Search Results (17)

Background: European health systems face growing pressure from population ageing, post-pandemic service backlogs, and fiscal constraints. Yet substantial cross-country differences in health outcomes persist despite comparable levels of healthcare expenditure. This study evaluated the relative efficiency of European health systems using a multidimensional framework that integrates expenditure, prevention, and population health outcomes. Methods: A cross-sectional analysis was conducted on 25 European countries using 2022 data or the nearest available year. An output-oriented constant returns to scale Data Envelopment Analysis (DEA) model was estimated with two inputs, public and private healthcare expenditure per capita, and five outputs, life expectancy at birth, inverse infant mortality, healthy life years at birth, breast cancer screening coverage, and poliomyelitis vaccination coverage. A robustness specification added physician density as an additional input. Bootstrap bias correction with 1000 replications was applied to the baseline model. A second-stage Simar–Wilson truncated regression with 2000 bootstrap replications examined the association between inefficiency and selected contextual variables, including GDP per capita, population ageing, obesity prevalence, and tobacco use prevalence. Results: In the baseline DEA model, 8 of 25 countries were located on the technical efficiency frontier (Croatia, Czechia, Estonia, Greece, Hungary, Latvia, Lithuania, and Poland; output-oriented DEA inefficiency score = 1.000 for each country), while inefficiency scores among the remaining countries ranged from 1.042 to 2.617. The highest inefficiency scores were observed for Germany (2.617), Austria (2.283), Belgium (2.230), Ireland (2.219), and France (2.167). When physician density was added as an additional input, 12 countries were located on the estimated frontier. Bootstrap correction of the baseline model increased the estimated output-oriented inefficiency scores, with bias-corrected values ranging from 1.100 to 2.941. In the second-stage analysis, higher log GDP per capita was positively associated with bias-corrected inefficiency (coefficient 1.993; 95% bootstrap CI 0.219 to 4.197), whereas population ageing, adult obesity prevalence, and tobacco use prevalence were not statistically associated with bias-corrected inefficiency. Conclusions: In this cross-sectional sample of 25 European countries, higher healthcare expenditure was not consistently associated with frontier performance when health outcomes and preventive coverage were considered jointly. The results were sensitive to the inclusion of physician density and to bootstrap correction, supporting the interpretation of Data Envelopment Analysis as an exploratory benchmarking tool rather than a definitive ranking of health systems. These findings highlight the importance of assessing how financial and workforce resources are converted into measurable health and prevention-related outputs. Full article

This work develops an inverse data envelopment analysis (Inverse DEA) framework for portfolio optimization, treating return as a desirable output and volatility as an undesirable output. Using 20 industry-level portfolios from the Taiwan Stock Exchange (1365 stocks; FY-2020), we first evaluate efficiency with a directional-distance DEA model and identify 7 inefficient industries. We then formulate an Inverse DEA model that holds inputs and desirable outputs fixed and estimates the maximum feasible reduction in volatility. Estimated reductions range from 0.000827 to 0.007610, and substituting these targets into the base model drives each portfolio’s inefficiency score to zero $(\varphi =0)$, thereby making them efficient. To test robustness, we extend the analysis to a calm pre-crisis year (2019) and a recovery year (2021), which confirm that inefficiency and volatility-reduction targets behave logically across regimes, smaller cuts in stable markets, larger cuts in stressed conditions, and intermediate adjustments during recovery. We interpret these targets as theoretical envelopes that inform risk-reduction priorities rather than investable guarantees. The approach adds a forward-planning layer to DEA-based performance evaluation and provides portfolio managers with quantitative, regime-sensitive volatility-reduction targets at the industry level. Full article

Focusing on the dielectric elastomer actuator (DEA), this paper proposes a backstepping implicit inverse adaptive control scheme with creep direct inverse compensation. Firstly, a novel fractional-order creep Krasnoselskii–Pokrovskii (FCKP) model is established, which effectively captures hysteresis behavior and creep dynamic characteristics. Significantly, this study pioneers the incorporation of the fractional-order method into a hysteresis-coupled creep model. Secondly, based on the FCKP model, the creep direct inverse compensation is developed to combine with the backstepping implicit inverse adaptive control scheme, where the implicit inverse algorithm avoids the construction of the direct inverse model to mitigate hysteresis. Finally, the proposed control scheme was validated on the DEA system control experimental platform. Under both single-frequency and composite-frequency conditions, it achieved mean absolute errors of 0.0035 and 0.0111, and root mean square errors of 0.0044 and 0.0133, respectively, demonstrating superior tracking performance compared to other control schemes. Full article

