Analysis of spatiotemporal difference and driving factors of green total factor energy efficiency in RCEP members: insights from SBM-GML and Tobit models

It is vital to determine the changing spatiotemporal patterns and driving factors of green total factor energy efficiency (GTFEE) in order to design scientific policies to promote energy efficiency in the Regional Comprehensive Economic Partnership (RCEP) region. From 2010 to 2019, the super-efficient SBM model and the global Malmquist-Luenberger index provide an appropriate framework for measuring the spatiotemporal evolution of GTFEE and the dynamics of energy productivity in RCEP countries. With the coefficient of variation and the Thiel index, an extensive view of the spatiotemporal variance in GTFEE is offered, taking regional heterogeneity into account. Furthermore, the Tobit model is introduced to investigate the factors influencing the GTFEE of RCEP members, which may address the restricted values of the dependent variable when compared to the least squares regression model. Findings suggest that (1) The GTFEE of RCEP members tends to be low and unevenly distributed spatially and temporally, with much room for improvement. (2) The energy productivity index fluctuates strongly, and the improvement primarily comes from technological progress. (3) The Non-ASEAN region possesses higher GTFEE than the ASEAN region, albeit regional variations are diminishing. (4) In terms of the major factors influencing the regional GTFEE, the non-ASEAN region looks to be distinct from the ASEAN region. The findings shed light on the trends and influencing factors of GTFEE in RCEP and serve as a resource for international energy cooperation and sustainable development.

Analysis of spatial and temporal characteristics of carbon emission efficiency of pig farming and the influencing factors in China

Pig farming has been a crucial contribution to China's food security although intestinal fermentation and its excrement during pig breeding are major sources of greenhouse gas emissions. In this paper, we measured the carbon emission efficiency of pig farming in 30 provinces (autonomous regions and municipalities) from 2010 to 2020 by using the non-expected output Slack-Based Measure (SBM) model and analyzed the spatial characteristics of the carbon emission efficiency of pig farming in China. We also examined and analyzed the factors influencing the carbon emission efficiency of pig farming by using the limited dependent variable model (Tobit). The results show that: the carbon emission efficiency of pig farming in China shows an M-shaped upward trend over time by comparing the carbon emission efficiency longitudinally during the study period and the carbon emission efficiency of pig farming shows a decreasing trend in the east, central and west regions of China by comparing the carbon emission efficiency of different regions horizontally. It's also shown that regions with low- and extremely-low-efficiency transfer from the east to the central and west regions and the central and regions with high-efficiency transfer to the east. The regression analysis of the factors influencing the carbon emission efficiency of pig breeding shows that the comparative advantage of the pig industry and transportation accessibility is positively correlated with the carbon emission efficiency of pig breeding, whereas the proportion of food resources and market scale is negatively correlated with the carbon emission efficiency of pig breeding. At the same time, the production layout index has no significant influence on the carbon emission efficiency of pig breeding. The research results provide a theoretical basis for regional differentiation of carbon emission management from pig farming, optimizing the layout of the pig industry and reducing environmental pollution.

Temporal and spatial changes and influencing factors of low-carbon economy efficiency in China

Low-carbon development has always been an important focus of China's economic transformation. In order to promote the development of low-carbon economy, this study used SBM-DEA model to evaluate China's provincial LCEE from 2005 to 2019, studied its temporal and spatial evolution law, used spatial autocorrelation to explore the correlation of China's provincial LCEE, and explored the key influencing factors of LCEE with Tobit model. The empirical results show that the LCEE of most provinces in China is declining, and there are significant differences among different regions in China. Because the eastern region of China can rely on its own human resources, capital environment, and economic foundation, the overall LCEE level is relatively high, while the central and western regions still have obvious deficiencies due to industrial conditions, geographical location, and other factors. LCEE has significant spatial correlation, and neighboring provinces have spillover effects on local LCEE. On this basis, the key factors that affect LCEE are determined. Urbanization level, traffic level, economic development level, financial development, investment in fixed assets, and energy consumption are the important factors that affect LCEE in China, but these influences vary from province to region. It is more reasonable for local governments to develop low-carbon economy according to their own conditions.

