Upgrading Of Industrial Structure Research Articles

Empirical Study on the Promotion of Industrial Structure Upgrading by Aviation Economy: A Case Study of National Airport Economic Zones

With the rapid growth of civil aviation and economic integration, aviation economic zones centered on large airports have a significant economic impact on surrounding areas. These zones foster the concentration of technology, capital, and labor, leading to the emergence of new regional economic models. This research, based on data from 17 national-level aviation economic demonstration zones, develops an evaluation index system for aviation economic development and constructs a regression model incorporating industrial structure coefficients. It empirically analyzes the relationship between the development of aviation economy and the upgrading of industrial structure in cities with national-level aviation economic zones, revealing the aviation economy’s role in promoting industrial structure upgrading and providing policy recommendations for regional economic innovation.

Digital economy and its effect on total factor productivity in services: evidence from China

ABSTRACT The emergence of the digital economy has provided a new development model and driving force for social and productive activities. The quest to accelerate the transformation and upgrading of the service economy through the digital economy has garnered significant attention in society and academia. In light of this context, this study employs data envelopment analysis (DEA) to measure total factor productivity (TFP) in the service sector, utilizing provincial panel data from China for the period 2007–2019. The empirical results indicate that the digital economy significantly contributes to the growth of TFP in the service sector, and specifically, the channels of its impact include alleviating resource mismatch and promoting industrial structure upgrading. Furthermore, the impact of the digital economy on services TFP varies by region and stage of development of the digital economy. Moreover, based on the informational characteristics of the digital economy, the digital economy not only affects the local service TFP, but also generates a spatial spillover effect on the service TFP of neighbouring regions. This study provides a new empirical evidence to examine the productivity improvement of the digital economy in the service sector and provides important policy implications for achieving high-quality development of the service sector.

Empirical Study on the Impact of New-Quality Productivity on Regional Economic Development in China

New-quality productivity (NQP) reflects the modernization of productivity, characterized by higher technological levels, better quality, and greater efficiency and sustainability. Against the backdrop of technological innovation, NQP plays an increasingly significant role in economic development. Sustained growth of NQP is key to maintaining stable and rapid economic progress. This paper adopts the new-quality productivity index developed by scholar Lu Jiang, Guo Ziang and Wang Yuping, which comprises three dimensions, including innovation capacity, technological research and development, and production efficiency. By using this index, an OLS regression analysis is conducted on the economic development levels of various regions. Through regression analysis, the paper examines the impact of these indicators on regional economic development and provides relevant policy recommendations. The results show with a higher new-quality productivity index tend to have a higher level of economic development. Theoretically, this result further illustrates that new-quality productivity enhances production efficiency through technological innovation and resource optimization, thereby driving economic growth. New-quality productivity not only transcends the traditional factor-driven growth model but also injects stronger innovative momentum and potential for sustainable development into regional economies. On a practical level, improving the level of new-quality productivity can effectively promote the rational allocation of resources, accelerate industrial structure upgrades, and significantly enhance the affluence and vitality of regional economies.

Exploring carbon emission effects of national-level industrial park policies on cities in China

Serving as the backbone of economic development, industrial parks have strong implications for reducing carbon emissions in China under the “carbon peak and carbon neutrality” background. This study explores the carbon emission reduction effects of three different types of national-level industrial parks on prefectural-level cities in China, including economic and technological development zones (ETDZs), eco-industrial demonstration parks (EIDPs), and low-carbon industrial parks (LCIPs). Data on 204 prefectural-level cities over the period of 1999 to 2019 were examined by using the difference-in-differences method and the mediating effect model. The study revealed that (1) the three types of industrial parks significantly reduced the intensity of city carbon emissions by 1,155, 395, and 450 tons per million CNY, respectively; (2) There existed lag effects of 7 years for the ETDZ and 3 years for the EIDP; (3) Industrial structure exhibited significant mediating effects, with ETDZ and EIDP reducing city carbon emission intensity by 58 and 56 tons per million CNY, respectively; (4) Strong heterogeneity in the effects was found, arising from the differences in geographical location, resources endowment, and amount of industrial parks; and (5) ETDZ and EIDP reduced the carbon emission intensity of neighboring cities by 174 and 144 tons per million CNY, respectively, while LCIP increased that by 686 tons per million CNY. The major contribution of this study is analyzing the city-level impacts of ETDZ, EIDP, and LCIP, three different types of national industrial park policies with different implementation periods, regional distributions, and policy focuses. This not only fills a gap in the analyses of ETDZ and LCIP policies in this area of research, but also draws analogies and contrasts between the effects of the three different policies. This study suggests that the stability and long-term nature of industrial park policies be maintained and further transformation and upgrading of industrial structure be attained. Additionally, intercity coordination could be introduced or enhanced.