The increasing demand for hydrogen has made it a promising alternative for decarbonizing industries and reducing CO₂ emissions. Although mainly produced through the gray pathway, the integration of carbon capture and storage (CCS) reduces the CO₂ emissions. This study presents a sustainability method that uses flare gas for hydrogen production through steam methane reforming (SMR) with CCS, supported by a techno-economic analysis. Data Envelopment Analysis (DEA) was used to evaluate the oil company’s efficiency, and inverse DEA/sensitivity analysis identified maximum flare gas reduction, which was modeled in Aspen HYSYS V14. Subsequently, an economic evaluation was performed to determine the levelized cost of hydrogen (LCOH) and the cost–benefit ratio (CBR) for Nigeria. The CBR results were 2.15 (payback of 4.11 years with carbon credit) and 1.96 (payback of 4.55 years without carbon credit), indicating strong economic feasibility. These findings promote a practical approach for waste reduction, aiding Nigeria’s transition to a circular, low-carbon economy, and demonstrate a positive relationship between lean and green strategies in the petroleum sector. Full article

With the rapid development of China’s economy, railway transport has increasingly become the main mode of medium and long-distance transport in China. At the same time, we find that in the process of technical improvement, the greenhouse gases emitted from railway locomotives not only affect the environment but also have a big influence on operational effectiveness. In order to clearly understand whether the total undesired output—CO₂ emissions—will have an impact on railway efficiency and the environment, we proposed a Malmquist–Network DEA model. Based on the data of 18 railway bureaus in China during the period of 2006–2020, we adopted the Malmquist–NDEA model to analyze the different efficiencies of each stage of the railway operation in China and analyze the environmental efficiency of China’s railway using temporal and spatial dimensions. We found that (1) including the CO₂ emissions as an undesirable output in the model has an inverse effect on both the overall efficiency and the production consumption and profit stage efficiencies; (2) the average overall efficiency of these 18 rail bureaus has shown relative stability, and the negative effects of CO₂ on the construction development and production stages are much lower than on the consumption and profit stages; and (3) the rail systems in the eastern areas have higher efficiencies in their construction development stage compared to the other two areas. Full article

Objective: College students are at risk of disordered eating, particularly students with overweight/obesity and with higher stress, but little is known about how disordered eating may be related to diet. This study evaluated the associations between the Disordered Eating Attitudes Scale (DEAS) and age, BMI, stress, and diet. Methods: This is a secondary analysis of the baseline data in participants from the Snackability Trial. Participants completed a questionnaire on socio-demographics, DEAS, and snacking, self-reported their weight and height (to calculate BMI), and completed two 24 h non-consecutive dietary recalls (to calculate diet quality using HEI-2015 and snack quality score using an algorithm developed by our group). Associations between variables were assessed with Spearman correlations. Results: A total of 140 participants completed all assessments. The median age was 21.0 and the median BMI was 28.5 kg/m² (43.7% had overweight and 41.5% had obesity). A total of 86.4% were females, 41.4% were white, 51.4% were low-income, and 30.7% were Hispanic/Latino. The total DEAS and the subscale ‘Relationship with food’ were positively correlated with stress and BMI (p < 0.05) but inversely correlated with HEI-2015 (p < 0.05). The subscales ‘Restrictive and compensatory behaviors’ and ‘Concern about food and weight gain’ were also positively correlated with stress (p < 0.001). Conclusion: College students with higher disordered eating attitudes also had higher stress and BMI but poorer diet quality. Interventions may be needed for this group to manage stress and improve weight and diet quality, as well as promote awareness about disordered eating attitudes. Full article

Road freight transport, an essential component of the logistics sector, faces challenges: high cost, low efficiency, and environmental impact. The need has become urgent to achieve a synergistic balance between low-carbon and high-efficiency development. This study used a three-stage DEA–Malmquist index model to analyze the road freight efficiency of Wuhan and 16 other cities in China from 2015 to 2020, and we compared Wuhan’s performance with its peers. In addition, grey correlation analysis was used to evaluate the low-carbon development of urban road freight transport in Wuhan. Through the calculation of the degree of synergy between low-carbon development and freight transport efficiency, this study provides insights into the synergistic development of low-carbon and efficient road freight transport in Wuhan. The key findings show that the total factor productivity of road freight transport in Wuhan was generally on a downward trend from 2015 to 2020, and was lower than that of the average of the 17 selected Chinese cities. The carbon emissions of road freight transport in Wuhan inversely related to its scale efficiency. This study also points out that the synergy between low-carbon development and the economic efficiency of road freight transport in Wuhan is not high and needs to be further integrated and optimized. Full article