Urban Households' Willingness to Pay to Improve Municipal Solid Waste Collection Services and Associated Factors: A Double-Bounded Contingent Valuation Study in Harar City, Ethiopia

Municipal solid waste collection (MSWC) service financing is a challenge for governments in developing countries, with little or no contribution from the service users. In most Ethiopian cities, residents do not pay for MSWC. This study aims to estimate households' willingness to pay (WTP) for improved municipal solid waste collection service in Harar city. A cross-sectional study was conducted among 331 households employing the contingent valuation method with a double-bounded dichotomous choice format. The hypothetical program works to collect solid waste twice a week, house-to-house, and safely dispose of it to reduce environmental and health impacts. The Tobit regression model was used to account for the determinants of households' WTP. Findings showed that 89% (95% CI: 85.4, 92.5) of households were WTP for the improved waste collection program, with an average yearly amount of US$12. The Tobit model shows that being married (β = 6.9, 95% CI: 1.2, 13.7), having a monthly household income of >8000 ETB (β = 31.9, 95% CI: 22.1, 41.7), attending education about MSWM (β = 11.8, 95% CI: 5.6, 18.1), having temporary storage at household level (β = 15.3, 95% CI: 9.5, 21.2), and recycling practices (β = 5.5, 95% CI: 1.2, 10.8) positively influenced the WTP. Interventions like providing educational programs about waste handling and recycling and providing or encouraging households to have temporary storage at the household level are needed to enhance users' WTP. The policy implication of the finding is that community contribution through service fees could be a strategy for sustainable financing.

Analysis and Measurement of Barriers to Green Transformation Behavior of Resource Industries

To effectively guide and stimulate the green transformation behavior of resource industries and promote the sustainable and high-quality development of the region, it is necessary to deeply analyze and clarify the barrier factors of the green transformation behavior of resource industries. This study measures the green transformation efficiency of the resource industries by selecting the panel data of the mining industry from 29 Chinese provinces, based on the DEA-SBM model, and employing the ideas and methods of system engineering, for the years 2012-2019. Hence, the study employs the Tobit model to verify the factors that hinder the green transformation behavior of the resource industries. The results show that the (1) resource industries' barriers against the green transformation behavior form a significant barrier effect by inhibiting the efficiency of green transformation; (2) there is a difference in the intensity of the effect of the resource industries' barriers to the green transformation behavior; (3) regional heterogeneity exists in the effects of the barriers to the green transformation behavior of the resource industries. The findings of the study can provide a scientific basis for further improving the effectiveness of policies related to the green transformation behavior of resource industries.

Exploring Tourism Efficiency and Its Drivers to Understand the Backwardness of the Tourism Industry in Gansu, China

Gansu Province is rich in tourism resources, and it is the hometown of the "copper galloping horse", which is the logo of China's tourism. However, the scale and revenues of tourism in Gansu province are still at a low level. This paper first evaluated the tourism efficiency of 14 cities and prefectures of Gansu Province in China from 2011 to 2019 using the super-slack-based measure (Super-SBM) and then investigated the internal driving mechanism of the efficiency change through the Global Malmquist-Luenberger (GML) index and its decomposition, and finally analyzed the external influencing elements of tourist efficiency by the Tobit model. The results revealed that the tourism efficiency of Gansu Province had increased rapidly during the study period, especially after 2016, the rising range increased. From 2011 to 2019, the cumulative changes in GML index, technological change (TC), and efficiency change (EC) of tourism efficiency in Gansu Province were 5.053, 4.145 and 1.160, respectively, indicating that the improvement of tourism efficiency in Gansu province is mainly due to technological progress. The regression results of the Tobit model show that the status of the tourism industry, trade openness, information level, and technological innovation level can significantly promote tourism efficiency in the province. At the same time, upgrading the industrial structure and the improvement of greening coverage inhibit tourism efficiency. However, the impact of the economic development level on the tourism efficiency of Gansu Province is not apparent. According to the research results, this paper puts forward corresponding suggestions to promote the development of tourism in Gansu Province. This study is crucial for hospitality, tourism, and policy sectors to understand the underlying factors and promote the healthy development of the tourism industry in Gansu Province.

Willingness to pay to enhance pandemic preparedness in Mauritius

OBJECTIVES

The objective of this study is to assess the determinants of willingness to pay to enhance pandemic preparedness in Mauritius.

STUDY DESIGN

A contingent valuation method is used to estimate willingness to pay to pay for enhancing pandemic preparedness using a sample of working people in Mauritius.

METHODS

A two-phase decision process analysis is carried out to model the willingness to pay to enhance pandemic preparedness. The first phase is to analyse the respondents' decision of whether or not to pay for enhancing pandemic preparedness using a Probit model. The second phase is to estimate the determinants of the amount of money respondents are willing to pay using a Tobit model.

