Upgrading Of Industrial Structure Research Articles

The Impact of Digital Economy Development on Industrial Structure Upgrading

The Impact of Digital Economy Development on Industrial Structure Upgrading

Research on the Coupled and Coordinated Development of Green Finance and Industrial Structure Upgrading:Taking Beijing-Tianjin-Hebei Region as an Example

Research on the Coupled and Coordinated Development of Green Finance and Industrial Structure Upgrading:Taking Beijing-Tianjin-Hebei Region as an Example

The collaborative innovation mode of university talent training under the background of industry-education integration

Abstract At present, with the adjustment of industrial structure and industrial restructuring and upgrading, the demand for high-end skilled personnel is increasing, and the state has timely launched the integration of industry and education and the school-enterprise cooperation policy to strengthen the “double subject” status of enterprises and universities. With the help of evolutionary game theory, the study constructs a two-party evolutionary game model of talent cultivation under school-enterprise cooperation between enterprises and colleges and universities, constructs the replication dynamic equations of the two main parties of the game, and explores the stability of the Nash equilibrium point. In order to verify the reliability of the game model results, numerical simulation is carried out, which more intuitively demonstrates the dynamic process of the evolutionary game of talent cultivation under school-enterprise collaboration. When the proportion of enterprises and colleges adopting the strategy of not actively participating in collaborative talent cultivation gradually decreases in the benefits of the two groups, the enterprises choose to deeply participate, and the colleges choose to actively participate in collaborative talent cultivation is an evolutionarily stable strategy and the optimal solution of the model (1,1). It can realize the innovation of university talent cultivation mode through university-enterprise collaboration by establishing a complete information channel, incentive, and constraint mechanism to protect the interests of the two main parties of the game.

Enterprise Industrial Structure Transformation and Upgrading and Regional Innovation Capability Enhancement Strategies - An Empirical Analysis Based on VAR Models

Abstract The transformation and upgrading of enterprise industrial structure and regional innovation ability are the concerns of social development in recent years. This paper introduces the global entropy method and VAR model to construct the indicators of enterprises’ industrial structure transformation and upgrading and regional innovation ability with the enterprises in X place as samples. The development level is measured through weight calculation and comprehensive evaluation, and after the smoothness test, the impulse response function and variance decomposition are applied to study the dynamic relationship between the two variables, to research the transformation and upgrading of enterprise industrial structure and the enhancement of regional innovation capacity. The study shows that the level of industrial structure transformation and upgrading of enterprises in the cities of X place has increased steadily from 2016 to 2020 as a whole, but only the level of the eastern cities is all over 0.3, which still needs to be further improved. Through the variance decomposition, the variance contribution rate of changes in regional innovation capacity to changes in the transformation and upgrading of enterprise industrial structure increases from 13% to 26.16%, and the variance contribution rate of changes in the transformation and upgrading of enterprise industrial structure to changes in regional innovation capacity decreases from 99.14% to 74.42%. The level of transformation and upgrading of the enterprise industrial structure can be improved to continuously promote the enhancement of regional innovation capacity and further promote the construction and development of the city.

Environmental regulation, energy consumption structure, and industrial pollution emissions

China has become the world’s largest carbon emitter due to its high-investment, low-efficiency development model. It is urgent to reduce industrial pollution emissions. This study analyzes the impact of environmental regulation intensity and energy consumption structure on industrial SO2 pollution emissions by establishing a fixed-effect regression model based on panel data from 2009 to 2018 in China. The results show that the overall environmental regulation intensity in China has a significant negative effect on industrial pollution emissions. In other words, increasing the level of environmental regulation is conducive to reducing industrial pollution emissions. The proportion of coal consumption in the overall national energy consumption structure directly and positively correlated with the concentration of industrial pollution emissions. Due to the differences in economic development and industrial foundation, the pollution emissions effect shows significant heterogeneity in the eastern and western regions of China under the constraint of environmental regulation. Based on these conclusions, this article proposes policy recommendations from four aspects: (1) strengthen environmental regulation, and pay attention to optimize the form of environmental regulation. For example, in the West of China, the government can encourage enterprises to carry out technological innovation and develop green energy hubs by policy and financial support; (2)improve the energy consumption structure, such as encouraging green production; (3) promote industrial structure adjustment and upgrading, such as promoting the energy saving transformation of energy-intensive enterprises, developing green technologies, and reducing the carbon emissions of industrial industries; (4)improve the foreign investment access system and guiding foreign investment to invest in key environmental protection projects.

