Industrial Structure Research Articles

Study on High-quality Development Strategy of Rural Economy Under the Strategy of Agriculture, Rural Areas and Farmers

With the in-depth implementation of the "three rural" strategy, the high-quality development of rural economy has become an important goal to achieve rural revitalization. This paper starts with the current situation of rural economic development, analyzes the main challenges facing rural economy, including infrastructure construction lag, unreasonable industrial structure and brain drain and innovation ability. On this basis, the core strategy of high-quality development of rural economy is put forward from three aspects: industrial revitalization, ecological revitalization and talent revitalization. By optimizing the industrial structure and promoting the integration of the primary, secondary and tertiary industries, the agricultural production efficiency is improved; Emphasizing green agriculture and environmental governance to promote sustainable development; Attention should be paid to attracting high-quality talents and improving rural education and training systems to promote innovation and entrepreneurship in rural areas. Through comprehensive measures, we will strive to provide systematic support for the high-quality development of the rural economy and help the smooth implementation of the rural revitalization strategy.

Research Framework of Regional Economic-Ecological System Vulnerability Evolution and Adaptive Leap under the Background of Climate Change

This study focuses on the vulnerability evolution mechanism of regional economic-ecological systems and its adaptive leapfrogging path under the background of climate change. Based on the theory of complex adaptive systems and the framework of social-ecological system coupling, a regional economic-ecological system vulnerability assessment index system was constructed. Using the system dynamics model and scenario simulation method, the impact transmission mechanism of climate change on regional economic-ecological systems was analyzed, and the spatiotemporal evolution law of system vulnerability was revealed. The study found that climate change has aggravated the vulnerability of regional economic-ecological systems by changing resource endowments, disturbing industrial structure, and affecting ecological service functions. In response to this problem, this study proposed a leapfrogging path based on adaptive management: including building a climate-resilient industrial system, optimizing resource allocation efficiency, enhancing ecosystem service functions, and improving regional adaptive governance mechanisms. The research results have important theoretical value and practical significance for promoting regional sustainable development and ecological civilization construction.

War Reparations, Structural Change, and Intergenerational Mobility

Abstract From 1944 to 1952, largely agrarian Finland had to export, on average, 4% of its yearly GDP in industrial products to the Soviet Union as war reparations. To meet the reparation demands, the Finnish state needed to provide extensive but temporary support to Soviet-assigned industries with insufficient production capacity. This paper documents the long-term impacts of this extensive and temporary industrial policy on industrial and local development and on individual outcomes. Using newly digitized datasets, I show in a difference-in-differences setup that the short-term nonmarket production persistently and significantly increased the employment and production of the manufacturing industries exposed to the policy. These industries plausibly benefited from large initial investments and exposure to export markets associated with the war reparations. The episode further led to local development and structural change, as the more exposed regions became persistently more industrialized. I substantiate these within-Finland results with triple-difference setups employing comparable Norwegian data. I further use Finnish administrative data to study the long-term individual impacts of the episode. Tracking individuals over 30 years, I show that the initial state investments and the persistent change in the local industrial structure increased long-term incomes, led to more educational attainment, and promoted the upward mobility of children and young adults living in the more exposed regions prior to the war reparations period. The observed effects are driven by the more advanced heavy industry, which received the majority of state assistance.

National Forest City Policy and Urban Ecological Resilience: Evidence from 292 Cities in China

The process of sustainable urban development faces complex and severe environmental problems. Therefore, enhancing urban ecological resilience (UER) has become an urgent and critical goal. In this study, the establishment of national forest cities (NFCs) in China is regarded as an exogenous shock event, and the impact of NFCs on UER and its mechanisms are investigated based on data from 292 cities spanning 2003 to 2021 using a difference-in-difference method. It is found that NFCs can significantly enhance UER, and this conclusion holds after a series of robustness tests. Mechanism analysis shows that NFCs can effectively strengthen environmental regulations, upgrade industrial structures, promote green innovation, and thus enhance UER. Heterogeneity analysis indicates that the effect of NFC on UER is more significant in low-carbon non-pilot cities, cities with higher levels of industrial development, and cities in central and western China. Spatial spillover analysis shows that NFCs can effectively improve the ecological resilience of neighboring cities. Therefore, NFCs should be continuously implemented and optimized to establish a long-term mechanism for urban forests to enhance ecological resilience.