RESULTS

Income earners are willing to pay an average of Rs. 1,900 (approximately USD 50) per annum to enhance pandemic preparedness. 'Perceived Response Efficacy', 'Awareness of the Need and Responsibility for Paying', 'Subjective Obligation to Pay' and the 'Theory of Planned Behaviour' are found to affect both stages of of the decision-making process. Knowledge on COVID-19 is found to have a positive impact on the decision to pay and health responsibility attitude is found to have a negative impact on the amount people are willing to pay.

CONCLUSIONS

On average, the government can potentially expect to mobilise an additional Rs. 1,047,470,000 (USD 27,565,000) from taxpayers to spend on enhancing pandemic preparedness in Mauritius. To increase willingness to pay for enhanced pandemic preparedness, the government can focus on improving knowledge on a pandemic, perceived response efficacy and awareness on need and responsibility of paying.

Willingness to pay for packaging cancer screening of Chinese rural residents

BACKGROUND

This study examined the acceptance and willingness to pay (WTP) of rural residents toward packaging cancer screening (PCS) to provide a reference basis for promoting the screening sustainable development.

METHODS

A face-to-face questionnaire survey was conducted among rural residents aged 40-69. The combination of double-bounded dichotomous choices and open-ended questions in the Contingent Valuation Method was used to guide participants' WTP. Logistic regression was used to explore the influencing factors of participants' screening acceptance, and Tobit model was used to analyze the associated factors of WTP.

RESULTS

Of the 959 respondents, 89.36% were willing to accept PCS, but 10.64% stated unwillingness for the dominant reason that they did not attend clinics until symptom onset. Willingness to accept screening was significantly associated with region (Dongchangfu, OR = 0.251, 95%CI: 0.113~0.557; Linqu, OR = 0.150, 95%CI: 0.069~0.325), age with 60-69 (OR = 0.321, 95%CI: 0.126~0.816), annual income with 10,000-30,000 (OR = 1.632, 95%CI: 1.003~2.656) and having cancer-screening experience (OR = 0.581, 95%CI: 0.371~0.909). And 57.66% of participants were willing to pay part of the screening cost among those willing to accept PCS. The residents' average WTP was ¥622, accounting for 20.73% of the total cost (¥3000). Willingness to pay for PCS was positively correlated with male gender, self-employed occupation, residence in Feicheng (than Linqu), higher income, and having cancer-screening experience.

CONCLUSIONS

Most rural residents were willing to accept free PCS, more than half of them were willing to pay part of the ¥3000 total cost, but their WTP-values were low. It is necessary to carry out PCS publicity activities to improve public awareness and participation in precancerous screening. Additionally, for expanding the coverage and sustainability of screening, the appropriate proportion of rural residents to pay for screening costs should be controlled at about 20%, and governments, insurance and other sources are encouraged to actively participate to cover the remaining costs.

The efficiency of health resource allocation and its influencing factors: evidence from the super efficiency slack based model-Tobit model

BACKGROUND

This study aims to analyze the health resource allocation efficiency in Sichuan Province from 2010 to 2018 and provide other countries with China's experience.

METHODS

We used the super efficiency slack based model (SBM) model and Malmquist index to analyze the super efficiency and inter-period efficiency of health resource allocation in 19 cities in Sichuan Province from 2010 to 2018 and propose the input-output optimization scheme of health resource allocation in 2018. Finally, the Tobit model was used to estimate the influencing factors of health resource allocation efficiency.

RESULTS

The total allocation of health resources in Sichuan Province was increasing in addition to the total number of visits from 2010 to 2018. The super efficiency SBM results identified that the sample's average score was between 0.651 and 3.244, with an average of 1.041, of which 15 cities had not reached data envelopment analysis effectiveness. According to the Malmquist index, the average total factor productivity index of Sichuan Province was 0.930, which showed an imbalance in resource input, and its fluctuation was mainly related to the technological progress index and scale efficiency. The efficiency score was affected by the average annual income of residents, population density and education level.

CONCLUSIONS

The amount of health resource allocation in Sichuan Province had shown an overall upward trend since 2010. However, resource allocation efficiency was not high, and there were problems such as significant regional differences, insufficient technological innovation capabilities and unscientific allocation of resource scale. To optimize the resource allocation structure, we suggest that the relevant departments pay attention to the impact of natural disasters, the average annual income of residents, population density and education level on efficiency to allocate health resources scientifically.