Empirical Analysis and Predictive Modeling of Return on Education Investment in Regional Economic Growth

Abstract The rate of return on education can measure the size of the return on investment in education, which is an important research area related to national development. The purpose of this paper is to analyze and discuss the relationship between education, regional economic development, and related influence variables using a multilayer linear model. CGSS data of 31 provinces and cities in 2021 are chosen as the empirical analysis data, which are divided into east, middle, and west regions according to geographic location, and the differences in industrial development of the three major regions are measured in terms of upgrading of industrial structure, seniorization, rationalization, urbanization, investment in education, and technological development. Create a model to evaluate the impact of industrial structure upgrading on education investment return in each region. Separately, the slope prediction model includes education variables and regional economic development variables to examine the predictive impact of regional economic growth on the return on education investment. The coefficient of the cross-level interaction term between years of education and regional economic development has a value of 0.07829, and it passes the 1% statistical significance test with a significant cross-level interaction effect. It indicates that the higher the degree of regional economic development, the greater the role of educational human capital in promoting residents’ income, i.e., the rise in the degree of regional economic development will significantly increase the return on investment in education.

Does environmental protection tax law accelerate energy transition? Evidence from electrification of 262 cities in China

While global climate risk is increasing substantially with greenhouse gas emission, energy transition is a key approach to alleviate this concern. This paper constructs the difference in difference model (DID) and the difference-in-differences based propensity score matching model (PSM-DID) to estimate the effects of China’s Environmental Protection Tax Law on energy transition and its transmission path. The empirical results show that (1) China’s Environmental Protection Tax Law can promote energy transition through electrification, and this conclusion is still valid after a series of robustness tests. (2) China’s Environmental Protection Tax Law can facilitate energy transition by improving both the quantity and the quality of industrial structure upgrading. The findings of this paper not only enrich the literature on the energy transition and environmental tax designs in developing countries but also provide an empirical reference for the government to promote energy transition orderly by implementing environmental tax.

公众环境认知与绿色产品贸易的关系——政策法律文本的调节作用

In today's increasingly accelerating globalization, environmental protection and sustainable development have become the focus of common concern for all countries. Public environmental awareness, that is, the public's understanding and attitude towards environmental issues, has a significant impact on environmental protection work. Meanwhile, with the rise of green product trade, the market trading of green products is becoming increasingly active. As one of the means to regulate the relationship between public environmental awareness and green product trade, the role of policies and legal texts is increasingly prominent. This article will explore the relationship between public environmental awareness and green product trade and analyze the regulatory role of policies and legal texts in it. This article explores the impact of trade and environmental policies on the financial system through computer software. It constructs a theoretical hypothesis model to explore the moderating effect of policy and legal texts on the relationship between public emotional perception of environmental policies and green product trade. After empirical testing, all research hypotheses in this study have been supported. The results showed that at a test level of 0.01, consumers' perception of green efficacy, perceived green responsibility, green purchasing behavior, emotional arousal, and moderate values were significantly positively correlated. Among them, the R-value of perceived green efficiency and green purchasing behavior is 0.701, and the R-value of perceived green responsibility and green purchasing behavior is 0.638, indicating the degree of correlation between perceived green efficiency, perceived green responsibility, and green purchasing behavior. Green purchasing behavior is highly correlated. The conclusion indicates that the government has further increased export subsidies for the clean industry, implemented differentiated environmental tax policies, and emphasized the coordinated use of procedures, promoting the development of the clean industry and the upgrading of industrial structure.

The Relationship between Service Economy and Carbon Emissions in Jiangsu Province China and the Influencing Factors

Aims: G20 leaders Riyadh put forward the approval of the carbon reduction, reuse, recycling and elimination (4R) framework at the 2020 Summit. In order to achieve carbon peak and carbon neutrality, promote the development of low-carbon economy, China is striving to build a new high-efficiency low-carbon market.
 Study Design: Taking the service industry in Jiangsu Province as the research object.
 Place and Duration of Study: long-term interactive relationship between the carbon emissions of the service industry in Jiangsu Province China and its economic development, from 2005 to 2022.
 Methodology: Through the vector autoregressive model (VAR) and Granger causality test. Then, five variables affecting the carbon emissions of the service industry are selected: the level of science and technology, the development of transportation, storage and postal industry, energy efficiency, industrial structure and tourism development.
 Results: As influencing factors, through the least squares method (OLS) analysis, it is found that the factor that has the greatest impact on the carbon emissions of the service industry in Jiangsu Province is the industrial structure, followed by the development of tourism and transportation, storage and postal industry.
 Conclusion: It is proposed to promote scientific and technological innovation and technological progress from many aspects, improve the scientific and technological innovation system of tourism, accelerate the upgrading of industrial structure, improve the efficiency of transportation, storage and postal industry, promote the formation of a benign interactive relationship between the development of the service industry and carbon emissions in Jiangsu Province and illustrate how the service industry can develop with high quality while saving energy and reducing emissions.

