Search

This paper investigates the impact of digital inclusive financial development on local government expenditure incentives at the income level. It does so by constructing a multi-level government Dynamic Stochastic General Equilibrium (DSGE) model that incorporates the financial sector. By employing empirical methods that involve uncertainty shocks and counterfactual simulations, the research yields several key findings. Firstly, the development of digital inclusive finance contributes to breaking down the urban-rural dual financial structure, thus facilitating balanced economic development within regions. Secondly, it reduces the proportion of financially excluded areas, accelerates fiscal decentralization, leading to an increase in local government fiscal revenue, and, consequently, an expansion of local fiscal expenditures. Thirdly, at a certain stage of digital inclusive finance development, it tends to crowd out residents' investment and consumption. Therefore, the decentralization of fiscal power and the expansion of local government expenditure at this stage may paradoxically inhibit regional economic growth. The study's conclusions validate the significant impact of digital inclusive finance on local government incentives at the income level. [ABSTRACT FROM AUTHOR]

On February 26, 2018 and July 24, 2021, the Chinese government respectively issued two significant regulatory policies to address the problems caused by off-campus training institutions in terms of students' extra-curricular and family financial burdens. These policies have had a tremendous and far-reaching impact on the off-campus training industry in China. With the help of these two events, we explored the role of industry-level regulatory policies in shaping and forming organizational culture. This paper adopts a text analysis method, combined with the dimensions of the Denison Organizational Culture Survey (DOCS) and MAXQDA 18 software, to obtain data on corporate culture. Then, the approaches of regression discontinuity in time (RDiT) and regression discontinuity (RD) designs with multiple cutoffs are used to estimate the policy treatment effect. This empirical research suggests that regulatory policies have a significant impact on corporate culture. Moreover, regulatory policies of varying degrees of strictness have differential effects on different dimensions of corporate culture. The research findings contribute to the theories of corporate culture and can guide enterprises to evaluate the impact of policies on corporate culture more clearly, thereby enabling them to make wiser operation decisions. [ABSTRACT FROM AUTHOR]

To stimulate economic growth, China has launched multiple economic stimulus plans in recent years, intensifying corporate debt financing and subsequently elevating the leverage levels. Addressing and effectively reducing the leverage levels of our country's enterprises has emerged as a pressing issue in the trajectory of our economic development. This paper primarily investigates the drivers, pathways, and mechanisms for reversing the over-leveraged values of enterprises. Key findings include: (1) Excessive indebtedness exerts a negative impact on corporate value, with the suppressing effect intensifying as the degree of over-leverage increases; (2) Over-leveraged enterprises can effectively decrease their debt levels and enhance their value through private placement. Further research suggests that this mechanism operates by amplifying the operational leverage of over-leveraged enterprises post private placement and alleviating financing constraints, thereby elevating corporate value. (3) Compared to non-state-owned enterprises, state-owned enterprises exhibit higher levels of indebtedness. Among over-leveraged firms, enhancements in corporate governance and increased investment efficiency can positively transform corporate value. This study offers valuable insights for the ongoing supply-side structural reforms and governance guidance from the regulatory bodies. [ABSTRACT FROM AUTHOR]

The leading role of the media is very important in the new media era to build the reporting system and framework of sexual violence crimes, guide people's awareness and public opinion, and improve society's vigilance on sexual crimes. This study took People's Daily Online, a representative online media in China, as a research object to analyse the reporting of sexual crimes over the past 15 years. We conducted relevant searches for specific keywords set in the Python crawler and used IBM SPSS Statistics 19 software to analyse the frequency of relevant content. The results of the research show that, firstly, there have been significant changes in the number of news stories about sexual crimes. Second, the majority of sexual crime news stories are from mainland China. Third, the focus of the news stories and people is relatively concentrated on the perpetrators. Fourth, the People's Daily Online's coverage of sexual crimes focuses on blaming the perpetrators. Fifth, sexual crimes show that the framework is more episodic. This paper examines changes in the coverage of sexual crimes in China and captures how the media cover socially relevant issues, providing important insights for future social health, psychological awareness and diversion, and media policy. [ABSTRACT FROM AUTHOR]

This study explores the impact of farm households' social capital characteristics and local government policies on the selection of farmland transfer contracts in China's rural industrial revitalization context. Utilizing field research data from 1,979 households in ethnic areas of Hunan Province, this paper constructs an econometric model to assess how farm households' social capital and local governments' involvement in rural industrial revitalization influence farmland transfer contract selections. The findings indicate that, lacking government program support, farmers' social capital significantly affects contract type and duration, but not the rent. Specifically, farmers possessing extensive social capital prefer verbal and short-term contracts (coefficients of 0.525 and 0.643, significant at the 5% level), whereas their influence on rent (coefficient of 2.418, significant at the 5% level) manifests under government program support. These results challenge the conventional theory of farmland transfer contracts and offer substantial empirical support for the development of local government policies in rural industrial revitalization, underlining the critical role of government guidance and social capital in enhancing farmland transfer. [ABSTRACT FROM AUTHOR]

Wheat is a major grain crop in China, accounting for one-fifth of the national grain production. Drought stress severely affects the normal growth and development of wheat, leading to total crop failure, reduced yields, and quality. To address the lag and limitations inherent in traditional drought monitoring methods, this paper proposes a multimodal deep learning-based drought stress monitoring S-DNet model for winter wheat during its critical growth periods. Drought stress images of winter wheat during the Rise-Jointing, Heading-Flowering and Flowering-Maturity stages were acquired to establish a dataset corresponding to soil moisture monitoring data. The DenseNet-121 model was selected as the base network to extract drought features. Combining the drought phenotypic characteristics of wheat in the field with meteorological factors and IoT technology, the study integrated the meteorological drought index SPEI, based on WSN sensors, and deep image learning data to build a multimodal deep learning-based S-DNet model for monitoring drought stress in winter wheat. The results show that, compared to the single-modal DenseNet-121 model, the multimodal S-DNet model has higher robustness and generalization capability, with an average drought recognition accuracy reaching 96.4%. This effectively achieves non-destructive, accurate, and rapid monitoring of drought stress in winter wheat. [ABSTRACT FROM AUTHOR]

The coal mining might cause the disturbance to the vegetation and the disturbance impacts might exist the differences for different areas, and few literatures compared and analyzed different disturbed areas based on the location of the mining face, and paid attention to the post mining self-healing effects of vegetation. Here, this paper selected the GaoFen multispectral images during 2017–2021 to study different areas of Shangwan Mine which includes the old mining area more than 5 years after mining, the new working face underground mined in 2018 and 2019, the natural growth control area and the open-pit mining affected area. The spatiotemporal changes of the surface fraction vegetation coverage (FVC) were analyzed in each area and the correlation between vegetation coverage and climatic factors was studied. The results showed that: (1) The overall vegetation coverage showed a moderate decrease trend in fluctuation from 2017 to 2021. The Open-pit mining affected areas showed the largest decline, reaching 68.3%. The FVC in the underground mining areas had a downward trend, but self-healing effect after mining was also observed. (2) The overall FVC in the study area was positively correlated with the number of precipitation days. (3) There were differences in the sensitivity to mining disturbance for different landform in the underground mining areas. (4) Although the FVC in the Old mining areas had recovered to the level of Natural growth control area, but the annual fluctuation was larger, which might mean lower ecological stability. [ABSTRACT FROM AUTHOR]

