Analysis of the mechanism of the impact of internet development on green economic growth: evidence from 269 prefecture cities in China

Spatio-temporal evolution and driving factors of the coupling and coordinated development of China's digital economy and older adult care services

Background

This study aims to examine the level of coupled and coordinated development between China's digital economy and older adult care services, analyzing their spatiotemporal evolution characteristics and key influencing factors, with the goal of providing feasible recommendations and scientific bases for the development of the digital economy and older adult care services in China.

Methods

This study uses publicly available panel data from China for the years 2015-2022. It employs the entropy method to measure the weights of various indicators in the digital economy and older adult care services. The study analyzes the level of coordinated development between the two using the coupling coordination degree model, and measures the main driving factors using the geographical detector model.

Results

(1) The overall level of coupling and coordinated development between China's digital economy and older adult care services shows an upward trend, but the growth rate is uneven, exhibiting an "M-shaped" pattern, with rapid growth followed by gradual slowdown, a bottoming-out rebound, and then a continuous decline. (2) There are significant spatial differences in the coupling and coordinated development of China's digital economy and older adult care services. Coastal areas are developing rapidly, inland areas have great potential, while peripheral areas are relatively lagging behind. Additionally, neighboring regions show regional linkage dynamics. (3) The main factors driving the coupling and coordinated development of China's digital economy and older adult care services include enterprise website ownership, technological contract turnover, the proportion of information technology service income, the building area of older adult care institutions, daily in-house visits, and the number of professional technical personnel.

Conclusion

To achieve coordinated development between the digital economy and older adult care services, efforts should focus on policy, market, technology, and talent. The government should support technological innovation and new service models, while tailoring strategies to regional market demands. Additionally, accelerating the industrialization of innovations and promoting intelligent upgrades in older adult care services are crucial. Finally, more investment is needed to cultivate composite talents in both the government and older adult care institutions.

Exploring the path of digital governance of urban industrial pollution: empirical evidence from 280 cities in China

Urban industrial pollution plays a dominant role in environmental pollution in China. Exploring the digital governance path of urban industrial pollution can provide strong support for improving environmental quality. This article empirically investigates the role and path of digitalization in the governance of urban industrial pollution from three dimensions: economic scale, structural scale, and technological scale. The results show that there is an inverted "U"-shaped relationship between digitalization and urban industrial pollution, with initial promotion followed by suppression. Among them, economic scale, industrial transformation and upgrading, and green innovation are the paths for digital governance of urban industrial pollution. In addition, there is a chain path of "green innovation-industrial transformation and upgrading" between the two. Through spatial Durbin model and regional heterogeneity analysis, it is found that digitalization has a spatial spillover effect on urban industrial pollution control, and eastern regions, regions with high economic development level and industrialized cities benefit more from digital urban industrial pollution control. The research conclusions of this article provide references for the Chinese government to formulate relevant policies, deepen the integration of digitalization and urban industrial pollution, and promote digital governance of urban industrial pollution.

Internet use, income mobility and the expansion of the rural middle-income group: Evidence from China

The expansion of the rural middle-income group has been a global focus as it contributes to narrowing income gaps and reducing social inequality. Using data from the China Family Panel Studies (CFPS), this study examines the impact of Internet use on the mobility of rural low-income groups to the middle-income group from the perspective of income mobility. Controlling for household and provincial-level variables, the results of this study indicate that Internet use significantly promotes the mobility of rural low-income groups to the middle-income group, thereby facilitating the expansion of the rural middle-income group. These conclusions hold even after conducting endogeneity and robustness tests. Mechanism analysis shows that household entrepreneurship and non-agricultural employment are crucial pathways through which Internet use facilitates the mobility of rural low-income groups to middle-income groups. Further investigation shows that mobility from rural low-income to middle-income groups is more difficult in central-western regions and among those with lower levels of education. Internet use exacerbates the "digital divide" between different areas and education groups. In particular, the effect of Internet use in promoting mobility from rural low-income to middle-income groups is more pronounced in the eastern regions and among those with higher levels of education. The results of this study provide new evidence on the role of Internet use in expanding the rural middle-income group.

Digital economy, resource distortion and low-carbon inclusive development-Evidence from the perspectives of a threshold effect and knowledge spillover effect

The low-carbon economy represents a global transformation that encompasses production methods, lifestyles, values, national interests, and the destiny of humanity. As a significant contributor to carbon emissions, China has made a momentous strategic decision on carbon peaking and neutralization, infusing momentum into the global effort to address climate change. The rapid growth of the digital economy offers a fresh approach to achieving the "double carbon" objective and advancing the development of low-carbon transformation. Based on the panel data of 30 provinces in China, this paper uses the least square method to investigate the impact of digital economy development on regional low-carbon inclusive development. It is found that there is a significant inverted U shape in the impact of the digital economy on low-carbon inclusive development and the mechanism is resource allocation and ecological inequality. The threshold test found that the role of the digital economy in promoting low-carbon inclusive development shows a marginal decreasing trend. The inverted U-shaped impact of the digital economy on low-carbon inclusive development in the eastern and coastal areas and areas with a low level of factor productivity is more significant. Based on the knowledge factor spillover perspective, we found that the impact of the digital economy on low-carbon inclusive development has a spatial spillover effect, and this effect is more obvious under the role of R&D personnel mobility.

Examining the relationship between international digital trade, green technology innovation and environmental sustainability in top emerging economics

Ensuring preserving a sustainable environment is a crucial concern for individuals worldwide. In previous research, CO2 emissions have been used to measure environmental deterioration. However, in this study, we have expanded the scope to include carbon emissions and several other gases. This comprehensive measure is referred to as the ecological footprint (EFP). More significant international digital trade (IDT) has the potential to achieve several positive results, including reducing EFP (economic frictions and barriers), stimulating economic growth, and minimizing trade risk and volatility. These benefits can be realized by implementing structural reforms in significant production and development sectors. Green technology innovation (GTI) has the potential to make substantial progress in ecological quality and energy efficiency. Nevertheless, previous studies still need to adequately prioritize examining rising economies in terms of international trade diversification and GTI. This study examined the effects of IDT, GTI, and renewable energy consumption (REC) on EFP in BRICST countries. The study utilized data from the period between 1995 and 2022. The cross-sectionally augmented autoregressive distributed lag (CS-ARDL) model demonstrates that EFP negatively correlates with trade diversification, REC, and GTI in the long and short term. These countries have demonstrated a significant presence of eco-friendly products in their trade portfolios, and their manufacturing processes are shifting towards GTI. The objective is to enhance the REC sources and minimize EFP from consumption. Conversely, the increasing economic growth within this economic group has a compounding impact on the environment's decline since it amplifies the carbon emissions from increased consumption. To reduce the EFP level, the paper suggests increasing investment in GTI, promoting worldwide digital trade, and embracing renewable energy sources.

Can digital economy development contribute to urban carbon emission reduction? - Empirical evidence from China

In the context of global digitalization, fostering the expansion of the digital economy holds immense importance in promoting energy efficiency and reducing emissions. Utilizing a sample of 281 prefecture-level cities in China from 2003 to 2019, this research analyzes the impact of the digital economy on urban carbon emissions in China. This study employs various methods, including principal component analysis, fixed-impact model, and mediating effect model. Based on the research findings, the development of the digital economy has the potential to significantly reduce carbon emissions in metropolitan areas. Moreover, these effects are especially noticeable in cities located to the east of the Hu Huanyong Line. These cities are characterized by limited reliance on resources and a high level of marketization. Further research reveals that promoting technical innovation and modernizing industrial structures can reduce the intensity of carbon emissions in metropolitan areas. This study provides empirical evidence supporting the effective reduction of carbon emissions in developing countries during the evolution of the digital economy. It acts as a crucial cornerstone for guiding policies and executing strategies aimed at fostering top-tier economic development in the future. The findings of this study confirm the inhibitory effect of the digital economy on urban carbon emission intensity. However, this study has limitations in data samples, research scope, and depth of mechanism analysis, which prevent a full exploration of the spatial spillover effect of the digital economy and other factors. Therefore, the conclusions drawn in this study can only provide empirical evidence for identifying the relationship between the digital economy and carbon emission intensity to a certain extent. Future research should aim to expand on these aspects.