Research on the Upgrading of Manufacturing Industry Structure in Emerging Countries under the Background of Climate Change: An International Comparison Perspective

Climate change has consistently commanded a central and pressing role in the development of countries and worldwide. The industrial structure upgrading of the manufacturing industry in emerging countries has gained significant attention due to its implications for economic growth and climate change. Through case studies and comparative analysis, this paper aims to thoroughly analyze and compare the industrial structure upgrading procedures between developed and developing countries, focusing on addressing climate change and reducing carbon emissions. The principal barriers encompass limitations in accessing advanced technologies due to insufficient research and development (R&D) investment, unreasonable energy consumption structure, infrastructural constraints and incoherent policy frameworks. The study proffers strategic imperatives to bridge the chasm between developed and developing countries. These encompass prioritizing targeted initiatives and augmenting R&D investments for innovation and technology acclimatization, countering infrastructure bottlenecks with substantial investments in energy and transportation networks, and fortifying policy frameworks to harmonize economic growth aspirations with sustainability objectives. By enhancing the understanding of how industrial structure upgrading can support climate change mitigation and sustainable development in developing nations, this study provides valuable advice for future policymaking and government actions.

The economic and environmental dividends of the digital development strategy: Evidence from Chinese cities

Digital development is critical for achieving coordinated regional economic growth, energy conservation, and emissions reduction, which makes it a viable method for achieving carbon neutrality and peaks. This study investigates the impact of the digital economy on urban total factor productivity and carbon emissions, as well as its mechanism, from 2011 to 2019 by developing a digital economy evaluation index system. We find that the growth of the digital economy can increase urban total factor productivity while lowering carbon emissions and also has a significant spatial spillover effect on regional economic growth, energy conservation, and emissions reduction. The main influencing mechanism is that the digital economy accelerates marketization by encouraging industrial structure upgrades and technological progress, which results in higher total factor productivity and lower energy consumption. In terms of the spatial distribution, the digital economy promotes total factor productivity more in the central and western regions and large cities and promotes carbon emission reduction less in the eastern regions and smaller cities. The findings extend the benefits of the digital economy beyond economic and social welfare benefits and serve as a model for achieving a win–win situation in terms of both economic growth and carbon emissions reduction.

Analysis of the Relationship between Regional Carbon Financial Market Development and Industrial Structure Upgrading: A Grey Relational Model Approach

Carbon finance, recognized globally as one of the effective solutions to combat global warming, is poised to inject fresh vitality into economic and societal production as it develops. Based on data from 13 cities in the Beijing-Tianjin-Hebei region, this study explores how the development of the carbon finance market affects industrial structure upgrading from the perspectives of carbon finance market development level and industrial structure upgrading. Firstly, by constructing an evaluation indicator system, a comprehensive comparative analysis of the carbon finance market development and industrial structure upgrading of these cities is conducted. Secondly, the study uses the grey relational model to delve into the degree of correlation between the development level of the carbon finance market and the upgrading of the industrial structure. The result shows significant regional disparities among these cities in terms of the development of the carbon finance market and the upgrading of industrial structure. Beijing and Tianjin lead in terms of carbon finance market development. Through the analysis using the grey relational model, it is found that there is a moderate to strong correlation between the level of development of the carbon finance market and industrial structure optimization, indicating the importance of all factors in influencing industrial structure upgrading. Empirical results demonstrate that, on a holistic scale, the development of carbon finance has a significantly positive impact on industrial structure advancement and rationalization. However, disparities exist among different cities, primarily attributed to varying levels of economic development, policy orientation, and developmental stages.

How does the location of high-speed railway stations affect the emission reduction effect of industrial structure upgrading?