Vietnam's agricultural exports to China have remained strong, with the country maintaining its position as the top destination for Agri-products. This article primarily utilizes the Revealed Comparative Advantage (RCA) Index, and Trade Complementarity (TC) index to examine the trade comparative advantage, and the complementary of twenty major agricultural products between China and Vietnam from 2012 to 2021. The study results showed that Vietnam and China frequently exchange agricultural products. Vietnam has more stronger competitiveness than China in terms of agricultural products. China's exports to Vietnam were highly complementary to Vietnam's imports in category 0 whiles Vietnam's exports to China showed strong complementarity with China's imports in category 2. This paper analyzes the complementarity and comparative advantages of agricultural trade between China and Vietnam, and proposes informed suggestions for policy-making to promote agricultural trade between the countries. The proposed suggestions aim to expand agricultural trade between the two countries, reduce the trade imbalance, and achieve mutual benefit and win-win results. [ABSTRACT FROM AUTHOR]

The Communist Party of China's 19th National Congress underlined the necessity of speeding the development of a manufacturing powerhouse and advanced manufacturing sector by supporting the deep integration of the Internet, big data, artificial intelligence, and the real economy. This study employed principal component analysis to extract the prominent risk factors from questionnaire data in order to manage the risks connected with the Internet strategic transformation of manufacturing firms. To confirm the major risk factors, a structural equation modeling was created using Amos-24 software. The findings revealed that risk factors of Internet strategic transformation in manufacturing businesses are mostly expressed in equipment flexibility risks, organizational versatility risks, smart technology risks, Internet technology risks, flexible management risks, and financing management risks. The paper offers useful theoretical and practical insights into the risks of China's manufacturing businesses' Internet strategic transformation. The findings can assist manufacturing firms in better identifying and managing these risks, supporting their smooth transition to the Internet economy. [ABSTRACT FROM AUTHOR]

As one of the key materials used in the civil engineering industry, concrete has a global annual consumption of approximately 10 billion tons. Cement and fine aggregate are the main raw materials of concrete, and their production causes certain harm to the environment. As one of the countries with the largest production of industrial solid waste, China needs to handle solid waste properly. Researchers have proposed to use them as raw materials for concrete. In this paper, the effects of different lithium slag (LS) contents (0%, 10%, 20%, 40%) and different substitution rates of recycled fine aggregates (RFA) (0%, 10%, 20%, 30%) on the axial compressive strength and stress-strain curve of concrete are discussed. The results show that the axial compressive strength, elastic modulus, and peak strain of concrete can increase first and then decrease when LS is added, and the optimal is reached when the LS content is 20%. With the increase of the substitution rate of RFA, the axial compressive strength and elastic modulus of concrete decrease, but the peak strain increases. The appropriate amount of LS can make up for the mechanical defects caused by the addition of RFA to concrete. Based on the test data, the stress-strain curve relationship of lithium slag recycled fine aggregate concrete is proposed, which has a high degree of agreement compared with the test results, which can provide a reference for practical engineering applications. In this study, LS and RFA are innovatively applied to concrete, which provides a new way for the harmless utilization of solid waste and is of great significance for the control of environmental pollution and resource reuse. [ABSTRACT FROM AUTHOR]

This study constructed a multidimensional indicator system to evaluate spatio-temporal heterogeneity of China's import and export trade of 31 provinces from 2000 to 2022. This study describes the distribution of China's import and export trade by using location Gini coefficient and exploratory spatial analysis. Additionally, Multiple linear regression was used to ascertain the extent of contribution by various factors on the spatio-temporal heterogeneity of import and export trade. The simulation results show that inter-provincial import and export trade displayed distinct spatio-temporal differentiation characteristics with a prominent east-to-west disparity from 2000 to 2022. The trade links between various regions of the country have gradually strengthened, with a corresponding high correlation to the level of economic development. GDP, financial expenditure, freight transportation volume, technology market turnover, foreign investment, and disposable income of all residents, significantly influence the per capita export and import volume. In general, it is suggested that China and developing countries should take effective measures to promote balanced trade development, strengthen regional cooperation and coordination, and promote green trade and sustainable development. [ABSTRACT FROM AUTHOR]

Using the panel data of 31 provinces in China between 2000 and 2018, this study theoretically and empirically analyses the impact of environmental regulations on the adjustment of the agriculture industrial structure from the perspectives of rationalisation and optimisation. Overall, variability in the impact of environmental regulation on the adjustment of the agricultural industrial structure is identified: a negative influence on the rationalisation of agricultural industrial structure and a positive influence on the optimisation of agricultural industrial structure. The impact of environmental regulations on the adjustment of agricultural industrial structure also reflects "large country characteristics": environmental regulations are more significant at the medium and low industrial structure levels. Environmental regulation significantly impacts the rationalisation of agricultural industrial structure in central and western regions and its optimisation in eastern and central regions. Through the panel threshold model test, this paper further finds that the effect of environmental regulations on the adjustment of agricultural industrial structure is not invariant. However, there is a non-linear relationship with significant threshold characteristics. Based on the above results, some countermeasures are suggested. [ABSTRACT FROM AUTHOR]

This study focuses on the objective assessment of sport development in socio-economic environments, considering the challenges faced by the industry. These challenges include disparities in regional investments, limited market participation, slow progress towards sports professionalization, and insufficient technological innovations. To tackle these challenges, we suggest implementing an integrated evaluation model that follows the DPSIR (Drivers, Pressures, States, Impacts, Responses) framework and incorporates comprehensive socioeconomic indicators. Subsequently, we utilized the Entropy power method and TOPSIS (Order Preference Technique for Similarity to an Ideal Solution, TOPSIS) analysis to comprehensively assess the progress of competitive sports development in 31 provinces and cities in China. Additionally, we recommended further developments in competitive sports and proposed precise strategies for promoting its growth. The framework and methodology developed in this paper provide an objective and scientifically based set of decision-making guidelines that can be adopted by government agencies and related industries in order to create successful plans that promote the sustainable growth of competitive sport. This is expected to bolster the nation's global influence, enhance social unity, and fuel economic expansion. The findings of this study offer policymakers valuable insights regarding competitive sports and can advance the development of the sports sector in China, thus making it a crucial driver of regional socio-economic progress. [ABSTRACT FROM AUTHOR]

The advancement of the sports industry's development constitutes a critical concern shared by regional authorities and the scholarly community, reflecting its significant role in economic and social development. This study employs a Fuzzy-set Qualitative Comparative Analysis (fsQCA) methodology to examine the 31 provincial-level administrative units in China. The objective is to elucidate the influence of technological, organizational, and environmental factors on the industry's development level, considering both a holistic national framework and dissected regional approaches (Eastern, Central, and Western China). This paper's contribution to the literature is structured around the following core findings: (1) The study establishes that a singular condition does not suffice as an essential prerequisite for achieving a heightened development state within the sports industry. (2) At the national level, there are three pathways to enhance the development level of the sports industry, specifically identified as "network-human resources dominant pathway," "technological innovation-human resources dominant pathway," and "comprehensive synergistic pathway."(3) From a regional perspective, the Eastern region has two pathways for sports industry enhancement: "network-economic pathway" and "comprehensive synergistic pathway." The Central region follows a "technology pathway," while the Western region has three pathways: "organization-environment pathway," "network-organization-environment pathway," and "organization pathway."(4) The synthesis of these findings underscores the multifactorial nature of sports industry development, suggesting a paradigm where diverse routes can lead to equivalent outcomes. This heterogeneity indicates that provinces or regions can tailor their development strategies to their unique situational contexts. [ABSTRACT FROM AUTHOR]