Study on the Coupling Coordination between New-Type Urbanization and Water Ecological Environment and Its Driving Factors: Evidence from Jiangxi Province, China

With the rapid development of urbanization, problems such as the degradation of water ecological environment have emerged. How to improve the water ecological environment in the process of urbanization has become one of the urgent problems facing policy makers. This paper studies the coupling coordination relationship between new-type urbanization and water ecological environment, with the purpose of using insights gained from the study to help improve the quality of water ecological environment and promote sustainable development of water ecological environment. We take 11 cities in China's Jiangxi Province as the research object, and construct the coupling coordination evaluation indicator system of new-type urbanization and water ecological environment, then using the coupling coordination degree model to examine the state of coupling coordination between new-type urbanization and water ecological environment from 2009 to 2019. We further explore its driving factors employing random effect panel Tobit model. The results show that: (1) The level of new-type urbanization in Jiangxi Province shows a steady upward trend, and the water ecological environment level tends to rise steadily and slowly, although the comprehensive score of water ecological environment in most cities is lower than 0.1, indicating that the situation of water ecological environment is not optimal yet and there is room for improvement. (2) In 2009, 2014 and 2019, the coupling coordination development level between new-type urbanization and water ecological environment in Jiangxi Province showed an upward trend, from moderate maladjustment recession to mild maladjustment recession, and from low coupling coordination to moderate coupling coordination, although the overall coupling coordination degree was low. (3) The investment in scientific and technological innovation, degree of opening-up and government capacity are positively correlated with the coupling coordination degree, while economic development level, resource agglomeration ability, education level and industrialization level are negatively correlated with the coupling coordination degree. These results can provide insights to support new-type urbanization and water ecological environment in the future, and hold great significance for urban sustainable development.

Investigating the eco-efficiency of China's textile industry based on a firm-level analysis

Industrial eco-efficiency has been an invaluable measurement for the relationship between production activities and environmental depletion, which is important to investigate when aiming for sustainable development. For the textile industry, however, limited rigorous studies have comprehensively evaluated the eco-efficiency from a firm-level perspective, and research on multi-level comparisons of the sub-sectors has also been lacking. Given the differences in environmental impacts due to the selection of various raw materials and unstandardized production processes in the textile industry, we focused on three sub-sectors, i.e., the cotton, chemical fibers textile sector (CCTS), the non-cotton textile sector (NCTS), and the printing and dyeing sector (PDS). By applying the slacks-based measure (SBM) model based on the principle of the data envelopment analysis (DEA), i.e., the SBM-DEA model, the eco-efficiency of China's textile industry was measured at the firm level from 2001 to 2011 using a large sample dataset. We then further analyzed the factors affecting eco-efficiency using the Tobit regression model. An empirical analysis showed an upward trend of eco-efficiency over time in the eastern, central, and western regions of China with great disparities for the three sub-sectors. Analyses of the typical provinces in the eastern region all showed increasing trends in eco-efficiency, with Shandong Province consistently performing the best. We also found that large-scale firms had the highest annual average eco-efficiency than that of small- and medium-scale firms. For the influencing factors on the eco-efficiency, our results indicated that the economic scale and export delivery value both had a significant positive correlation with the eco-efficiency, while foreign direct investment and environmental regulation were both significantly negative for the eco-efficiency in all three sub-sectors. These findings provide valuable insights into helping the textile industry address high-quality green development and sustainability.

Energy efficiency of the industrial sectors in Beijing-Tianjin-Hebei urban agglomeration: does technological gap matter?

As the political and technological innovation center of China, Beijing-Tianjin-Hebei urban agglomeration (BTHUA) is an important engine of national economic development. However, the BTHUA is faced with uneven industrial development and environmental pollution problems. Energy efficiency of the industrial sector, critical to energy conservation and environmental protection, is the key to achieving green economic transformation. For this reason, this study adopts the parametric meta-frontier approach to measure the industrial total-factor energy efficiency (TFEE) of the BTHUA, centering on the evaluation of regional technology gap ratio (TGR). Empirical results indicate that there are significant regional disparities of industrial TFEE in the BTHUA. In particular, industrial TFEE tends to be underestimated without considering technological heterogeneity in production technology. The TGRs of manufacturing cities, tourist cities, and the modernized metropolis (Beijing) are the highest among the region. On this basis, the influencing factors of industrial TFEE of the BTHUA are further accessed based on the fixed effects model and the Tobit model. This article verifies that the evaluation of TFEE in the BTHUA must take regional technological gap into account, and provides additional empirical evidence on how to promote coordinated regional industrial development and energy efficiency improvement.