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.

Research on the coupling mechanism and influencing factors of digital economy and green technology innovation in Chinese urban agglomerations

This paper examines the coupling coordination degree between digital economy and green technology innovation in 19 urban agglomerations across China from 2011 to 2020. Through the analysis of the coupling coordination degree model, spatial autocorrelation, multi-distance spatial clustering analysis, kernel density analysis and grey correlation model, this study uncovers the mechanism of coupling between digital economy and green technology in Chinese urban agglomerations. Data analysis revealed a significant increase in the coupling coordination between the digital economy and green technology innovation within urban agglomerations. However, there are noticeable spatial imbalances in this trend. Additionally, the multi-distance spatial distance analysis highlights a shift from a random distribution to a clustered distribution of spatial characteristics. The polarization features vary among each urban agglomeration and exhibit a significant positive spatial correlation. Factors such as economic sustainability, creative talent, policy support, digital impetus, and technological support will affect the coupling mechanism of green technology innovation and the digital economy in China's urban agglomerations. Policy recommendations are proposed to foster the development of the digital economy, promote coordinated growth within and beyond urban clusters, and ultimately build a digital ecological civilization that is both green and intelligent.

Energy saving effects of digital technologies from a life-cycle-analytical perspective: evidence from China

Digital technology has become a key driver of industrial transformation and resource utilization. However, no consensus has been reached on the exact relationship between digital technology and energy utilization. This study adopted a comprehensive index system to investigate the impact of digital technologies on energy utilization across 30 provinces in China. The results reveal a non-linear relationship between digital technologies and energy efficiency in China (represented by an N-curve), which is validated by robustness tests. This indicates digital technology exerts a fast-slow-rapid impact on improving energy efficiency throughout its initial-rapid-stable developmental stages. Geographically, this effect is more pronounced in eastern and central China, as well as in areas with lower energy efficiency. Furthermore, the impact of digital technology on total energy consumption can be characterized by an inverted N-shaped curve. As regional energy efficiency improves, the energy consumption associated with the development of digital technologies gradually decreases. These findings can contribute valuable insights for enhancing energy efficiency and provide practical guidance for the formulation of energy and digital technology policies.

Research on the dynamic mechanism of digital economy system coupling to enhance urban ecological resilience

Urban ecological environment resilience is an important characteristic that should be possessed in the process of urban development. It is conducive to coping with the challenges of multiple risks and disturbances such as climate change, resolving chronic pressure, improving the ability to resist disaster risk, self-adjustment, and recovery, to maintain the structure and function stability of the urban system. The digital economy is a new economic form caused by the new technological revolution, which may effectively promote economic ecology and ecological economization. We clarify the elements of the digital economic system, construct the coupling evaluation index system of "digital infrastructure-industrial digitization-digital industrialization," and establish the coupling degree model to analyze the characteristics of the integration interaction, coordination, and self-organization of the digital economy subsystem. Based on emergency management theory, adaptive management concept, and resilient city theory, an evaluation index system is constructed from four levels of prevention, resistance, adaptation, and recovery to measure urban ecological resilience. Taking 278 cities in China from 2011 to 2021 as the research object, we established a spatial econometric model to explore the dynamic mechanism of digital economy system composition and coupling coordination to enhance urban resilience and summarize the theoretical model form. Based on this, we further propose countermeasures and suggestions for improving urban ecological resilience by using a digital economic system.

Can greater openness improve green economy efficiency of countries along the Belt and Road Initiative?

Openness is the core concept of the Belt and Road initiative (BRI), which plays a significant role in promoting the sustainable economic development of countries along the BRI. This study uses the entropy method to measure openness based on six dimensions: trade, investment, finance, tourism, technology, and information. Simultaneously, a super-SBM model with undesired output is proposed to measure green economy efficiency (GEE). Using the panel data of 66 countries along the BRI from 2008 to 2019, we empirically examine the impact of openness on GEE. The results are as follows: (1) The openness level of countries along the BRI is generally increasing, but the relative differences between countries tend to widen. (2) Openness has a significant U-shaped nonlinear effect on GEE, and the conclusion is still valid after considering the robustness test; (3) The spatial econometric model shows that openness not only affects the GEE of the local country, but also has a spillover effect on neighboring countries. Therefore, we believe that BRI countries should strengthen policy communication, break down border barriers, actively promote the orderly flow and diffusion of openness elements, and pay attention to the quantity and quality of openness development, which is key to the high-quality construction of the BRI.

Assessing the impact of human capital, renewable energy, population growth, economic growth, and climate change policies on achieving the sustainable development goals

The global emphasis on achieving sustainable development goals necessitates the involvement of researchers and regulators worldwide. In light of this, recent research has examined the effect of human capital, renewable energy, population growth, economic growth, and environmental protection on the sustainable development goals (SDGs) in a developed economy like Pakistan, which is the most important country in the South Asian Association for Regional Cooperation (SAARC) region. This study analyzed secondary data from 1990 to 2019, using the World Development Indicators as the secondary data source. Using the augmented Dickey-Fuller test to investigate stationarity and the autoregressive distributed lag model to evaluate the nexus between variables, the researchers analyzed the relationship between the variables. The findings indicate that all predictors, such as the human capital index (HCI), renewable energy consumption, and renewable energy, exhibit a negative correlation with carbon emissions and a positive correlation with the SDGs. In this study, sustainability and the HCI are positively correlated. Reducing carbon emissions requires competent and dependable employees. As Pakistan transitions to renewable energy and strives for 30% green electricity by 2030, the report highlights the ecological benefits of controlled population growth. According to the Climate Change Performance Index (CCPI), effective climate policies advance the environmental objectives of a nation. Economic and population growth have a positive correlation with carbon emissions as well. These results facilitate Pakistani policymakers' creation of effective SDG-related initiatives for sustainable development.

Digital economy impact on inclusive green growth: intermediary and spatial spillover effects in China

As a new economic form that has emerged from the technological and digital revolution, the digital economy has great benefits to the green development of the economy, protection of the ecological environment, and improvement in social well-being. This study examines whether the digital economy affects the inclusive green growth (IGG). Measurement index system for the digital economy and IGG from 2013 to 2020 in China was constructed and the entropy evaluation method and super-efficiency epsilon-based measure (Super-EBM) model was used to evaluate them. We examined the direct effect, mediation effect, and spatial spillover effect of the digital economy on IGG using the basic regression model, mediating effect model, and the spatial Durbin model. Our results revealed that the development of the digital economy has clear regional differences. The role of digital economy on IGG has positive direct effects and positive spatial spillover effects. The digital economy affects IGG through industrial structure upgrading, so industrial structure upgrading has a significant intermediary effect. By comparing the coefficients, we found that the spatial spillover effects are stronger than the direct effects. Absorbing the spillover of the digital economy in surrounding areas is particularly important for promoting IGG. Heterogeneity analysis revealed that the digital economy is better for IGG and releases more digital dividends in eastern China. Finally, the research conclusions of this paper provide reference for the Chinese government to formulate relevant policies to deepen the integration of digital information technology and IGG, and promote the coordinated development of regional digital economy and IGG.

