Optimization Of Industrial Structure Research Articles

Digital carbon neutrality: evidence of carbon emission reduction based on digital inclusive finance.

As a powerful engine for economic reform and curbing carbon emissions, digital inclusive finance provides solid support for achieving the goal of digital carbon neutrality. This study reveals the positive effect of digital inclusive finance on carbon emission reduction and the deeper reasons behind it by digging deeper into the panel data of 213 cities in China. The study adopts advanced empirical analysis methods to rigorously test the association between digital inclusive finance and carbon emissions. The results show that there is a strong positive correlation between the booming development of digital inclusive finance and the significant decline in carbon emissions. This finding remains solid after several rounds of robustness tests, which fully proves the reliability of the research results. Further mechanism analysis reveals the multiple paths of digital financial inclusion on carbon emission reduction. First, it promotes the optimization and upgrading of industrial structure by optimizing the allocation of financial resources, thus reducing the proportion of high-carbon emission industries. Second, digital inclusive finance attracts more foreign capital inflows and introduces advanced low-carbon technologies and management experience, further promoting the development of low-carbon economy. In addition, the study also found that the differences between different cities in terms of geographic location and city size have a significant impact on the carbon emission reduction effect of digital inclusive finance. In particular, the carbon emission reduction effect of digital inclusive finance is particularly significant in western regions, central cities, and first-tier cities. In response to these findings, this paper proposes a series of targeted policy recommendations. First, the financial service system should be further optimized to increase the coverage and penetration of digital inclusive finance, especially in less developed regions and small- and medium-sized cities. Second, regional policy synergies should be strengthened to form a strong synergy to promote the development of a low-carbon economy. In addition, it should guide capital flows to low-carbon industries and encourage enterprises to increase green technology research and development and application, while actively promoting low-carbon consumption concepts and guiding consumers to form green consumption habits. Through the implementation of these measures, it is expected that the potential of digital inclusive finance in the development of a low-carbon economy will be further stimulated, making a greater contribution to the realization of the goals of carbon peaking and carbon neutrality.

A waste extended input-output-based Transformer-LSTM method for analyzing hazardous waste reduction patterns: A case study of shanghai

Population growth, economic development, and industrialization have resulted in a notable surge in the hazardous waste (HW) generation, consequently leading to adverse effects on human health and environmental safety. In this work, a Waste Extended Input-Output-based Transformer-Long Short-Term Memory (WEIO-TL) method was developed to simulate the HW generation patterns of various economic industries in the supply chain and generate the desired strategies for reducing HW generation. The WEIO-TL method was applied to Shanghai to identify its HW reduction path and potential by 2035. Multiple scenarios were designed to investigate the impacts of different degrees of economic and technological development on HW generation. The primary results indicated that the economic proportion of each key industry and the technological innovation capability were the main factors influencing the HW generation in Shanghai. The six key industries identified by the WEIO were the chemical industry (CI), other services (OS), transportation equipment (MTE), computers, communication, and other electronic equipment (MCCOEE), wholesale and retail trades (WRT), and construction (C). HW generation would peak at 1570.9 kt in 2025 and subsequently decrease to 949.0 kt by 2035 under the optimal scenario based on the optimal TL model (R2 and RMSE values of 0.976 and 5.968), associated with industry structure optimization (i.e., part of high-polluting industries would be shifted to service) and technological innovation capability improvement. The results of the study will serve as a theoretical foundation to guide other cities toward achieving "zero waste."

Industrial structure optimization and green growth in China based on a population heterogeneity perspective

AbstractPopulation and industrial structure, as foundational characteristics of economic and social systems, exhibit significant spatial heterogeneity and dynamic evolutionary trends in their impact on sustainable economic and social development. However, existing research often employs subjective spatial categorization of samples and overlooks the dynamic transitions of influencing patterns, potentially leading to biases in empirical results. To address this, the current study, based on the calculation of green total factor productivity (GTFP) for 30 provinces in China from 2000 to 2018, incorporates a finite mixture model. This model examines the objective heterogeneity and dynamic transition patterns of industrial structure's impact on GTFP, both from the perspectives of industrial structure advancement (ISA) and rationalization (ISR), and reveals the mechanisms of heterogeneity and dynamic changes from a population standpoint. The findings indicate that there are three patterns in the impact of industrial structure on GTFP, with nearly half of the provinces undergoing pattern transitions during the observation period. The key factors for these transitions are identified as the improvement in human capital levels and urbanization rates. In provinces like Beijing, Guangdong, and Shanghai, ISA and ISR significantly promote GTFP, with their effects further enhanced by increased urbanization and human capital levels. Conversely, in regions such as Shanxi and Hebei, ISA does not favor GTFP improvement, and while ISR can enhance GTFP, this positive effect diminishes with increasing urbanization and labor force numbers. This research not only enriches the literature on the positive interaction patterns between industrial and population structures but also provides a comprehensive analytical framework for governments to adopt differentiated policy measures for sustainable economic development.

