Industrial Structure Research Articles

The Impact of Digital Finance on the Efficiency of Urban Green Economy

Digital finance is a new financing model for small and medium-sized enterprises and individuals. In recent years, with the rapid development of big data, cloud service technology, and artificial intelligence (AI) technology, it has to some extent promoted the efficient development of urban green economy. From the perspective of applying digital finance to urban enterprises and individual consumers, this study explores the important role of digital finance in enterprise investment and financing services, industrial structure upgrading, technological innovation, and the promotion of personal credit, consumption patterns, job employment, and environmental participation activities. Based on this, the impact of digital finance on the operation and efficiency improvement of urban green economy is obtained, and the problems of inadequate digital transformation and low coordination level in different industries of the city's economy are solved.

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.

Seasonal Variations of PM2.5 Pollution in the Chengdu–Chongqing Urban Agglomeration, China

During the development of the Chengdu–Chongqing Urban Agglomeration (CCUA) in China, PM2.5 pollution severely threatened public health, presenting a significant environmental challenge. This study employs a novel spatial interpolation method known as High Accuracy Surface Modeling (HASM), along with the geographical detector method, local and regional contributions calculation model, and the Hybrid Single–Particle Lagrangian Integrated Trajectory model to analyze the seasonal spatial distribution of PM2.5 concentrations and their anthropogenic driving factors from 2014 to 2023. The transport pathway and potential sources of seasonal PM2.5 concentrations were also examined. The results showed the following: (1) HASM was identified as the most suitable interpolation method for monitoring PM2.5 concentrations in the CCUA; (2) The PM2.5 concentrations exhibited a decreasing trend across all seasons, with the highest values in winter and the lowest in summer. Spatially, the concentrations showed a pattern of being higher in the southwest and lower in the southeast; (3) Industrial soot (dust) emissions (ISEs) and industry structure (IS) were the most important anthropogenic driving factors influencing PM2.5 pollution; (4) The border area between the eastern part of the Tibet Autonomous Region and western Sichuan province in China significantly contribute to PM2.5 pollution in the CCUA, especially during winter.

Is environmental information disclosure driving green energy development? Contextual evidence from Chinese city level data in the lens of sustainability

As an important supplement to mandatory environmental regulation, third-party participation in environmental regulation has become an important driving force for the comprehensive green transformation of economic and social development. Environmental information disclosure (EID) has become a widely used form of third-party participation ecological regulation, and the study of its impact on green energy development (GED) is receiving more and more academic attention. However, the research on this issue is still insufficient in academia. Based on resource-based theory and information processing theory, with IPE project of pollution information survey in China as an exogenous impact, this paper analyzes the causal impact of EID for GED using panel data of 285 Chinese cities from 2000 to 2020. The findings revealed that EID is a strong driver of GED in the long run, further amplified by the smart city pilot program. Besides, industrial structure transformation (IST), substantive green technological innovation (SGTI), non-substantive green technological innovation (NOSGTI), and green finance development (GFD) are important mediating mechanisms through which EID facilitates the GED. Concerning resource endowments of different regions and cities, the heterogeneity test asserted that the promotion effect of EID for GED is best in resource-based cities and old industrial parks. These results emphasize the importance of public participation in urban sustainable development and provide new ideas for promoting green growth.

The impact of pilot policies for low carbon city construction on the development of urban circular economy multiple time-point difference-in-differences model