Creating a greener future: the crucial role of green innovation and supply chain management in corporate sustainability

One of the most pressing concerns today is how to improve green innovation and supply chain management for company sustainability. It has been discovered that inefficient supply chain management is a major barrier limiting eco-friendly innovation. The supply chain management process is crucial to a company's long-term viability, yet previous research barely scratched the surface of its significance. This article uses a resource-based view to investigate how integrating green innovation and organizational agility into the supply chain management process contributes to the long-term success of businesses. This study used a cross-sectional approach. Structured equation modeling was used to examine data collected through convenience sampling from 475 employees of Chinese multinational manufacturing enterprises. Green innovation helps smooth over the bumps on the road between supply chain management and sustainable business results. Green innovation and business sustainable performance also benefit from organizational agility, which was not shown to moderate this relationship. The study teaches that in today's knowledge-based economy, firms that invest in novel technologies and adopt greener strategies are better able to address sensitive issues like supply chain management and organizational agility and achieve long-term success. This research aims to provide light on the complex interconnections between supply chain management, green innovation, and the sustainable performance of businesses. The theoretical framework for the present research was validated by the occurrence of a positive association between these variables.

Linking energy crises and solar energy in China: a roadmap towards environmental sustainability

Fossil fuels are the primary energy sources of China, which are not only expensive but have adverse environmental impacts. To cope with this situation, the Chinese government wants to fulfil 25% of its energy consumption by non-fossil fuels by 2030. In this perspective, we selected the solar sources of the country and collected solar irradiation data for one year in the six big cities of China in 2022. For the analysis of data and assessing the effectiveness of photovoltaic (PV), RETScreen and MATLAB were utilized. A further step was taken by performing the life cycle assessment (LCA) to scrutinize the different features of solar energy, including fuel consumption, price, average lifetime, maintenance and operation expenses, land requirements, and greenhouse gas emissions. Results reveal that all these cities have enormous solar power potential. However, the highest solar power (0.27 kW) is generated in Nanchang city, while the lowest power (0.21 kW) is generated in Sanya city. Solar energy is durable and has a good average lifespan but can be costly, as PV panels lose efficiency due to dust and pollution. The regular cleaning of PV panels, in turn, demands substantial cost. Based on research results, significant policy suggestions have been recommended to fulfil the country's energy demand on its way to a future of sustainable development.

Green growth strategies in Asia: unleashing the heterogeneous asymmetry of ICT capital, financial fragility, environmental policy stringency, and education

Financial fragility, ICT capital, environmental policy stringency, and education are the main factors that have also gained popularity regarding their impact on green growth. This study examines the impact of financial fragility, ICT capital, environmental policy stringency, and education on green growth. For analyzing the short- and long-run estimates, we have applied the panel QARDL model. The results of the panel QARDL model highlight that the estimates of non-performing bank loans and bank costs are negatively significant in both the short and long run, implying that financial fragility hurts green growth in the short and long run. Similarly, the estimated coefficients of the internet (mobile) and education estimates are positively significant in the short and long run, confirming that ICT capital and education are causing green growth, while environmental policy stringency promotes green growth only in the long run. Regarding the asymmetric effects of all the factors on green growth, the Wald test only confirms asymmetric effects in the long run. The study offers several significant recommendations for sustainable green development policies.

Spatiotemporal differentiation and convergence characteristics of green economic efficiency in China: from the perspective of pollution and carbon emission reduction

Accurate quantification of pollution and carbon emission reduction policies, as well as analysis of green economic efficiency (GEE), are of great significance to accelerating green economic development in China and contributing to pollution prevention and carbon peaking. Using data from 2006 to 2022, this study incorporates pollution and carbon emission reduction policies into the evaluation system, and uses a model with slacks-based measures and a directional distance function (SBM-DDF) to calculate the GEE of 30 provinces. The Dagum Gini coefficient, kernel density estimation, and spatiotemporal convergence analysis are used to analyze the spatiotemporal differentiation and convergence characteristics of GEE. The findings show that the strengths of the pollution and carbon emission reduction policies are increasing but vary greatly among the provinces. China's overall GEE has a time trend with the characteristics of "decline-fluctuation-stable." The Dagum Gini coefficient reveals the relative differences between the major regions. Both the intra-regional and inter-regional differences tend to widen over time and the latter explains most of the sources of the overall differences. Kernel density estimation shows that the absolute differences between the provinces are generally widening, whereas the absolute differences between the provinces in the central and western regions are smaller than those in the eastern region. No obvious σ convergence characteristics exist in the country overall and the three major regions, but β convergence characteristics are present in each region. The factors affecting changes in the GEE of each region are not the same. The study suggests that the China should further improve the implementation of pollution and carbon emission reduction policies, pay attention to the regional differences and convergence issues of GEE, and promote the coordinated development of green economy in different regions. This study innovatively quantifies the policies related to pollution and carbon emission reduction, providing empirical evidence for understanding the performance of pollution and carbon emission reduction policies in various regions. Furthermore, this study incorporates policies as inputs into the GEE evaluation system, reveals the spatiotemporal differentiation of GEE, thereby providing reference for green economic transformation and sustainable development.

Nonlinear and spatial spillover effects of the digital economy on green total factor energy efficiency: evidence from 281 cities in China

Although the digital economy has become a new driving force for development worldwide, it is still unclear how digital economy development affects green total factor energy efficiency (GTFEE). Using panel data from 281 prefecture-level cities in China from 2003 to 2018, this study empirically analyzes the effect of digital economy development on GTFEE by adopting a dynamic panel model, a mediation effect model, a dynamic threshold panel model, and a spatial Durbin model. The empirical results show that digital economy development has a significantly negative direct effect on GTFEE. The digital economy can impact GTFEE by the mechanisms of electrification, hollowing out of industrial scale, and hollowing out of industrial efficiency. Neither innovation nor environmental regulations significantly change this negative impact. The dynamic threshold panel model shows a nonlinear relationship between digital economy development and GTFEE, which indicates that the effect of digital economy development on GTFEE significantly inverts from negative to positive as the digital economy develops. In addition, GTFEE has a significantly positive spatial correlation, and the digital economy has a positive spatial spillover effect on GTFEE.

On the urban resource and environment carrying capacity in China: A sustainable development paradigm

As urbanization progresses, the number of resource and environmental problems that impede sustainable growth in cities is increasing. The urban resource and environment carrying capacity (URECC) serves as a crucial indicator for understanding the interaction between human activities and urban resource and environmental systems, guiding the practice of sustainable urban development. Thus, accurately comprehending and analyzing the URECC and coordinating the balanced growth of the economy and the URECC is essential to ensure cities' sustainable development. In this research, we combine DMSP/OLS and NPP/VIIRS night-time light data to assess the economic growth of Chinese cities using panel data for 282 prefecture-level cities in China from 2007 to 2019. The findings reveal the following outcomes: (1) Economic growth significantly contributes to the enhancement of the URECC, and the economic expansion of neighboring areas also promotes the URECC within the region. Economic growth can indirectly improve the URECC by fostering internet development, industrial upgrading, technological progress, opening up opportunities, and educational advancements. (2) The results from the threshold regression analysis suggest that as the level of internet development improves, the influence of economic growth on the URECC is initially constrained and then facilitated. Similarly, as financial development improves, the effect of economic growth on the URECC is initially constrained and subsequently promoted, with the promotion effect gradually increasing. (3) The relationship between economic expansion and the URECC varies across regions with different geographic locations, administrative levels, scales, and resource endowments.

