environmental perspective is known as a critical indicator for this purpose. Here, the window-based data envelopment analysis model was applied to dynamically assess the relative annual efficiency of STPs under different window widths. A total of five STPs across Malaysia were analyzed during 2015-2019. The labor cost, utility cost, operation cost, chemical consumption cost, and removal rate of pollution, as well as greenhouse gases' (GHGs) emissions, all were integrated to interpret the eco-environmental efficiency. Moreover, the ordinary least square as a supplementary method was used to regress the efficiency drivers. The results indicated the particular window width significantly affects the average of overall efficiencies; however, it shows no influence on the ranking of STP efficiency. The labor cost was determined as the most influential parameter, involving almost 40% of the total cost incurred. Hence, higher efficiency was observed with the larger-scale plants. Meanwhile, the statistical regression analysis illustrates the significance of plant scale, inflow cBOD concentrations, and inflow total phosphorus concentrations at [Formula: see text] on the performance. Lastly, some applicable techniques were suggested in terms of GHG emission mitigation.

R&D performance and relevant factors of renewable energy projects: separating innovation and economic perspectives

Many countries, including South Korea, focus on securing renewable energy technologies to cope with climate change and foster new industries. This study analyzed R&D performance and relevant factors through tracking data on the Korean government's renewable energy R&D project, which ended in 2010-2014. The main findings provide several meaningful information. First, the overall performance of completed projects is relatively low, both innovation and economic perspectives. Second, renewable energy source, R&D organizer, and The R&D stage are relevant factors on R&D performance. The R&D stage significantly influences innovation performance. Lastly, R&D performance is under an imbalance between innovation and economic perspectives. This paper can provide useful information to policy and decision-makers to improve future R&D project performance. In addition, scholars also may refer to related researches. Ultimately, we expect to promote renewable energy R&D projects and help manage their performance.

Evaluating sustainable efficiency of decision-making units considering undesirable outputs: an application to airline using integrated multi-objective DEA-TOPSIS

Sustainable development has gained significant attention in the literature due to the increased global awareness of environmental sustainability during the last decade. Sustainable development has three aspects, including economic, social, and environmental. The challenge of sustainable development is to establish a balance between these three aspects. Assessing the efficiency of a company contributes comprehensive information to improve its overall performance. Despite numerous studies in this field, the literature lacks studies that simultaneously consider all three aspects of sustainable development, especially the social aspect. The main objective of this paper is to calculate the technical, social, and environmental efficiency scores. We also introduce a new efficiency called sustainable efficiency that merges all three sustainable development aspects in one efficiency score. This study applies two existing data envelopment analysis (DEA) models to evaluate technical, social, environmental, and sustainable efficiencies. These models, namely the three-step method and the modified three-step method, are computationally intensive. Also, this paper introduces two new DEA models, namely the common weight goal programming DEA and the common weight DEA, to assess the efficiencies with much fewer computations. Each model produces results that are different from one another. Therefore, the TOPSIS approach is applied to provide an overall result by integrating the results obtained from the four presented models. For this purpose, the implementation of four TOPSIS models is required. To illustrate the capability and validity of the developed models in efficiency calculation, a case of Iranian airlines is presented. The selected airlines are evaluated in different aspects, and final results are obtained by applying TOPSIS. The findings show that using TOPSIS to combine the results of several DEA models leads to a fully ranking of airlines in four aspects of technical, social, environmental, and sustainable efficiencies. Also, it is recommended to managers to probe pairwise comparison between different efficiencies of airlines in order to find and improve the weak ones.

Carbon mitigation by quota allocation

To avoid the calamitous consequences of an even warmer world, the efforts are focused on overarching and immediate solutions to reduce the greenhouse gases. The emissions trading scheme is deemed worldwide as an ecological and robust management mechanism to curb carbon emissions. The challenge is how to design such a scheme to attain the basic purpose of installing a uniform system and equilibrium efficiency achievement. For the first time, existing idea of group method of data handling (GMDH) type neural network (NN) is developed to predict capital stock, labor force, CO₂ emission, energy consumption, and gross domestic product (GDP) based on past information for the top-26 emitting countries. Then, this study deals with the allocation of emission quotas by proposing a two-step optimization mechanism that takes full advantages of the context-dependent data envelopment analysis (DEA) and equilibrium efficient frontier DEA (EEFDEA) models. In the first step, under the premise of constant total carbon emissions, a pragmatic efficiency-oriented carbon quota trading system is established to attain equilibrium state. In the second step, under the measured total emission mitigation target, the carbon quotas allocation mechanism is formulated to translate the top emitters' mitigation target into national purposes from two features of efficiency and fairness as well as to specify the comprehensive targets for the top emitters to maintain their equilibrium state. Two of the main findings are: 1) The top emitters should decrease the total CO2 emission by at least 37% by 2023. 2) In light of the CO2 emission mitigation allocation, the countries with larger potentials are China, Japan, and the US yet to receive the larger portions of 20%, 9% and 22%, respectively. Finally, the allocation method that takes regional heterogeneity into account is more logical since it alleviates pressure on the emitters to decrease carbon emissions and establishes a baseline for distributing CO₂ emission quotas across the emitters to enhance adaptation to nations' present circumstances.