Does Industrial Intelligence Promote Sustainable Employment?

One of the key driving factors for achieving the goal of sustainable economic development is to ensure decent employment opportunities. This article explores the relationship between industrial intelligence and sustainable development in China from the perspective of employment. Based on interprovincial panel data from 2006 to 2019, using the fixed-effect regression model and mediating-effect regression model, this study empirically tests the impact of industrial intelligence on sustainable employment in China. The following conclusions are drawn: (1) Industrial intelligence has a significant positive impact on the overall scale of employment. Industrial intelligence has promoted the optimization and upgrading of employment skill structure and industrial structure. Industrial intelligence will reduce the employment proportion of low-skilled labor and increase the employment proportion of medium-skilled labor and high-skilled labor. Industrial intelligence significantly reduces the employment share of the manufacturing sector and increases the employment share of the service sector. (2) Industrial intelligence reduces employment levels through capital deepening effects. Industrial intelligence has significantly improved regional labor productivity and significantly improved employment levels through productivity effects. (3) The results of regional heterogeneity show that industrial intelligence has promoted the improvement of employment level and the upgrading of employment structure in the eastern region but has not had a significant positive impact on other regions.

From pixels to production: the impact of digital finance on the industrial fabric of rural China

PurposeThe aim of this study is to discern the role of digital finance in driving rural industrial integration and revitalization. Specifically, it intends to shed light on how the deep development of digital finance can contribute to the optimization and transformation of the rural industrial structure. The research further explores the particular effects of this financial transformation in the central and western regions of China.Design/methodology/approachThis research studies the influence of digital finance on rural industrial integration across 30 Chinese provinces from 2011 to 2020. Utilizing the entropy weight method, a comprehensive evaluation index system is established to gauge the level of rural industrial integration. A two-way fixed effects model, intermediary effect model, and threshold effect model are employed to decipher the relationship between digital finance and rural industrial integration.FindingsFindings reveal a positive relationship between digital finance and rural industrial integration. A single threshold feature was identified: beyond a traditional finance development level, the marginal effect of digital finance on rural industrial integration increases. These effects are more noticeable in central and western regions.Originality/valueEmpirical outcomes contribute to policy discourse on rural digital finance, assisting policymakers in crafting effective strategies. Understanding the threshold of traditional finance development provides a new perspective on the potential of digital finance to drive rural industrial integration.

Research on the mechanism of enhancing digital innovation capability of strategic emerging enterprises-taking Haining manufacturing enterprises as an example

In the context of the digital economy era, digital transformation has become a key driving force for the development of strategic emerging enterprises. The enhancement of digital innovation ability is especially important for strategic emerging industries, which can not only improve the market competitiveness of enterprises, but also promote the optimization and upgrading of industrial structure. After investigation and analysis, strategic emerging industries face the challenges of imperfect management and organization system within enterprises, weak government support, and insufficient innovation atmosphere in the social environment on the road to digitalization, and the enhancement of their digital innovation capability often requires the synergy of internal enterprise mechanism and external support. To address the above issues, this study takes manufacturing enterprises in Haining City, Zhejiang Province, as the object of research, and investigates the mechanism of enhancing the digital innovation capability of strategic emerging enterprises from three levels: the enterprise level, the government level, and the social environment level. This study has important theoretical and practical significance for understanding how strategic emerging enterprises can enhance their competitiveness through digital means, and how governments can formulate effective policies to support enterprises' digital innovation.