Despite significant growth in fiscal expenditure, the overall level of public services in China remains inadequate. One approach to improving government public service efficiency from the perspective of management psychology is to strengthen government competition. However, only a few studies have explored the improvement of public service efficiency through government competition, with even fewer addressing the phenomena of market segmentation and spatial effects that accompany the process of government competition. This paper aims to fill this research gap by examining the effects of government competition and market segmentation on public service efficiency, as well as their spatial disparities. We initially employs the DEA method to assess the efficiency of public services based on inputs and outputs, and examines its spatial variations. Subsequently, a semi-parametric spatial lag panel model is utilized to validate the effects of market segmentation and government competition on public service efficiency. Our findings indicate that inter-provincial market segmentation leads to a decline in public service efficiency. Moreover, the influence of horizontal competition between local governments on public service efficiency varies depending on the degree of positive and negative effects in their competition dynamics. The impact of vertical competition between central and local governments on public service efficiency is influenced by the degree of fiscal decentralization. When the level of fiscal decentralization is below 0.808, vertical competition between central and local governments has a promoting effect on public service efficiency. However, when the degree of fiscal decentralization exceeds 0.08, this promoting effect weakens and gradually transforms into a negative influence. The insights and evidence provided by this study offer valuable guidance for for effectively reshaping the fiscal relations between the central and local governments in China and improving public service efficiency in the context of a new round of fiscal and tax system reforms. [ABSTRACT FROM AUTHOR]

As an essential material basis and power source for economic and social development, Western China's low energy use efficiency has hindered its sustainable economic development. This study aims to evaluate the total factor energy efficiency of the region and identify its influencing factors. A three-stage DEA model was used to measure the efficiency of 11 provinces from 2006 to 2021, and the Tobit model was employed to investigate internal factors. The findings show that (i) external environmental factors and stochastic perturbations have a significant impact on TFEE in the western region, overestimating integrated efficiency and scale efficiency and underestimating pure technical efficiency. (ii) the study of external influencing factors finds that the level of economic development increases input redundancy; the industrial structure increases capital input and labor input redundancy while decreasing energy input redundancy; and the energy consumption structure increases capital input and energy input redundancy while decreasing labor input redundancy. (iii) the study of internal influencing factors finds that the level of scientific and technological innovation, the level of openness to the outside world, and the TFEE have a positive correlation. In contrast, the intensity of environmental regulation has a negative correlation. [ABSTRACT FROM AUTHOR]

Human-to-human contact plays a leading role in the transmission of infectious diseases, and the contact pattern between individuals has an important influence on the intensity and trend of disease transmission. In this paper, we define regular contacts and random contacts. Then, taking the COVID-19 outbreak in Yangzhou City, China as an example, we consider age heterogeneity, household structure and two contact patterns to establish discrete dynamic models with switching between daytime and nighttime to depict the transmission mechanism of COVID-19 in population. We studied the changes in the reproduction number with different age groups and household sizes at different stages. The effects of the proportion of two contacts patterns on reproduction number were also studied. Furthermore, taking the final size, the peak value of infected individuals in community and the peak value of quarantine infected individuals and nucleic acid test positive individuals as indicators, we evaluate the impact of the number of random contacts, the duration of the free transmission stage and summer vacation on the spread of the disease. The results show that a series of prevention and control measures taken by the Chinese government in response to the epidemic situation are reasonable and effective, and the young and middle-aged adults (aged 18-59) with household size of 6 have the strongest transmission ability. In addition, the results also indicate that increasing the proportion of random contact is beneficial to the control of the infectious disease in the phase with interventions. This work enriches the content of infectious disease modeling and provides theoretical guidance for the prevention and control of follow-up major infectious diseases. [ABSTRACT FROM AUTHOR]

Based on the integrated model of Super-SBM model, spatial Durbin model (SDM) and Grey neural network model, this paper analyzes the panel data of various provinces in China from multiple angles and dimensions. It was found that there were significant differences in eco-efficiency between organic rice production and conventional rice production. The response of organic rice to climate change, the spatial distribution of ecological and economic benefits and the impact on carbon emission were analyzed. The results showed that organic rice planting not only had higher economic benefits, but also showed a rising trend of ecological benefits and a positive feedback effect. This finding highlights the importance of organic rice farming in reducing carbon emissions. Organic rice farming effectively reduces greenhouse gas emissions, especially carbon dioxide and methane, by improving soil management and reducing the use of fertilizers and pesticides. This has important implications for mitigating climate change and promoting soil health and biodiversity. With the acceleration of urbanization, the increase of organic rice planting area shows the trend of organic rice gradually replacing traditional rice cultivation, further highlighting the potential of organic agriculture in emission reduction, environmental protection and sustainable agricultural production. To this end, it is recommended that the Government implement a diversified support strategy to encourage technological innovation, provide guidance and training, and raise public awareness and demand for organic products. At the same time, private sector participation is stimulated to support the development of organic rice cultivation through a public-private partnership model. Through these measures, further promote organic rice cultivation, achieve the dual goals of economic benefits and environmental benefits, and effectively promote the realization of double carbon emission reduction targets. [ABSTRACT FROM AUTHOR]

The severe global warming issue currently threatens humans' existence and development. Countries and international organizations have effectively implemented policies to reduce carbon emissions and investigate low-carbon growth strategies. Reducing carbon emissions is a hot topic that academics and government policy-making departments are concerned about.Through necessary condition analysis (NCA) and fuzzy set qualitative comparative analysis(fsQCA), this paper investigates local governments' configuration linkage effect and path choice to improve carbon emission performance from six dimensions: energy consumption, industrial structure, technological innovation, government support, economic development, and demographic factors. The research findings include the following: (1) Individual condition does not represent necessary conditions for the government's carbon performance. Among the two sets of second-order equivalence configurations(S and Q) (five high-level carbon performance configurations), those dominated by economic development or low energy consumption can produce high-level carbon performance. Therefore, the six antecedent conditions dimensions work together to explain how the government can create high levels of carbon performance. (2)According to the regional comparison, China's eastern, central, and western regions exhibit similarities and differences in the driving forces behind high carbon emission performance. All three regions can demonstrate carbon emission performance when all the factors are combined. However, when constrained by the conditions of each region's resource endowment, the eastern region emphasizes the advantage of economic and technological innovation, the central region favors government support and demographic factors, and the western region prefers upgrading industrial structure based on a specific level of economic development. [ABSTRACT FROM AUTHOR]

Enhancing green innovation for business sustainability represents a pressing global challenge. In the context of the manufacturing industry, the relationship between proactive green innovation (PGI) and structural social capital (SSC) remains a profoundly under-researched area. Drawing upon the theories of social capital and dynamic capability (DC), this study investigated the relationship between SSC and PGI within manufacturing enterprises via three individual and sequential mediating factors, namely cognitive social capital (CSC), relational social capital (RSC), and DC. Adopting a cross-sectional quantitative design, this study collected survey data from 485 manufacturing sector employees in China using purposive sampling. Structural equation modeling analysis of the data revealed no significant direct impact of SSC on PGI, but a strong indirect impact through the sequential mediating influences of CSC, RSC, and DC. The findings suggests that PGI within manufacturing enterprises is not wholly shaped by SSC; rather, firm-level dynamic capabilities, characterized by a sequential mechanism, plays a crucial role in achieving PGI within these enterprises. This paper offers both theoretical and practical contributions and provides recommendations for future research based on its limitations. [ABSTRACT FROM AUTHOR]

