Efficiency evaluation of China's transportation system considering carbon emissions: Evidence from big data analytics methods

China's transportation sector is a vital link between production and consumption, but it also has issues with low efficiency, high carbon emissions, and technological bottlenecks. To improve efficiency and provide actionable recommendations and strategies, this study first constructs a comprehensive evaluation index system to gauge the transportation sector's inputs using panel data from different Chinese provinces from 2007 to 2021. Within the assessment system, the principal component analysis (PCA) method is used to reduce the dimension of the indexes, thereby yielding a set of adjusted inputs. Subsequently, the transportation system efficiency (TSE) is evaluated using the super-efficiency SBM-DEA model, which includes unexpected outputs such as carbon emissions, and three-stage DEA modifies the efficiency. Then, we calculate the Malmquist-Luenberger index (TML) and its components: technological change (TTC) and technological efficiency change (TEC). Lastly, the influential factors impacting TSE are analyzed via a truncated regression Tobit model. The following are the conclusions: (1) The transportation industry in China exhibits inefficiency, and the average TSE in Stage I and III is 0.91 and 0.93, respectively. TSE is underestimated due to the influence of external environmental factors and inefficiencies in management in Stage I. (2) TSE in the eastern area also produces significant carbon emissions that surpass the national average. At the same time, other regions face efficiency limitations due to geographical constraints and management obstacles. (3) Insufficient technical capacity is a major cause of inefficiency in the transport sector and is prevalent in the northeast, west, and central regions. (4) Population growth and income per capita advancements foster transportation industry development, while increased GDP, fiscal revenues, and traffic accidents contribute to declining efficiency. The study above findings serve as a foundation for regional and national management initiatives and policies to enhance transportation effectiveness.

Optimization of coupling crop and livestock production system's eco-efficiency in northern China based on a life cycle assessment and data envelopment analysis method

Under the twin pressures of global food security and dual‑carbon strategies, improving farm eco-efficiency is critical for achieving China's goal of a 50 Pg increase in grain production, meeting the ambitious climate mitigation targets set by the Paris Agreement, and meeting seven of the seventeen Sustainable Development Goals (SDGs) set by the United Nations. However, there is limited research on eco-efficiency measures supported by localised fine-scale data and coupling mechanisms for the structure, production process, efficiency improvement, and carbon reduction synergies of integrated farming systems in China. This study used the Life Cycle Assessment (LCA) and Data Envelopment Analysis (DEA) methods to assess eco-efficiency at the farm level in northern China, included in the National Coupling Crop and Livestock Production Pilot Programs, to improve the eco-efficiency of farms to achieve increased production and emission reductions. The results showed that the overall eco-efficiency of farms was in the lower-middle range, with only 20.18 % of the farms having a technical efficiency exceeding 1. Problems included a backward level of pure technical efficiency and a return to scale. Non-integrated farms have the lowest profitability (41.33 %) and the highest carbon emission intensity of 3.03 kg CO2eq/USD. The global warming potential impact of non-integrated farms optimization could be reduced by 25 Pg CO2eq. Implementing the integrated farming mode has a significant advantage in reducing carbon emissions and improving productivity. Overall, farm fodder optimization can be increased by up to 42.41 %. Simultaneously, farms with sufficient farmland are more likely to realise a highly integrated business mode for crop cultivation and livestock breeding. Therefore, constructing a new type of green integrated farming system will help farms achieve increased production and emission reductions, promote the development of sustainable agriculture, and provide a Chinese model for the realisation of global SDGs.

Study on the measurement of coupling and coordinated development level between China's internet and elderly care services and its influencing factors

BACKGROUND

With the intensification of China's aging population, the demand for elderly care services has become increasingly prominent. At the same time, rapid development of internet technology provides more convenience and possibilities for the elderly. However, the coordinated development between the internet and elderly care services still faces challenges. This study aims to measure the level of coupling and coordinated development between the internet and elderly care services in China, and analyze the influencing factors, in order to provide reference for promoting elderly care services.