Digital Economy, Marine Industrial Structure Upgrading, and the High-Quality Development of Marine Economy Based on the Static and Dynamic Spatial Durbin Model

Achieving marine sustainable development goals requires improving the quality of the marine economy. In this study, we constructed a multi-dimensional evaluation index system to quantify the high-quality development of the marine economy (HDME) and digital economy for China’s 11 coastal regions between 2012 and 2020, and systematically explored the mechanisms between the digital economy, marine industrial structure upgrading, and high-quality development of the marine economy. We further empirically analyzed the influence of the digital economy and marine industrial structure upgrading on the HDME by using the static and dynamic spatial Durbin model and threshold model. We found that the digital economy improved the HDME of local and neighboring regions, and the sub-dimensional indicators had a significant heterogeneous effect. The marine industrial structure upgrading only positively affected the quality of the marine economy in neighboring areas. Furthermore, the digital economy and marine industrial structure upgrading also had synergistic effects on improving the marine economy, which mainly depended on digital infrastructure and digital industrialization. There also existed digital infrastructure and digital industrialization thresholds within marine industrial structure upgrading, affecting the HDME. Our results provide new insights for the green and sustainable development of the marine industry and marine economy from a broader technical perspective in the digital age. Governments should recognize the spatial spillover and synergistic effects of the digital economy and marine industrial structure between different regions and implement policies considering their impacts to achieve the marine sustainable development goals.

Do public-private partnerships (PPPs) promote the sustainable development of infrastructure (SDI)? Evidence from China

PurposeTo address challenges such as inadequate funding and inefficiency in public infrastructure construction, PPPs have gained significant global traction. This study aims to comprehensively assess the impacts and mechanisms of PPPs on the SDI and to provide rational policy recommendations based on the findings.Design/methodology/approachWe collated a dataset from 30 Chinese provinces covering the years 2005–2020 as our research sample. The study’s hypotheses are tested using a double fixed-effects model, a chained mediated-effects model and a multidimensional heterogeneity analysis.FindingsOur findings indicate that PPPs have a facilitating effect on SDI in general. This boost usually lags behind policy implementation and is cyclical in the time dimension. In the spatial dimension, PPPs contribute significantly to SDI in the eastern and western regions, but not in the central region. From the perspective of the dynamics of economic, social and industrial development, PPPs in economically backward areas are difficult to promote SDI, promote it the most in economically medium regions and are slightly less in economically developed regions than in medium regions. This promotion effect has an inverted U-shaped relationship with social development and diminishes with industrial structure upgrading. Finally, due to the negative relationship between PPPs and social development and between social development and SDI, PPPs are shown to contribute to SDI and are identified as critical paths. However, PPPs suppress SDI by inhibiting economic and industrial development.Originality/valueThis study makes three novel contributions to the existing body of knowledge: (1) we innovatively introduce the United Nations Sustainable Development Goals (SDGs) into the field of infrastructure research, offering fresh perspectives on SDI enhancement; (2) revealing the mechanisms by which PPPs affect SDI through the three dimensions of economic, social and industrial development enabling policymakers to better understand and optimize resource allocation and improve planning, design and management of PPP projects for sustainable infrastructure and (3) we assess the spatiotemporal variances of PPPs’ effects on SDI and the diversity across regions at different social, economic and industrial structures developmental stages, offering critical insights to global decision-makers to devise tailored policy measures.