The opening of high-speed railway (HSR) has accelerated the reorganization and reallocation of regional production elements, and constantly promoted the adjustment and upgrading of industrial structure. The cleaner production effect produced by industrial structure upgrading is of great significance to industrial pollution reduction. As a bridge connecting resources within the city and elements outside the city, the location of HSR stations has become an important factor affecting the structural emission reduction effect. Based on the data of 285 prefecture level and above cities in China from 2004 to 2018, this paper investigates the structural emission reduction effects of HSR opening and the impact of HSR station location on it by employing difference-in-differences (DID) model combined with mediation effect method. The results demonstrate that the opening of HSR has significant structural emission reduction effect, and the upgrading of inter-industry structure and the intra-industry structure are important mechanisms for HSR to achieve industrial emission reduction. The structural emission reduction effect of HSR opening is closely related to the location of HSR stations. With the increase of the distance between HSR station and city center, the industrial structure upgrading effect will continue to weaken, thus inhibiting the exertion of structural emission reduction effect, of which 10km away from the city center is the optimal site strategy for the HSR service to give full play to the structural emission reduction effect, and exceeding 50km will be significantly detrimental to its role in promoting industrial structure upgrading.

The impact of FDI on industrial structure upgrading and carbon emission under the constraints of environmental regulation

ABSTRACT Foreign direct investment (FDI) plays an important role in promoting industrial structure and curbing carbon emission. The study is based on panel data from 30 provinces in China from 2011 to 2021 and verifies the impact of FDI under environmental regulation on industrial structure upgrading and carbon emission. The empirical results show that FDI under environmental regulation can inhibit carbon emission and promote industrial structure upgrading. The carbon emission reduction effect and industrial structure upgrading effect of FDI show regional heterogeneity, with the strongest effect in the eastern region, followed by the central region, and no significant effect in the western region. The moderating effect examination of environmental regulation illustrates that formal and informal environmental regulation can effectively regulate the relationship between FDI and carbon emission, but due to differences in various factors such as economic development level and population quality, the moderating effect also exhibits regional heterogeneity. In the mechanism test, industrial structure upgrading plays a perfect mediating role in the path of FDI inhibiting carbon emission, and environmental regulation can further enhance the mediating effect of industrial structure upgrading. There is a threshold of industrial structure upgrading between FDI and carbon emission, and FDI can only suppress carbon emission after crossing the threshold of industrial structure upgrading.

The Regionally Heterogeneous Impact of China’s Environmental Regulation on the Transformation and Upgrading of Its Industrial Structure

Approaches to promoting the transformation and upgrading of China’s industrial structure represent an important issue in high-quality economic development. The upgrading of industrial structures is beneficial not only for environmental protection but also for sustainable economic development. This article first tests the correlation between environmental regulation and the transformation and upgrading of industrial structure through an impulse response function and then uses provincial panel data to analyze the regionally heterogeneous impact of environmental regulation on industrial structure upgrading. The research results indicate that: (1) the presented impulse response graph indicates that environmental regulation shocks have a significant impact on the rationalization and upgrading of industrial structure, and subsequent variance decomposition indicates that environmental regulation has a strong explanatory power on the transformation and upgrading of industrial structure; (2) overall, strengthening the level of environmental regulation is not conducive to the rationalization of industrial structure (RIS), but a strong level of environmental regulation can significantly promote the upgrading of industrial structure (UIS); and (3) at the regional level, there is significant regional heterogeneity in the impact of environmental regulation on the transformation and upgrading of industrial structure in different regions. Environmental regulation can promote UIS in China’s eastern and western regions, but it is not conducive to RIS. Environmental regulation can promote RIS in China’s central region, but it has a negative impact on UIS. The conclusion of this article provides inspiration for sustainable economic development.

Toward a low carbon path: Do E-commerce reduce CO2 emissions? Evidence from China

To address global climate change, achieving carbon peak and carbon neutrality has become a global consensus. However, the means to simultaneously achieve carbon reduction and promote green economic development, particularly in developing countries, require further investigation. This study evaluates the impact of e-commerce on CO2 emissions. Through an examination of the effects of the National E-Commerce Demonstration City (NEDC) policy from 2006 to 2017, this paper reveals that e-commerce growth facilitated by the NEDC policy resulted in a 7.89% reduction in total CO2 emissions and a per capita reduction of 1.1146 tons in the pilot cities. Mechanism analysis demonstrates that the upgrading of industrial structure, development of digital finance, and the growth of innovation and entrepreneurship serve as primary pathways for this impact. The robustness of the findings is supported by parallel trend tests, placebo tests, and additional sensitivity analyses. Furthermore, the research reveals that the NEDC policy exhibits a more significant reduction in CO2 emissions in cities with higher levels of economic development and non-resource-based cities. Welfare analyses show that the NEDC policy has significant socio-economic effects. These findings provide new evidence on the environmental effects of the digital economy and offer insights into achieving carbon neutrality.