METHODS

In this paper, the entropy method and coupling coordination degree model were used to measure the coupling coordination development index of the internet and elderly care services in China from 2012 to 2021. In addition, considering that the coordinated development between the two is affected by many factors, the Tobit model was used to analyze the main factors affecting the integration of the internet and elderly care services.

RESULTS

(1) The coupling and coordination of the Internet and senior care services is in its infancy, but the coupling and coordination of the two is on the rise, and there is still a lot of room for development in the future. (2) In terms of time scale, the coupling coordination development level between the internet and elderly care services in China has gone through three stages of "disorder recession-transition coordination-coordinated development". (3) In terms of influencing factors, government management ability has a more positive impact on the development of the integration of the Internet and senior care services, financial support, scientific and technological investment and the level of innovation play a mild pulling role, while the level of informatization to a certain extent restricts the level of integration of the Internet and senior care services.

CONCLUSION

In order to promote the coordinated development of China's Internet and senior care services, it is necessary to comprehensively understand the current situation and development space of China's Internet and senior care services coupling coordination degree, accurately grasp the dynamic trend of China's Internet and senior care services coupling and coordinated development, promote the stage of leapfrogging, and fully consider the influencing factors, so as to realize the optimal allocation of policies and resources. These measures will help to promote a more coordinated and sustainable development of the internet and elderly care services in China.

Mixture of regressions with multivariate responses for discovering subtypes in Alzheimer's biomarkers with detection limits

There is no gold standard for the diagnosis of Alzheimer's disease (AD), except from autopsies, which motivates the use of unsupervised learning. A mixture of regressions is an unsupervised method that can simultaneously identify clusters from multiple biomarkers while learning within-cluster demographic effects. Cerebrospinal fluid (CSF) biomarkers for AD have detection limits, which create additional challenges. We apply a mixture of regressions with a multivariate truncated Gaussian distribution (also called a censored multivariate Gaussian mixture of regressions or a mixture of multivariate tobit regressions) to over 3,000 participants from the Emory Goizueta Alzheimer's Disease Research Center and Emory Healthy Brain Study to examine amyloid-beta peptide 1-42 (Abeta42), total tau protein and phosphorylated tau protein in CSF with known detection limits. We address three gaps in the literature on mixture of regressions with a truncated multivariate Gaussian distribution: software availability; inference; and clustering accuracy. We discovered three clusters that tend to align with an AD group, a normal control profile and non-AD pathology. The CSF profiles differed by race, gender and the genetic marker ApoE4, highlighting the importance of considering demographic factors in unsupervised learning with detection limits. Notably, African American participants in the AD-like group had significantly lower tau burden.

Research on agri-environmental technology efficiency--take Jilin Province in China as an example

From the perspective of the world agricultural development law, agricultural economic development and ecological environmental protection usually fall into a dichotomy paradox, according to the history of agricultural development in developed countries, they also experienced the rapid development of agriculture led to the destruction of the agro-ecological environment, which has become a key element hindering the sustainability of agriculture. Subsequently, developed countries rely on modern technology to achieve the transition from traditional agriculture to modern agriculture, crossing the paradoxical trap of economic development and ecological construction. At the present stage, China also shows the sharp contradiction between agricultural development and ecological construction, the traditional agricultural production methods of agricultural output has basically reached the limit, however, the established production methods of the ecological environment caused by the negative effects of the more and more serious, so that the agricultural environmental technology efficiency is not optimistic, so there is an urgent need to have a clear understanding of the main grain-producing areas of China's agricultural environmental technology efficiency and the factors affecting it. As an important grain producing area in China, Jilin Province's agricultural development level is in the forefront of the country, and it is also facing the contradiction between agricultural development and ecological environmental protection at the present stage. In order to realize the green transformation of agriculture and improve the technical efficiency of agricultural environment, it is necessary to rely on the optimisation of multi-dimensional factors such as technology and system. The study of agricultural environmental technical efficiency in Jilin Province has important theoretical significance and practical value for guiding other agricultural areas to realize the green transformation of production mode.