Do Fiscal Incentives Contribute to Pollution Control? Empirical Evidence from China

Given the growing concerns over environmental degradation and the demand for sustainable development, the Chinese government has implemented several fiscal incentive policies to enhance environmental governance. Taking the phased comprehensive demonstration cities of the Energy Saving and Emission Reduction Fiscal Policy (ESERFP) as an exogenous shock, this study uses a staggered difference-in-differences method to evaluate the impact of the fiscal incentive policy on pollution control using panel data from 268 prefecture-level cities in China from 2003 to 2017. The results indicate that the industrial pollutant emissions in the demonstration cities significantly decreased compared with those in the non-demonstration cities under the influence of the ESERFP. Specifically, industrial wastewater discharges in the demonstration cities decreased by 15.5% while industrial sulfur dioxide emissions decreased by 19.5%. Moreover, promoting industrial structure upgrades and green technology innovations are the main mechanisms of the ESERFP in reducing industrial pollution emissions. Furthermore, the emission-reduction effect of the ESERFP is more significant in areas with more fiscal resources, lower promotion incentives based on local economic performance, greater emphasis on environmental protection, and those with no old industrial bases. Further analysis shows that the positive effect of the ESERFP on pollution control in the demonstration cities remains relatively effective after the demonstration period ends, and the policy does not sacrifice economic dividends. Overall, this study explores the impact of fiscal incentive policies designed to achieve environmental improvements via pollution control, offering valuable fiscal policy insights for China and other developing economies seeking solutions to environmental pollution, including fiscal incentive policy formulation and implementation, fiscal incentives to support regional green transformations, improving the differentiation and precision of fiscal incentives and enhancing environmental performance assessment.

Technological Change and Entrepreneurial Activities: Evidence from China

This study is among the first to examine the impacts of technological change on entrepreneurial activities. Using new registered enterprises data and industrial robot data from 2010 to 2018, we find that robot adoption is broadly negatively associated with regional entrepreneurial activities. However, our analysis reveals a more nuanced understanding, in which robot adoption boosts high-quality entrepreneurial activities in regions, specifically those in technology-based industries, but reduces low-quality entrepreneurial activities. We also find that a favorable labor allocation environment and sufficient labor resources, as well as abundant high-skilled labor resources, can mitigate the negative impact. Credit constraints and the upgrading of industrial structures are effective in mitigating the crowding-out effect. In cities with higher unemployment risks, the negative effect is attenuated. The extent of the negative effect varies depending on the prevailing macroeconomic conditions, and the hukou reform helps to mitigate the negative impact. In addition, robot adoption has a significant spatial spillover effect between adjacent cities. These findings shed light on the effects of industrial robot adoption on local entrepreneurial activities, as well as the role of technological change in fostering entrepreneurial activities. Our findings suggest that it is crucial to grasp the strategic opportunities embedded in technological change to spur entrepreneurship.

Emissions Reduction Effects and Carbon Leakage Risks of Carbon Emissions Trading Policy: An Empirical Study Based on the Spatial Durbin Model

China’s carbon emissions trading policy represents a significant institutional innovation designed to advance the country’s economic and social development towards sustainability and low-carbon growth. This study investigates the effects of China’s carbon emissions trading policy by employing the difference-in-differences model and spatial Durbin model, using provincial panel data spanning from 2005 to 2020. We find that the carbon emissions trading policy can inhibit per capita carbon emissions in the pilot areas. This work is primarily driven by green technological innovation and the upgrade of industrial structure. Furthermore, the carbon emissions trading policy exhibits a positive spatial spillover effect, inhibits per capita carbon emissions in the areas adjacent to the pilot through demonstration effect and competition effect, and does not cause carbon leakage. These findings reveal the policy’s effectiveness in emissions reduction, and may be useful reference for promoting sustainable economic and social development. This is of great practical significance for exploring how to optimize environmental governance measures, avoid carbon leakage, and achieve balance and fairness in responsibilities in achieving low-carbon sustainable development. Our study proposes policy recommendations for synergizing the national trading market in China.