How smart city construction affects destination tourism efficiency

To investigate the impact of smart city construction (SCC) on destination tourism efficiency (TE), this study analyzed the impact paths and mechanisms of SCC on destination TE from 3 aspects: technological innovation, informatization, and industrial structure upgrading. Based on panel data of Chinese prefecture-level cities from 2004–2019, we combined a stochastic frontier analysis model with a difference-in-differences model to conduct an empirical analysis to assess the policy effects of SCC on destination TE and validate the impact paths and mechanisms. The results show that the tourism of 153 sample cities show a low TE level overall, an increasing trend year by year, a distribution pattern of high in the east, and low in the middle and west. SCC can significantly improve destination TE, and the impact of SCC on destination TE has spatially heterogeneous.

Exploring digital finance, financial regulations and carbon emission nexus: New insight from resources efficiency, industrial structure and green innovation in China

The global climate crisis is exacerbated by the massive burning of fossil energy, represented by natural resource extraction and usage. Likewise, digital finance (DF) is critical to enable financial support for reducing natural resource consumption and supporting low-carbon development. Against this backdrop, this paper analyses DF's impact on carbon emissions under financial regulatory constraints using 274 Chinese cities data from 2011 to 2020. Results reveal that DF does not present a carbon mitigation effect but rather stimulates carbon emissions. The breadth of DF use mainly materializes the carbon emission effect of DF. Realizing the carbon reduction effect of DF depends on the moderating effect of financial regulatory constraints. DF has prominent universality characteristics under the constraints of financial regulation; such effect is more evident in resource-based cities, third- and fourth-tier cities, and central and western regions. The carbon reduction effect of DF under financial regulatory constraints is mainly achieved by stimulating green innovation, resource efficiency, and industrial structure upgrading.

Digital economy drives regional industrial structure upgrading: Empirical evidence from China’s comprehensive big data pilot zone policy

With the development of the digital economy, industrial structure upgrading plays an important role in realizing high-quality development. Exploiting the quasi-natural experimental setting provided by the Big Data Comprehensive Pilot Zone (BDCPZ) policy in China in 2016, this study evaluates the impacts of the BDCPZ policies on regional industrial structure upgrading using a combination of propensity score matching and difference-in-differences (PSM-DID) with panel data of 30 regions for the period 2008–2021. The results are as follows: (1) BDCPZ policies significantly promote regional industrial structure upgrading. This finding holds after conducting the placebo test and replacing explained variables. (2) BDCPZ policies enhance upgrading through technological innovation and financial deepening. (3) Heterogeneity analysis shows that the promotional effect of BDCPZ policies on industrial structure upgrading is more obvious in economically developed regions, megacities, and east-central regions; overall, regions with high industrialization benefit more. These findings have important implications: First, they provide new empirical evidence from the perspective of policy evaluation on how the digital economy affects industrial structure upgrading. Second, this study sheds light on the mechanism underlying this relationship, helping us understand how the digital economy can further affect the development of the industrial structure. Third, the policy effect is heterogenous, providing a scientific basis for the government to formulate differentiated implementation policies for different regions. This can help local industrial transformation and upgrading, and economic development in these regions through the implementation of big data and digital technologies.

Investigating the relationship between energy‐consuming rights trading and urban innovation quality

AbstractThe Energy‐consuming rights trading policy (ECRTP) is an important environmental regulatory policy in China. The study's goal is to determine how trading in energy‐consuming rights and urban innovation status effects also promote ecological civilization and high‐quality development. The purpose of the study examines the relationship between ECRTP and urban innovation quality (UIQ). Using data from 271 Chinese cities between 2011 and 2020, a difference‐in‐difference (DID) model is used to theoretically and empirically analyze the effects of ECRTP on UIQ. The findings of the study are as follows: First, ECRTP showed a significant improvement in UIQ, although a lagged effect. This outcome offers fresh proof that the “Porter hypothesis” holds water in China. Second, mechanism analysis indicated that ECRTP could improve UIQ with industrial structure upgrading (ISU) and capital deepening. Third, analysis of spillover effects indicates that ECRTP has a key spillover impact on UIQ. Analysis of spillover effects indicates a positive influence of ECRTP on UIQ in surrounding cities. Fourth, heteroggeneity analysis further reveals the impact of ECRTP on UIQ is particularly pronounced in resource‐based and large‐scale cities. These findings are significant and also provide a valuable supplement to the existing study.