With the changes of social and economic development, more and more people pay attention to the development of non-profit organizations, and the performance research of non-profit organizations has become the focus of research. As the internal governance organization of non-profit organization, the board of directors and the management organization are related internal factors that will affect the organizational performance of non-profit organization. Based on the data of Form 990 of the US Internal Revenue Service, this paper conducted an empirical study on the relationship between internal governance and organizational performance of non-profit organizations, and studied the moderating effects of board size, average weekly working hours, number of managers, members' work involvement and compensation incentives on internal governance and organizational performance of non-profit organizations. The results show that the number of managers in non-profit organizations is negatively correlated with organizational performance, the average weekly working hours of managers are significantly correlated with organizational performance, and the compensation of managers is significantly correlated with organizational performance. Through the empirical demonstration, this study promotes the management and development practice of non-profit organizations, and lays a solid foundation for the construction of socialist harmonious society in China. [ABSTRACT FROM AUTHOR]

This study explores the influencing factors on intelligent transformation and upgrading of China's logistics firms under smart logistics, and designs the corresponding framework to guide the practice of firms. By analyzing the characteristics of smart logistics and the transformation and upgrading needs of traditional logistics, from the micro perspective of logistics firms, this paper constructs influencing factor index system of smart transformation and development from four dimensions: logistics technology innovation, logistics big data sharing, logistics management upgrading and logistics decision-making transformation. Logistics firms are divided into firms with medium scale and above and small and medium-sized firms according to their scale. Then EWIF-AHP model is proposed to measure the weight of index system and score the decision-making, so as to evaluate the impact of various influencing factors on transformation and development of logistics firms. The results show that, for logistics firms above medium scale, logistics technology innovation and logistics big data sharing have the most significant impact on transformation and development, followed by logistics management upgrading and logistics decision-making transformation. For small and medium-sized logistics firms, the biggest factor is the upgrading of logistics management, followed by the upgrading of logistics technology, which is almost as important as the influencing factors of the upgrading of logistics management, and followed by the sharing of logistics big data and the transformation of logistics decision-making. Therefore, corresponding countermeasures and suggestions for intelligent transformation of logistics firms have been put forward. [ABSTRACT FROM AUTHOR]

The literature has confirmed that when managers increase profits through earnings management, the readability of annual reports may be reduced Lo (2017), Ye (2018). Whether this conclusion is suitable for Chinese corporate social responsibility (CSR) reports, however, is still unclear. Based on the panel data of 5083 Chinese non-financial listed companies from 2010 to 2019, this paper adopts multiple linear regression to investigate the impact of earnings management on the readability of Chinese CSR reports. The results show that: (1) There is a significant negative correlation between earnings management and the readability of Chinese CSR reports, with the readability of Chinese annual reports as a mediating variable. (2) The negative effect is more significant when companies are not punished for violations, when the internal control index is low, when companies lack ISO14001 certification and when companies do not have independent third-party authentication for Chinese CSR reports. (3) When earnings management just exceeds zero, the readability of Chinese CSR reports decreases. (4) The economic consequences of reducing the readability of Chinese CSR reports are that financing costs are increased and environmental performance is decreased. To improve the quality of information disclosure of listed companies, the recommendations are as follows: First, the government should issue CSR reporting standards to reduce the manipulation of Chinese CSR reports. Second, Chinese CSR reports disclosed by listed companies must be audited by independent third parties to enhance the credibility of the information. Third, the company needs to strengthen its external and internal supervision to reduce the manipulation space for the readability of Chinese CSR reports. This study extends the negative relationship between earnings management and the readability from annual reports to Chinese CSR reports. To prevent investors from detecting earnings management, the readability of Chinese CSR reports may be reduced. At the same time, the study has definitely added value to the existing literature in the domain of CSR. [ABSTRACT FROM AUTHOR]

Adoption of clean electric energy depends not only on administrative regulations, but also on public support, in particular, the public is willing to pay for environmental improvements. However, the increase of solar photovoltaic power generation willingness to pay (WTP) associated with higher education attainment and the identification of their causality has been missing. Present paper used the enactment of the Compulsory Schooling Law as an instrumental variable to solve the causal relationship between education and willingness to pay for photovoltaic power generation. The results are as follows:Heckman two-stage model and instrumental variable both confirmed that higher education has a positive impact on WTP for solar photovoltaic power generation. For each level of public education in the east, the WTP of photovoltaic power generation will increase by 7.540 CNY, 8.343 CNY and 8.343 CNY respectively, the central public will increase by 9.637 CNY, 10.775 CNY and 11.758 CNY, and the western public will increase by 12.723 CNY, 15.740 CNY and 17.993 CNY respectively. The positive influence of education level is smaller among the people who know the ladder price better, but it is bigger among the people who are male, older than 45 years old, healthier, higher income and stronger awareness of safe electricity use. The total socio-economic value of photovoltaic power generation is significantly different in eastern, central and western region China. [ABSTRACT FROM AUTHOR]

Smart cities improve services for businesses, among many other benefits. A comprehensive understanding and effective utilization of these advantages is crucial for promoting business development. Using panel data from Chinese listed companies (2010–2020), this study employs a multi-stage DiD model to investigate the impact of smart cities on corporate earnings management. The findings indicate that the smart city pilot policy has significantly reduced corporate earnings management. Further analysis suggests that smart cities primarily reduce earnings management by improving firms' external information environments. Additionally, the results show that the policy impact of smart cities is more significant in regions with lower regulatory intensity or higher marketization levels, compared to regions with higher regulatory intensity or lower marketization levels. Similarly, firms in less concentrated markets or those more closely related to smart city development tend to experience greater reductions in earnings management due to smart city construction, unlike firms in more concentrated markets or those less involved. Finally, this paper offers several brief suggestions. [ABSTRACT FROM AUTHOR]

Taking 30 provinces in China from 2011 to 2020 as a research sample, this paper empirically tests the impact of digital village construction on carbon emissions. This study found that there is an "inverted U" curve relationship between digital rural construction and rural carbon emissions. Agricultural planting structure and agricultural technology efficiency are important ways for digital village construction to reduce agricultural carbon emissions. The study also found that the higher the level of economic development, the stronger the carbon emission reduction effect of digital village construction. In addition, there are also significant differences in the carbon emission reduction effect of digital village construction in regions with different environmental regulation intensities. Finally, in terms of the relationship between digital economic activities and carbon emission reduction, the research conclusions of this paper have important implications. [ABSTRACT FROM AUTHOR]