COVID-19 and the efficiency of health systems in Europe

BACKGROUND

This study aims at analyzing the efficiency of the health systems of 31 European countries in treating COVID-19, for the period January 1, 2020 - January 1, 2021, by incorporating some factors from a multidimensional perspective.

METHODS

The methodology used in the research was Data Envelopment Analysis (DEA), through which efficiency scores for health systems have been calculated. The research was performed considering three stages: the first wave (January 1-June 15), the relaxation period (June 15-October 1) and the second wave (October 1-December 31). In evaluating the determinants of the efficiency of health systems, six major fields of influence were taken into account: health care, health status, population, economic, cultural/societal and governmental issues, all covering 15 indicators. After measuring the efficiency, we used the Tobit type regression to establish the influencing elements on it.

RESULTS

The results for the public health systems of European states were determined for each country and period. We evaluated the efficiency of health systems in Europe against COVID-19, starting from health inputs (COVID-19 cases, physicians, nurses, hospital beds, health expenditure) and output (COVID-19 deaths). The obtained outputs show that, especially in the first phase of the pandemic, the inefficiency of the health systems was quite high, mainly in Western countries (Italy, Belgium, Spain, UK). In the relaxation phase and in the second wave, the Western states, severely affected at the beginning of the pandemic, began to take adequate measures and improve the efficiency of their sanitary systems. Instead, Eastern European countries were hit hard by the inefficiency of health systems (Bulgaria, Greece, Hungary, Romania). After Tobit regression, results of the study show that the influencing elements are different for the three stages: concerning the first wave, comobirdities, population age, and population density are important; for relaxation period a great influence have government effectiveness and power distance; with respect to second wave, the relevant factors are education and population density.

CONCLUSIONS

The results obtained could serve as starting points for health policymakers to perform comparative analyzes in terms of good practices in the health system and to develop national plans to better deal with health crises. At the same time, they can be used internationally to achieve a coherent and effective community response to the pandemic.

Inclusive ecological efficiency analysis in China's Hainan Island: an extended meta-frontier DEA approach

China is advocating the ecological civilization for a sustainable society and resource-economic-environmental system due to its environmental and climate problems. As a special resource-economic-environmental system, island systems are facing severe challenges due to the vulnerable coordination ability between ecological environment and economic development. To measure the sustainable performance of island systems more directly and specifically, this paper extends the concept of ecological efficiency to inclusive ecological efficiency. For the first time, we analyze the inclusive eco-efficiency of Hainan Island, the second largest island in China, from 2008 to 2017. Due to the large technological heterogeneity among the diverse industries, this paper combines inclusive eco-efficiency with meta-frontier data envelopment analysis (DEA). And we propose a revised meta-frontier slack-based measure (SBM) model and meta-frontier non-radial directional distance function (NRDDF) model, which makes the technology gap rate (TGR) no larger than 1. The empirical results show that the average inclusive total factor energy efficiency (ITFEE) of the tertiary industry under the group-frontier is the largest while the average ITFEE of the primary industry is the highest under the meta-frontier. Moreover, the technology gap rate of the primary industry is the largest. Policy implementations are presented based on the empirical results.

Selection and performance estimation of Green Lean Six Sigma Projects: a hybrid approach of technology readiness level, data envelopment analysis, and ANFIS

Nowadays budget and schedule constraints have forced organizations to select six sigma projects based on pre-defined success criteria. Also, progressive approaches based on green and lean paradigm are vital for companies to enhance their social and environmental performance. Then, Green Lean Six Sigma (GLS) projects play the main role in improving the performance of an organization while augmenting its sustainability. Accordingly in this paper, past studies were reviewed, and GLS projects' indicators and performance evaluation criteria were identified. Data envelopment analysis (DEA) was employed for the appropriate selection of GLS projects. Next, the ranking and performance weight of each project were investigated, and also the projects were categorized based on the technology readiness level (TRL). Additionally, an adaptive neuro-fuzzy inference system (ANFIS) method was applied for the successful prediction of selected GLS projects. Twenty-eight inputs and 9 outputs for the first project category (with TRL 9) and 28 inputs and 6 outputs for the second project category (with TRL 8) were entered into the model. The statistical assessment measures such as Nash-Sutcliffe efficiency (NSE), root mean squared of error (RMSE), mean absolute error (MAE), and R2 were employed for capability appraisal of ANFIS model. Results of NSE and R2 indicators for both project categories were 1.00 that proved the efficiency of the ANFIS model for success prediction of GLS projects. Also, RMSE and MAE indicators for category 1 were 0.01 and 0.02 respectively. Similarly, these measures for category 2 were 0.02 and 0.02. The results advocate a proper approximation for observed values by the ANFIS model. Also, the results indicated that TRL as an important enabler of the GLS project has a meaningful role in the performance of GLS projects.