Does advanced human capital structure improve carbon emission performance in China? Empirical research from a spatial spillover perspective

Facilitating coordination between economic growth and carbon mitigation is vital for the sustainability of human society. Identifying the driving factors of Carbon emission performance (CEP) is crucial for its improvement. Nevertheless, empirical research on the relationship between advanced human capital structure (AHCS) and CEP remains scarce. This study analyzes the impact of AHCS on CEP utilizing a dataset covering 30 Chinese provinces from 2006 to 2021. First, we construct a global epsilon-based measure (EBM) model with undesired output to accurately measure the multi-period CEP for Chinese provinces. Next, we evaluate the level of AHCS from the perspective of dynamic evolution. Subsequently, a spatial Durbin model (SDM) is employed to examine the spatial spillover effects of AHCS on CEP. The results illustrate that CEP exhibits significant positive spatial spillover effects across provinces. Additionally, AHCS has a direct and significant positive impact on local CEP and can indirectly enhance CEP in neighboring regions through spillover effects, although the impact varies across different regions. The impact mechanism analysis indicates that AHCS enhances CEP via technological advancement, industrial structure upgrading (ISU), and energy efficiency improvement, despite the asymmetric effects observed between local and neighboring provinces. Therefore, shaping a favorable educational environment to optimize the human capital structure is critical for the improvement of CEP. In addition, promoting resource sharing and technology exchange through regional cooperation is essential for China’s low-carbon transition development.

Does urban shrinkage impact energy efficiency?: Evidence from Chinese Counties

Some cities in China are facing challenges due to population loss while also attempting to address energy conservation and emissions reduction. Although urban shrinkage can relieve pressure from energy consumption demands, such as water, electricity and gas, does it improve urban energy efficiency? This study attempts to answer this question. Based on Point of Interest (POI) big data and Global Human Settlement Layer (GHSL) raster data, this study identifies urban shrinkage from the coupling perspective of administrative and economic boundaries. It also examines the impact of urban shrinkage on energy efficiency. The results suggest that Chinese counties’ overall energy efficiency is experiencing a four-stage "decline-rise-decline-rise" trend, and the urban shrinkage of Chinese counties exists in three major areas: the Northeast, the Southwest, and the Centre. Compared to non-shrinking cities, urban shrinkage has a significant negative impact on improving energy efficiency. This impact exhibits significant heterogeneity. Specifically, compared with mature resource cities and cities in Western China, regenerative cities, non-resource cities and cities in Central China have less impact on energy efficiency. In addition, urban shrinkage may impede energy efficiency improvement by hindering industrial structure transformation and upgrading, energy-saving technology innovation, and financial development. Clarifying the relationship between urban shrinkage and energy efficiency is helpful for shrinking cities to change their development strategies, which is critical for sustainable development.

The smarter the cleaner: Evaluating the impact of artificial intelligence on haze pollution

This paper innovatively evaluates the level of artificial intelligence (AI) by counting AI firms and employs a two-way fixed-effects model to analyze the impact of AI on haze pollution (HP), using panel data of 264 Chinese cities from 2006 and 2021. It is found that AI is an effective means to reduce urban HP, and that for every 1 % increase in the number of urban AI firms, PM 2.5 is reduced by about 2.22 %. Regarding mechanisms, AI mainly reduces urban HP through two ways: stimulating technology innovation and promoting industrial structure upgrading. Heterogeneity tests show that the haze reduction effect of AI varies due to urban HP level, urban location and urban characteristics, and is more pronounced in cities with high HP, as well as in western cities, northern cities, cities of high administrative levels, and resource-based cities. Our findings provide new insights for policy makers to better utilize AI technology to reduce HP.

Research on the Mechanism of Population Agglomeration's Role in High-Quality Economic Development in Anhui Province

In the early stages of economic development, population agglomeration significantly promotes economic growth. However, with the disappearance of the demographic dividend, negative externalities begin to strengthen. Currently, the economic development in Anhui Province faces challenges, necessitating a shift in focus from pursuing speed to pursuing quality, particularly concerning sustainable development. This paper analyzes the role of population agglomeration in high-quality economic development from the perspective of the five development concepts, constructing a mechanism to understand this relationship. Targeted recommendations for formulating appropriate population control policies and deepening the upgrading of industrial structures are proposed to promote high-quality economic development.