Joint modeling approaches for censored predictors due to detection limits with applications to metabolites data

Measures of substance concentration in urine, serum or other biological matrices often have an assay limit of detection. When concentration levels fall below the limit, exact measures cannot be obtained, and thus are left censored. The problem becomes more challenging when the censored data come from heterogeneous populations consisting of exposed and non-exposed subjects. If the censored data come from non-exposed subjects, their measures are always zero and hence censored, forming a latent class governed by a distinct censoring mechanism compared with the exposed subjects. The exposed group's censored measurements are always greater than zero, but less than the detection limit. It is very often that the exposed and non-exposed subjects may have different disease traits or different relationships with outcomes of interest, so we need to disentangle the two different populations for valid inference. In this article, we aim to fill the methodological gaps in the literature by developing a novel joint modeling approach to not only address the censoring issue in predictors, but also untangle different relationships of exposed and non-exposed subjects with the outcome. Simulation studies are performed to assess the numerical performance of our proposed approach when the sample size is small to moderate. The joint modeling approach is also applied to examine associations between plasma metabolites and blood pressure in Bogalusa Heart Study, and identify new metabolites that are highly associated with blood pressure.

Measurement and influencing factors of carbon emission efficiency based on the dual perspectives of water pollution and carbon neutrality

The achievement of the 'Carbon Dioxide Removal' vision has become a crucial strategic objective for national development. However, the carbon emissions produced during wastewater treatment processes hinder the attainment of the 'Carbon Dioxide Removal' targets. Addressing water pollution is not only essential for achieving the goal of 'carbon dioxide removal' but also for enhancing the carbon emission efficiency (CEE). In order to evaluate the CEE of five provinces in the Northwest of a certain developing country in East Asia from 2011 to 2020, this paper proposes a new method that calls the super-efficiency SBM model with unexpected output. Then, the study also analyzes the temporal and spatial evolution characteristics by generating kernel density curves. Furthermore, the Tobit panel regression model is used to examine the factors that influence CEE and analyze the internal mechanisms and reasons behind these factors. Finally, a tailored treatment policy is suggested based on the local water pollution situation. The results show that: (1) The CEE of the entire study area exhibited a consistent upward trend over time. By the conclusion of the study period, the efficiency value had not yet reached 1. (2) Based on the year 2015 as a turning point, the overall gap in CEE of researched areas shows a tendency of first narrowing and then gradually widening. (3) The level of economic development, industrial structure, and green innovative technology are positively correlated with CEE. Conversely, there is an inverse relationship between CEE and the level of urbanization and energy consumption. Through the research conclusion and the reality of water pollution, the policy suggestions to improve the efficiency of urban carbon emission.

Agricultural tridimension pollution emission efficiency in China: An evaluation system and influencing factors

We innovated traditional one-sided agricultural carbon emission efficiency research, comprehensively explored the agricultural tridimension pollution emission efficiency (ATPEE), constructed an ATPEE evaluation system considering technological heterogeneity characteristics based on the meta-frontier nonradial directional distance function (NDDF) model in a total-factor framework, evaluated the ATPEE in 30 mainland China provinces from 1997 to 2021 for the first time, and empirically studied the factors influencing the ATPEE in China with the Tobit model. The results showed the following: (1) ATPEE improvement potentials of 75.16 % and 50.88 % occur under the meta and group frontiers, respectively. (2) The eastern region represents the potential optimal agricultural tridimension pollution emission technology, while the central and western regions exhibit a large gap with the national potential optimal technology level. (3) The ATPEE loss in the eastern and western regions mainly results from management inefficiency, while that in the central region largely results from technology gap inefficiency. (4) The effects of the industrialization rate, urban-rural income gap, agricultural production structure, financial support for agriculture, natural conditions and effective irrigation rate on the ATPEE in the different regions vary.

Effects of School Physical Education on the Exercise Habits of Children and Adolescents: An Empirical Analysis Using China Health and Nutrition Survey Data

BACKGROUND

Since 2002, the Chinese Ministry of Education has conducted reform in the physical education (PE) curriculums of schools in China, with a focus on shifting from sports skills to regular participation in physical activity (PA) and promoting health. The aim of the study, therefore, is to examine the effects of school PE on the exercise habits of children and adolescents in China over time.