Measuring the Efficiency of Health Systems: A Case of Mental Health in Middle East and North Africa Countries

Background:

Mental disorders and problems put a heavy burden on communities. Since resources allocated to the mental health systems are finite, it seems necessary to assess the efficiency of mental health systems. In this study, we assess the efficiency of mental health care systems across 12 Middle East and North Africa (MENA) countries in 2014.

Methods:

We used data envelopment analysis (DEA). The number of psychiatrists and nurses working in the mental health sector, the number of beds in mental hospitals, and the healthcare expenditures were included as inputs. The disability-adjusted life years (DALYs) of mental and substance use disorders was considered as the output. This approach is an input-oriented and a variable returns to scale.

Results:

Countries such as Egypt, Iraq, Lebanon, and Qatar with the efficiency scores of 1.00 are entirely efficient. However, Bahrain and Iran with the efficiency scores of 0.50 and 0.58 are the most inefficient countries, respectively. After measuring the efficiency model, the radial super-efficiency showed that Egypt and Lebanon with the efficiency scores of 4.73 and 4.09 were ranked as the first and second by far. Qatar and Iraq compared with the previous analysis, and with the efficiency scores of 1.72 and 1.58, were ranked as the third and fourth. Bahrain and Iran were as inefficient as the previous model.

Conclusion:

This study depicted a general portrait of the performance of mental health systems across MENA countries. Countries performed efficiently, have taken advantage of comprehensive programs in mental health sector. Countries are strongly recommended to complement their datasets of mental health to make future studies able to evaluate mental health systems more accurately and perfectly.

From income inequality to social inequity: impact on health levels in an international efficiency comparison panel

BACKGROUND

Health equity, although addressed in several publications dealing with health efficiency analysis, is not easily translated into the operationalization of variables, mainly due to technical difficulties. Some studies provide evidence that it does not influence health outcomes; others demonstrate that its effect is an indirect one, with the hegemony of material living conditions over its social connotation. The aim of this article is to evaluate the role of health equity in determining health outcomes, in an international comparative analysis of the effectiveness and efficiency of health systems.

METHOD

Fixed Effects Model Panel and Data Envelopment Analysis, a dynamic and network model, in addition to comparative analysis between methods and health impacts. The effect variables considered in the study were life expectancy at birth and infant mortality, in 2010 and 2015, according to the sociocultural regions of the selected countries. Inequity was assessed both economically and socially. The following dimensions were considered: physical and financial resources, health production (access, coverage and prevention) and intersectoral variables: demographic, socioeconomic, governance and health risks.

RESULTS

Both methods demonstrated that countries with higher inequity levels (regarding income, education and health dimensions), associated or not with poverty, are the least efficient, not reaching the potential for effective health outcomes. The outcome life expectancy at birth exhibited, in the final model, the following variables: social inequity and per capita health expenditure. The outcome infant mortality comprehended the level of education variable, in association with the following healthcare variabels: care seeking due to diarrhea in children under five, births attended by skilled health professionals and the reduction in the incidence of HIV.

CONCLUSION

The dissociation between the distribution of health outcomes and the overall level of health of the population characterizes a devastating political choice for society, as it is associated with high levels of segregation, disrespect and violence from within. Countries should prioritize health equity, adding value to its resources, since health inequties affect society altogether, generating mistrust and reduced social cohesion.

A methodological proposal to determine the optimal levels of inter-municipal cooperation in the organization of solid waste management systems

The paper proposes a procedure based on data envelopment analysis (DEA) in order to identify the optimal dimension for inter-municipal cooperation in waste management. Given: (a) a set of decision making units (DMUs) and a production process that virtually transforms municipal expenditure in different amounts of sorted and unsorted waste, (b) a set of exogenous variables conditioning the operational environment of the DMUs and (c) a variable used for measuring the dimension of inter-municipal cooperation, the procedure realizes an iterative correction of input values and efficiency scores to purge, first, the effects of the exogenous variables, and then those of the dimensional variable. In this way, an indicator of the impact of the dimensional variable on the efficiency is obtained for each of the observed DMUs. An application on waste collection services is proposed using data relative to a set of Italian DMUs with a population ranging between 20,000 and 300,000. The results show that DMUs not exceeding the total population of around 55,000 (upper bound of the eighth population decile) provide the best solution for inter-municipal cooperation. Over that level, increases of the population consistently worsen average efficiency (the mean of the impact of the dimensional variable on efficiency scores more than doubles from the eighth to the ninth decile and more than quintuples from the eighth to the last decile). The procedure can be applied to different regional and national contexts and even to inter-municipal cooperation concerning other public services.