The road to inclusive green growth in China: Exploring the impact of digital-real economy integration on carbon emission efficiency

With the emergence of digital transformation, China confronts the dual challenge of fostering sustainable economic and social development while fulfilling its "dual-carbon" commitments. Is the digital-real economy integration a blessing or a curse for inclusive green development? The study was conducted under this backdrop. This paper explores the impacts and mechanisms of digital-real economy integration on carbon emission efficiency, utilizing panel data from 274 Chinese cities over the period from 2011 to 2021. The results indicate that this profound integration significantly enhances urban carbon emission efficiency, although this relationship is partially mediated by industrial structure upgrading. Additionally, natural resources dependence may compromise efficiency gains, exhibiting varying effects across different contexts. The impact of digital-real economy integration on carbon efficiency (Cee) manifests as a non-linear U-shaped relationship that intensifies with increased integration. Heterogeneity analysis reveals that major, eastern, coastal, and resource-scarce cities experience the most profound benefits. These findings highlight the urgency of advancing digital carbon neutrality and offer strategies for emerging economies to transcend traditional constraints, thereby achieving green economic recovery and inclusive development.

Identifying the antecedents for the green transformation of resource-exhausted cities in China

To address the issue of green transformation in resource-exhausted cities, this study employs the Policy Modeling Consistency (PMC) index model to carry out a comprehensive analysis of the effectiveness of support policies execution at both central and local levels, covering 16 policies at the different administrative levels. Meanwhile, utilizing the fuzzy-set Qualitative Comparative Analysis (fsQCA) method, the study investigates the interaction mechanisms and effects of various internal and external factors in the context of policy coordination, from the perspective of green transformation condition configurations. The findings reveal that the overall effect of supporting policies for resource-exhausted cities in China is generally commendable. Moreover, there is a notable characteristic that “the lower the administrative level, the higher the quality of the support policies”. Notably, organizational, technological, environmental, and policy conditions alone cannot solely facilitate the green transition of resource-exhausted cities. Instead, it is the harmonious configuration of these antecedents that drives successful green transformation. Additionally, the configuration of antecedent conditions for green transformation exhibits the heterogeneity of different types. Specifically, the eastern region primarily relies on technological innovation and production process improvement, while the central region focuses on both production process improvement and support policy combinations. By contrast, the western region primarily emphasizes support policy combinations and the fostering of environmental conditions. Furthermore, the green transformation of resource-exhausted cities with coal and oil types mainly depends on the combination of policy support and technological innovation. Metal, forestry, and other types of resource-exhausted cities rely on the upgrading and advancement of industrial structures. In the grouped analysis of administrative level, innovation capability, and distance to the provincial capital city, cities with higher administrative levels, higher innovation capabilities, and closer proximity to the provincial capital city are more likely to achieve green transformation. Thereby, this study emphasizes the critical role of support policies and the identification of effective pathways in promoting the green transformation of resource-exhausted cities.

The spatial spillover impact of artificial intelligence on energy efficiency: Empirical evidence from 278 Chinese cities

Within the framework of global sustainable development, improving energy efficiency (EE) is recognized as a crucial strategy to address environmental challenges and foster economic growth. This research employs the Spatial Durbin Model to investigate the spatial spillover effects of advancements in artificial intelligence (AI) technology on EE across 278 Chinese cities. The analysis reveals several key findings: first, the advancement of AI technology significantly enhances urban EE and generates a positive spatial spillover effect across different spatial weight matrices; second, there is a nonlinear, inverted U-shaped relationship between AI levels and urban EE; third, industrial structure upgrades play a significant moderating role in the impact of AI technology on urban EE. These insights not only illuminate the complex role of AI in improving regional EE but also provide critical recommendations for policymakers aiming to enhance urban EE and achieve sustainable development goals.

Promoting Cultural Industry Management in the Context of a Green Ecological Environment

The green cultural industry is a key driving force for economic transformation and the upgrading of industrial structures. However, to achieve its development while protecting the environment, its influencing factors and the interactive relationship between the economy and the environment must be considered. This paper examines the environmental promotion effect of the green cultural industry by analyzing the interaction mechanism among these three elements, using the entropy method and coupling coordination model. The results show that the green cultural industry can develop cultural resources in line with national cultural characteristics, foster cultural innovation, promote economic growth, and reduce ecological resource consumption. At the same time, economic improvement enhances infrastructure, provides services to support the cultural industry, strengthens environmental protection, and improves ecological carrying capacity, offering greater resource support for cultural industry development.