Socioeconomic Disparities in Health Care Consumption: Using the 2018-China Family Panel Studies

The existing research on residents’ health care consumption mostly covers medical care consumption and seldom regards residents’ health care consumption as an independent research object. This article takes residents’ healthcare consumption as the research object and aims to explore the impact of socioeconomic status on healthcare consumption and its mechanisms. The data of this study came from the 2018-China Family Panel Studies (CFPS). The binary probit regression model and the Tobit model explored the impact mechanism of residents’ income, education, occupation, and physical activity on health care consumption decision-making and health care expenditure, respectively. The research results showed that, from the perspective of the direct influence mechanism, residents’ work income (0.029, p < 0.01) and education level (811.149, p < 0.01) had a significant positive impact on health care consumption. Residents whose occupations (−99.697, p < 0.01) tend to be more skilled and also have higher health care consumption. From the perspective of the mediating mechanism, residents’ physical exercise duration had a significant positive impact on their participation in healthcare consumption (0.005, p < 0.01) but had a weaker impact on healthcare consumption expenditure (21.678, p < 0.1). In general, socioeconomic status represented by income, education, and occupation had a significant positive impact on residents’ health care consumption. The duration of physical exercise also played an important mediating role.

Intensity of adoption and welfare impacts of drought-tolerant rice varieties cultivation in Bangladesh

Rice production in Bangladesh is vulnerable to climate-related risk such as drought, which contributes to food insecurity. Adoption of drought-tolerant rice varieties can play an important role in increasing productivity, food grain supply, and income. However, to the best of our knowledge, no studies have measured the welfare impacts of drought-tolerant rice varieties in the South Asian and Bangladeshi context. Therefore, this study identifies the factors that influence the intensity of adoption and welfare impacts of drought-tolerant rice varieties in Bangladesh. To accomplish these objectives, 300 rice growers from three drought-prone districts of Bangladesh were surveyed. To analyze the impacts, the entire sample was divided into three groups depending on their share of land under drought-tolerant rice variety cultivation: full adopters, partial adopters, and non-adopters. The descriptive statistics, two-limit Tobit model and multivalued treatment effect models were used to analyze the data. According to the findings, training as well as technology-related factors play a major role in boosting the intensity of adoption. Full adopters of drought-tolerant varieties receive 1222-1473 kg higher yield per hectare compared to non-adopters. Based on several treatment effect models, the impact on income ranges from 3.46% to 4.22%. When compared to non-adopters, full adopters can consume 1.02-1.29 months more rice from their own production in a year. Shows about climate change and other relevant topics should be broadcast on the television on a regular basis to raise awareness. Modifying the extension method with modern communication technologies will aid in widespread adoption of new technologies. Drought-tolerant rice varieties can help to mitigate the harmful effects of drought and alleviate poverty in drought-prone areas.

Can Green Economy and Ecological Welfare Achieve Synergistic Development? The Perspective of the "Two Mountains" Theory

China’s high-speed economic growth and severe environmental problems have resulted in a poor Environmental Performance Index and have affected China’s sustainable development and ecological welfare improvement. Therefore, exploring whether there is a certain relationship between the two and their influencing factors is an important way and a breakthrough to solve the problems regarding green economic progress and ecological welfare enhancement. To this end, by using the undesirable slack-based measure (SBM) model, this paper measures the ecological welfare performance and the green economic efficiency of 11 cities in Zhejiang Province, China, from 2000 to 2019. Through the methods of spatiotemporal evolution, coefficient of variation, coupling coordination degree, and the Tobit model, we found that: (1) The development trend of urban green economic efficiency and ecological welfare performance were both in a “U” shape that first fell and then rose; (2) The coupling coordination degree between green economic efficiency and ecological welfare performance showed a wave-like upward trend as a whole and most cities have entered a more advanced coupling coordination stage during the study period. The coefficient of variation revealed a downward trend; (3) The urbanization level, industrial structure, and government investment can promote the regional coordinated development, while the industrialization degree and the opening level had a negative impact on it; (4) The “Two Mountains” theory was beneficial to the improvement of regional urban green economic efficiency and ecological welfare performance and their coordinated development both in theory and practice. Finally, according to the findings, we offer relevant suggestions on making good use of the country’s preferential policies and informatization means from the perspective of the regional coordinated development.