Research on the Impact of Carbon Emission Trading Market on Regional Economic Development: A Case Study of East China

This article delves into the impact of carbon emission trading mechanism on regional economy, especially in East China, and focuses on analyzing how this mechanism promotes green transformation and high-quality development of the economy by influencing green technology innovation of enterprises. Research has found that carbon emission trading not only incentivizes companies to reduce greenhouse gas emissions, but also guides capital and technological innovation to flow towards low-carbon areas through market mechanisms, thereby promoting the optimization of industrial structure and sustainable economic development. This article also discusses the impact of different quota allocation methods on green innovation in enterprises, pointing out that the benchmark method can more effectively stimulate the innovation drive of enterprises compared to the historical method. Therefore, according to the research findings, it is necessary to improve the construction of carbon markets, scientifically formulate quota allocation systems, avoid negative impacts on early green innovation enterprises, and provide policy support to reduce innovation costs for enterprises.

Investigating the Influence of Digital Economy Growth on Industrial Structural Optimization and Upgrading

With the rapid development of the social economy, science and technology continue to upgrade and optimize, ushering in the digital era, which provides technical support for industrial innovation and development across all sectors. At this stage, vigorously developing the digital economy has gradually become the only means to optimize and upgrade the industrial structure. Therefore, local leaders and relevant departments need to enhance the importance of constructing the digital economy, enabling the local industrial structure to be optimized and upgraded under the impetus of the digital economy, ultimately promoting overall economic high-quality development. To this end, this paper, combined with existing research results, first elaborates on the positive impact of the digital economy on the optimization and upgrading of the industrial structure. It then analyzes the challenges hindering the process of industrial structure optimization and upgrading and proposes practical pathways to address them, benefiting relevant stakeholders.

Study on the Impact of Digital Inclusive Finance on Urban and Rural Residents' Entrepreneurship

Based on the number of newly registered enterprises each year as a measure of the level of entrepreneurship among urban and rural residents, this study empirically examines the impact of digital inclusive finance on entrepreneurial activities based on panel data from 31 provinces across the country and digital inclusive finance indices from 2011 to 2020. The findings reveal that digital inclusive finance significantly promotes entrepreneurial activities overall. In terms of specific indicators, this promotion effect is primarily driven by the dimensions of coverage breadth and usage depth. When dividing the total sample into four regions: East, Central, West, and Northeast, the study further explores the impact of digital inclusive finance on entrepreneurial behavior in urban and rural areas and across different regions. Therefore, it is recommended to accelerate the development and construction of digital inclusive finance, strengthen the establishment of comprehensive digital infrastructure, and promote the deep integration of digital inclusive finance with traditional industries. This will optimize the allocation of financial resources while also achieving industrial structure optimization and upgrading.

Pathway for China's provincial carbon emission peak: A case study of the Jiangsu Province

This study establishes the LEAP-Jiangsu model and uses the improved multilevel logarithmic mean Divisia index, Tapio decoupling, and synergistic effect models to explore the carbon reduction paths. The improved multilevel logarithmic mean Divisia index model analyzed the influencing factors of the historical and future carbon emissions. A provincial LEAP model was established to predict the time and value of carbon emission peaks. The Tapio decoupling and synergistic effect models were used to clarify the relationship between carbon emissions and economic development, the synergistic effect of carbon and pollutant reduction, and the terminal sector's carbon reduction potential. The results show that Jiangsu Province will most likely achieve carbon peaking in 2025∼2030, and the peak carbon emission is about 792∼853.9 Mt. Terminal energy intensity, power production structure, and terminal energy consumption structure are the main influencing factors of carbon reduction, with a cumulative contribution rate of about 74.4 %–83.5 %. The power production structure is critical in promoting the decoupling of economic development and carbon emissions. The contribution rates of energy intensity reduction, industrial structure optimization, improving terminal electrification level, and energy structure adjustment are 30.3 %, 26.2 %, 20.9 %, and 17 %, respectively. Coordinating carbon reduction measures will have better synergistic carbon and pollutant reduction effects.