Job destruction or job creation?: Evidence from carbon emission trading policies

Based on the panel data of 285 cities in China from 2007 to 2019, this paper constructs a theoretical framework to analyze the employment effect of carbon emission trading policy, and quantitatively evaluates the effectiveness, decomposition effect and influence mechanism of carbon emission trading policy on employment based on PSM-DID method. The study shows that the carbon emissions trading policy has a positive impact on the level of urban employment while producing significant environmental governance effects, and that its positive impact on employment in the pilot cities stems from the negative effect of reducing employment destruction rather than from the positive effect of increasing the job-creating effect. Carbon emissions trading policy promotes employment in the pilot cities through structural transformation effects, specifically through the three paths of green technology innovation, energy structure optimization and industrial structure upgrading. At the same time, the impact of the policy on employment varies significantly across cities of different locations, sizes and resource endowments. The study proposes that the construction of the national carbon market should be accelerated, a market-oriented green technology innovation system should be constructed, the optimization of the energy structure and the upgrading of the industrial structure should be promoted, and training in employment skills should be strengthened. The theoretical analysis of this study provides a theoretical basis for the micro-mechanism of carbon emissions trading policy, and the empirical results provide practical reference for the change of employment structure and the high-quality development of employment.

Impact and mechanisms of high-speed rail construction on carbon emissions: A quasi-natural experiment in China

Carbon emissions present a significant climate challenge for China. As a major source of these emissions, reducing transportation-related carbon output is essential to achieving the country's dual carbon goals. In this context, high-speed rail (HSR) emerges as a green, low-carbon alternative with an increasingly significant role in reducing carbon emissions. This paper explores the impact of HSR station construction on carbon emissions using data from 248 prefecture-level cities from 2003 to 2019, treating the construction as a quasi-natural experiment. Employing a spatial DID model, the research investigates how HSR construction affects carbon emission intensity within the region and in neighboring areas. It also considers socioeconomic factors to understand their mediating roles. The findings reveal that HSR construction significantly reduces regional carbon emissions over time, with long-term and gradually increasing effects. Spatially, HSR also has substantial spillover effects in reducing carbon emissions in adjacent regions. Numerically, HSR reduces carbon emissions by an average of 1.7% in the local region and 2.3% in the surrounding areas. The mechanism analysis indicates that the carbon reduction benefits of HSR stem from a complex interplay of multiple factors, with each selected factor playing a partial mediating role. Notably, the concentration of human capital and the flow of innovation are crucial pathways for regional carbon reduction. However, despite HSR's promotion of industrial structure upgrades and substitution of traditional transportation, these factors have not yet significantly contributed to carbon reduction under current conditions. These results underscore the critical position of HSR in carbon reduction and provide a theoretical foundation for future HSR planning and sustainable development policy formulation.

Research on the Mechanism of Digital Economys Impact on Regional Industrial Structure Upgrading: A Case Study of Shenzhen

The digital economy, as an integrated economy, has become the driving force behind economic growth in various regions, fueling economic transformation and upgrading and serving as the focal point of industrial competition. Shenzhen, as a major first-tier city and a pilot demonstration area for socialism with Chinese characteristics, is taken as an example in this study. By exploring the mechanisms through which the digital economy impacts the upgrading of regional industrial structures, this paper analyzes how the digital economy promotes regional industrial transformation and upgrading through technological innovation, industrial integration, and market competition. It also discusses the existing problems and challenges, and proposes corresponding policy recommendations in areas such as talent cultivation, improving social welfare, and supporting enterprises to better leverage the role of the digital economy in upgrading the regional industrial structure. These efforts aim to ensure the sustainable development of Shenzhens economy, making the new engine more powerful in leading development, creating jobs, supporting international competition, and driving Shenzhens economic and social progress toward high quality.