Evaluation and Influencing Factor Analysis of Sustainable Green Transformation Efficiency of Resource-Based Cities in Western China in the Post-COVID-19 Era

Under the impact of the coronavirus disease 2019 (COVID-19), green, low-carbon, and sustainable development has become a global consensus, and the world will enter a low-carbon and intelligent production mode faster. As the largest contributor to world economic growth and an active participant in global environmental governance, achieving green recovery and the high-quality economic and social development of China is of great significance to promote the global sustainable development strategy. The green transformation of resource-based cities in Western China is the key factor for China to build a high-quality modern economic system and promote long-term sustainable development. This article used the Super Efficiency Slack Based Model (Super-SBM) model and Malmquist index model of the Data Envelope Analysis (DEA) method to measure the static and dynamic green transformation efficiency of resource-based cities in Western China. It investigated the impact of different factors on the static and dynamic efficiency by constructing panel Tobit and dynamic panel models. The research found that the static efficiency of the green transformation of resource-based cities in Western China is low, and the development is uneven. The dynamic efficiency of green transformation showed a fluctuating upward trend first and an accelerating upward trend later. Different factors have different effects on green transformation efficiency. This article holds that the combination of post-epidemic economic recovery and green transformation is expected to promote the green transformation of western resource-based cities while injecting new vitality into China's green sustainable development in the post-COVID-19 era.

Assessing the financial efficiency of healthcare services and its influencing factors of financial development: fresh evidences from three-stage DEA model based on Chinese provincial level data

Pediatrics is an integral part of public health services. With the impact of the epidemic and the high-quality transformation of China's development, the contradiction in the supply of pediatric public services has become more prominent. Scientific evaluation of the efficiency and quality of pediatric services, clarifying the redundancy of pediatric input resources and adjusting the construction of pediatric services with the help of influencing factors have become important research topics. This paper uses the three-stage SBM-DEA model to summarize the efficiency of China's pediatric services using panel data from 31 provinces and cities in 2008-2019, taking into account undesired outputs such as doctor-patient disputes. Among them, the evaluation system focuses on the role of financial, capital, and other factors, and the Tobit regression model is used to clarify the degree of influence of various factors. The study found that (1) China's pediatric service supply has the characteristics of geographic heterogeneity. (2) The redundancy of various resource inputs is apparent, and the supporting capacity of financial capital is not significant. (3) The economic, technological, and professional environment helps to digest the redundancy of inputs. (4) Capital, urbanization, education development, and birth rate increase under financial operation will promote the increase of the efficiency of pediatric public services.

Joint Optimization of Kinematics and Anthropometrics for Human Motion Denoising

In this paper, we propose a novel technique for human motion denoising by jointly optimizing kinematic and anthropometric constraints for a noisy skeleton data. Specifically, we are focused on depth-sensor-based motion capture (D-Mocap) data that are often prone to error, outliers and distortion. To capture human kinematics, we first propose a joint-level Tobit particle filter (TPF) that incorporates a unique observation model to characterize the censored measurement of D-Mocap data. A skeleton-level Differential Evolution (DE) algorithm is then integrated with the sequential Monte Carlo sampling in the TPF, allowing joint-level particles to be re-distributed and re-weighted according to the stability and consistency of skeletal bone lengths as well as the suitability of joint kinematics. This leads to an integrated TPF-DE algorithm that significantly improves the quality of D-Mocap data by making 3D joint trajectories more kinematically admissible and anthropometrically stable. Experimental results on both simulated and real-world D-Mocap show that the errors of joint positions and the bone lengths have been reduced by 30-60%, and the accuracy of joint angles has been improved by 40-60%. The proposed TPF-DE method outperforms the recent filtering-based and deep learning methods and demonstrate the synergy between the TPF and DE algorithms for effective human motion enhancement.

Hospital efficiency measurement in the west of Iran: data envelopment analysis and econometric approach

Objective

Measuring hospital efficiency is one of the way how to use resources.The optimal hospital performance is the goals of healthcare policymakers. This study aimed to the current study was conducted to evaluate the efficiency the current study was conducted to evaluate the efficiency and assess the association between hospital size and hospital area population with technical efficiency in public hospitals.

Methods

In this descriptive-analytical study, the statistical population consisted of 15 public hospitals in the west of Iran. First, the data envelopment analysis (DEA) method was used to evaluate technical efficiency. inputs included staff and beds, and outputs consisted of the number of surgeries, the number of patients, and the average length of stay. Then, according to the public ownership of all hospitals, their educational and therapeutic activities, as well as their size and population were considered as the environmental factor affecting efficiency. Thus, regression was applied to measure their effects on efficiency.

Results

The average technical efficiency of the studied hospitals, the average management efficiency, and the average efficiency of the scale were 0.935, 0.961, and 0.987, respectively. Out of the total evaluated hospitals, six and nine hospitals had an efficiency of less than one and one, respectively. Moreover, the size of the hospital and the population as the environment variable were significant in the Tobit model. Our regression demonstrated that although the size of the hospital is positively associated with its technical efficiency, the hospital population negatively affects hospital efficiency.