IntroductionAs a means of environmental regulation, the low-carbon city pilot policy aims to address climate change and alleviate environmental resource pressures in economic development. The development of low-carbon cities often requires changes to the existing industrial and energy structures, which will have a significant impact on the regional economy.MethodsThe study is based on panel data from 273 prefecture level cities in China from 2012 to 2022, and uses the Analytic Hierarchy Process and Entropy Comprehensive Evaluation Method to construct an evaluation index system for urban circular benefits. Finally, the multiple time point differences model and mediation effect model were used to evaluate the impact and influencing factors of policies on urban economy.ResultsThe results indicate that at the 1% level, the explanatory variable coefficient significantly improves the level of urban circular economy development after adding control variables. The construction of low-carbon pilot cities has improved the performance of circular economy development by about 6.42%. The mediating effect of industrial structure rationalization is significantly positive at the 1% significance level, indicating that the construction of low-carbon pilot cities has greatly promoted the coordinated development of industrial relations within China’s low-carbon development regions.DiscussionIt can be seen that the low-carbon city pilot policy has a significant promoting effect on China’s economic development and the development of urban circular economy. Therefore, it is recommended to further expand the pilot scope of low-carbon cities and fully leverage their promoting role.

A pathway design framework for national freight transport decarbonization strategies

ABSTRACT National and international freight transport emissions represent about 40% of global transport emissions, with demand expected to triple by 2050, which will increase emissions further. However, to meet the 1.5°C climate goal, a rapid decrease in transport emissions is required, along with the achievement of zero emissions as soon as possible around mid-century. Given this context, long-term low-emission national development pathways provide a strategic instrument to align short-term action with long-term objectives and to reduce national freight transport emissions. However, current transport-energy modelling studies often exclude the structural and systemic mitigation options that influence the industrial production and supply chain structure, as well as modal and logistics choices, and instead focus mainly on the technological options related to road freight vehicles and fuels. In addition, such studies lack relevant policy and stakeholder-oriented explanations of the barriers and enablers associated with these options. In this paper, we introduce a new framework to design and compare long-term national and sectoral decarbonization pathways for freight transportation, facilitating the consideration of all decarbonization options and the organization of stakeholder-oriented policy dialogues. The development of this sectoral framework builds on the general Deep Decarbonization Pathways (DDP) framework and a first implementation in France. It is then applied and tested in three emerging countries: Brazil, India and South Africa and the results show that the linking of systemic and technological changes could reduce emissions per tonne-km by at least 60%, and up to 100% by 2050, while also reducing energy consumption and supporting national development.

Integrating carbon reduction and ecological resilience strategies in the silk road economic corridor

The Silk Road Economic Belt has become a pivotal region for China's sustainable development, focusing on the balance between carbon emissions and ecological resilience. Understanding the coordination between these factors is crucial for advancing China's westward economic shift and optimizing urban and demographic structures. This study investigates the coupling and coordination dynamics between carbon emissions and ecological resilience across 15 key cities in the Silk Road Economic Belt, using data from 2008 to 2018. By applying a "pressure-state-response" framework, the ecological resilience of the region is quantitatively assessed. Spatial disparities and the dynamic evolution of coupling coordination are analyzed through the Gini coefficient and kernel density estimation. The findings reveal significant regional variations in ecological resilience and a decline in coupling coordination over time. Shifts in the patterns of coordination indicate opportunities for enhancing resource utilization and environmental management. This research provides theoretical insights for policymakers to improve green development strategies, optimize industrial structures, and plan urban green spaces more effectively within the Silk Road Economic Belt.

Process development and heat flow analysis for thin walls made of aluminum using extreme high-speed laser material deposition (EHLA3D)

Extreme high-speed laser material deposition (EHLA) is an adapted variant of directed energy deposition (DED-LB-P/M), also known as laser material deposition, and has been developed for the efficient manufacturing of thin layers with high deposition speeds. With precise control of the energy input into the powder gas jet and the substrate, EHLA allows deposition speeds of up to 200 m/min and weld beads as thin as 25 μm. Advantages include a smaller melt pool and a heat-affected zone, allowing the processing of difficult-to-weld material combinations. The development of EHLA for additive manufacturing (EHLA3D) aims to produce highly customized components with improved structural accuracy compared to standard LMD at increased build rates compared to laser powder bed fusion (PBF-LB/M). A promising application is complex lightweight structures for the aerospace industry. However, there is a lack of systematic investigation on lightweight materials processed with EHLA3D at feed rates >20 m/min. In this work, a specially designed tripod machine (maximum feed rate 200 m/min) was used to investigate the buildup of aluminum in process regimes at 30 m/min. After confirming the existing single-track parameters, the tracks were metallographically examined and checked for pores, cracks, and bonding defects. The process was applied to thin-wall geometries and line energies as well as return-times that were varied. To gain an understanding of process-induced heat development, the process was monitored using thermography. Since the process shows geometry-specific heat flow patterns, guidelines have been developed that enable the buildup using different process adaptions.