METHODS

Data based on 5941 observations of 3708 individuals aged 6 to 17 were collected from the China Health and Nutrition Survey (CHNS) for the period 2004 to 2015. The data were analyzed using the fixed-effect Logit model and the random-effect Tobit model.

RESULTS

The likelihood of exercising outside of school is 20.2% higher for students who have school PE than those who do not. Our study found that increasing the duration of PE at school by 100%, increases the duration of out-of-school PA by 22.3%. The variety of the types of sports schools offer encourages students to participate in out-of-school physical activity. The likelihood of students exercising outside of school increases by 5.6% when 1 more exercise type is provided in school PE. In addition, soccer, basketball, badminton, and volleyball education increases students' participation in after-school exercises. Soccer and basketball education, in particular, improves the duration of after-school PA.

CONCLUSIONS

To form exercise habits in children and adolescents, we encourage the promotion of a variety of physical activities in schools, especially team sports such as soccer and basketball.

Spatiotemporal evolution and influencing factors of water resource green efficiency in the cities of the Yangtze River Economic Belt

Effectively utilizing water resources, which is a fundamental natural resource and a vital economic resource, directly impacts how a country's economy develops. In this study, the Super-SBM model is used to calculate the city water resource green efficiency (CWRGE) of the Yangtze River Economic Belt (YREB), 108 cities that are prefecture level or higher, from 2006 to 2021. And its temporal and spatial evolution as well as its affecting variables are examined. The results indicate that, as a whole, the YREB's CWRGE has not yet achieved an effective level. The CWRGE in the YREB generally exhibits a trend of "first decreasing and then increasing, then decreasing and then increasing" and shows a "W"-shaped evolution law, and the overall trend is upward. There are just seven cities with effective data envelopment analysis (DEA), namely Changzhou, Hangzhou, Shanghai, Xuzhou, Changde, Changsha, and Yuxi. During the reporting period, the CWRGE of cities of various scales showed significant gaps: mega cities > big cities > small and medium-sized cities. From a regional perspective, the highest rate of CWRGE was found downstream of the YREB cities, then upstream, and the middle was the lowest. Spatial correlation findings demonstrated that both the agglomeration range and the outlier range were distributed, and there were mainly two positive aggregations of space forms ("high-high (H-H) type" and "low-low (L-L) type"), and the spatial distribution changed. The results of the spatiotemporal evolution demonstrate that there are more and more cities with high efficiency, as well as cities with low efficiency. From the results of the Tobit regression model, the CWRGE in the YREB are significantly improved by the economical development level, industrial scale, and water usage structure. While foreign direct investment and environmental regulation have considerable detrimental impacts, the impact of scientific and technological investment is not significant.

Analysis of the impact and moderating effect of high-density development on urban flooding

Although previous studies have posited that the high-density development of urban buildings and infrastructure contributes to urban flooding, empirical analyses and in-depth investigations into the interaction factors have remained limited. This study aims to analyze the influence and moderating effect of high-density development on urban flooding. Thus far, various land-use and interaction factors related to urban development density have been explored. Subsequently, the urban watershed was selected, utilizing panel data 2002 to 2017, and employing the Tobit model for analysis. The analysis revealed that high-density development had an adverse effect on urban flooding and that the runoff characteristics of high-density development were not limited to those of impervious surfaces. The horizontal and vertical aspects of dense buildings and structures acted as sub-watersheds that increased the time to reach peak flow. Moreover, high-density development had a moderating effect in low-lying areas. The results of this study underscore the necessity of urban disaster prevention planning to consider the direct and indirect effects, as well as the runoff characteristics, of high-density development on urban flooding.