Agricultural carbon emissions in China: measurement, spatiotemporal evolution, and influencing factors analysis

IntroductionThe agricultural sector is the second largest emitter of greenhouse gases, accounting for 23% of global anthropogenic carbon emissions. Analysis of the basic state of carbon emissions from China's agriculture is helpful to achieve carbon reduction targets.MethodsAgricultural carbon emissions were calculated using the emission factor method, based on data from the China Rural Statistical Yearbook and various provincial statistical yearbooks. To analyze spatial patterns, the standard deviation ellipse method and the center of gravity migration model were employed, uncovering the migration path of agricultural carbon emissions. Regional disparities and the driving factors of agricultural carbon emissions were further examined using the Theil index and the Logarithmic Mean Divisia Index (LMDI) model.ResultsThe analysis indicated that the emissions center has gradually shifted towards the central and western regions, reflecting changes in agricultural production activity areas. Intraregional differences are the primary contributors to the imbalance in agricultural carbon emissions, with pronounced disparities in grain production and consumption balance regions. Key influencing factors include agricultural production efficiency, adjustments in agricultural industrial structure, economic structure and output, and urbanization levels. The economic output effect and urbanization effect are identified as the main drivers of increased carbon emissions, while declining production efficiency has hindered emission reduction efforts.ConclusionThe findings provide valuable insights for regional management and policymaking in China's agricultural sector, highlighting the need to enhance production efficiency and optimize agricultural structure to reduce emissions.

National Governance and Economic Transformation in the Digital Economy

The digital economy, as a product of the information age, is reshaping economic and social structures. It is not only a new form of economic development, but also infrastructure and general purpose technology. Digital technologies, such as big data analytics and blockchain, are transforming government decision-making and public services, improving governance efficiency and transparency. At the same time, the digital economy is driving industrial upgrading and transforming the industrial structure to “software-defined and data-driven”, in order to realize sustainable economic growth and social well-being.

Coupling Coordination Relationships Between Ecosystems and Economic Development in Qinghai and Tibet

The coordinated development of ecological protection and socioeconomics in the Tibetan Plateau is of great significance. This study examines the coupling coordination of urban ecosystems and economic development across 15 municipal administrative units in Qinghai Province and the Tibet Autonomous Region, the core areas of the Tibetan Plateau. The findings reveal that a larger proportion of the Qinghai and Tibet ecosystems are classified above the medium vulnerability level, primarily due to inherent natural geographic conditions. Additionally, the area of the two provinces and regions below the medium development level is larger, which is mainly influenced by indicators of economic strength and industrial structure. The degree of coupling coordination between the ecosystem and economic system in Qinghai and Tibet is predominantly driven by economic factors. Given the existing natural environmental conditions, the eastern regions of Qinghai and Tibet still possess certain development potential, while the economic development in the western areas is somewhat constrained by the natural environment. Based on this, further policy recommendations have been proposed to adjust and upgrade the industrial structure, aligning ecological protection with economic development in the Qinghai–Tibet Plateau. These recommendations aim to facilitate the formulation of strategies and policies for sustainable urban construction and social development in such high-ecological-value regions as the Tibetan Plateau.

Experimental Studies of Corrosion Resistance of Welded Seams of Steel Structures with a High Sulfur Content in Surface Layers Using Modern Methods of Modeling

Analysis of literature sources and empirical data indicate a variety and a large volume of experimental material, which often characterizes the uncertainty and contradiction of information regarding the effect of sulphur and manganese on the corrosion behaviour of steels obtained using traditional methods. This leads to the need to search for new, alternative methods for its effective analysis. The task of assessing and predicting the corrosion properties of structural steels is a key one in the general problem of managing the operational reliability of welded metal structures and equipment for the chemical, metallurgical, oil and gas, mining and other industries. The possibilities of its solution consist of using new information technologies, a component of which is intelligent means of information processing, such as artificial neural networks (ANN). The use of ANN makes it possible to create qualitatively new hardware and software that significantly expand the classes of emerging problems and increase the efficiency of analysis and forecasting. In the process of long-term operation of metal structures in many industrial industries, the metal is in direct contact with sulfur-containing agents at high temperatures. This leads to the saturation of the surface layer of the metal with sulfur with a concentration of up to 0.6%, which further makes it impossible to carry out repair and welding operations due to the formation of hot cracks. It was found that adding metallic manganese into the electrode coating in an amount of 20-25% significantly increases (4-5 times) the resistance against the formation of hot cracks. Sulfur content in the deposited metal has the opposite effect on the appearance of hot cracks. So, with a sulfur content of 0.042% and more, the resistance of the metal against the formation of hot cracks decreases sharply. It is shown that an increase in the content of metallic manganese in the electrode coating significantly reduces the content of dissolved sulfur in the deposited metal. Moreover, this tendency is typical for steels with different sulfur content in the surface layers and with different service life. For example, for steel with a service life of 20 years, the initial sulfur content in the surface layer of the metal (up to 1 mm) was about 0.52%. Adding metallic manganese in the coating of electrodes in an amount of 20-25% made it possible to reduce the sulfur content in the deposited metal to 0.03-0.045%, i.e. 12.6-17.3 times. In addition, the corrosion rate decreases with an increase in the content of metallic manganese in the electrode coating. The lowest corrosion rate for all steels involved in the research was established at 20-25% manganese content in the coating.