Impact of digital economic development and environmental pollution on residents' health: an empirical analysis based on 279 prefecture-level cities in China

BACKGROUND

The digital economy based on the internet and IT is developing rapidly in China, which makes a profound impact on urban environmental quality and residents' health activities. Thus, this study introduces environmental pollution as a mediating variable based on Grossman's health production function to explore the impact of digital economic development on the health of the population and its influence path.

METHODS

Based on the panel data of 279 prefecture-level cities in China from 2011 to 2017, this paper investigates the acting mechanism of digital economic development on residents' health by employing a combination of mediating effects model and spatial Durbin model.

RESULTS

The development of digital economy makes direct improvement on residents' health condition, which is also obtained indirectly by means of environmental pollution mitigation. Besides, from the perspective of spatial spillover effect, the development of digital economy also has a significant promoting effect on the health of adjacent urban residents, and further analysis reveals that the promoting effect in the central and western regions of China is more pronounced than that in the eastern region.

CONCLUSIONS

Digital economy can have a direct promoting effect on the health of residents, and environmental pollution has an intermediary effect between digital economy and residents' health; At the same time, there is also a regional heterogeneity among the three relationships. Therefore, this paper believes that the government should continue to formulate and implement scientific digital economy development policies at the macro and micro levels to narrow the regional digital divide, improve environmental quality and enhance the health level of residents.

Can data center green reform facilitate urban green technology innovation? Evidence from China

With the expansion of the digital information industry, the size of global data centers is exploding. As part of a high-energy-consuming industry, data centers can support sustainable urban development through green transformation. This study uses a quasi-natural experiment of China's national green data center pilot policy implemented in 2015 to examine the impact of data center green transformation on green technology innovation in cities. Using a difference-in-difference (DID) analysis, this study finds that the national green data center pilot policy leads to higher levels of green technology innovation in cities, but the spillover effect of the policy on neighboring cities is insignificant. The mechanism test showed that the national green data center pilot policy could facilitate urban green technological innovation through capital deepening, market competition, and industrial agglomeration. In addition, the policy impact is more pronounced for cities with poorer environments, less civilization, high levels of network infrastructure, and more innovative endowments. The findings can provide new guidance for cleaner regional production from the standpoint of data center green development.

Industrial co-agglomeration, Internet utilization, and the development of green and low-carbon cycle - based on the empirical study of 41 cities in the Yangtze River Delta of China

The construction of green and low-carbon circular (GLC) development economic system is conducive to the promotion of "carbon peaking and carbon neutral." The level of GLC development in the Yangtze River Delta (YRD) region is related to the realization of the ambitious goal of "carbon peaking and carbon neutrality" in the region. This paper use principal component analysis (PCA) to process GLC development level of 41 cities in the YRD from 2008 to 2020. Then, we constructed panel Tobit model and threshold model from the perspective of industrial co-agglomeration and Internet utilization and empirically tested the influence of the two key variables on GLC development of the YRD. We found that (1) the YRD's level of GLC development showed a dynamic evolution trend of "fluctuation, convergence, and rise." The four provincial-level administrative regions of the YRD are in the order of  GLC development level: Shanghai, Zhejiang, Jiangsu, and Anhui. (2) There is an inverted "U" Kuznets curve (KC) between industrial co-agglomeration and the development of GLC of the YRD. In the left segment of KC, the industrial co-agglomeration promotes GLC development of the YRD. In the right segment of KC, the industrial co-agglomeration inhibits GLC development of the YRD. Internet utilization enhances GLC development of the YRD. And the interaction of industrial co-agglomeration and Internet utilization cannot significantly enhance GLC development. (3) Double-threshold effect of opening-up is manifested as follows: industrial co-agglomeration on GLC development of the YRD goes through an insignificant-inhibited-improved evolutionary trajectory. Single-threshold effect of government intervention is manifested as follows: the impact of Internet utilization on GLC development of the YRD shifts from insignificant role to significant enhancement. In addition, there is an inverted-N type KC effect between industrialization and GLC development. Based on the above findings, we proposed suggestions in terms of industrial co-agglomeration, Internet-like digital technology application, anti-monopoly, and rational industrialization.

Do green innovation, I.C.T., and economic complexity matter for sustainable development of B.R.I. economies: moderating role of higher education

The research intends to enlarge the environmental economics literature by displaying the probable mechanisms between green innovation, higher education, and sustainable development. In the context of a new era, sustainability faces challenging obstacles. Many studies have looked at fundamental factors affecting CO₂ emissions, while the impact of green innovation and higher education is essential but mostly ignored. This study looked at 60 Belt and Road Initiative (B.R.I.) economies to see how factors, including green innovation, economic complexity index, I.C.T., and higher education, affect carbon emissions in the presence of sustainable development using annual data from 2000-2020. In order to calculate the persistence of the connection between the factors, this research uses the CS-ARDL. The results' robustness and reliability were examined using PMG estimation. The results indicate that the economic complexity index and urbanization positively impact carbon emission (CO₂). Higher education (E.D.U.) has a significant positive impact in the short run and a negative effect in the long run-on carbon emissions. Similarly, information and communication technology (I.C.T.) and green innovation have a negative impact on carbon emission (CO₂). Moreover, the results indicate that the moderate effect of green innovation with economic complexity index, information and communication technology, and higher education has a negative impact on carbon emission. The estimated coefficients also provide significant policy implications for the chosen and the other developing markets in designing an adequate route ahead to a sustainable environment.

Assessing eco-label knowledge and sustainable consumption behavior in energy sector of Pakistan: an environmental sustainability paradigm

The energy needs of Pakistan have increased many folds in recent years due to improved lifestyle, ever-increasing population, and economic development. Though the government and private sectors are considering efficient energy resources to overcome energy scarcity in the country, studies focusing on assessing consumers' sustainable consumption behavior in the form of energy-saving home appliances are limited in the country. This study aims to address this research gap and also contribute by augmenting the theoretical mechanism of the theory of planned behavior by including three unique dimensions (eco-label knowledge, attitude toward environment, and customer green trust) to comprehensively analyze sustainable consumption behavior in the Pakistani context. An analysis is performed on survey data of 631 consumers in the four largest cities of Pakistan: Karachi, Lahore, Faisalabad, and Islamabad. For the purpose of evaluating formulated hypotheses, the structural equation modeling approach is employed. Empirical findings suggest that eco-label knowledge positively and significantly influences attitude toward environment and consumer green trust. Similarly, attitude toward environment and consumer green trust has a positive and significant influence on purchase intention. Moreover, a significant positive relationship exists between consumer green trust and purchase intention. The research outcomes further disclose that purchase intention positively and significantly influence paying attention to environmental labels. These findings contribute to the literature on sustainable consumption behavior and provide academics and practitioners with future directions to transform social norms, raise consumers' awareness, and redesign policy frameworks through integrative and consistent efforts.