Strengthening the construction of ecological civilization is an inevitable requirement for promoting high-quality economic and social development. It is of great significance to study the evolutionary trend and relationship between urban spatial structure and ecological efficiency to promote high-quality social development. Taking Shandong Province as an example, this paper obtains data on urban factors such as points of interest, night light, number of employed people at the end of the year and water supply; uses Anselin Local Moran’s I index to identify urban centers; analyzes the distribution form characteristics and agglomeration degree of urban space; and studies the spatial distribution characteristics and causes of differences in ecological efficiency based on the Super-SBM DEA model with undesirable output. The results show that all cities in Shandong Province show an inverse S-shaped circle decreasing trend, Laiwu city has the highest compactness (compactness index is 2.96), and Tai ‘an city has the lowest compactness index of 0.04. The level of eco-efficiency in Shandong Province is “low in the west and high in the east”, and the difference in eco-efficiency between regions is increasing year by year. Urban compactness has a “first increasing and then decreasing” effect on eco-efficiency. Technological innovation and industrial structure narrow the spatial difference in eco-efficiency, and the level of economic development expands it to a certain extent. This study aims to fill the gaps in existing research. By analyzing data on the evolution of urban spatial structure and resource consumption, it will reveal the trends of changes in the urban spatial structure of Shandong Province and study the impact of these changes on ecological benefits. Full article

Economic growth is essential for nations endowed with natural resources as it reflects how well those resources are utilized in an efficient and sustainable way. For instance, OPEC member nations, which hold a large proportion of the world’s oil and gas reserves, may require a frequent evaluation of economic growth patterns to ensure that the natural resources are best used. For this purpose, this study proposes an inverse data envelopment analysis model for assessing the optimal increase in input resources required for economic growth among OPEC member nations. In this context, economic growth is reflected in the GDP per capita, taking into account possible environmental degradation. Such a model is applied to the selected OPEC member nations, which suggests that in terms of increasing the GDP per capita, only one member was able to achieve the best efficiency (i.e., reaching the efficiency frontier), resulting in a hierarchy or dominance within the sample countries. The analysis results further identify the economic growth potential for each member country. For the case of Indonesia, the analysis suggests that further economic growth may be achieved for Indonesia without additional input resources. This calls for diversification of the nation’s economy or investment in other input resources. In addition, the overall results indicated that each member nation could increase its GDP per capita while experiencing minimal environmental degradation. Our analysis not only benchmarks the growth efficiency of countries, but also identifies opportunities for more efficient and sustainable growth. Full article

Browsing is a prevalent activity on the World Wide Web, and users usually demonstrate significant expectations for expeditious information retrieval and seamless transactions. This article presents a comprehensive performance evaluation of the most frequently accessed webpages in recent years using Data Envelopment Analysis (DEA) adapted to the context (inverse DEA), comparing their performance under two distinct communication protocols: TCP/IP and QUIC. To assess performance disparities, parametric and non-parametric hypothesis tests are employed to investigate the appropriateness of each website’s communication protocols. We provide data on the inputs, outputs, and efficiency scores for 82 out of the world’s top 100 most-accessed websites, describing how experiments and analyses were conducted. The evaluation yields quantitative metrics pertaining to the technical efficiency of the websites and efficient benchmarks for best practices. Nine websites are considered efficient from the point of view of at least one of the communication protocols. Considering TCP/IP, about 80.5% of all units (66 webpages) need to reduce more than 50% of their page load time to be competitive, while this number is 28.05% (23 webpages), considering QUIC communication protocol. In addition, results suggest that TCP/IP protocol has an unfavorable effect on the overall distribution of inefficiencies. Full article