Index System of Low-carbon Driving Factors of Construction Industry in Hebei Province

Under the background of "double carbon" goal, the low-carbon development of construction industry in Hebei Province has become an important part of achieving the carbon peak in 2030 and carbon neutrality in 2060. The construction industry is one of the main sources of carbon emission in Hebei Province, and how to promote its low-carbon development is an urgent issue to be solved. Based on the five aspects of technology, energy, society, economy and industry, this paper constructs the low-carbon driving factor index system of the construction industry. The research shows that technological innovation, energy structure optimization and economic structure adjustment are the key factors to promote the low-carbon construction industry. In addition, by analyzing the current situation and future trend of carbon emissions of the construction industry, this paper puts forward corresponding policy suggestions, which provides theoretical support for the government to formulate countermeasures for the low-carbon development of the construction industry. The conclusion points out that the research and development and application of low-carbon technology, the optimization of energy structure and the green transformation of industrial structure will be the core path to realize the low-carbon development of the construction industry.

Spatial impact of green finance reform pilot zones on environmental efficiency: A pathway to mitigating China's energy trilemma

The energy trilemma is a critical global challenge requiring urgent resolution; however, existing solutions remain inefficient. This study utilizes a detailed environmental input-output indicator system, applying the SBM-DEA model for measurement and incorporating the Spatial Difference-in-Differences (SDID) model to assess the impact of Green Finance Policy (GFP) on environmental efficiency in Chinese cities from 2006 to 2021. The findings demonstrate that GFP significantly enhances environmental efficiency within a 500-km radius, as confirmed by various robustness tests. Mechanism analyses indicate that optimizing industrial structure, reducing energy consumption, advancing green innovation, and strengthening environmental regulations are critical pathways to improving environmental efficiency. Heterogeneity tests further examine the spatial policy effects under different factor endowments. Ultimately, the study concludes that improving environmental efficiency through GFP can alleviate the energy trilemma. This paper highlights the importance of implementing city-specific policies, offering new insights into energy economics, and providing fresh perspectives for policymakers, financial institutions, and enterprises. Despite the study's contributions, future research should further explore the comprehensive effects of GFP on energy, the environment, and the economy to provide more precise and holistic solutions for addressing the energy trilemma.

Research on Whether Artificial Intelligence Affects Industrial Carbon Emission Intensity Based on the Perspective of Industrial Structure and Government Intervention

Artificial intelligence serves as the fundamental catalyst for a new wave of technological innovation and industrial transformation. It holds vital importance in reaching carbon reduction targets and the objectives of “carbon peak and neutrality”. This factor contributes significantly to the reduction in carbon emissions in the industrial domain. This article utilizes panel data from 30 provinces in China, covering the years 2013 to 2021, to develop an evaluation framework for assessing the progress of artificial intelligence development. Through the use of double fixed-effect models, mediation effect models, and threshold effect models, the empirical analysis examines the industrial carbon reduction effects of artificial intelligence and its operating mechanisms. Research indicates that the advancement of AI can significantly reduce carbon emission intensity within the industrial sector. This conclusion remains valid following comprehensive robustness tests. Furthermore, there exists temporal and regional variability in AI’s impact on industrial carbon reduction, particularly more pronounced after 2016 and in central and western regions. AI influences carbon emission reduction in China’s industrial sector through the advancement and optimization of industrial structures. Here, the increase in senior-level operations acts as a partial masking effect, while optimization serves as a partial mediator. The relationship between AI and industrial carbon emission intensity is non-linear, being influenced by the threshold of government intervention; minimal intervention weakens AI’s effect on carbon intensity reduction. These findings enhance our understanding of the factors influencing industrial carbon emissions and contribute to AI-related research. They also lay a solid empirical groundwork for promoting carbon emission reduction in the industrial domain via AI. Additionally, the results offer valuable insights for formulating policies aimed at the green transformation of industry.