Influencing factors of consumers' buying intention of solar energy: a structural equation modeling approach

Due to China's massive usage of fossil fuels, climate change concerns have become serious challenges to the country's sustainable development. Despite the fact that China has effectively employed solar technology to address these problems, there is a paucity of research examining consumers' intention to adopt solar energy in the rural region of China. This study intends to fill this gap in the literature by studying consumers' buying intentions for solar energy in rural China for household purposes. Additionally, the study added to the theory of planned behavior by adding three new variables, namely, environmental knowledge, environmental concern, and beliefs about the benefits of solar energy. Primary data were collected from 847 respondents in Hebei Province using a comprehensive questionnaire survey. Structural equation modeling was employed to examine the data. Empirical results revealed that attitude, environmental knowledge, subjective norm, perceived behavioral control, and beliefs about the benefits of solar energy positively influence buying intention of solar energy. On the contrary, environmental concern had no significant effect on buying intention for solar energy. Study outcomes emphasize the critical significance of changing societal norms, boosting consumer awareness, redesigning regulatory mechanisms, and stressing the benefits provided by solar power through coherent and persistent efforts while simultaneously enhancing environmental sustainability practices.

Towards the road of eco-efficiency improvement: evidence from China's economic and technological development zone

The economic and technological development zone (ETDZ) serves an essential role in driving green development and ecological civilization. Therefore, it is crucial to investigate the impact of ETDZs on eco-efficiency for sustainable development. This paper investigates the impact of the establishment of ETDZs on eco-efficiency by constructing a differences-in-differences (DID) model on the basis of 253 cities in China from 2004 to 2017 as the dataset. This paper also explores the possible intrinsic impact mechanisms through the channels of industrial structure and technological innovation by constructing a mediating effect model, and the heterogeneous effects of ETDZs on eco-efficiency from the perspectives of regional imbalance and city class heterogeneity. Statistical results report that ETDZs significantly positively affect eco-efficiency and such effects are most significant in the first year after the establishment of ETDZs. Industrial structure upgrading and technological innovation are essential role mechanisms for ETDZs to enhance eco-efficiency. Besides, the enhancement effect of ETDZs on eco-efficiency is only observed in the eastern part of the city, with an insignificant inhibitory effect in central and western parts of the cities. However, the establishment of ETDZs in cities with higher city classes is more beneficial to improve eco-efficiency.

How to improve total factor energy efficiency under climate change: does export sophistication matter?

Climate change has a profound impact on human survival and development. Climate change is an energy and economic issue, which should be driven by technology. Total factor energy efficiency (TFEE) improvement is undoubtedly a breakthrough in solving energy problems. In this paper, the fixed effect model, impulse response function, and threshold regression model are used to test the complex relationship between export sophistication and TFEE. The results reveal that export sophistication improvement leads to higher TFEE. The impulse response results verify the existence of a phased and positive correlation between export sophistication and TFEE. Finally, the relationship between export sophistication and TFEE significantly varied across different threshold levels of regional corruption score, economic development, and openness. This article led the foundation for supporting China's export sophistication promotion strategy and also provides a reference for energy efficiency improvement and energy crisis response in the post-pandemic era.

How digitalization works in promoting corporate sustainable development performance? The mediating role of green technology innovation

How does organizational digitalization enable enterprises to achieve sustainable development? To explore this question, in this paper, sustainable development performance is characterized by the corporate's financial performance and environmental performance respectively, and the intermediary role of green technology innovation is explored. Taking China's listed companies from 2011 to 2020 as the research sample, the empirical results suggest the following: (a) corporate digitalization positively affects corporate sustainability in terms of its financial performance and environmental performance; (b) exploratory green-tech innovation fully mediates the relationship between digitalization and corporate sustainability, while the exploitative counterpart partially mediates this relationship and negatively affects financial performance; (c) state-owned enterprises tend to improve environmental performance through digitalization accelerating green-tech innovation process, while non-state-owned enterprises pay more attention to financial performance. Moreover, enterprises in high-tech industries focus on both financial performance and environmental performance, while enterprises in non-high-tech industries emphasize environmental performance. Therefore, this research can be conducive for enterprises to make full use of digitalization and green technology innovation to achieve sustainable development including the improvement of financial performance and environmental performance.

Can artificial intelligence improve green economic growth? Evidence from China

Not only has artificial intelligence changed the production methods of traditional industries; it has also presented a great opportunity for future industrial development to decouple from environmental degradation and the promotion of green economic growth. The article studies the influence of artificial intelligence on green economic growth and its mechanism. The research shows that (1) artificial intelligence can promote green economic growth in China. After accounting for spatial factors, it was found that artificial intelligence could promote local green economic growth, but had a siphon effect on neighboring green economic growth. From the perspective of dynamic effects, in the short term, artificial intelligence will not significantly dampen green economic growth in neighboring regions. In the long run, artificial intelligence will have a stronger role in promoting green economic growth, and the siphon effect on neighboring cities will be more significant. (2) As the level of human capital increases, the negative spillover effect of artificial intelligence will be significantly weakened. The promotion effect of artificial intelligence on green economic growth is relatively weak in resource-based cities. (3) Artificial intelligence has obvious attenuation characteristics on the spatial spillover effect of green economic growth, but significant influence is limited to within 200 km. (4) Artificial intelligence has the greatest impact on productivity, accounting for 30.59% in promoting green economic growth. The green innovation effect was 0.0181, accounting for 5.64%. The resource allocation effect is 0.0011, accounting for 3.44%. This paper provides policy enlightenment for promoting industrial intelligence and green economic growth.

Can carbon emission trading pilot policy drive industrial structure low-carbon restructuring: new evidence from China

Industrial structure low-carbon restructuring is an essential channel to accelerate China's economic growth and fulfilling carbon emission reduction goals. Whether carbon emission trading pilot policy, as an influential carbon reduction instrument, fosters industrial structure low-carbon restructuring is of major significance to green economic development. This paper empirically investigates the shock of the carbon emission trading pilot policy on industrial structure low-carbon restructuring using the differences-in-differences (DID) and synthetic control method (SCM). Statistics reveal that sectors with low carbon productivity, such as electricity, steam, and hot water production and supply, ferrous metal smelting and pressing, etc., and sectors with high carbon productivity, such as electrical equipment and machinery, electronics and telecommunication equipment, etc. The industrial structure did not develop a stable trend of change before the 12th Five-Year Plan, but a stable trend of low-carbon restructuring emerged after such a period. Carbon emission trading pilot policy significantly facilitates industrial structural low-carbon restructuring. Carbon emission trading pilot policy inhibits energy-intensive industries in the industrial sector significantly, which promotes industrial structure low-carbon restructuring. Therefore, policymakers need to develop a nationwide carbon emission trading market that includes more industries to guide production factors to industrial sectors with high carbon productivity for industrial restructuring and dual carbon goals.

Does green technology advancement and renewable electricity standard impact on carbon emissions in China: role of green finance

Renewable energy growth should be accelerated in order to meet our goal of carbon neutrality and peak carbon emissions. Laws like the Renewable Electricity Standard (RES) are becoming increasingly important in producing renewable energy. Using green technology advancements is seen as balancing economic growth with environmental security. Though the connection between green technology advancements and CO₂ emissions is poorly understood, empirical research is lacking, especially in developing countries. Climate change action now falls under a single overarching contract, signed in Paris on November 4, 2016. Global warming mitigation aims to keep temperature increases to no more than 2 °C above preindustrial levels. By 2060, China intends to reach carbon neutrality by developing green technologies (GTI). Because of these interconnections, this research explores the relationship between green technology innovation (GI) and renewable energy investment (REI) in selected Chinese provinces from 2005 to 2019. GI, REI, urbanization, industrial value-added, and income per capita were all considered in the STIRPAT model. We used a panel of chosen regions to test two relatively new panel estimation methods empirically: "continuously updated fully modified" (Cup-FM) and "continuously updated bias-corrected" (Cup-BC). According to our findings, urbanization and green technological developments positively impact CO₂ emission reduction. The panel also finds that investments in renewable energy and the industrial sector fail to reduce pollution levels. A positive and negative coefficient of income per capita indicates that the inverted U-shaped EKC hypothesis is valid for the Chinese provinces. The results provide vital strategy insights and recommendations for the panel of experts and countries worldwide.

