Dynamic assessment of material living conditions across europe: a window data envelopment analysis approach

Handling negative data in slacks-based measure data envelopment analysis models

Many countries are attempting to reduce energy consumption and CO2 emissions while increasing the productivity and efficiency of their industries. An undesirable-output-oriented data envelopment analysis (DEA) model with slacks-based measure (SBM) was used to evaluate the changes in the environmental efficiency of the transportation sector in 30 Chinese provinces (municipalities and autonomous regions) between 2003 and 2012. The potential for decreasing CO2 emissions and energy saving was also assessed. Transportation was found to be inefficient in most of the provinces and the average environmental efficiency was low (0.45). The overall average efficiency reached a maximum in 2005 and continually decreased until a minimum was reached in 2009; since then, it has increased. In general, transportation is more efficient in eastern than in central or western China. A sensitivity analysis was also carried out on the input and output indicators. Based on these findings, some policies are proposed to improve the environmental efficiency of the transportation sector in China.

A dynamic multi-stage slacks-based measure data envelopment analysis model with knowledge accumulation and technological evolution

Standard Data Envelopment Analysis (DEA) models consider continuous-valued and known input and output statuses for measures. This paper proposes an extended Slacks-Based Measure (SBM) DEA model to accommodate flexible (a measure that can play the role of input and output) and integer measures simultaneously. A flexible measure’s most appropriate role (designation) is determined by maximizing the technical efficiency of each unit. The main advantage of the proposed model is that all inputs, outputs, and flexible measures can be expressed in integer values without inflation of efficiency scores since they are directly calculated by modifying input and output inefficiencies. Furthermore, we illustrate and examine the application of the proposed models with 28 university hospitals in Germany. We investigate the differences and common properties of the proposed models with the literature to shed light on both teaching and general inefficiencies. Results of inefficiency decomposition indicate that “Third-party funding income” that university hospitals receive from the research-granting agencies dominates the other inefficiencies sources. The study of the efficiency scores is then followed up with a second-stage regression analysis based on efficiency scores and environmental factors. The result of the regression analysis confirms the conclusion derived from the inefficiency decomposition analysis.

One problem raised by the lack of energy efficiency is the generation of more greenhouse gases (GHGs) that can cause air pollution and climate change. Ecological efficiency (eco-efficiency) means the efficiency of resources used. A poor performance from this efficiency can then be detected for further improvement. In this research, we conduct an assessment on the eco-efficiency for some European countries as they consume a large part of global energy annually. A total of 17 European countries were selected as decision making units (DMUs) and assessed by the Slacks-based measure (SBM) Data Envelopment Analysis (DEA) model. Indices including Catch-Up, Frontier-Shift, and Malmquist Productivity Index (MPI) have been used to evaluate eco-efficiency, as well as efficiency change, technological change, and productivity change, over 2013–2017. In the model, energy consumption and share of renewable energy are used as energy inputs, and labor productivity and gross capital formation are used as economy inputs. On the other hand, GDP is used as a desired output, and CO2 emissions is used as one undesired output. The experimental results show that the 17 countries as a whole lacked eco-efficiency in 2013–2017, implying more efforts are required to improve their eco-efficiency.

Sustainable concerns are reputed to be of the utmost priority among governments. Consequently, they have become more and more of a concern among supply chain partners. Logistics service providers (LPs), as significant contributors to supply chain success but also one of the greatest generator of emissions, play a significant role in reducing the negative environmental impact. Thus, the performance evaluations of LPs should necessarily involve such a measure which, firstly, represents a balance between all three pillars of sustainability and, secondly, consider the desirable and undesirable performance criteria. This paper proposes an integrated analytic hierarchy process (AHP) and slack-based measure (SBM) data envelopment analysis (DEA) model, based on the assumption of a variable return to scale (VRS). An AHP pairwise comparison enables selecting the most influential input/output variables. Output-oriented SBM DEA provides simultaneously evaluation of both the undesirable and desirable outputs. The proposed model was tested on a numerical example of 18 LPs. The comparison of output Charnes, Cooper and Rhodes (CCR) and SBM DEA models resulted in a higher number of inefficient LPs when the SBM DEA model was applied. Moreover, efficiency scores of inefficient LPs were lower in SBM DEA model. The proposed model is fair to those LPs that are environmentally friendly.