Identification and correction of congestion in wastewater treatment plants in the Community of Valencia, Spain

The present work analyses the existence of congestion in a set of wastewater treatment plants (WWTPs) for the first time. The study sample included 47 WWTPs managed by the same operator and located in the Valencia region (eastern Spain). The method of analysis consisted in applying a new statistical model to identify and correct congestion situations based on data envelopment analysis (DEA), which takes into account undesirable outputs and multiple projections. The results showed a strong concentration of congested WWTPs (48.94-57.45%). Furthermore, the necessary corrections to avoid the congestion statuses entailed an average input reduction between 57.03 and 74.13% and an average increase in desirable outputs between 46.08% and 50.08%. In addition, only plant size had a significant relationship with the correction levels. The remaining contextual variables (age, overcapacity and type of water and sludge line) failed to show any significant impact on those corrections. To conclude, policy recommendations to improve the management of WWTPs are put forward, notably improving the management of smaller plants, which concentrate the largest percentage of correction.

Ecological development efficiency index of tropics and subtropics in China

This paper proposes an ecological development efficiency index (EDEI) based on comprehensive metrics to measure the ecological efficiency and human development of the tropics and subtropics in China for the 2005-2016 period. In particular, the proposed index integrates the ecological footprint into the input metrics considering resource exploitation, carbon emission, and energy infrastructures. The traditional output factor, i.e., GDP, is substituted with the human development index to evaluate the local development quality on the basis of health, education, and income. It is observed that the EDEI of the tropics and subtropics in China grew slowly before stabilizing at approximately 0.92. Moreover, as shown in the Theil index analysis, the spatial heterogeneity of the EDEI in tropics and subtropics of China is increasing significantly. The EDEI of the eastern region of China is higher than that of the central region, and the EDEI of the western region is the lowest. Finally, based on the Tobit factor model, research density and urbanization are observed to be the keys to improving the EDEI for achieving sustainable growth.

Economics of energy and environmental efficiency: evidence from OECD countries

The purpose of this research is to determine the efficiency of energy usage and its role in carbon dioxide emissions (CI) and economic-environmental efficiency (EEE) for some countries Organization for Economic Co-operation and Development (OECD) economies. For environment quality assessment, data envelopment analysis (DEA) is used to assess the data cover the period from 2013 to 2017. In this study, primary energy consumption (PEC) and population are two basic inputs along with gross domestic product (GDP) and carbon dioxide emissions that are desirable and undesirable  outputs, respectively. The practical outcomes illustrate that Brunei, Australia, Singapore, and Hong Kong are the most effective and efficient states for the 5 years periods (2013-2017) in terms of energy efficiency and to reduce emission of carbon dioxide. In addition, other states in the OECD region shows greater economic proficiency than environmental proficiency. Furthermore, the results shows that energy efficiency has strong bonding with carbon emissions; however there is a weaker association between economic-environmental efficiency. Thus, the attainment of optimal level of energy efficiency could be more pivotal than economic efficiency to improve environmental efficiency in countries from the OECD region.

Measuring and improving adaptive capacity in resilient systems by means of an integrated DEA-Machine learning approach

Resilient systems strive to enhance the safety of complex systems through building and developing adaptive technological and organizational capacities. This study aims at analyzing and improving the level of adaptive capacity in a petrochemical plant by means of an integrated quantitative approach. The data were gathered by a questionnaire whose reliability is examined by statistical methods. To compute and analyze the influence of resilience engineering (RE) indicators, teamwork, and redundancy on adaptive capacity, data envelopment analysis (DEA) method was used. The results indicate that teamwork and redundancy have a positive effect on enhancing the level of adaptive capacity. Multilayer perceptron (MLP), a machine learning approach, was used to estimate the level of adaptive capacity on the basis of a dataset. The results of DEA and MLP approaches are confirmed by statistical methods. To the best of our knowledge, this is the first study that measures quantitatively and improves adaptive capacity by an integrated DEA-MLP approach based on the stress-strain model. The outcomes of this study could assist managers and other decision-makers of complex systems to compute and improve the level of adaptive capacity for coping with upcoming events in abnormal conditions.