Has the Anti-Corruption Campaign Decreased Environmental Pollution? Evidence from China

Whether anti-corruption efforts help reduce environmental pollution is a hot topic in academia. This paper analyzes the impact of anti-corruption on the emissions of environmental pollutants using panel data from 31 provinces (municipalities) in China from 2015 to 2022. By using the 2018 supervision system reform as an exogenous policy shock, a Difference-in-Differences (DID) model is employed to examine the impact of the anti-corruption campaign on environmental pollutant emissions. The results show that the effectiveness of anti-corruption measures has strengthened over time, especially after the 2018 system reform, although these reforms exhibit a lag effect before significantly reducing pollution levels. Furthermore, heterogeneity analysis indicates that due to the high-pollution, high-energy-consumption industrial structure, the pollution reduction effect of anti-corruption measures is more pronounced in resource-based provinces than in non-resource-based provinces. Our findings emphasize the importance of strengthening anti-corruption measures and establishing a sound legal framework to effectively curb corruption and enhance environmental protection.

Scenario-Based Analysis of Electrification Effects on Value Creation and Employment Structures for the Automotive Industry in the Federal State of Baden-Wuerttemberg, Germany

The transformation path to electric mobility will have fundamental impacts on the existing value chain and employment structures in the automotive industry. The purpose of this paper is to derive and examine these effects based on two different electric mobility market scenarios for the European (EU27) passenger car as well as truck market 2040 with special focus on the highly export-oriented industrial automotive cluster in Baden-Wuerttemberg. To achieve this, both a moderate and a progressive market scenario were simulated using the scientifically validated DLR VECTOR21 vehicle technology scenario model, based on two different parameter sets derived from actual and possible framework conditions on the European car and truck markets. Based on a detailed analysis of the industrial branch, value creation, and employee structure in Baden-Wuerttemberg and its automotive cluster, the effects resulting from the transformation to electric mobility will be displayed. With detailed Fade-In and Fade-Out analysis, the shifts from internal combustion engine components to electrified components will be derived and illustrated for each employee segment in the automotive cluster in Baden-Wuerttemberg, which leads to completely new and original results at this level of detail. Furthermore, the detailed display of the automotive cluster in this study allows for regionalized statements on employment effects, considering, for the first time, not only the car but also the truck segment. The analysis shows that battery electric vehicles will achieve a share of 34% or 57% for new registrations on the German car market in 2030, depending on the scenario framework conditions. The resulting employment effects for the entire automotive cluster in Baden-Wuerttemberg reach −37,000 (−8%) or −66,000 (−14%) by 2030 with further negative development until 2040 (−155,000, −30%) for the respective scenarios. Employment segments, in particular powertrain-dependent production employees, are at risk, with a potential decline of up to −60%. R&D employees could be also be significantly, affected with a reduction in workforce of about −50%.

Green Financial Policy for Fostering Green Technological Innovation: The Role of Financing Constraints, Science Expenditure, and Heightened Industrial Structure

The environment has become an increasing concern due to the accelerated expansion of the world’s economy. Green finance is a crucial strategy for China to address challenges in fostering green innovation and achieving sustainable development. By employing the difference-in-differences (DID) method, this study assessed the influence of green financial policy (GFP) on green technological innovation (GTI) in the Yangtze River Economic Belt (YREB). The results indicate that GFP significantly improves GTI, especially in cities with a lower level of green finance development, cities with a medium level of GTI, and cities upstream of the Yangtze River. A mechanism analysis found that GFP promotes GTI in the YREB by alleviating financing constraints and increasing science expenditures. However, it fails to improve GTI through the heightened industrial structure. The findings provide empirical proof and policy direction for the reformation of green financing and the achievement of ecological transformation in the river basin economy in accordance with the ‘dual-carbon’ goal.