Effects of ICT diffusion on environmental pollution: analysis of industrial reallocation effects in China

The development of information and communication technology (ICT) has brought about fundamental changes in social progress worldwide. Using panel data from 288 Chinese cities for the period from 1999 to 2019, this study evaluates the effect of the pilot Broadband China Strategy (BCS) program on environmental pollution. We find that BCS significantly reduces environmental pollution, and that this effect is stronger in eastern China and in Chinese cities with higher financial progress or broadband development. Interestingly, the negative effect of BCS on environmental pollution decreases with the improvement of human capital in the cities. We further discuss industrial efficiency and reallocation mechanisms and ascertain that BCS affects environmental pollution in pilot cities not only through the efficiency mechanism as established in the existing literature but also through the industrial scale change and labor transfer between different industries, which we refer to as the industrial reallocation mechanism in this study. Specifically, via the industrial efficiency and reallocation mechanisms, the implementation of the BCS increases the scale and efficiency of the primary and tertiary industries but decreases the scale and efficiency of the secondary industry. This reduction in the secondary industry results in a decline in environmental pollution. It indicates that promoting the balanced development of a country's ICT infrastructure and pushing forward ICT diffusion can help alleviate environmental pollution by industrial reallocation and efficiency improvement, especially in nations with significant regional economic and technological differences.

How green finance reduces CO2 emissions for green economic recovery: empirical evidence from E7 economies

The present study examines the effects of green finance on green economic performance index in the presence of income per capita, corporate social responsibilities, green energy, and technical innovations in emerging seven (E7) countries from 2005 to 2018. This study employed second-generation panel cointegration methodologies. The result of the cross-sectional dependency and slope heterogeneity test confirms that the panels are correlated and there exists slope heterogeneity. The results for the short- and long-run confirm the relationship between green economic performance index, green finance, GDPC, technological innovation, CSR, and green energy. In both the short- and long-run, green finance, technological innovation, and CSR decrease the carbon emissions and increase green economic growth, whereas income per capita and GDPC significantly increase the carbon emissions. The robustness check findings obtained D-H panel causality test validate the results. Reducing energy usage by adopting efficient technologies should be encouraged through green financing reforms implemented by policymakers.

The influence and mechanism of health expenditures on investment of financial assets decisions: A case study of China's economy

Policymakers worldwide have been actively involved in the past few decades to ensure that human diseases are kept to a minimum. A new econometric technique, dynamic ARDL simulations, was used in this study to estimate and model the influence of health expenditures on investment in non-financial assets in China from 1990 to 2019. An economic growth framework, gross capital formation, information and communication technologies, foreign direct investment, and carbon emissions are all considered in the empirical model-the analysis produced interesting results. First, the estimates show that health expenditures and foreign direct investment have a significant long-run decreasing impact on non-financial assets in China by 0.451 and 0.234%. Second, economic growth and gross capital formation significantly affect the economy's non-financial assets. Likewise, ICT and carbon emissions also positively correlate with an explained variable in China. The findings show that the economy is becoming less investment-intensive as health spending and foreign direct investment rise. The study develops important policy implications for the selected country to achieve desired targets based on the empirical results.

How does digital economy affect green total factor productivity at the industry level in China: from a perspective of global value chain

The digital economy is an important way to relieve current pressure on resources and the environment. Based on ecological modernization theory and global value chain theory, this paper adopts panel data of 17 manufacturing industries from 2000 to 2014, uses the non-radial directional distance function and the meta-frontier method to measure China's green total factor productivity (GTFP) and its sub-indices, and takes the embedding degree and embedding position as moderating variables and threshold variables to construct an econometric model to explore the relationship among the digital economy, global value chain, and GTFP. The results show that (1) the digital economy has a positive effect on GTFP in both time and space. And in terms of time, the digital economy mainly enhances GTFP by improving technical efficiency and narrowing the technology gap. (2) Global value chain embedding position positively moderates the relationship between the digital economy and GTFP; In terms of sub-samples, labor-intensive and capital-intensive industries show the same impact characteristics as the total sample. (3) Further, it is found that the digital economy and GTFP have nonlinear characteristics. There is a single threshold effect on the embedding position. When the embedding position is low, the digital economy is positively correlated with GTFP but not significant; when the threshold value is crossed, the digital economy can significantly promote GTFP. The conclusions of this paper are helpful to realize the digital economy to promote the green development of the manufacturing industry, and provide an effective reference for the realization mechanism of China's green economy transformation and ecological civilization construction in the post-pandemic era.

Does industrial intelligence improve resource misallocation? An empirical test based on China

Resource misallocation has become a new threat to China's high-quality economic development, and industrial intelligence may play an important role in optimizing resource allocation. Using panel data of 30 Chinese provinces from 2010 to 2020, the relationship between industrial intelligence and resource misallocation is studied using the spatial Durbin (SDM) model. To further explore the indirect effect of environmental pollution on resource misallocation, the interaction term between industrial intelligence and environmental pollution is added to test how environmental pollution affects the relationship between industrial intelligence and resource. The research results show that industrial intelligence in China has significant spatial correlation. Local industrial intelligence can improve the local resource allocation, but the intelligence of neighboring industries will intensify the resource misallocation in the region. The interaction between environmental pollution and industrial intelligence also further affects resource allocation, and the interaction term can intensify local capital allocation to improve local labor allocation, and the interaction term in the surrounding area will also improve capital and labor misallocation in the region. Heterogeneous results find that industrial intelligence exacerbates resource misallocation in regions with insufficient capital allocation, and the mediating effect of environmental pollution is not significant. However, in places with excess capital allocation, the development of industrial intelligence helps improve resource misallocation, while the mediating effect of environmental pollution is also present, and industrial intelligence can improve resource misallocation through the indirect effect of improving environmental pollution. Therefore, the policies of local industrial development policies need to fully consider the resource allocation situation in the region. At the same time, it needs to smooth the capital circulation mechanism, reduce the cost of capital allocation, establish a sound employment mechanism, and improve labor misallocation.

The nexus between digital finance and carbon emissions: Evidence from China

Finance is significant support for the low-carbon transformation of the real economy, in which digital finance as a new direction of financial development exerts a significant influence on carbon emissions. Therefore, it is crucial to investigate the association between digital finance and carbon emissions in order to develop carbon reduction strategies from the financial side. For this purpose, using the sample set covering 30 provincial areas during 2011–2020, this paper investigates the direct, indirect, and non-linear effects of digital finance on carbon emissions by applying fixed effects, mediating effects, and threshold effects analysis techniques. The results indicate that: (1) digital finance can significantly mitigate carbon emissions at the national level. (2) Digital finance inhibits carbon emissions as it drives green technological innovation and industrial structure upgrading. (3) Significant regional heterogeneity is observed in the effect of digital finance on carbon emissions, i.e., the effects of digital finance on carbon emissions are higher in the east-central region than in the overall sample, while the opposite is true in the western region. (4) The dampening effect on carbon emissions steadily increases as digital finance levels cross the first and second thresholds, respectively. Based on the above considerations, policymakers shall not only develop differentiated digital finance initiatives, but shall also fully unleash carbon emission reduction potential by rationalizing and optimizing industrial layout and strengthening financial subsidies for green technology innovation.