How public environmental concern affects the sustainable development of Chinese cities: An empirical study using extended DEA models

China is now facing the formidable tasks of saving energy and reducing emissions, so it is very important to analyze China's energy and environmental efficiency. However, previous studies have rarely paid attention to the cross-impacts that different forms of public environmental concern (PEC) have simultaneously on energy and environmental efficiency. To investigate how these two types of efficiency change along with PEC variations, this paper employs six extended programming models which are developed based upon the theory of Data Envelopment Analysis (DEA) and the directional distance function (DDF). An empirical analysis of data from 239 Chinese prefecture-level cities demonstrates the techniques. The empirical results show that PEC variations can significantly affect the environmental efficiency only if the city is experiencing unsustainable development. This work also shows that PEC about input resources may exaggerate the environmental efficiency, implying that the public may be more tolerant of resource over-consumption than of pollutant over-emission.

A Study of Different Types of Air Pollutants on the Efficiency of China's Hotel Industry

This study focuses on visible and invisible air pollutants and their impacts on China's hotel industry. Overall, visible air pollutants may block the sights and sceneries and worsen the quality of visitors' sensory experiences, and invisible air pollutants are unlikely to result in the same perceptions and sensations. Hence, different types of air pollutants may have various impacts on the hotel industry's operational performance. We employed a bootstrapped truncated regression model to investigate whether different types of air pollutants had distinctive impacts on the hotel industry. The dataset consisted of 31 provinces of China for the period 2012-2015. Empirical results indicate that visible air pollutants significantly decrease the operational efficiency of China's hotel industry, while invisible air pollutants insignificantly affect the hotel industry.

Energy and environmental efficiency of OECD countries in the context of the circular economy: Common weight analysis for malmquist productivity index

Circular economy (CE) aims at sustainable development (SD) by focusing more on renewable sources of energy and precise management of waste to i) guarantee the secure access to resources, ii) combat climate change and global warming. Environmental issues arising from energy use and lack of policies to monitor them challenge sustainable development. Circular economy emphasizes the economic development with the least amount of undesirable environmental impacts. To evaluate the environmental performance of decision-making units (DMUs) with data envelopment analysis (DEA), this paper develops a common set of weights (CSW) model using the ideal point method. Therefore, energy and environmental efficiency of the organization for economic cooperation and development (OECD) countries is analyzed using the Malmquist productivity index (MPI) during 2012-2015. Although Switzerland has the highest energy and environmental efficiency during 2012-2014, findings indicate that Ireland and the USA have continuously improved their energy and environmental efficiency.

Health expenditure efficiency in rural China using the super-SBM model and the Malmquist productivity index

BACKGROUND

Health expenditure efficiency (HEE) is an important research area in health economics. As a large agricultural country, China is faced with the daunting challenge of maintaining equality and efficiency in health resource allocation and health services utilization in the context of rapid economic growth in rural areas. The reasonable allocation of limited rural health resources may be achieved by scientifically measuring the current rural HEE. This subject may help to formulate effective policy or provide incentives for the health sector.

METHODS

The combination of a super-slack-based measure (SBM) model with the Malmquist productivity index (MPI) is proposed to evaluate the static health expenditure efficiency (HEE) and dynamic health expenditure efficiency (DHEE) in rural China from 2007 to 2016.

RESULTS

The results show that the HEE and DHEE values exhibit unstable trends over time. The HEE does not follow China's economic development and presents an average of 0.598 (< 1); and the DHEE presents an average value of approximately 0.949 (< 1), indicating that the DHEE of most provinces is not moving in a desirable direction. The level of technological progress and scale optimization are the main factors hindering total factor productivity (TFP) growth.

CONCLUSIONS

The Chinese government could improve the efficiency of rural health resources allocation by improving the rural health service system, optimizing the allocation of material resources and enhancing the level of health of financial resources allocation. The state should continue to moderate policy for different regions. Moreover, scientific and technological advancements should be introduced to improve the scale optimization levels.

Green certification, e-commerce, and low-carbon economy for international tourist hotels

Increasing population and over-consumption are placing unprecedented demands on agriculture and natural resources. The Earth is suffering from global warning and environmental destruction while our agricultural systems are concurrently degrading land, water, biodiversity, and climate on a global scale. For a sustainable future, green certification, e-commerce, and environment education can boost low-carbon economy with decreasing carbon emissions, but very few researches address them for the hotel industry. This research studies the performance impact of e-commerce, international hotel chain, local hotel chain, and green certification for carbon emission reductions of international tourist hotels of Taiwan. It reveals that, after a sufficiently long time, there is an improvement in the environmental and economic performance of the green-certified hotel group. In addition, it reveals that, as recommended by the operation policy, the international hotel chain group together with e-commerce has better performance than local hotel chain. It is also discussed how to sustain the continuing improvement in low-carbon performance of the hotel industry.