Background: The paper established indexes of coordination efficiency, the theoretical framework and operation mechanism of emergency information sharing for coastal cities of China. Method: First of all, we analyzed the operational relationship between the participants of emergency information sharing and information transmission, and based on the collaborative theory, constructed the emergency information sharing framework and operational mechanism suitable for the actual disaster prevention and reduction of coastal cities. Around the 3 dimensions of emergency information sharing mechanism construction, resource guarantee ability and collaborative driving force of emergency information sharing, the paper proposed the evaluation index system and the evaluation method. Results: The empirical results showed that the efficiency of emergency information sharing in coastal cities in China was generally low, and the contribution rate of the construction level of emergency information sharing mechanism is higher than that of the resource guarantee ability and the collaborative driving force of emergency information sharing, but the efficiency of emergency information sharing in coastal cities in China was still at the bottom level. Conclusion: The research results provided theoretical basis and methods for the emergency management departments of coastal cities in China. [ABSTRACT FROM AUTHOR]

Acute coronary syndrome (ACS) is a serious cardiovascular disease that can lead to cardiac arrest if not diagnosed promptly. However, in the actual diagnosis and treatment of ACS, there will be a large number of redundant related features that interfere with the judgment of professionals. Further, existing methods have difficulty identifying high-quality ACS features from these data, and the interpretability work is insufficient. In response to this problem, this paper uses a hybrid feature selection method based on gradient boosting trees and recursive feature elimination with cross-validation (RFECV) to reduce ACS feature redundancy and uses interpretable feature learning for feature selection to retain the most discriminative features. While reducing the feature set search space, this method can balance model simplicity and learning performance to select the best feature subset. We leverage the interpretability of gradient boosting trees to aid in understanding key features of ACS, linking the eigenvalue meaning of instances to model risk predictions to provide interpretability for the classifier. The data set used in this paper is patient records after percutaneous coronary intervention (PCI) in a tertiary hospital in Fujian Province, China from 2016 to 2021. In this paper, we experimentally explored the impact of our method on ACS risk prediction. We extracted 25 key variables from 430 complex ACS medical features, with a feature reduction rate of 94.19%, and identified 5 key ACS factors. Compared with different baseline methods (Logistic Regression, Random Forest, Gradient Boosting, Extreme Gradient Boosting, Multilayer Perceptron, and 1D Convolutional Networks), the results show that our method achieves the highest Accuracy of 98.8%. [ABSTRACT FROM AUTHOR]

Background: China has been exploring a sustainable development path that harmonizes economic growth and environmental protection, targeting to build a beautiful China. The role of green finance in adjusting the misallocation of financial resources and leading the green sustainable development of the real economy is receiving increasingly more attention. Currently, green credit accounts for more than 90% of the total green finance funding in China and constitutes the most significant component of the green finance matrix. Whether green credit effectively promotes the green and sustainable development of the regional economy largely determines the success of China's economic green transformation. Objective: Existing studies of green credit mainly focus on its influences on financing, investment, and emission reduction of environmental pollution industries or companies. Extending the literature by exploring whether green credit is effective in promoting green sustainable development and what impact green credit exerts on the upstream (energy inputs), midstream (technological innovation), and downstream (pollution outputs) stages of the green sustainable development value chain, is the leading research objective of this paper. Methods: This paper discusses the impact of green credit on green sustainable development based on city panel data from 2012 to 2019. The level of green sustainable development is calculated by the GML index based on SBM directional distance function. The city-level green credit scale is calculated from the green credit issued by banks, weighted by the density of bank branches in a city. Synthetic control methods are employed in the robustness analysis to reduce the impact of endogeneity issues. Results and conclusion: The results of this paper indicate that green credit can promote green sustainable development and the impact gradually strengthens over time as the incremental implementations of complementary policies with substantial constraints and incentives, through which pollution control and economic growth achieve a "win-win" situation. Furthermore, the results indicate that green credit reduces the overall amount of energy inputs while optimizing the energy input structure. However, green credit does not boost the green technological level and even crowds out high technical value green innovations. Besides, the pollution reduction effects of green credit are associated with the strength of green credit constraints and the importance of pollution industries in the local economy, which means green credit performs better pollution reduction effects in regions with relatively strong green credit binding effects or in regions where pollution industries are not local economic pillars. The empirical results are further validated through robustness tests, including changing scope and measurement variables and applying the synthetic control method. Limitations: Although this paper provides valuable contributions to the research area of green credit and green sustainable development, specific limitations exist in the current study. Firstly, as the official information disclosure of green credit in China is not sufficient, existing studies, including ours, could only use estimation methods through different perspectives to measure green credit, which is overall logical and reasonable but may lose some accuracy. Secondly, since there might be a certain degree of lag in the effect of green credit on the economy, the dynamic impact and long-term effects of green credit deserve further study. Thirdly, considering the characteristics of the Chinese administrative systems, introducing the behavior of local governments and local officials into the analysis of green credit and green sustainable development could be valuable. [ABSTRACT FROM AUTHOR]

According to the standard of GB/T4754-2017 Classification of National Economic Industry and the characteristics of the textile and apparel industry, the textile and apparel industry is divided into three categories: textile industry, clothing industry and chemical fiber manufacturing industry. Based on the panel data of the textile and apparel industry from 2010 to 2019, this paper measures green total factor productivity (GTFP) by using the unexpected output super efficiency SBM model and the ML index. On this basis, this paper empirically tests the impact of digital economy on the GTFP of textile and apparel industry, and the dual intermediary effects of rationalization of industrial structure and advanced industrial structure are discussed. The results show that: (1) The GTFP of the textile and apparel industry shows a fluctuating upward trend, but it is in a state of low growth. (2) Digital economy has a significant effect on promoting the GTFP. Among them, it has a positive effect on the improvement of GTFP in textile industry, but has no obvious effect on the clothing industry, and has a restraining effect on the chemical fiber manufacturing industry. (3) In the process of the impact of digital economy on GTFP, the rationalization of industrial structure has a partial intermediary effect, and the level of effect reaches 35.81%, while the advancement of industrial structure does not necessarily have a "structural dividend", and its influence on GTFP is non-linear. This paper enriches the research on the influencing factors of GTFP, and is also an effective supplement to the research on digital economy. The conclusions provide a reliable empirical basis for digital economy to help the textile and apparel industry pollution control, and also provide policy references for giving full play to the green value of digital economy. [ABSTRACT FROM AUTHOR]

Border tourism plays an important and positive role in international economic and cultural cooperation, and the tourism cooperation relationship between China and North Korea has lasted for more than 30 years. China has become the country with the largest number of tourists to North Korea. However, because the relevant data of tourism to North Korea are not public, it also brings difficulties to the further study. This paper based on the Baidu Index of 31 provinces and regions in China and discusses the temporal and spatial distribution characteristics and influencing factors of travel demands to North Korea. The findings from the research are as follows. First, the travel demands from 2011 to 2018 showed an overall trend of initial increase followed by later decrease. The seasonal difference is significant. The peak season is longer than the off-season. Secondly, on the whole, the travel demands to North Korea showed a spatial agglomeration effect, and the provinces with high demands or low demands gather significantly in space. Taking "Hu line" as the boundary, the east is higher than the west. The hot spot areas and cold spot areas gradually transition from east to west. Thirdly, holidays, population, GDP, per capita disposable income, Internet penetration and education are the main influencing factors of tourism demand to North Korea. By using Baidu Index, this paper overcomes the bottleneck of inaccessible tourism data to North Korea. At the same time, from the perspective of tourist source countries, this paper discusses the spatial-temporal differentiation and influencing factors of travel demands in terms of geographical space, and compares it with existing studies, expanding the research framework of China's outbound tourism. [ABSTRACT FROM AUTHOR]