The Impact Analysis of the Digital Economy on Green Total Factor Productivity in the Yangtze River Delta Urban Agglomeration

The deep integration of digitalization and greening is a driving force for promoting high-quality economic development. The rapid development of the digital economy empowers green innovation, and the Yangtze River Delta urban agglomeration, as the most developed region in China's economy, carries an important mission for the future economic and social development of China. Clarifying the differences and influencing factors of digital economy and green total factor productivity (GTFP) among different cities within the Yangtze River Delta urban agglomeration is of great significance for formulating regional and national green development policies, achieving regional coordinated development, and environmental sustainability. This paper takes the impact of digital economy development on changes in GTFP as the starting point. Through the analysis of innovation efficiency, a theoretical model is established to reveal the internal mechanism by which digital economy development promotes GTFP. The research results show that digital economy development significantly promotes the improvement of GTFP, with greater impacts on large and medium-sized cities, regions with higher productivity levels, and regions with a more advanced industrial structure. Additionally, the internal mechanism test results indicate that digital economy development enhances GTFP by improving regional innovation efficiency and resource allocation efficiency.

Analyzing Barriers to Innovation Management Implementation in Sustainable Tourism Using DEMATEL Method

The integration of sustainable practices in tourism is increasingly critical, given the sector’s substantial environmental and social impacts. Although the need for innovation management to promote sustainable tourism is widely recognized, various barriers hinder its effective implementation. This study employs the Decision-Making Trial and Evaluation Laboratory (DEMATEL) methodology to systematically examine these barriers, identifying their interconnections and assessing their broader implications. The findings indicate that a short-term focus and financial constraints are the primary effect barriers to implementing innovation management in sustainable tourism. Their prominence as endpoints in the flow of impact within the model of interconnected barriers developed in this study underscores the need to further address the deeper, cause-related barriers that propagate these effects, such as inadequate leadership support, resistance to change, poor stakeholder communication and collaboration, insufficient knowledge and skills, and restrictive regulatory policies. Additionally, industry-specific challenges like a fragmented industry structure and fluctuating market conditions exacerbate these difficulties. Therefore, a comprehensive, holistic approach is essential for transitioning the tourism sector towards sustainable practices through innovation management and overcoming inherent financial and strategic barriers. This study advocates adopting the recently published Management System Standard ISO 56001:2024 as a structured innovation management framework capable of systematically and holistically mitigating these barriers. By analyzing the cause-and-effect relationships among the identified barriers, this study ultimately provides valuable insights that aid stakeholders—including policymakers, business leaders, and community representatives—in devising more effective, inclusive, and forward-thinking approaches to innovation in sustainable tourism. This is crucial for fostering a tourism sector that is not only economically beneficial but also environmentally responsible and socially equitable.

Digital development and rural financial inclusion: Evidence from China

Digital technology has profoundly influenced the development of the financial sector and is of great importance to financial inclusion. This paper employs sub-provincial panel data from 2005 to 2019 to analyse the impact mechanisms of digital economy development on rural finance, exploring the impact of digitalization and overall digital literacy on rural finance. Our findings verify that digitalization has a positive contribution to rural finance, while digital literacy has a significant inhibitory effect on rural finance. This still holds after a series of robustness tests. Subsequent mechanism analysis reveals that digital technology benefits rural finance by optimizing industrial structure and promoting technological progress, while digital literacy accelerates urbanization, leading to the loss of rural labor and thus inhibiting rural finance. Heterogeneity analysis shows that the role of the digital economy in rural inclusive finance is more pronounced in the eastern and central regions. Additionally, higher levels of human capital, economic development, entrepreneurship, and digitalization will further enhance the impact of the digital economy on rural inclusive finance. This study offers a new pathway for the realization of financial inclusion and a theoretical reference for financial development in rural areas. Our empirical analysis also provides new perspectives and insights for the formulation of policies and measures to coordinate the development of various elements of digital finance and cope with the impact of the digital economy on rural finance.

GLOBAL–LOCAL DRIVING FORCES of CHINA’S GREENING of INDUSTRY

ABSTRACT The greening of industry is an inevitable path for developing economies to achieve sustainability transition. However, the specific roles of global and local driving forces are still not substantially understood. This study develops a three-dimensional framework, which includes coercive pressures, normative pressures, and technology acquisition to analyze the influence of global and local drivers on China’s greening of industry. We measure the industrial eco-efficiency (IEE) using Super-SBM model and analyze its influencing factors using the Tobit regression model at the provincial level in China from 2010 to 2020. China’s IEE evolution and its drivers are stage-specific and regionally differentiated, and differences also exist in the roles of global and local drivers. Developing countries initially start the green development of industry under global normative pressures through integration in the global production network. Thereafter, global coercive pressures and local forces, including domestic technologies, market demands, and effective regulations, drive the further greening of industry. The different potentials of regional coercive and normative pressures depend on industrial structures and socio-technical regimes. Policy recommendations for the greening of industry in developing economies are proposed.