Allocating on coal consumption and CO2 emission from fair and efficient perspective: empirical analysis on provincial panel data of China

This paper considers a problem of how to allocate resource effectively and equitably among provinces. To address the problem, a total factor resource input-oriented data envelopment analysis (DEA) model is used to evaluate the energy and environmental efficiency for 30 provinces in China during 2009-2013 in this paper. Based on the evaluation results, from efficient and fair perspective, a revised DEA-based resource allocation model is established. It is worth pointing out that the model takes the input orientation and output orientation into account at the same time and can be used to allocate coal consumption and carbon emission by 2020 for 30 provinces in China. Results indicate that if the Chinese government wants to fulfill the CO₂ emission reduction targets of 40-45% by 2020, and coal consumption intensity reduction target during 13th Five-Year Plan, inefficient provinces will undertake more coal consumption and carbon emission intensity reduction obligation share. And provinces with historical high coal consumption and high CO₂ emission intensity will have greater potential of coal consumption and carbon emission intensity reduction. In addition, this paper set several scenarios of gross domestic product (GDP) growth rate, under the scenarios analysis, finds the growth rate of GDP has negative effect on reduction of coal consumption and carbon dioxide emissions intensity. This research provides more realistic practical significance for achieving sustainable economic development.

Environmental performance of Chinese listing manufacturing enterprise: from investment perspective

With decades of high-speed economic miracle, China inevitably encountered with environmental pressure and sustainable development problem. As the main carrier of the environmental responsibility, Chinese government set series of regulations and standards to supervise and guide enterprise to fulfill this challenge emission reduction task. Based on data envelopment analysis (DEA) approach, this paper focuses on air pollutant highly emission manufacturing tycoons to figure out "whether the yearly billions environmental input really worth it?" during 2014 to 2016. Unlike previous studies mainly from consumption perspective and got macro-regional evidence, we choose micro-enterprise to analyze individual environmental performance and draw general conclusions. Possible suggestions are also proposed for various industries and some salient enterprises.

Efficiency of wastewater treatment facilities: The influence of scale economies

The water cycle, from catchment to discharge, is a sector that involves an important investment and operation and maintenance costs. In particular, sewage treatment is a challenge for governments because they are having to consider economic, environmental, and social aspects. Within the European Union, implementation of Directive 91/271/EEC is responsible for the location of wastewater treatment facilities in the territory, due to the requirement that all urban areas must have this infrastructure to reduce the environmental impact of treated water in water bodies. Different sizes of municipalities affect the design of each wastewater treatment plant (WWTP) and cause variations in the operation process. The presence of scale economies in this sector has a significant influence on the efficiency of the wastewater treatment process and has a direct impact on the operational costs. Based on the pursuit of economic and environmental efficiency, this analysis extends the scope of the current literature because it recommends a specific, population equivalent (p.e.) range for which it would be suitable to achieve efficiency in wastewater treatment facilities-shedding light on the open debate about scale economies in WWTPs.

A novel mixed sustainability-resilience framework for evaluating hospital information systems

Information systems (ISs) are one of the most widely used systems in different organizations especially hospitals. Improving the performance of a hospital information system (HIS) is one of the most important tasks for patient satisfaction and health. To do this, a mixed sustainability-resilience framework for evaluating HISs is proposed in this study in order to enhance their performance from a mixed sustainability-resilience view. First, a comprehensive framework including suitable sustainable and resilience indicators for performance enhancement of HISs is provided. Then, the importance weight of each indicator is achieved by using the best-worst method (BWM). Required data is obtained through a standard questionnaire. A data envelopment analysis (DEA) is applied to evaluate HIS performance in different departments of a real case study. Additionally, improvement actions are obtained by considering the effect of each selected indicator on the HIS performance through a sensitivity analysis. Also, appropriate strategies for improving the resilience and sustainability aspects of the HIS are presented using strengths-weaknesses-opportunities-threats (SWOT) matrix. Using the results, designers can build more intelligent HISs from both sustainability and resilience perspectives.

Productivity change of national health systems in the WHO Eastern Mediterranean region: application of DEA-based Malmquist productivity index

BACKGROUND

The pursuit of efficiency and productivity is one of the goals of health systems. In the era of Sustainable Development Goals and particularly the move towards universal health coverage, it is imperative to curb wastage of resources to ensure sustainable access of the population to needed and effective health services without enduring financial hardship. This study aims to assess total factor productivity change of national health systems of 20 countries in the WHO's Eastern Mediterranean Region.

METHODS

Data Envelopment Analysis (DEA)-based Malmquist index is used to assess total factor productivity change and its components - efficiency change and technical change. To assess the robustness of the Malmquist index estimates, bootstrapping was performed. Outputs used are life expectancy at birth for both sexes and infant mortality; while total expenditure on health per capita in international dollars (PPP) is used as a measure of input. Panel data for the period 2003-2014 was extracted from databases of the WHO and the World Bank.