The Research on Cultivating Pathways for Vocational High School Students' Professional Qualities

The demand structure for talent in today's society is undergoing significant changes. To meet regional economic development needs and achieve the goals of socialist modernization, there is an urgent need to transform the national industrial structure, which in turn drives the enhancement of technical skills among practitioners. Consequently, the vigorous development of vocational education has become a new focal point and endpoint in the current education system, with the cultivation of vocational skills in vocational high school students emerging as a critical issue. This paper, based on an in-depth analysis of the current status of vocational high school education and students' vocational skills in China, explores the existing problems within the current vocational education training system and proposes several improvement paths. The study highlights that despite progress in curriculum design, practical teaching, and teacher development, challenges remain, including an incomplete curriculum system, insufficient practical teaching, and inadequate evaluation mechanisms. To address these issues, the paper suggests strategies such as optimizing the curriculum system, reforming practical teaching, developing a high-quality teaching staff, and establishing a scientific evaluation and feedback mechanism to enhance students' vocational skills and improve the quality of vocational education. The research indicates that systematic reforms and innovations targeting vocational skills can significantly improve the comprehensive abilities of vocational high school students, laying a solid foundation for their career development.

Analysing the Capital Structure of Indian Entertainment and Pharmaceutical Industry: A Comparative Study

This research work has been done through the various analysis regarding the capital structure of different industries. The work has been done to know the different capital structure mix of Entertainment and Pharmaceutical industry of India. Where to know the Capital structure impact on the profitability of different companies along with Covid 19 period. I also had been used the statistical analysis for comparison of both the industries which is R Software programme. The panel data models had been analysed in this research with Fixed effect method of Least squared Dummy Variable [LSDV] model.

Determinants of Capital Structure in the Hospitality Industry: Empirical Evidence

This paper studies the determinants of hotel SMEs' capital structure using the theoretical framework, and the leading indicators suggested by the Trade-off and Peeking Order theories. We collected financial information from the Bureau Van Dijk database, observing a ten-year time horizon (2010 to 2019 included). The companies were selected based on the indication in paragraph 3, and all fell into the category of SMEs according to the European Commission criteria. Based on the accounting information, we calculated the dependent variables (Total Debt, Long-Term Debt, and Short-Term Debt) and the independent variables (Profitability, Tangibility of Assets, Growth, Size, and Age). For our analysis, we first used a panel data methodology, developing the least squares regressions (POLS) and the fixed effects models (FEM) and then, based on the results, we chose the fixed effects model (FEM) as it was more significant. Subsequently, we tested the hypotheses of the two theories (Trade-Off and Pecking Order) with our analysis model. The results highlighted that profitability, asset tangibility and size are the most significant variables in explaining the behaviour of hotel SMEs.

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.

Exploring the complex relationship between industrial upgrading and energy eco-efficiency in river basin cities: A case study of the Yellow River Basin in China

The synergistic advancement of industrial upgrading and energy eco-efficiency is crucial for the attainment of the Sustainable Development Goals. This study explored the coupling coordination relationship and its spatial-temporal evolution characteristics between industrial structure advancement and energy eco-efficiency, industrial structure rationalization and energy eco-efficiency in Yellow River Basin cities from 2010 to 2020. The super-SBM model and coupling coordination degree model were used to calculate the energy eco-efficiency and coupling coordination degree. Moran's I and Tobit model were used to analyze the spatial autocorrelation and the factors of coupling coordination degree. The coupling coordination degree of industrial structure advancement and energy eco-efficiency decreased from 0.535 to 0.489, with a growth rate of −8.60 %, showing a fluctuating downward trend. The coupling coordination degree of industrial structure rationalization and energy eco-efficiency decreased from 0.296 to 0.246, with a growth rate of −16.88 %, showing an "M" -shaped downward trend. The coupling coordination degree had a significant spatial correlation, and the global Moran's I value was stable around 0.2. Additionally, public transport and degree of opening-up can significantly promote the coordination relationship between industrial upgrading and energy eco-efficiency. These consequences can supply evidence for industrial and energy structure adjustment in river basin cities.