Energy, economic, and environmental impacts of electricity market-oriented reform and the carbon emissions trading: A recursive dynamic CGE model in China

Electricity market-oriented reform and carbon emissions trading, as the main policies implemented in China's power sector, have a profound impact on China's green and low-carbon transition by promoting resource allocation efficiency and internalizing external environmental costs, respectively. Therefore, this paper constructed a dynamic recursive CGE model to measure the energy, economic, and environmental impacts of carbon emissions trading and electricity market-oriented reform from electricity market structure and pricing mechanism. The results show that the two policies have a synergistic effect on industrial structure optimization, energy consumption structure optimization, and carbon emission reduction. Specifically, the share of value-added of the tertiary sector, the growth rate of coal consumption, the share of thermal power consumption, and carbon emissions in 2030 are reduced by 5.70 %, 18.29 %, 2.55 %, and 2.838 trillion tons, respectively, compared with the scenario without carbon emissions trading and electricity market-oriented reform. However, imperfectly competitive market structures outperform perfectly competitive market structures in energy consumption structure and carbon emission reduction. Electricity price regulation is also more beneficial to GDP growth and increase in residential disposable income compared to price liberalization. To this end, returning emission trading scheme revenues to residents can effectively mitigate the adverse impacts caused by market-oriented reforms.

Environmental regulation influences urban land green use efficiency: Incentive or disincentive effect? Evidence from China

China's crude economic development has led to high pollution and inefficiency of urban land use. Environmental regulation (Er) is crucial for governments to promote green growth and efficient land use. Using a dataset of 271 cities in China from 2011 to 2020, this paper investigates the threshold effect of green innovation in science and technology and industrial structure optimization on Er impacts of urban land green use efficiency (Ulee). The results show that (1) Er positively affects Ulee. (2) There is a threshold effect of green innovation in science and technology (Gin) and industrial structure upgrading (Ind) in Er affecting Ulee, and the force decreases as the threshold value increases. (3) Within the examination of heterogeneity, the impact of Er on Ulee is more significant in eastern, high levels of urbanization and large cities, but the force of action is smaller. Based on the nonlinear force of Er, it is crucial to maximize the effectiveness of green land use by giving full play to the interactive synergistic effect of the "combination box" and dynamically and flexibly adjusting the intensity of Er according to the time, place, and state of urban development.

How can green finance promote the transformation of China's economic growth momentum? A perspective from internal structures of green total-factor productivity

Green financing is a crucial tool for promoting China's economic growth and helping to achieve carbon neutrality, but its implications on the internal dynamics of green economy remain uncertain. This study examines the impacts of green finance on China’s Green Total Factor Productivity (GTFP) and its internal factors, including technical innovation, industrial structure, balanced regional growth, scale, and resource allocation efficiency, by using a three-hierarchy meta-frontier Data Envelopment Analysis (DEA) and provincial panel data from 2008 to 2020. The findings show that: (1) regional green finance development may greatly boost the growth of GTFP, and the findings remain reliable after applying a series of robustness tests; (2) further research finds that green finance enhances GTFP by promoting technological innovation, facilitating the optimization of industrial structure, and improving resource allocation efficiency; and (3) there are significant spatial heterogeneities in this effect. The effect of green finance on GTFP is more pronounced in developed and market-oriented regions. This study helps to understand the pathways of green finance affecting the transformation of green economic growth and formulate differentiated regional policies in light of local conditions.

Agricultural carbon reduction in China: The synergy effect of trade and technology on sustainable development

The control of carbon emissions from agriculture is imperative in addressing the challenges posed by the greenhouse effect. China must develop a specific pathway for reducing its agricultural carbon emissions, accounting for its unique circumstances and considering the impacts of trade liberalization. (1) The study revealing that agricultural trade liberalization (ATL) has a marked effect on lowering China's agricultural carbon emission intensity (ACEI), with robustness and endogeneity tests supporting these findings. (2) In the pursuit of emissions reduction, the crucial role of technology spillovers (TS) and the optimization of industrial structure (OIS) are essential. (3) The reduction in ACEI is particularly notable in coastal regions, areas with low environmental regulations and during periods characterized by more stable agricultural tariffs. This study shows a synergistic association between ATL and ACEI, indicates the potential for a mutually beneficial situation with advantages in both economic and environmental aspects.