Conclusion

According to the size and area population of the hospitals, they decrease their inputs to maximize their efficacy by optimizing their surplus amounts. Tobit regression analysis concludes that hospital size and population covered by the hospital significant effect on hospitals' efficiency.

Evaluating Green Innovation Efficiency and Its Socioeconomic Factors Using a Slack-Based Measure with Environmental Undesirable Outputs

Understanding green innovation efficiency (GIE) is crucial in assessing achievements of the current development strategy scientifically. Existing literature on measuring green innovation efficiency with considering environmental undesirable outputs at the city level is limited. Consulting existing studies, this paper constructs an evaluation index system to measure green innovation efficiency and its socioeconomic impact factors. Employing a super slacks-based measure (Super-SBM) model, which takes into account undesirable outputs (industrial wastewater emissions, industrial exhaust emissions and CO₂ emissions), and a Global Malmquist–Luenberger index (GML), we calculate the green innovation efficiency of 15 cities in the Pearl River Delta (PRD) urban agglomeration from 2009 to 2017, exploring the impact factors behind green innovation efficiency using a Tobit panel regression model. The empirical results are as follows: Due to the heterogeneity of urban functional division and economic development in the Pearl River Delta, more than half of the region’s cities were found to be in ineffective or transitional states with respect to their green innovation efficiency. A GML decomposition index shows that technological efficiency and technological progress are out of step with one another in the Pearl River Delta, an asymmetry which is restricting regional green innovation growth. The influencing factors of industrial structure, the level of economic openness, and the urban informationization level are shown to have promoted green innovation efficiency in the Pearl River Delta’s cities, while government R&D expenditure and education expenditure exerted negative effects. This paper concludes by highlighting the importance of cooperation between the government and enterprises in achieving green innovation.

[Influence of Social Capital on the Life Quality of Patients with Chronic Diseases-A Study Based on EQ-5D-5L Scale]

OBJECTIVE

To explore the influence of social capital on the quality of life of patients with chronic non-communicable diseases.

METHODS

A multi-phase stratified cluster sampling method was adopted to select the survey respondents. Professionally trained surveyors made home visits in order to conduct face-to-face questionnaire surveys in person. European Quality of Life Five Dimension Five Level Scale (EQ-5D-5L) and a self-developed social capital scale were used to investigate the quality of life and social capital of the respondents. Factor analysis and Cronbach's α coefficient test were done to verify the reliability and validity of the self-developed social capital scale. The χ 2 test and robust Tobit regression model were used to analyze the impact of social capital on the quality of life of patients with chronic non-communicable diseases.

RESULTS

The self-developed social capital scale showed excellent performance. The Cronbach's α coefficient was 0.728, the KMO value was 0.716, and the result of Bartlett's test of sphericity was statistically significant ( P<0.001), indicating that the data were well suited for factor analysis. The four common factors cumulatively explained 68.27% of the total variation. The health utility value of the survey respondents was 0.869±0.181. Those who could walk around, shower and dress themselves, and perform usual activities without any problem accounted for 75.70%, 80.10%, and 74.1% of the respondents, respectively. Those who had pain or discomfort and anxiety or depression, with no self-perceived problem were 43.40% and 58.90%, respectively. In the EQ-5D-5L scale, the self-rated health influencing factors of the physical health dimension were community safety and interpersonal network relationships. The influencing factors of social function health was community safety and mental health was affected by community safety, community trust and interpersonal network relationships. When community safety improved by one level, the health utility value of patients with chronic non-communicable diseases increased by 0.046, and when interpersonal network relationships improved by an additional level, their health utility value increased by 0.037.

CONCLUSION

The main problem of the quality of life of patients with chronic non-communicable diseases was found in the mental health dimension. In the process of treating chronic non-communicable diseases, attention should also be given to psychological counseling. Community safety and interpersonal network relationships are the protective factors for self-rated health status. Providing a safe community environment and expanding interpersonal networks help improve the health of patients.

Mothers' Acceptance and Willingness to Pay an Out-of-Pocket Payment for Maternal and Child Nutritional Services in Northwest Ethiopia

BACKGROUND

Around $3.5 trillion globally and up to $2.78 billion in Ethiopia, losses are reported annually due to malnutrition. Even if in Ethiopia nutrition services are delivered free of charge, specific public health programs may start to charge users of services that include maternal and child health services. Therefore, this study was aimed to assess mothers' willingness to pay an out-of-pocket payment for maternal and child nutritional services and associated factors in Northwest Ethiopia.