The development of globalization has separated the production and consumption of products spatially, and the international trade of products has become a carrier of embodied carbon trade. This paper adopted the perspective of value-added trade to calculate the amount of embodied carbon trade of China from 2006 to 2015 and perform a structural decomposition analysis of the changes in China's embodied carbon trade. This study found that: (1) China's embodied carbon exports are much larger than its embodied carbon imports, and there are differences between countries. China imported the largest amount of embodied carbon from South Korea, and it exported the largest amount of embodied carbon to the United States. (2) The structural decomposition analysis shows that changes in the value-added carbon emission coefficient during the study period would have caused China's embodied carbon trade to decrease, and changes in value-added trade would have caused China's embodied carbon trade to increase. Therefore, countries trading with China need to strengthen their cooperation with China in energy conservation, emission reduction, and product trade. In order to accurately reflect China's embodied carbon trade, it is necessary to calculate embodied carbon trade from the perspective of value-added trade. [ABSTRACT FROM AUTHOR]

This paper empirically studies the relationship among inclusive finance, industrial structure upgrading and farmers' income, using the panel data of 28 provinces in China from 2006 to 2016.The research finds that inclusive finance can significantly promote the increase of farmers' income. Moreover, the Upgrading of Industry Structure (UIS) is the intermediary mechanism of inclusive finance to promote the increase of farmers' income, and this intermediary mechanism is heterogeneous among farmers with different income levels. Finally, the promotion effect of the UIS on farmers' income is affected by the threshold effect of inclusive finance. Compared with the development level of low inclusive finance, the promotion effect of the UIS on farmers' income is stronger under the development level of high inclusive finance. According to the results of empirical analysis, we suggest that the development strategy of inclusive finance should aim at the industrial development in rural areas, promote the organic connection between farmers and modern agricultural industry, and drive farmers to increase their income through the transformation and upgrading of rural industries. [ABSTRACT FROM AUTHOR]

In this paper, we take the Yangtze River Economic Belt as the study area and analyze three types of environmental regulation tools, namely, command-and-control (CAC), market-incentivized (MI) and public-type (PT). We apply the threshold effect to test the impact of each of these tools on regional economic growth and analyze the relationships between the tools and environmental regulation. The entropy method is used to calculate the comprehensive environmental pollution index of each province and city in the Yangtze River Economic Belt. Using Stata 14.0 measurement software and based on provincial data with respect to the Yangtze River Economic Belt from 2014 to 2021, a panel threshold model is used to test the impact of the three types of environmental regulation tools on regional economic growth and analyze the relationship between environmental regulation and regional economic growth. It is found that the relationship between environmental regulation and economic growth is non-linear. There is no significant relationship between CAC environmental regulation and regional economic growth; there is a single threshold effect between market-incentive environmental regulation and public participation environmental regulation on the economic growth of the Yangtze River economic belt. [ABSTRACT FROM AUTHOR]

This paper constructs a theoretical model of biased production decisions due to the import of environmental intermediate goods. Additionally, it analyzes the influence of these imports on CO2 emissions based on the trade and CO2 emission data of Chinese prefecture-level cities from 2000 to 2016. Furthermore, it empirically explores how environmental intermediate imports affect CO2 emissions. The study found the following: first, the import of environmental intermediate goods can effectively reduce CO2 emissions; this conclusion still holds under robustness and endogeneity tests. Second, the carbon emission reduction effect related to the import of environmental intermediate goods is affected by differences in geographical location, environmental pollution, sustainable development ability and government efficiency. Third, the mechanism test found that the import of environmental intermediate goods exerts emission reduction effects through the green technological innovation and industrial structure upgrading mechanisms. The conclusions of the research in this article provide a reference for coordinating trade development and environmental protection. [ABSTRACT FROM AUTHOR]

Goodwill has been a controversial issue in China since 2007 when the new accounting standards changed the subsequent measurement of goodwill from periodic amortization to impairment testing. Using the change in subsequent measurement of goodwill, this paper examines the impact of goodwill accounting on corporate M&A and industry development. The paper finds that adopting the goodwill impairment test significantly increases firms' M&A incentives, as evidenced by a significant increase in the frequency and probability of M&A and a significant reduction in the time interval between successive M&A at the industry level. From an industrial perspective, the impairment policy has significantly improved industry concentration, total factor productivity, and competitive advantage in international trade across Chinese industries. The positive impact of goodwill impairment policy on M&A is more pronounced among firms with asset-light characteristics or high P/E ratios, and its contribution to industry competitiveness is more pronounced in asset-light or high P/E ratios industries. From the perspective of promoting capital market mergers and acquisitions and industry competitiveness, the article finds that the current goodwill impairment policy can have positive economic consequences. Our study breaks through existing perspectives to provide compelling empirical evidence for the current theoretical and practical controversy over goodwill measurement standards. [ABSTRACT FROM AUTHOR]

Scientific evaluation of yachting tourism safety risks (YTSRs) is crucial to reducing accidents in this sector. This paper is based on the data of 115 yachting tourism accidents in China's coastal areas from 2008 to 2021. A fishbone diagram and the analytic hierarchy process (AHP) were used to identify the risk factors of yachting tourism from four aspects human, yachting, environmental, and management risk and to construct an evaluation index system. To perform dynamic evaluation, a dynamic evaluation model of YTSRs was built using dynamic Bayesian networks (DBN). The results indicate that human factors, such as the unsafe behavior of yachtsmen and tourists, are the primary risk factors; the risk is higher in summer than in winter, and the Pearl River Delta region has a greater risk of yachting tourism. It is suggested to improve the normal safety risk prevention and control system of yachting tourism, to advocate for multi-subject coordination and co-governance, and to improve the insurance service system so as to provide a guarantee for the safe and healthy development of yachting tourism in China. The findings provide theoretical and practical guidance for marine and coastal tourism safety management, as well as the prevention and control of YTSRs. [ABSTRACT FROM AUTHOR]

This paper explores the impact of artificial intelligence and industrial robots on firms' export behaviour and divides the impact mechanism into the productivity effect and labour substitution effect. It examines the effect of industrial robots on firms' export value by using Chinese Customs data, Chinese Industrial Firm data and robot data from the International Robot Federation (IRF). The main findings are as follows: Firstly, the impact of artificial intelligence and industrial robots on Chinese firms' export value is generally negative, which means the negative labour substitution effect dominates the positive productivity effect. Secondly, the impact of artificial intelligence varies significantly by industry, and the export value of firms from high-tech industries benefits from the use of industrial robots. Thirdly, the impact of artificial intelligence on firms' export value also varies by time; before 2003, the use of industrial robots showed mainly an inhibiting effect on firms' exports, which turned into a driving effect thereafter, and after 2006, industrial robots began to significantly promote firms' export. Finally, the higher the quality of export products, the more likely the use of industrial robots will be to promote firms' export value, and the higher the capital–labour ratio is, the more likely firms' export value will be to benefit from the use of artificial intelligence and industrial robots. On the basis of these findings, this study proposes promoting the productivity effect to dominate the labour substitution effect through technological progress and the improvement of export product quality. [ABSTRACT FROM AUTHOR]