A threshold longitudinal Tobit quantile regression model for identification of treatment-sensitive subgroups based on interval-bounded longitudinal measurements and a continuous covariate

Identification of a subgroup of patients who may be sensitive to a specific treatment is an important problem in precision medicine. This article considers the case where the treatment effect is assessed by longitudinal measurements, such as quality of life scores assessed over the duration of a clinical trial, and the subset is determined by a continuous baseline covariate, such as age and expression level of a biomarker. Recently, a linear mixed threshold regression model has been proposed but it assumes the longitudinal measurements are normally distributed. In many applications, longitudinal measurements, such as quality of life data obtained from answers to questions on a Likert scale, may be restricted in a fixed interval because of the floor and ceiling effects and, therefore, may be skewed. In this article, a threshold longitudinal Tobit quantile regression model is proposed and a computational approach based on alternating direction method of multipliers algorithm is developed for the estimation of parameters in the model. In addition, a random weighting method is employed to estimate the variances of the parameter estimators. The proposed procedures are evaluated through simulation studies and applications to the data from clinical trials.

Measurement and influencing factors of industrial carbon unlocking efficiency under the background of "double carbon"

Based on the panel data of 11 provinces and cities in the Yangtze River Economic Belt of China from 2011 to 2018, the DEA model and Malmquist index were used to calculate the industrial carbon unlocking efficiency of the Yangtze River Economic Belt in a static and dynamic way, and the Tobit model was used to empirically test its influencing factors. The results show that (1) the overall efficiency of industrial carbon unlocking in the Yangtze River Economic Belt is on the rise, but there are regional differences. The efficiency of industrial carbon unlocking in the lower reaches of the Yangtze River is higher than that in the upper and middle reaches. (2) The total factor productivity of industrial carbon unlocking in the Yangtze River Economic Belt has increased steadily on the whole, and technological progress is the main source of growth. (3) Industrial carbon unlocking efficiency is affected by many factors. Environmental regulation and degree of openness have a promoting effect on industrial carbon unlocking efficiency, while government investment and innovation level have a restraining effect on industrial carbon unlocking efficiency.

Consumption of Genetically Modified Food Products and Its Determinants (Case Study: Edible Oil in Mashhad)

In recent decades, the global increase in the demand for food and the increasing growth of the world population has caused an inevitable transition from traditional to advanced agriculture and the use of new technologies in the production of food and agricultural products. One of the new achievements of biotechnology is the production and use of genetically modified plants. The benefits of genetically modified crops can be seen well beyond the farm as well, from helping to conserve natural resources to fighting climate change. Identifying the factors that influence people's acceptance of genetically modified (GM) foods can inform industries and policymakers regarding their innovation trajectories, as well as policy development and implementation. Therefore, the current research evaluates the effect of the marketing mix and other effective factors on the consumption of genetically modified (GM) edible oil in Mashhad, Iran. The required information was collected by completing 390 questionnaires and using the available sampling method in 2022. Factors affecting the probability of consumers making a decision to consume GM edible oil and the consumption amounts of this oil were analyzed through Heckman's two-stage Tobit model using the STATA 16 software package. The results showed that factors affecting the intention of consuming GM edible oils are different from factors affecting the amount of consumption of GM edible oils. Moreover, selected marketing mixes have a significant effect on the amount of consumption of GM edible oils, and therefore, policy-makers can influence the consumption of GM edible oils by using marketing tools. The effect of household monthly income on the consumption of GM edible oil is also negative and significant, which shows that households with higher incomes have less consumption of GM edible oils. Based on the results, trust in the government has a positive and significant effect on the consumption of GM edible oil, so when consumers have trust in their government about GM food products, the consumption of GM edible oil will increase. Therefore, it is suggested that the country's food security authorities gain the trust of consumers by clarifying the production process of GM products and holding scientific debates between the proponents and opponents of the production and consumption of GM food products in order to express the advantages and disadvantages of these products to inform consumers and help them choose between products.

Fiscal decentralization, local government environmental protection preference, and regional green innovation efficiency: evidence from China

Green technological innovation has gained in importance in regional policy making towards gaining competitive advantage and sustainable development. This paper used the data envelopment analysis method to calculate regional green innovation efficiency in China, and empirically tested the effect of fiscal decentralization through Tobit model. The regression results show that the local governments with higher fiscal autonomy would prefer to strengthen environmental protection; thus, the regional green innovation efficiency was improved. After the guidance of relevant national development strategies, these effects became more apparent. Our research provided theoretical support and practical guidance for promoting regional led green innovation, improving environmental quality, achieving carbon neutrality, and promoting the high-quality and sustainable development.