To achieve the goal of limiting global warming to 1.5 °C above preindustrial levels, net-zero emissions targets were proposed to assist countries in planning their long-term reduction. Inverse Data Envelopment Analysis (DEA) can be used to determine optimal input and output levels without sacrificing the set environmental efficiency target. However, treating countries as having the same capability to mitigate carbon emissions without considering their different developmental stages is not only unrealistic but also inappropriate. Therefore, this study incorporates a meta-concept into inverse DEA. This study adopts a three-stage approach. In the first stage, a meta-frontier DEA method is adopted to assess and compare the eco-efficiency of developed and developing countries. In the second stage, the specific super-efficiency method is adopted to rank the efficient countries specifically focused on carbon performance. In the third stage, carbon dioxide emissions reduction targets are proposed for the developed and developing countries separately. Then, a new meta-inverse DEA method is used to allocate the emissions reduction target to the inefficient countries in each of the specific groups. In this way, we can find the optimal CO₂ reduction amount for the inefficient countries with unchanged eco-efficiency levels. The implications of the new meta-inverse DEA method proposed in this study are twofold. The method can identify how a DMU can reduce undesirable outputs without sacrificing the set eco-efficiency target, which is especially useful in achieving net-zero emissions since this method provides a roadmap for decision-makers to understand how to allocate the emissions reduction targets to different units. In addition, this method can be applied to heterogeneous groups where they are assigned to different emissions reduction targets. Full article

Forest carbon sink efficiency refers to the efficiency of input-output indicators related to carbon sinks. This paper studies carbon sink efficiency from the perspective of resource allocation; guides the optimal allocation of resources; and selects forestry employees, forestry investment amount and afforestation area as input indicators; the forest carbon sink efficiency in China is calculated and analyzed based on a data envelopment analysis model by converting the forest volume into the forest carbon sink through the volume expansion factor method. The grey prediction model is used to estimate the change in the input indicator, and the production possibility set is constructed with the input indicator before and after the change and the current output indicator. The efficiency of the decision units before the change is calculated, and through the comparison of efficiency, the conditions of forest carbon sink increase in 15 provinces are obtained. The optimal allocation of the output indicator is calculated based on the inverse data envelopment analysis model. The largest increase in forestry carbon sink is 169,362 megatons in Guangdong, and the smallest is 619 megatons in Tianjin. Finally, some suggestions for the path of forest carbon sink increment are put forward. Full article

This study aims to assess the economic efficiency of Tunisian olive oil firms in order to identify the organizational and technological variables that are directly associated with greater efficiency. The Data Envelopment Analysis (DEA) and fuzzy sets Qualitative Comparative Analysis (fsQCA) method were used to achieve this. We find the managing director’s education level and information and communication technologies (ICT) training, the longevity of the company in inverse relationship with efficiency, the company’s presence on and use of virtual social networks, and the outsourcing of ICT management in combination have significant explanatory power in the companies that display greater economic efficiency. Full article

Financial and geophysical data, like many other low and high frequency time series, are known to exhibit some memory effects. These memory effects may be long or short, permanent or temporal depending on the event that is being modeled. The purpose of this study is to investigate the memory effects characterized by the financial market closing values and volcanic eruption time series as well as to investigate the relation between the self-similar models used and the Lévy process. This paper uses highly effective scaling methods including Lévy processes, Detrended Fluctuation Analysis (DFA) and Diffusion Entropy Analysis (DEA) to examine long-range persistence behavior in time series by estimating their respective parameters. We use the parameter of the Lévy process (α) characterizing the data and the scaling parameters of DFA (H) and DEA (δ) characterizing the self-similar property to generate a relationship between the three (3) aforementioned scaling methods. Findings from the numerical simulations confirm the existence of long-range persistence (long-memory behavior) in both the financial and geophysical time series. Furthermore, the numerical results from this study indicates an approximate inverse relationship between the parameter of the Lévy process and the scaling parameters of the DFA and DEA (i.e., $H,\delta \approx \frac{1}{\alpha }$ ), which we prove analytically. Full article

In recent years, there has been an increasing interest in applying inverse data envelopment analysis (DEA) to a wide range of disciplines, and most applications have adopted radial-based inverse DEA models. However, results given by existing radial based inverse DEA models can be unreliable as they neglect slacks while evaluating decision-making units’ (DMUs) overall efficiency level, whereas classic radial DEA models measure the efficiency level through not only radial efficiency index but also slacks. This paper points out these disadvantages with a counterexample, where current inverse DEA models give results that outputs shall increase when inputs decrease. We show that these unreasonable results are the consequence of existing inverse DEA models’ failure in preserving DMU’s efficiency level. To rectify this problem, we propose a revised model for the situation where the investigated DMU has no slacks. Compared to existing radial inverse DEA models, our revised model can preserve radial efficiency index as well as eliminating all slacks, thus fulfilling the requirement of efficiency level invariant. Numerical examples are provided to illustrate the validity and limitations of the revised model. Full article