Modeling the influencing factors of electronic word-of-mouth about CSR on social networking sites

Corporate social responsibility (CSR) information can now be disseminated via social networking sites. An organization's image and upcoming portfolios are directly affected by electronic word of mouth (eWOM). It generates from its customers, employees, and other stakeholders. We developed a critical model to enlighten the behavior to share and comment on a negative news story about CSR displayed on Wechat and QQ to figure out what was causing this behavior. Structural equation modeling (SEM) and the partial least squares regression (PLS) approach were used to conduct a self-administered survey of hotel customers in China. Social and environmental awareness, information usefulness, corporate image, and a company's motivation to comment and share on CSR news were all considered explanatory variables in our study. We asked 300 Wechat and QQ users to rate a fake environmental news story. We found that social and environmental awareness affects the effectiveness of information and the attitude toward behavior, which may describe the eWOM intent of the particular news. On the other hand, corporate reputation could discourage people from disseminating eWOM and sharing the news with their social linkage contacts. The findings of the study suggest having a better understanding of how specific CSR activities can increase customers' commitment, which leads to positive eWOM, will benefit the hotel industry.

Can information infrastructure development improve the health care environment? Evidence from China

Existing studies ignore the importance of information infrastructure development in improving regional health care environment. This paper adopts a spatial difference-in-difference (DID) model to assess the impact of information infrastructure development on urban health care environment based on a quasi-natural experiment of the "Broadband China" city pilots (BCCP). A balanced panel of 259 cities from 2010 to 2019 is selected for empirical analysis in this paper. Our findings show that the implementation of BCCP resulted in a 4.1 and 2.9% improvement in local medical workforce and medical infrastructure. In addition, there is significant spatial spillover effects of the implementation of BCCP, with 7.2 and 12.5% improvement in medical workforce and medical infrastructure in the surrounding areas. Our findings also suggest that information infrastructure development enhances the health care environment by driving industrial upgrading and education levels. Further analysis shows that BCCP has the strongest improvement on medical workforce in the eastern region and non-ordinary prefecture-level cities. For medical infrastructure, BCCP has stronger improvement in central region, western region, and non-ordinary prefecture-level cities. Finally, the paper conducts a series of robustness tests to ensure the reliability of the analysis results, including parallel trend tests, placebo tests, and re-estimation with different methods. Policies to improve the health care environment through information infrastructure development are proposed.

Digital Transformation on Enterprise Green Innovation: Effect and Transmission Mechanism

With the development of blockchain, big data, cloud computing and other new technologies, how to achieve innovative development and green sustainable development in digital transformation has become one of the key issues for enterprises to obtain and maintain core competitiveness. However, little of the literature has paid attention to the impact of digital transformation on enterprise green innovation. Using the data of Chinese A-share listed companies from 2010 to 2020, this paper empirically analyzes the impact of enterprise digital transformation on green innovation and its transmission mechanism, by constructing double fixed-effect models. The results show that digital transformation has remarkably promoted the green innovation of enterprises. R&D investment, government subsidies, and income tax burden have played a conductive role between digital transformation and enterprise green innovation. Furthermore, digital transformation can significantly promote the high-quality green innovation of enterprises and also plays a more significant role in promoting the green innovation of high-tech enterprises and state-owned enterprises. A robustness test is carried out by using the lag data and changing the measurement methods of the dependent variable and independent variables, and the research conclusions are still valid. Based on resource-based theory and dynamic capability theory, this paper reveals the impact path of digital transformation on enterprise green innovation, further expanding the research field of digital transformation and enriching the research on the influencing factors of enterprise green innovation. This paper provides policy suggestions for the government to improve the enterprise green innovation level by increasing government subsidies and providing tax incentives and also provides reference for digital transformation enterprises to accelerate green innovation by increasing R&D investment, obtaining government subsidies, and acquiring tax policy support.

The road to green development: How can carbon emission trading pilot policy contribute to carbon peak attainment and neutrality? Evidence from China

Carbon emission trading is not only a market-based instrument but also one of the government's macro-policies, which is extremely crucial to fulfilling both carbon peak attainment and carbon neutrality goals. For this purpose, this paper adopts a 30-region dataset for the period from 2008 to 2020 in China and employs the difference-in-difference (DID) method to quantify the effect of the carbon emission trading pilot policy (CETP) on carbon emissions on the basis of introducing industrial structure upgrading and green technology innovation as moderating variables. The results show that (1) CETP has a statistically significant dampening effect on carbon emissions, while its carbon emission reduction effect follows a significant strengthening trend as the policy year of CETP implementation is delayed. (2) CETP has a significant carbon emission reduction effect. However, its effect demonstrates a gradual decrease from the eastern to the central and finally to the western regions. (3) CETP can inhibit carbon emissions depending on industrial structure upgrading to a certain extent, and this dependence is significant in the national and eastern regions but not in the central and western regions. (4) CETP's carbon emission reduction effect is dependent on green technology innovation, which is only revealed in the western region and performs as a dampening effect in the national, eastern, and central regions, but not significantly.

How does multidimensional R&D investment affect green innovation? Evidence from China

Under the background of green development, multidimensional R&D investment and institutional quality have injected strong power into green innovation. Based on China's provincial panel data from 2009 to 2018, this study examines the threshold effect of R&D and R&D personnel input on China's green innovation capability from three perspectives, namely, political institutional quality, economic institutional quality, and legal institutional quality. The core study results show that the influence of R&D on China's green innovation capability has an obvious double-threshold effect based on institutional quality. This study expands the research on the influencing factors of green innovation and the influence effect of multidimensional R&D investment and provides a theoretical basis for regional green innovation management. In addition, the research results of this study provide a reference for accurately formulating regional green innovation capability promotion strategies.

Green Total Factor Productivity Growth: Policy-Guided or Market-Driven?

The green growth mode of modern economy is affected by both policy and market, but previous studies have lacked a comparison between the two effects on green economy development. Which is the leading factor of green growth: policy or market? Using the Panel Smooth Transition Regression (PSTR) model and the twelve-year data of more than 200 prefecture-level cities in China, we compared and analyzed the linear and non-linear effects of environmental regulation and marketization degree on green total factor productivity (GTFP). The results show that: (1) both environmental regulation and marketization degree have a non-linear promoting effect on GTFP. (2) GTFP is mainly market-driven rather than policy-guided. (3) Environmental regulation and marketization promote the improvement of GTFP through the industrial upgrading effect and the innovation development effect, respectively. This paper makes up for the comparative analysis gap of factors in the field of green growth and extends from the single determination of influencing factors to the importance of the comparison of influencing factors with the transition perspective. The conclusions provide a reference for the green development of countries and regions, emphasizing the importance of green development policies adapting to local conditions and time and providing evidence for market-oriented green economy development.

Central environmental inspection and corporate environmental investment: evidence from Chinese listed companies

As a new type of environmental policy, the central environmental inspection (CEI) policy is an important innovative strategy in economic transition. Using the panel data of Chinese listed companies from 2011 to 2018, we apply the extended STIRPAT model to examine the direct impact of CEI policy on corporate environmental investment and its heterogeneity effects. The main findings are as follows: (1) The CEI policy has a positive influence on the environmental investment of all listed companies. (2) The promotion effect of CEI policy is quite different among five-round campaigns; while companies in later rounds fails to learn some experiences and lessons from the earlier rounds. (3) Due to the differences in property rights, industries, and environmental situations, the positive effect of CEI policy will be more significant in non-SOEs, companies in non-heavy-pollution industries, and companies in provinces with poor environment performance. This study supplements the research of environmental regulations, potentially contributing to the next stage of green and sustainable development in China.