Hierarchy performance assessment of industrial solid waste utilization - tracking resource recycling and utilization centers in China

The massive production and accumulation of industrial solid waste (ISW) have led to environmental pollution and natural resource underutilization. China's efforts to build trial industrial waste resource utilization centers provide strong support for sustainable development. However, these centers and the factors driving ISW utilization have yet to be evaluated. This paper utilizes context-dependent data envelopment analysis models without explicit inputs (DEA-WEI) to evaluate the overall utilization performance of 48 industrial waste resource utilization centers in China from 2018 to 2020. It also builds a Tobit model to assess which indicators and waste types affect overall ISW utilization. The results show overall ISW utilization performance of centers in the sample has improved, with the average value falling from 1.7193 in 2018 to 1.5624 in 2020. However, there are clear regional performance gaps, with East China having the highest utilization performance (1.3113) while the Southwest had the lowest (2.2958). Finally, this paper proposes measures to improve the overall utilization of industrial waste resources based on an analysis of the factors driving solid waste utilization.

The Tobit-Unscented-Kalman-Filter-Based Attitude Estimation Algorithm Using the Star Sensor and Inertial Gyro Combination

For the orbit operation of spacecraft, due to environmental factors, a star sensor installed on the spacecraft must have data censoring, which greatly reduces the attitude determination ability of the traditional combined-attitude-determination algorithm. To address this problem, this paper proposes an algorithm for high-precision attitude estimation based on a Tobit unscented Kalman filter. This is on the basis of establishing the nonlinear state equation of the integrated star sensor and gyroscope navigation system. The measurement update process of the unscented Kalman filter is improved. The Tobit model is used to describe the gyroscope drift when the star sensor fails. The latent measurement values are calculated using the probability statistics, and the measurement error covariance expression is derived. The proposed design is verified via computer simulations. When the star sensor fails for 15 min, the accuracy of the Tobit unscented Kalman filter based on the Tobit model is improved by approximately 90% compared to the unscented Kalman filter. Based on the results, the proposed filter can effectively estimate the error caused by the gyro drift, and the method is effective and feasible, provided there is theoretical support for the engineering practice.

What were the spatiotemporal evolution characteristics and the influencing factors of urban land green use efficiency? A case study of the Yangtze River Economic Belt

China's rapid urbanization has had a tremendous impact on the country's limited land resources, and one of the major issues of green development is how to utilize the limited land resources to maximize social, economic, and environmental advantages. From 2005 to 2019, the super epsilon-based measure model (EBM) was employed to assess the green land use efficiency of 108 prefecture-level and above cities in the Yangtze River Economic Belt (YREB), as well as investigate its spatial and temporal evolution and influential factors. The findings demonstrate that overall, urban land green use efficiency (ULGUE) in the YREB has been ineffective; in terms of city scale, megacities have the highest efficiency, followed by large cities and small and medium-sized cities; and at the regional level, downstream efficiency does have the greatest average value, followed by upstream efficiency and middle efficiency. The results of temporal and spatial evolution reveal that the number of cities with a high ULGUE is increasing in general but that their spatial characteristics are relatively dispersed. Population density, environmental regulation, industrial structure, technology input, and the intensity of urban land investment all have major beneficial effects on ULGUE, whereas urban economic development level and urban land use scale clearly have inhibitory effects. In light of the previous conclusions, some recommendations are made to continuously improve ULGUE.