Measurement and Analysis of Carbon Emission Efficiency in the Three Urban Agglomerations of China

China aims to reduce its carbon emissions to achieve carbon peaking and neutrality. Measuring the carbon emission efficiency of three urban agglomerations in China, exploring their spatiotemporal characteristics, and investigating the main influencing factors are crucial for achieving regional sustainable development and dual carbon goals. Using the super-slack-based measurement (super-SBM) model, we calculated the carbon emission efficiency of the Beijing–Tianjin–Hebei (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD) urban agglomerations from 2011 to 2021 and explored the spatiotemporal non-equilibrium characteristics of carbon emission efficiency and its influencing factors. The results indicated that: (1) Overall, the carbon emission efficiency showed an N-type trend, with the PRD having the highest average efficiency. Regional differences between the YRD and BTH regions gradually increased. (2) The efficiency hotspots shifted from the PRD to the YRD, whereas the cold spots were mainly concentrated in the BTH region. The variation in the standard deviation ellipse radius of carbon emission efficiency in the urban agglomerations was clear, and the spatial disequilibrium was significant. (3) Economic level and opening up had positive impacts on carbon emission efficiency, whereas energy intensity and industrial structure had negative impacts. The effects of population size, government intervention, and technological level varied among the regions.

The Economics of Music Streaming: Impact on Artist Compensation and Industry Structure in the Digital Era

The advent of music streaming platforms has radically transformed the music industry landscape, altering traditional revenue models and reshaping artist compensation structures. This study examines the economic implications of the shift from physical and digital sales to streaming-based consumption. Using a mixed-methods approach, we analyze industry data from major streaming platforms, conduct surveys with artists across various genres, and interview industry executives. Our findings reveal a complex picture: while streaming has expanded music accessibility and industry revenues, it has also led to a more concentrated distribution of earnings, with a small percentage of top artists capturing a disproportionate share of streaming revenue. We identify key factors influencing artist compensation, including playlist placement, algorithmic recommendations, and the challenge of converting streams to sustainable income. The study also explores how streaming has affected industry structure, including the evolving roles of record labels, publishers, and emerging intermediaries. We conclude by discussing potential policy interventions and industry initiatives to address disparities in artist compensation and ensure a more equitable digital music ecosystem.

How to enhance the resilience of domestic tourism?

Enhancing domestic tourism resilience (DTR) is crucial to achieving high-quality development of the tourism industry. However, owing to the vulnerability of the tourism industry during the COVID-19 pandemic, the enhancement pathways and associated mechanisms of DTR need to be further investigated. Therefore, this study measures the DTR of China's 31 provinces by creatively combining the simple harmonic motion and regime-switching vector autoregressive models and explores its characteristics to lay the foundation for an empirical analysis. Furthermore, the study empirically analyzes the enhancement pathways and associated mechanisms of DTR using a spatial econometric model. First, this study found that tourism agglomeration, specialization, and diversification determine the characteristics of dynamic response and spatial distributions of DTR. Second, from the perspective of spatial effects, DTR in one region positively impacts that in adjacent regions, and tourism agglomeration in a specific region positively impacts DTR in adjacent regions. Third, in terms of mechanisms, tourism agglomeration enhances DTR by optimizing industrial structure and improving production efficiency, whereas tourism specialization and diversification enhance DTR by improving production efficiency and optimizing industrial structure, respectively. These findings provide information for the enhancement of DTR and achievement of high-quality development of the tourism industry.

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.