Background and objectives: Addressing climate change and reducing greenhouse gas emissions have emerged as shared global objectives. Enhancing the development performance of low-carbon cities has become an urgent and widely acknowledged concern for both government policy-making departments and academics. Drawing upon the complex grouping perspective and resource allocation theory, this study investigates how varying conditions related to technology, organization, and environment in Chinese low-carbon pilot cities can effectively allocate resources to shape the governance performance of low-carbon cities. Methods and data: This paper employs a comprehensive grouping analysis perspective, treating the research object as a combination of various ways between condition variables. It integrates the advantages of case studies and variable studies, and investigates the collective relationships between elemental groupings and outcomes using the fsQCA analysis method. This approach facilitates the understanding of multiple concurrent causal relationships within the technology-organization-environment (TOE) framework, accounting for different performance levels in Chinese low-carbon pilot cities, as well as addressing complex causal issues such as asymmetry and multiple scenario equivalence. Data from 30 representative low-carbon pilot cities in China were employed to validate the TOE theoretical framework. Conclusion: No single element alone can be considered a necessary condition for low-carbon city governance performance. However, environmental enhancement plays a more prominent role in the governance performance of low-carbon cities. Additionally, the presence of "multiple concurrent" technical, organizational, and environmental conditions leads to a diverse range of governance performance in Chinese low-carbon pilot cities. In other words, the driving paths of low-carbon city performance exhibit distinct pathways. Contribution: The findings of this study can assist low-carbon pilot city managers in generating effective governance ideas, facilitating the successful implementation of low-carbon city pilot projects, and drawing valuable lessons from the experience of low-carbon city development in China. [ABSTRACT FROM AUTHOR]

In the current era of big data, the exponential increase in the volume of social data has exerted a significant influence on the government and all sectors of society, with the opening of government data becoming an irresistible trend. In this paper, several regional central cities are selected as the representatives of municipal governments to analyze the characteristics and weaknesses of their data-opening policies from various perspectives including policy effectiveness, policy tools, and policy targets. This is of reference significance for the municipal governments of an individual country in the formulation of data opening policies. To be specific, with 2015–2021 as the timeline, based on the six regions of the country, the central cities of each region are selected as representatives of municipal cities, and the text coding of 85 data opening policies implemented in regional central cities are performed. On this basis, a "policy tool-policy targets-policy effectiveness" collaborative measurement model is constructed through the policy tool theory, and the co-evolution analysis of the relevant policies is conducted. The research results are as follows. Firstly, there is a positive correlation between the total policy effectiveness and its quantity, indicating that the number of data-opening policies plays a positive role to a certain extent. However, the average effectiveness shows no significant increase, indicating the inadequate specificity of each policy. Secondly, the degree of synergy between policy tools fluctuates periodically, indicating that the government is constantly trying new methods, with more importance attached to the synergy between government capacity cultivation and positive incentive tools. Thirdly, policy targets continue to show new connotations over time, and there has been new progress made in the coordination between the other three objectives driven by data opening. However, it is imperative to enhance the synergy between the objectives of building a smart city and improving the services related to livelihood. Finally, some targeted suggestions are put forward on how to further improve the data opening policy implemented by municipal governments from three perspectives. [ABSTRACT FROM AUTHOR]

As an important means of environmental regulation, environmental punishment lacks in empirical evidence on its impact on regional green technology innovation in China. Based on panel data of 30 provinces in China from 2010 to 2020, this paper systematically examines the relationship between environmental punishment and regional green technology innovation. It is found that environmental punishment has the quantity and quality enhancing effects on regional green technology innovation, and the quantity enhancing effect is greater than the quality enhancing effect. There is no significant effect difference between monetary punishment and non monetary punishment on green technology innovation effect, but the effect of punishment on institutions is obviously greater than that of punishment on individuals. And the performance of ecological provinces and provinces with better legal environment is also relatively better. Environmental punishment enhances the quantity and quality of green technology innovation through pressure, and improves the quality of green technology innovation through deterrence. Besides, in China, deterrence promotes regional green technology innovation together with the Central Government's environmental protection inspection, the national green manufacturing strategies and other policies concerned. [ABSTRACT FROM AUTHOR]

Our paper explores whether Chinese insurance companies exhibit a local preference in deciding their equity portfolios and the incentive of this preference. Our research finds that Chinese insurance institutional investors significantly tilt to invest in local firms geographically close to them, and local investments do not significantly outperform non-local investments. The results indicate that the behavioral aspect of home bias, rather than information advantage, play a more significant role in deciding equity holdings of China's insurance companies. Additionally, local equity preference is more pronounced in dialect-segmented areas and life insurance firms. This paper incorporates hometown identification into the analysis framework of insurance companies' portfolio decision-making and enriches the research of their investing strategies from the perspective of behavioral finance. [ABSTRACT FROM AUTHOR]

Corporate environmental information disclosure is an important way for stakeholders to understand the performance of corporate environmental responsibilities. To explore the group relevance of corporate environmental information disclosure, this paper empirically tests the intra-industry peer effect of corporate environmental information disclosure using a panel fixed-effects model based on data of Chinese heavily polluted listed companies from 2015 to 2019 and studies its formation mechanism and impact path. The results show that there is an intra-industry peer effect in corporate environmental information disclosure; this effect exists in corporations of different ownership; social learning mechanism and environmental pressure mechanism are the channels to form the intra-industry peer effect of corporate environmental information disclosure; there are both intra-group imitation and inter-group imitation in the intra-industry peer effect of corporate environmental information disclosure. Based on the research results, the government can select corporations in various industries with excellent quality of environmental information disclosure as benchmarks to provide learning templates for corporations with inferior information. At the same time, the government can impose appropriate environmental protection pressure to promote learning and imitation among corporations. It is important to note that when selecting benchmarking companies, priority should be given to large and high-performing corporations. [ABSTRACT FROM AUTHOR]

This paper takes the 2014 pilot project of accelerated depreciation of fixed assets as a quasi-natural experiment, and builds a Propensity Score Matching–Difference in Differences (PSM-DID) model based on the data of Chinese listed companies from 2000 to 2019 to test the impact of tax preference on enterprise investment efficiency and its mechanism. The results show that the policy inhibits supported enterprises investment efficiency significantly. Heterogeneity analysis shows that the policy causes greater investment efficiency losses for small and medium-sized enterprises, non-state-owned enterprises and asset-heavy enterprises. The mechanism test found the reason why the policy eased financing constraints but inhibited investment efficiency in short-term. After a variety of robustness tests, the above basic conclusions are still valid. Although the accelerated depreciation policy of fixed assets is conducive to expanding the scale of investment, the incentive effect on investment efficiency is not obvious, and even shows a restraining effect. Given the existence of heterogeneity, the design of the policy should not only distinguish industries, but also pay attention to the differences between different enterprises in the same industry. Strengthening research and development (R&D) innovation and improving the matching mechanism between human capital and fixed investment will help give full play to the incentive effect of this policy. The research in this paper helps to deepen the understanding of the microeconomic effects of tax policy and identify the internal mechanism, which not only enriches the relevant literature, but also provides a reference for the government to better use tax policy to promote the high-quality development of enterprises. [ABSTRACT FROM AUTHOR]