Impact of carbon lock-in on green economic efficiency: Evidence from Chinese provincial data

Carbon lock-in is a major obstacle to transforming carbon-based energy systems toward carbon peaking and neutralization, affecting the green economy. However, its impacts and paths on green development are unclear, and it is difficult to represent carbon lock-in using a single indicator. This study measures five types of carbon lock-ins and their comprehensive effect using the entropy index of 22 indirect indicators in 31 Chinese provinces during 1995-2021. Moreover, green economic efficiencies are measured using a fuzzy slacks-based model considering undesirable outputs. The panel Tobit models are used to test the impacts of carbon lock-ins on green economic efficiencies and their decompositions. Our results show that provincial carbon lock-ins in China range from 0.20 to 0.80, with notable type and regional differences. Overall carbon lock-in levels are similar, but the severity of different carbon lock-in types varies, with social behavior being the most serious. However, the overall trend of carbon lock-ins is declining. Low pure green economic efficiencies, rather than scale efficiencies, contribute to China's worrisome green economic efficiencies, but they are decreasing and accompanied by regional gaps. Carbon lock-in hinders green development, but a specific analysis is needed for different carbon lock-in types and development phases. It is biased to assume that all carbon lock-ins hinder sustainable development, as some are even necessary. The impacts of carbon lock-in on green economic efficiency depend more on its effect on technology than on scale change. Implementing various measures to unlock carbon and maintaining reasonable levels of carbon lock-in can promote high-quality development. This paper may promote the development of new unlocking CLI measures and sustainable development policies.

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.

Identifying the causal effects of long-term exposure to PM2.5 and ground surface ozone on individual medical costs in China-evidence from a representative longitudinal nationwide cohort

BACKGROUND

There is little evidence on whether PM_2.5 and ground surface ozone have consistent effects on increased individual medical costs, and there is a lack of evidence on causality in developing countries.

METHODS

This study utilized balanced panel data from 2014, 2016, and 2018 waves of the Chinese Family Panel Study. The Tobit model was developed within a counterfactual causal inference framework, combined with a correlated random effects and control function approach (Tobit-CRE-CF), to explore the causal relationship between long-term exposure to air pollution and medical costs. We also explored whether different air pollutants exhibit comparable effects.

RESULTS

This study encompassed 8928 participants and assessed various benchmark models, highlighting the potential biases from failing to account for air pollution endogeneity or overlooking respondents without medical costs. Using the Tobit-CRE-CF model, significant effects of air pollutants on increased individual medical costs were identified. Specifically, margin effects for PM_2.5 and ground-level ozone signifying that a unit increase in PM_2.5 and ground-level ozone results in increased total medical costs of 199.144 and 75.145 RMB for individuals who incurred fees in the previous year, respectively.

CONCLUSIONS

The results imply that long-term exposure to air pollutants contributes to increased medical costs for individuals, offering valuable insights for policymakers aiming to mitigate air pollution's consequences.

Analysis of financial support efficiency and influencing factors of listed seed companies from the perspective of energy consumption and carbon emissions

The seed industry has a prominent role in strengthening ecological stability and national food security as it provides the basic ground for agriculture sector. In the current research, the effectiveness of financial support provided to listed seed enterprises and its influencing factors from the perspectives of energy consumption and carbon emissions are examined using a three-stage DEA-Tobit model. The dataset for the underlined study variables mainly comes from the financial data published by 32 listed seed enterprises and the China Energy Statistical Yearbook from 2016 to 2021. In order to make the results more accurate, the influence of external environmental factors such as economic development level, total energy consumption, and total carbon emission on listed seed enterprises are excluded. The results revealed that the mean value of financial support efficiency of listed seed enterprises increased significantly after excluding the influence of external environmental and random factors. External environmental factors such as regional energy consumption and carbon dioxide emission played an important role in the process of the financial system supporting the development of listed seed enterprises. The development of some listed seed enterprises with high financial support efficiency came at the cost of high local carbon dioxide emission and high energy consumption. Internal factors such as operating profit, equity concentration, financial structure, and enterprise size are the key intra-firm factors that affect the efficiency of financial support for listed seed enterprises. Thus, it is suggested that enterprises must pay attention to the environmental performance to reach a win-win situation in reducing and improving the energy consumption and financial performance, respectively. Similarly, the improvement of energy use efficiency through endogenous and external innovation should be prioritized to achieve sustainable economic development.