METHODS

A community-based cross-sectional study design was conducted at Yilmana Densa district from March to May 2017. The sample size was 569, and a systematic random sampling technique was used. Bi-variate, multivariable logistic regression, and Tobit econometric analysis models were done. Adjusted odds ratio (AOR) and B-coefficient with 95% confidence interval (CI) and p-value were used.

RESULTS

A total of 545 (response rate of 95.8%) study participants were included in the study. The finding indicates that 88.8% of households were willing to pay for maternal and child nutrition services. The average amount of money to pay per visit was 19.6 ETB (CI = 18.8, 20.4) (0.84 USD). Mothers with good knowledge, good perceived family health status, medium and high perceived quality of services, and satisfaction with maternal and child nutritional services were significant variables to accept an out-of-pocket payment. In addition, the Tobit econometric model analysis reveals that knowledge, mothers' age, pregnancy status, mothers' educational status, wealth status, and self-reported satisfaction were identified as significant factors.

CONCLUSION

The majority of mothers were willing to accept out-of-pocket payments for maternal and child nutritional services with an average of 19.6 ETB. Therefore, strengthening awareness and improving the quality of nutritional services and maternal satisfaction may increase mothers' willingness to pay an out-of-pocket payment.

The Impact of Mental Health Status on Health Consumption of the Elderly in China

Based on the national baseline survey data of the CHARLS2015, the comprehensive evaluation index of depression degree of the elderly in China is calculated using a principal component analysis method. The Tobit model is used to investigate the influence of mental health status with depression degree as a proxy variable on the health consumption of the elderly in China. The results show that the overall effect and the phased effect of depression on the health consumption of the elderly are positive. In other words, high levels of depression lead to a higher probability and amount of health consumption. Research findings show that chronic illness and increased social activity can weaken the effect of depression on the health spending of the elderly. Fully considering the factors affecting the mental health of elderly people is required to improve their level of mental health. Importantly, the quality audit system of health products and the supervision and management system of the health consumption market should be improved to realize the benign operation of the health consumption market.

The impact of economic growth, FDI, and innovation on environmental efficiency of the logistics industry in provinces along the belt and road in China: An empirical study based on the panel Tobit model

Due to the high-quality development of the Chinese economy, the improvement of environmental efficiency in Chinese industries has become a significant task. Understanding the environmental efficiency of the logistics industry is essential for implementing effective environmental policies. This study aims to explore the impacts of economic growth, foreign direct investment (FDI), and innovation on the environmental efficiency of the logistics industry. In this paper, we apply the undesirable SBM model to calculate the environmental efficiency of the logistics industry and use the Tobit model to analyze the impacts of economic growth, foreign direct investment (FDI), and innovation on the environmental efficiency of the logistics industry in provinces along the Belt and Road in China from 2009 to 2018. Based on the results indicate the average environmental efficiency of the logistics industry in Chinese provinces along the Belt and Road is 0.7880, indicating that the environmental efficiency of the logistics industry was generally low in some regions along the belt and road. Innovation and FDI were found have a significant impact on the environmental efficiency, while economic growth fails to significantly impact on the environmental efficiency of the logistics industry in provinces along the Belt and Road. Therefore, we should encourage improvement of the level of environmental efficiency of the logistics industry. It is necessary to realize the co-ordinated development of the logistics industry and the environment through optimization of the development of innovation and transforming the FDI model in provinces along the Belt and Road.

Do consumers understand health claims on extra-virgin olive oil?

Health claims have been introduced in food labelling to support consumers' awareness of healthy food choices and to enhance a healthy diet. Even though many countries around the world have developed legislation and guidelines to regulate the introduction of health claims on food labels, there is the evidence that many consumers do not understand the meaning of these claims. This study analyses whether Italian consumers really understand authorized health claims on extra-virgin olive oil and what are the drivers of such understanding. An Olive Oil Health Claims Understanding index was constructed and embedded in a structured questionnaire, which was then administered to a representative sample of Italian household members who are responsible for food shopping (N = 1,030). Results from the survey showed that only 36% of the respondents understood the meaning of the authorized health claims on extra-virgin olive oil. Moreover, the findings confirmed that the understanding of health claims is related to socio-demographic, personal and psychographic characteristics of consumers, as well as to their attitudes toward using food as medicine. Outcomes also proved the central role of nutrition knowledge in affecting understanding of health claims.