The Influence of the Development of the Internet of Things Industry on the Optimization of the High- and New-Tech Industry Structure under the Wireless Mobile Network

At present, the pressure on China's economic development is increasing day by day due to the profound changes in the internal and external environment. The global economic pattern is undergoing significant changes in terms of the external environment. Adjusting and optimizing the industrial structure will aid in achieving the goal of facilitating transformation through steady growth in the short term. Meanwhile, it will also accelerate sustainable economic development. In this study, the relevant theories of industrial structure optimization are described based on the impact of wireless mobile networks and the Internet of things (IoT) industry. Based on the gray correlation degree, the high- and new-tech industries under the development of the IoT industry are analyzed and the impact of optimization of the high- and new-tech industry structure is investigated. The results show that the development of the IoT industry has driven the development of the high- and new-tech industry. The gray correlation between the development of the IoT industry and the high- and new-tech industry obtained is 0.64, indicating a strong correlation. The average output share of the electronic computer and office equipment manufacturing industries is 47.09%. The average output ratio of the industrial structure optimization of the electronics and communication manufacturing industry is 42.55%. Moreover, the proportion of the output of medical manufacturing and medical equipment and instrument manufacturing industrial structure optimization is small, 15.63% and 10.54%, respectively. The results have significant value in the research on the impact of the development of the IoT industry on the high- and new-tech industry under the wireless mobile network and the effect of its industrial structure optimization.

Impact of environmental regulation on green total factor productivity: a new perspective of green technological innovation

Green total factor productivity (GTFP) is an essential indicator to measure economic and environmental efficiency. Moreover, formulating a reasonable environmental regulation system and promoting green technological innovation is a systematic way to improve GTFP. However, previous related studies lack to investigate the impact of environmental regulation on GTFP from the perspective of green technological innovation. For this purpose, this paper aims to examine the specific impact of environmental regulation on GTFP based on the perspective of green technology innovation, so as to provide some policy insights for the formulation of more effective implementation of environmental regulation, improve green technology innovation level, and achieve a win-win situation for both economic growth and environmental protection. Furthermore, epsilon-based measure (EBM), which includes both radial and non-radial distance functions, is used to measure the GTFP. The spatial autoregressive method is also employed to quantify the impact of environmental regulation on GTFP from the perspective of green technological innovation using panel data of 269 prefecture-level cities in China from 2004 to 2018. The main findings indicate that there is a significant spatial autocorrelation between environmental regulation and GTFP. Environmental regulation has a significant positive effect on GTFP. Environmental regulation in the local regions also significantly contributes to GTFP in neighboring regions. Besides, environmental regulation indirectly promotes GTFP by enhancing green technological innovation level. Regional heterogeneity results show that environmental regulation can not only directly promote GTFP but also indirectly significantly promote GTFP through green technological innovation in the eastern and central regions, but insignificant in the western region. Based on the above findings, we conclude that policymakers should not only develop differentiated environmental regulation standards and steadily improving the intensity and rationality of environmental regulation but also add green innovation funds supply, enhance green innovation factor allocation efficiency, and strengthen R&D talents, funds, and policies to green technology innovation, so as to drive GTFP improvement.

The Effects of Broadband Infrastructure on Carbon Emission Efficiency of Resource-Based Cities in China: A Quasi-Natural Experiment from the "Broadband China" Pilot Policy

Resource-based cities (RBCs) face serious environmental pollution, and there are efforts to try to overcome those challenges by transforming industrial structure through investing in new technologies. Based on the panel data of 114 prefecture-level resource-based cities in China, this paper uses the difference-in-differences (DID) method to identify the effects of the “Broadband China” pilot policy on the carbon emission efficiency of resource-based cities. The results show that the “Broadband China” pilot policy has a significant effect on the improvement of carbon emission efficiency of resource-based cities, and the results are still valid after parallel trend test, PSM-DID estimation and placebo test. This study also finds that there are differences in the carbon emission efficiency of different locations and types of resource-based cities. In addition, the results of the mechanism analysis show that the “Broadband China” pilot policy can promote the improvement of carbon emission efficiency by promoting the upgrading of the industrial structure, the accumulation of human capital and the improvement of the level of urban innovation of resource-based cities. The findings provide a reference for China’s resource-based cities to develop the Broadband infrastructure, realize industrial upgrading, accumulate human capital and improve urban innovation level, and promote low-carbon transformation and improve carbon emission efficiency.

Digital Economy, Agricultural Technological Progress, and Agricultural Carbon Intensity: Evidence from China

China is the largest carbon emitter in the world, with agricultural carbon emissions accounting for 17% of China’s total carbon emissions. Agricultural carbon emission reduction has become the key to achieving the “Double Carbon” goal. At the same time, the role of the digital economy in achieving the “dual carbon” goal cannot be ignored as an important engine to boost the high-quality development of China’s economy. Therefore, this paper uses the panel data of 30 provinces in mainland China from 2011 to 2019 to construct a spatial Durbin model and a mediation effect model to explore the impact of the digital economy on agricultural carbon intensity and the mediating role of agricultural technological progress. The research results show that: (1) China’s agricultural carbon intensity fluctuated and declined during the study period, but the current agricultural carbon intensity is still at a high level; (2) The inhibitory effect of the digital economy on agricultural carbon intensity is achieved by promoting agricultural technological progress, and the intermediary role of agricultural technological progress has been verified; (3) The digital economy can significantly reduce the carbon intensity of agriculture, and this inhibition has a positive spatial spillover effect. According to the research conclusions, the government should speed up the development of internet technology and digital inclusive finance, support agricultural technology research and improve farmers’ human capital, and strengthen regional cooperation to release the contribution of digital economy space.

The dynamics of public spending on sustainable green economy: role of technological innovation and industrial structure effects

In order to achieve the goal of sustainable green economic development, it is necessary to conduct a comprehensive assessment of the efficiency of the green economy and compare it with emission reductions. The green economy idea is a much-discussed solution to economic growth. Therefore, this study investigated the impact of government spending on the performance of the green economy of various countries under the "Belt and Road" (BRI) initiative project. The data were analyzed using the BRI economy panel data from 2008 to 2018. The generalized method of moments (GMM) was used to estimate the effect of government expenditures on education and research and development (R&D) on green economic performance index (GEE) in BRI countries. The results reveal that during the study period, BRI countries have experienced an upward transition towards green development, except for Pakistan and Bangladesh; their GEE decreased gradually from 2010 to 2018. Further, the findings of the system GMM revealed that both education and R&D have a positive impact on the green economy. Moreover, the compositional and technological effects of the overall sample were verified with the GMM process. Nevertheless, the sub-sample results revealed a heterogeneous impact on countries with a high per capita GDP. Following the results, useful policy measures for promoting sustainable green economic development have been proposed.

Multimodal Sentiment Analysis of Online Product Information Based on Text Mining Under the Influence of Social Media

Currently, with the dramatic increase in social media users and the greater variety of online product information, manual processing of this information is time-consuming and labour-intensive. Therefore, based on the text mining of online information, this paper analyzes the text representation method of online information, discusses the long short-term memory network, and constructs an interactive attention graph convolutional network (IAGCN) model based on graph convolutional neural network (GCNN) and attention mechanism to study the multimodal sentiment analysis (MSA) of online product information. The results show that the IAGCN model improves the accuracy by 4.78% and the F1 value by 29.25% compared with the pure interactive attention network. Meanwhile, it is found that the performance of the model is optimal when the GCNN is two layers and uses syntactic position attention. This research has important practical significance for MSA of online product information in social media.