Digital economy and industrial energy efficiency performance: evidence from the city of the Yangtze River Delta in China

Industry dominates energy consumption and carbon emissions in China, and industrial energy efficiency is critical for the achievement of energy transformation and carbon emission reduction. With the rapid development of the digital economy, its impact on energy efficiency is gradually emerging, and it is necessary to clarify the influencing mechanism on industrial energy efficiency. Based on the panel data of industrial sectors in 41 cities in the Yangtze River Delta from 2011 to 2019, the main objectives of this study are to more accurately measure the industrial total factor energy efficiency in each city by using the Super-Dynamic-SBM model. It analyses the influence mechanism of the digital economy and other influencing factors on industrial total factor energy efficiency with different methods. The research results indicate that, first, the total factor energy efficiency of the industrial sector in the Yangtze River Delta urban agglomeration generally showed a steady upward trend. Second, the digital economy and environmental regulation play a significant role in promoting total factor energy efficiency. In addition, industrial energy efficiency and the digital economy show an inverted "U" shaped relationship. With the improvement of the digital economy, its marginal contribution to total factor energy efficiency gradually weakens. Finally, technological progress is an important transmission channel for the impact of the digital economy on total factor energy efficiency.

Impact of the development of information society on healthcare efficiency: Empirical evidence from 31 Chinese provinces

The development of information society has deeply changed the style of the healthcare service delivery and medical information access. This study aims to investigate how the information society development affects the efficiency of healthcare system in China, and explore provincial disparities in the impact. Based on the two-stage Data Envelopment Analysis (DEA) framework, this paper uses a panel data from 31 Chinese provinces from 2014 to 2017 to estimate efficiency of healthcare service and analyze the influence of the development of information society on efficiency. With the information society index (ISI) increased from 0.423 to 0.488 during the sample period, the healthcare efficiency experienced a slight decrease from 0.892 to 0.869. Moreover, the pure technical efficiency (PTE) is much lower than the scale efficiency (SE), and thus is the key to enhance the overall technical efficiency (TE). The time-fixed Tobit regression analysis suggests that information society development leads to a significant increase in PTE, but results in a decrease in SE, and therefore has little effect on TE. Further analysis reveals that the impact differs sharply between low-efficiency and high-efficiency provinces. For the low-efficiency provinces, the TE increases significantly with the development of the information society, mainly due to a considerable increase in PTE. In contrast, the TE decreases for the high-efficiency provinces, mainly caused by a decrease in SE. This paper highlights the importance of information infrastructure investment in healthcare system and the application of emerging information technologies to breakout the time and space boundaries of healthcare services in improving overall efficiency. In inefficient provinces, it is also necessary to properly control the growth of healthcare inputs.

The impact of environmental regulations on the performance of regional collaborative innovation-in case of China's 30 provinces

With rapid economic growth in the twenty-first century, innovation has become an essential component of national development, and industry-university-research regional collaborative innovation is the key to implementing China's innovation plan. Using panel data from 30 provinces and cities in China (excluding Tibet Autonomous Region) from 2011 to 2018, this paper employs the two-stage dynamic DEA model to develop a rating index system of regional collaborative innovation performance, which is divided into knowledge innovation stage and technology innovation stage, and measures the collaborative innovation efficiency of 30 provinces in China. The environmental regulation score is then determined by using the entropy method. Finally, an experimental application of the panel Tobit model is conducted to investigate the impact mechanism of environmental regulation on regional collaborative innovation. The results reveal that the collaborative innovation efficiency values of the majority of provinces are between 0.5 and 0.7, leaving ample room for growth. When the efficiency value of collaborative innovation is broken down by region, the eastern, central, and western regions show a pattern of "rising in the east, stable in the center, and falling in the west." The findings of the Tobit regression reveal that the effect of environmental regulation on regional collaborative innovation performance follows a "U"-shaped distribution, confirming the "Porter Hypothesis." This study proposes remedies and proposals to enhance regional collaborative innovation performance from the perspective of environmental regulation.

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.