Socio-Economic and Demographic Changes in Rural Development in Eastern China — Comparative Studies

Socio-Economic and Demographic Changes in Rural Development in Eastern China — Comparative Studies

Carbon reduction effects of digital financial inclusion: Evidence from the county-scale in China

All countries in the world are faced with varying degrees of environmental pollution problems and carbon reduction responsibilities. In the case of China, digital transformation emerges as a new growth catalyst for the future economy and a pivotal avenue for optimizing resource allocation, enhancing energy structure, and reducing energy dependence for development. Therefore, this study delves into the carbon reduction effect of digital financial inclusion and explores its pathways. It focuses initially on the counties of the Yangtze River Delta in China, utilizing nighttime light data to estimate carbon emissions and scrutinizing the spatial and temporal distribution characteristics of emissions. Empirical results reveal that digital financial inclusion positively influences carbon emission reduction, with notable spatial and temporal variations in the emission reduction effect. Furthermore, the study uncovers that digital financial inclusion contributes to reducing carbon emissions through the optimization of industrial structure and the promotion of technological innovation. These research findings offer a scientific foundation for guiding the government in developing digital finance to attain local carbon emission reduction targets. Concurrently, local governments should leverage the role of digital financial inclusion in optimizing industries and driving technological innovation to propel the low-carbon, sustainable development of China.

Research on the Relationship Between Digital Transformation and Urban and Rural industrial Integration and Development

This study explores the relationship between digital transformation and the integrated development of urban and rural industries. In the context of economic and social development in the 21st century, the integration of urban and rural development has become an important part of the national strategy, aiming to break the urban-rural dual structure and achieve common prosperity through institutional innovation and technology application. The study found that digital transformation introduces advanced information technology, changes the traditional production management mode, improves efficiency and efficiency, and provides new impetus for the integration of urban and rural industries. This paper analyzes the role mechanism, actual effect, and challenges of digital transformation in urban and rural integration, and predicts the future development trend. The policy proposal emphasizes the deep integration of technology and traditional industries, promoting the development of digital industries, and the two-way flow of urban and rural factors. The forecast shows that the proportion of the primary industry will decline, the innovation capacity of the secondary industry will be enhanced, and the tertiary industry will become the dominant economy. Digital transformation will play a key role in urban-rural integration, promoting the optimization of industrial structure and urban-rural integration.

Retraction Note: Industrial structure optimization, economic development factors and regional economic risk prevention in post COVID-19 period: empirical analysis based on panel data of Guangdong regional economy

Retraction Note: Industrial structure optimization, economic development factors and regional economic risk prevention in post COVID-19 period: empirical analysis based on panel data of Guangdong regional economy

A Study on the Impact of Green Finance on the High-Quality Economic Development of Beijing–Tianjin–Hebei Region

China’s economy has shifted to a new stage of high-quality development, which means that economic development is no longer simply pursuing the increase of quantity, but a balance of quality and quantity. High-quality economic development (HQED) has become essential for China to achieve sustainable economic and social advancement. This paper explores the influence of green finance on HQED, along with the mediating roles of green innovation and industrial structure upgrading. A fixed-effects model is employed to assess the relationship between green finance and HQED and conduct an empirical test in the Beijing–Tianjin–Hebei (BTH) region of China. The findings reveal that green finance significantly contributes to the HQED of the BTH region, and green innovation and industrial structure upgrading have intermediary effects in this process. Based on these insights, this paper proposes several strategies to improve HQED in China, including the development of a green financial system, the promotion of green innovation, and the acceleration of industrial structure optimization and upgrading in the BTH region.

A mechanism for upgrading the global value chain of China's wood industries based on sustainable green growth

With climate change and increasingly fierce international trade competition, upgrading the global value chains (GVCs) under the sustainable development mode is becoming a key transformation for China's wood industry. This study applies system dynamics theory to build a model of upgrading and evolution of the GVC of the wood industry based on sustainable green growth and uses Vensim PLE software for system simulation. The results demonstrate that (1) under the framework of sustainable green growth, the optimization of industry structure and security of resource supply play an important role in promoting the position of the GVC. (2) improving technological innovation capacity, plantation forest stock, carbon emission reduction intensity, and wage growth is essential to upgrade the wood industry's position in the GVC. (3) different policy implementations have different impacts on the coupled and coordinated development of the system, and implementing innovation-driven policies is the optimal realization path to promote the synergistic upgrading of the GVC. The findings enrich the holistic and systematic study of the evolution of GVC upgrading in traditional manufacturing industries and provide a fresh perspective for assisting the wood industry in realizing GVC upgrading under a sustainable green growth model.