Urban economic development is crucial to regional economy and people's life, and enhancing the efficiency of urban economic development is of great significance to boost sustainable and healthy economic and social development. In this paper, from the perspective of sustainable development, data of 104 cities in China's Yangtze River Economic Belt (YREB) from 2004 to 2019 are selected, and the urban resource consumption index and urban pollutant emission index are synthesized as new input-output indicators using the Time Series Global Principal Component Analysis (GPCA), combined with the Global Malmquist-Luenberger (GML) Index Model, Standard Deviation Ellipse (SDE) Model to measure the total factor productivity index of urban economic development in China's YREB and analyze its spatial and temporal evolution. The results show that from 2004 to 2019, the total factor productivity index of urban economic development in China's YREB showed an overall fluctuating upward trend with an average annual growth of 5.8%, and the analysis by decomposing indicators shows that the growth of total factor productivity of urban economic development in China's YREB is mainly influenced by the growth of technological progress. Meanwhile, there are obvious regional differences in the efficiency of urban economic development in China's YREB, with the largest difference in the middle reaches of the Yangtze River, the second largest in the upper reaches, and the smallest in the lower reaches. From 2004 to 2019, the efficiency center of gravity of urban economic development efficiency in the YREB has always been located in the middle reaches of the Yangtze River region. The spatial distribution pattern of urban economic development efficiency in the YREB is dominated by the northeast-southwest direction and tends to be concentrated in the study time period. [ABSTRACT FROM AUTHOR]

In the context of China's commitment to peak carbon emissions by 2030 and achieve carbon neutrality by 2060, as well as its strategy to build a strong transportation country, it is of foremost importance to study the carbon emission reduction effect of the opening of high-speed rail (HSR). This paper innovatively introduces the frequency of HSR stops as an indicator of HSR operation, and uses a time-varying difference-in-difference (DID) model, a mediating effect model and a spatial DID model to assess the direct and indirect impact, transmission mechanism, and spatial spillover effects of the opening and operation of HSR on carbon emission reduction based on a panel of 279 prefecture-level cities from 2003 to 2017. We found that the opening and operation of HSR significantly reduced urban carbon emissions. The direct transmission mechanism analysis shows that the opening of HSR can reduce carbon emissions by replacing highway passenger traffic. Indirect mechanism analysis shows that the opening of HSR can reduce carbon emissions through technological effect, structural effect and opening effect. The test of spatial spillover effect shows that the opening of HSR can promote carbon emission reduction not only in node cities, but also in neighboring cities. [ABSTRACT FROM AUTHOR]

Microblog has become the "first scenario" under which the public learn about the epidemic situation and express their opinions. Public sentiment mining based on microblog data can provide a reference for the government's information disclosure, public sentiment guidance and formulation of epidemic prevention and control policy. In this paper, about 200,000 pieces of text data were collected from Jan. 1 to Feb. 26, 2020 from Sina Weibo, which is the most popular microblog website in China. And a public sentiment analysis framework suitable for Chinese-language scenarios was proposed. In this framework, a sentiment dictionary suitable for Chinese-language scenarios was constructed, and Baidu's Sentiment Analysis API was used to calculate the public sentiment indexes. Then, an analysis on the correlation between the public sentiment indexes and the COVID-19 case indicators was made. It was discovered that there is a high correlation between public sentiments and incidence trends, in which negative sentiment is of statistical significance for the prediction of epidemic development. To further explore the source of public negative sentiment, the topics of the public negative sentiment on Weibo was analyzed, and 20 topics in five categories were got. It is found that there is a strong linkage between the hot spots of public concern and the epidemic prevention and control policies. If the policies cover the hot spots of public concern in a timely and effective manner, the public negative sentiment will be effectively alleviated. The analytical framework proposed in this paper also applies to the public sentiment analysis and policy making for other major public events. [ABSTRACT FROM AUTHOR]

China is a large country with rapid economic expansion and high energy consumption, which implies that the country's overall carbon emissions are enormous. It is vital to increase urban low-carbon economy efficiency (ULEE) to achieve sustainable development of China's urban economy. Digital finance is a significant tool to boost ULEE by providing a convenient and effective funding channel for urban low-carbon economic transformation. Analyzing the coupled and coordinated relationship between ULEE and digital finance is of vital importance for the sustainable development of the urban economy. This paper selects panel data of 100 cities in China's Yangtze River Economic Belt (YEB) in 2011-2019, and analyzes the research methods such as the Global Malmquist-Luenberger index model, coupling coordination degree (CCD) model, standard deviation ellipse model, gray model, and geographic detector by The spatial and temporal distribution, dynamic evolution characteristics and influencing factors of the CCD between ULEE and digital finance are analyzed. The study shows that: (1) the CCD of ULEE and digital finance grows by 3.42% annually, reflecting the increasingly coordinated development of the two systems; (2) The CCD of ULEE and digital finance shows a distribution pattern of gradient increase from the upstream region of Yangtze River to the downstream region, meanwhile, the spatial center of gravity moves mainly in the midstream region; (3) The spatial center of gravity of CCD of ULEE and digital finance is expected to move 22.17 km to the southwest from 2019 to 2040; (4) In terms of influencing factors, the influence of informatization and industrial structure on the CCD increases over time, while the influence of factors such as population development, greening, transportation, and scientific research decreases over time. Finally, this paper proposes policy recommendations for improving the CCD of ULEE and digital finance based on the empirical results. [ABSTRACT FROM AUTHOR]

Intelligentization-oriented development is a fast-developing trend of technological revolution. It promotes the reconstruction of the industrial system of a region and affects its overall industrial competitiveness. This paper sets up a variety of models featuring intelligentization level and multi-dimensional industrial competitiveness, and collects data of 28 provinces and cities in China from 2003 to 2017 to test the influence of industrial intelligentization level on the industrial competitiveness of a region. The result reveals that: 1) In China's provincial jurisdictions, the higher the level of intelligentization is, the lower the overall level of industrial competitiveness and the lower the proportion of industry in the economic system will be. In regions where the facilities are highly intelligentialized, the production sectors tend to move to the less developed regions, and the growth effect of technological dividends is the focus. 2) Compared with the middle region and the Western region of China, the Eastern region, which is more developed with higher intelligentization level, has stronger ability in the research and development (R&D) of technologies, and the economic structure of the industry there tends to be stable, manifesting a strong growth potential. [ABSTRACT FROM AUTHOR]

With the development of information technology, improving the efficiency of public services with the help of the Internet has become an important work of local governments. However, under different institutional environments, the impact mechanism of Internet development on the supply efficiency of government public services is still unclear. Based on China's interprovincial panel data from 2011 to 2019, this paper constructs a threshold effect model, sets the institutional environment as the threshold variable, and empirically analyzes the impact of Internet development on the supply efficiency of government public services. The results show that the difference in regional institutional environment will lead to the obvious threshold effect of Internet development on the supply efficiency of government public services: When the institutional environment is poor, the role of Internet development on the supply efficiency of government public services is not significant. With the improvement of the institutional environment, the role of Internet development in promoting the supply efficiency of government public services gradually appears, but the marginal intensity of promotion weakens. Compared with existing studies that mostly use linear models, this paper incorporates the institutional environment into the complex relationship between Internet development and government public service supply efficiency, and clarifies the role of the institutional environment in the process of Internet development affecting government public service supply efficiency and the non-linear relationship among the three. This paper reveals the mechanism of Internet development affecting the supply efficiency of government public services under different institutional environments and provides a new perspective for solving the shortage of public services. [ABSTRACT FROM AUTHOR]