RESULTS

In all but five countries covered in the study, a decline in the mean total factor productivity is observed during the period 2003-2014. The decline is driven by technical regress. In all countries, the technical change component of the Malmquist TFP index is less than unity (range: 0.896 to 0.945). All countries exhibited growth in efficiency (efficiency change exceeding one) except two countries (Djibouti and Iraq). The growth in efficiency was mainly due to change in scale efficiency. Overall, total factor productivity in the region declined by 3.8%. This was due to a 9.1% decline in technical change, which overshadowed the 5.8% increase in efficiency. Three countries - Libya, Qatar and Yemen - showed a marginal growth in total factor productivity. There was no change in total factor productivity in Kuwait and Lebanon.

CONCLUSION

The decline in total factor productivity over the study period is likely to hamper achieving the targets of Sustainable Development Goal 3 of ensuring healthy lives and promoting well-being for all at all ages. It is recommended that country-level studies on efficiency and productivity of health systems be conducted in order to intensively examine the determinants of inefficiency and productivity decline and implement appropriate interventions that could enhance efficiency and productivity.

Efficiency in the European agricultural sector: environment and resources

This article intends to compute agriculture technical efficiency scores of 27 European countries during the period 2005-2012, using both data envelopment analysis (DEA) and stochastic frontier analysis (SFA) with a generalized cross-entropy (GCE) approach, for comparison purposes. Afterwards, by using the scores as dependent variable, we apply quantile regressions using a set of possible influencing variables within the agricultural sector able to explain technical efficiency scores. Results allow us to conclude that although DEA and SFA are quite distinguishable methodologies, and despite attained results are different in terms of technical efficiency scores, both are able to identify analogously the worst and better countries. They also suggest that it is important to include resources productivity and subsidies in determining technical efficiency due to its positive and significant exerted influence.

Assessing the Relative Performance of Nurses Using Data Envelopment Analysis Matrix (DEAM)

Assessing employee performance is one of the most important issue in healthcare management services. Because of their direct relationship with patients, nurses are also the most influential hospital staff who play a vital role in providing healthcare services. In this paper, a novel Data Envelopment Analysis Matrix (DEAM) approach is proposed for assessing the performance of nurses based on relative efficiency. The proposed model consists of five input variables (including type of employment, work experience, training hours, working hours and overtime hours) and eight output variables (the outputs are amount of hours each nurse spend on each of the eight activities including documentation, medical instructions, wound care and patient drainage, laboratory sampling, assessment and control care, follow-up and counseling and para-clinical measures, attendance during visiting and discharge suction) have been tested on 30 nurses from the heart department of a hospital in Iran. After determining the relative efficiency of each nurse based on the DEA model, the nurses' performance were evaluated in a DEAM format. As results the nurses were divided into four groups; superstars, potential stars, those who are needed to be trained effectively and question marks. Finally, based on the proposed approach, we have drawn some recommendations to policy makers in order to improve and maintain the performance of each of these groups. The proposed approach provides a practical framework for hospital managers so that they can assess the relative efficiency of nurses, plan and take steps to improve the quality of healthcare delivery.

Multimethodology applied to the evaluation of Healthcare in Brazilian municipalities

The integration of quantitative indicators with qualitative descriptions of context is a noticeable demand from many different scientific disciplines, since it contributes to linking theoretical and practical approaches to problem solving. Amongst them are the problem structuring methods, systems thinking and multimethodology. This work presents a mixed quantitative and qualitative methodological approach to aid formulation and structuring of performance measurement of health care in 5565 Brazilian municipalities. Data mining and data envelopment analysis (DEA) are applied in the context of conceptual mapping, thus shedding light on both quantitative and qualitative factors that influence health performance. Our aim is to propose a methodology for performance indicators to support health care policy making in Brazil, using quantitative indicators. However, the approach does not lose track of the role of important qualitative factors in the attribution of meaning to performance assessments. The methodological and analytical results can strengthen mutual understanding by analysts and stakeholders of the problem at hand. Quantitative results allow inefficient municipalities to understand the causes of their overall efficiency in terms of particular low partial DEA efficiencies combined with high deathrates.

The Efficiency Assessment of Dental Units Using Data Envelopment Analysis Approach: The Case of Iran

BACKGROUND

During the last decades, the number of dentistry units increased significantly across the country. The aim of this study was to assess the efficiency of dental units of Iran provinces regarding dental health inputs and outputs using Data Envelopment Analysis approach.

METHODS

In this applied descriptive-analytical study, the study population included all of Iran 31 provinces. The output variables included DMFT and DMFT indices of 6-12 yr old students. The data about DMFT and DMFT indices were taken from 2013 Nationwide School Pupils Screening Program. Input variables included active dental chairs located in the public sector, general dentists of public sector, general and specialist dentists of private sector by different provinces. The data were analyzed using Deap software version 2.1.