Evaluating the energy efficiency of wastewater treatment plants in the Yangtze River Delta: Perspectives on regional discrepancies

Environmental efficiency of land transportation in China: A parallel slack-based measure for regional and temporal analysis

Considering both sectoral and regional heterogeneities, this article develops a structural meta-frontier slacks-based measure data envelopment analysis model to decompose the inefficiency level, input reduction and output expansion potentials and efficiency change into three components: sectoral heterogeneity, regional heterogeneity, and resource utilization. Subsequently, an empirical study of China’s provincial tourism subsectors between 2000 and 2014 is conducted. The results show that regional heterogeneity and resource utilization failure are the main contributors to the inefficiency of travel agencies, but the inefficiency of star-rated hotels and tourist attractions are dominated by sectoral heterogeneity. The tourism inefficiency of China is mainly characterized by insufficient output rather than input redundancy, and there are significant differences in the sources of output expansion potential for different tourism subsectors. In addition, the driving force for improving the efficiency of travel agencies ascribed to resource utilization capabilities are pure technological progress and technology scale change.

Environmental efficiency of Japanese regions before and after the Great East Japan Earthquake

As the fundamental physical carrier for human production and socio-economic endeavors, enhancing urban land green use efficiency (ULGUE) is crucial for realizing sustainable development. To effectively enhance urban land green use efficiency, this study systematically examines the intrinsic relationship between industrial policies and ULGUE based on panel data from 286 Chinese cities (2010–2022), employing an integrated methodology that combines the Difference-in-Differences (DID) model, Super-Efficiency Slacks-Based Measure Data Envelopment Analysis model, and ArcGIS spatial analysis techniques. The findings clearly demonstrate that the establishment of the “Made in China 2025” pilot policy significantly improves urban land green use efficiency in pilot cities, a conclusion that endures following a succession of stringent evaluations. Moreover, studying its mechanisms suggests that the pilot policy primarily enhances urban land green use efficiency by promoting industrial upgrading, accelerating technological innovation, and strengthening environmental regulations. Heterogeneity analysis further indicates that the policy effects are more significant in urban areas characterized by high manufacturing agglomeration, non-provincial capital/non-municipal status, high industrial intelligence levels, and less sophisticated industrial structure. This research not only provides valuable policy insights for China to enhance urban land green use efficiency and promote high-quality regional sustainable development but also offers meaningful references for global efforts toward advancing urban sustainability.

Evaluating economic and environmental efficiency of global airlines: A SBM-DEA approach

As countries worldwide strive for a sustainable energy transition, the role of natural gas in achieving carbon neutrality targets has gained increasing attention. This study evaluates the energy efficiency of natural gas (EENG) in China from 2008 to 2021, using the Slacks-Based Measure Data Envelopment Analysis model to examine temporal dynamics and regional disparities. The spatial Durbin model is employed to investigate the factors influencing EENG, considering spatial spillover effects. The results reveal an overall improvement in China’s EENG over time, with significant temporal and regional variations. Urbanization, environmental regulation, natural gas infrastructure, industrial structure, and technological innovation are found to have significant positive impacts on EENG, with notable spatial spillover effects and regional heterogeneity. These findings contribute to the literature on sustainable energy transitions and provide valuable insights for policymakers to develop targeted strategies for enhancing natural gas efficiency and achieving carbon neutrality in China.

Geological disasters in China have caused enormous damage to humans and the economy. The Chinese government has made significant efforts to mitigate geological disasters. Usually, the efficiency of disaster emergency response holds top priority. In this study, we considered the historical analysis of China’s geological disaster emergency response as the primary line and developed a slacks-based measure data envelopment analysis model to evaluate the performance of 18 geological disasters reliefs during 2015–2019 in China. This model is used to examine the performance of the geological disaster emergency response activities. The results indicate that although the capabilities of geo-disaster relief have continuously improved from 2015 to 2019, China’s geological disaster emergency response system remains in its primary stage. In particular, the efficiency of landslide emergency response operations is low. We analyzed the factors influencing efficiency and provided several suggestions for capacity improvement in geo-disaster emergency responses.

We examined the efficiency of the health system in improving maternal health outcomes, i.e. increasing institutional delivery (desirable output) and reducing the maternal mortality ratio (undesirable output). We used a nonradial, nonoriented Slack-based measure data envelopment analysis model to assess the efficiency of the health system across 19 states of India between 2016 and 2020. The overall average efficiency score suggested potential for a 30% improvement in the health system efficiency in India, with only six states emerging as efficient. Interestingly, few states that were endowed with more than adequate health resources were inefficient. We find that resource constraint states such as Bihar and Jharkhand have emerged as efficient. To substantiate the use of undesirable adjusted model instead of the transformed model, we used the Wilcoxon ranked-signed test to estimate the statistical significance. We conclude that incorporating undesirable outputs while measuring efficiency is imperative. Our findings suggest that states that are inefficient with excess capacity should prioritize the efficient utilization of resources. Additionally, adequate resources should be allocated to resource constraints and efficient states such that they achieve better health outcomes. Furthermore, the diversification of health resources across levels of care could be a suggestive measure for some states.