RESULTS

The lowest amount of scale efficiency was for Tehran Province (0.204) followed by Isfahan Province (0.205). Provinces of Isfahan, Razavi Khorasan, Kerman, Zanjan, Hamedan, Kordestan, Golestan, Yazd and Tehran, Iran had decreasing return to scale and provinces of Gilan, West Azerbaijan, Mazandaran, Fars, Kermanshah, Markazi, Lorestan, Qazvin, Sistan-and-Baluchestan, Bushehr, Alborz, Hormozgan and Khuzestan had increasing return to scale.

CONCLUSION

Despite provinces of Isfahan, Razavi Khorasan, Kerman, Zanjan, Hamedan, Kordestan, Golestan, Yazd and Tehran which had a better situation in terms of the number of dentistry chairs, public dentists, general and specialist dentists of private sector than other provinces, they had decreasing return to scale. Investment in dental primary health care, preventive and educational programs can be more cost-effective.

Optimization of healthcare supply chain in context of macro-ergonomics factors by a unique mathematical programming approach

This study presents an integrated approach for analyzing the impact of macro-ergonomics factors in healthcare supply chain (HCSC) by data envelopment analysis (DEA). The case of this study is the supply chain (SC) of a real hospital. Thus, healthcare standards and macro-ergonomics factors are considered to be modeled by the mathematical programming approach. Over 28 subsidiary SC divisions with parallel missions and objectives are evaluated by analyzing inputs and outputs through DEA. Each division in this HCSC is considered as decision making unit (DMU). This approach can analyze the impact of macro-ergonomics factors on supply chain management (SCM) in healthcare sector. Also, this method ranks the relevant performance efficiencies of each HCSC. In this study by using proposed method, the most effective macro-ergonomics factor on HCSC is identified as "teamwork" issue. Also, this study would help managers to identify the areas of weaknesses in their SCM system and set improvement target plan for the related SCM system in healthcare industry. To the best of our knowledge, this is the first study for macro-ergonomics optimization of HCSC.

A novel framework for improvement of road accidents considering decision-making styles of drivers in a large metropolitan area

Road accidents can be caused by different factors such as human factors. Quality of the decision-making process of drivers could have a considerable impact on preventing disasters. The main objective of this study is the analysis of factors affecting road accidents by considering the severity of accidents and decision-making styles of drivers. To this end, a novel framework is proposed based on data envelopment analysis (DEA) and statistical methods (SMs) to assess the factors affecting road accidents. In this study, for the first time, dominant decision-making styles of drivers with respect to severity of injuries are identified. To show the applicability of the proposed framework, this research employs actual data of more than 500 samples in Tehran, Iran. The empirical results indicate that the flexible decision style is the dominant style for both minor and severe levels of accident injuries.

An integrated experiment for identification of best decision styles and teamworks with respect to HSE and ergonomics program: The case of a large oil refinery

Decision making failure is a predominant human error in emergency situations. To demonstrate the subject model, operators of an oil refinery were asked to answer a health, safety and environment HSE-decision styles (DS) questionnaire. In order to achieve this purpose, qualitative indicators in HSE and ergonomics domain have been collected. Decision styles, related to the questions, have been selected based on Driver taxonomy of human decision making approach. Teamwork efficiency has been assessed based on different decision style combinations. The efficiency has been ranked based on HSE performance. Results revealed that efficient decision styles resulted from data envelopment analysis (DEA) optimization model is consistent with the plant's dominant styles. Therefore, improvement in system performance could be achieved using the best operator for critical posts or in team arrangements. This is the first study that identifies the best decision styles with respect to HSE and ergonomics factors.

Assessing the relative efficiency of water companies in the English and Welsh water industry: a metafrontier approach

The assessment of relative efficiency of water companies is essential for managers and authorities. This is evident in the UK water sector where there are companies with different services such as water and sewerage companies (WaSCs) and water-only companies (WoCs). Therefore, it is a critical limitation to estimate a common production frontier for both types of companies, as it might lead to biased efficiency estimates. In this paper, a robust and reliable methodology, the metafrontier model, is applied to compare the efficiency of water companies providing different services. The results illustrate the superior performance of WaSCs compared to WoCs. It also confirms the presence of economies of scope in the UK water industry. The methodology and results of this study are of great interest for both regulators and water utility managers to make informed decisions.

Taiwan quality indicator project and hospital productivity growth

The Taiwan Quality Indicator Project (TQIP) is a quality management program that measures and monitors the healthcare quality of hospitals in Taiwan. This paper examines the impact of TQIP participation on hospital productivity growth with the application of the Malmquist productivity change index based on data envelopment analysis (DEA). Analyzing operations data from 31 TQIP regional hospitals over the period 1998-2004, we find that TQIP hospitals improved their productivity in the post-TQIP period. This improvement is attributable to quality change and relative efficiency progress. The simultaneous enhancement in both quality and relative efficiency coincides with the philosophy of total quality management (TQM) spirit, and confirms the efficiency improvement and quality assurance functions of TQIP.