Does the Adjustment of Industrial Structure Restrain the Income Gap between Urban and Rural Areas

Abstract Industrial structure adjustment is a process that involves reconfiguring input factors to enhance productivity and efficiency. A crucial aspect of this adjustment is the transformation of the labor force composition, which subsequently affects the employment structure. Consequently, variations in productivity levels lead to the cross-departmental migration of workers, resulting in changes to the income disparities among employees. This article examines the impact of China’s industrial structure adjustment and labor mobility on the urban–rural income gap between 1990 and 2019. Employing an empirical approach, the study investigates the influence of industrial structure adjustment and the direction of labor mobility on the urban–rural income gap. The findings indicate that the quality of industrial structure adjustment contributes to the widening of the urban–rural income gap, whereas labor mobility helps to narrow it. In regions experiencing a net influx of labor, superior industrial structure adjustment amplifies the urban–rural income gap, whereas labor migration diminishes it. Conversely, in regions witnessing a net outflow of labor, superior industrial structure adjustment reduces the income gap, while labor mobility widens the urban–rural income disparity. Notably, in more developed areas of China, the quality of industrial structure adjustment has widened the income gap, whereas labor mobility has narrowed the urban–rural income gap. However, in less developed regions, labor mobility exacerbates the urban–rural income gap.

Dynamic role of medium- and high-tech industries and environmental policy stringency in environmental sustainability: fresh insights from Dynamic Seemingly Unrelated Regression (DSUR) analysis.

Since the last two decades, carbon neutrality has become a primary target of all economies. Governmental environmental policies stand as the most potent tools in the arsenal when it comes to tempering the effects of climate change. Fostering the adoption of green energy sources and embracing energy efficiency principles may assume an essential role in upholding the standard of ecological integrity. The primary objective of this inquiry revolves around the meticulous analysis of the intricate interplay between economic growth, the trajectory of industrialization, the up-gradation of industrial sector structure, the integration of green energy paradigms, and the implementation of energy efficiency strategies and environmental policies in the frame spanning from 2000 to 2019. To tackle the matter of cross-sectional dependency and heterogeneity, second-generation cointegration estimators, Dynamic Seemingly Unrelated Regression (DSUR) and Augmented Mean Group (AMG), were employed to estimate long-run relationships. The consequences of DSUR and AMG indicate that while economic and industrial growth contributes to environmental degradation, renewable energy usage, and medium-high-tech industries mitigate the carbon emissions in selected countries. Further study results suggest that energy intensity positively impacts environmental degradation, which means energy efficiency helps mitigate CO2 emissions in these countries. This study also reveals that the degree of stringency in environmental policy negatively affects CO2 releases in the selected nations. Consequently, our study recommends the enhancement of the stringency of environmental policies, promoting environmentally friendly energy usage, the efficient use of energy, and the advancement of industries into medium-high-tech industries as effective ways to mitigate climate change in specific developing countries.

Do impoverished regions benefit from climate change mitigation measures? Evidence from the Forest Carbon Sink Project in China

ABSTRACT Forests play a crucial role in achieving global climate change mitigation goals. The Forest Carbon Sink Project (FCSP) was initially proposed by the Clean Development Mechanism under the Kyoto Protocol, aiming to address externalities in climate governance through ecological compensation mechanisms. For impoverished regions, the FCSP is more attractive than the mandatory administrative approaches to forest protection. This Currently, due to the lack of empirical research, there is still debate in the academic community about whether the FCSP can produce overall positive economic benefits in poor areas. Based on panel data from 634 impoverished counties in China from 2002 to 2019, this study attempts to address this issue using a multi-period Difference-in-Differences (DID) model. The results demonstrate that, compared to non project counties, the implementation of the FCSP led to an increase in actual GDP and per capita GDP of 8.40% and 11.10% in project counties, respectively. That is, the FCSP can expand the economic scale while also promoting economic growth of project counties. The results of the dynamic model show that the economic benefits generated by the FCSP in these counties are long-term and sustainable. Based on the results of theoretical analysis and mechanism testing models, this study concludes that the FCSP generates short-term economic benefits through capital investment. It generates long-term economic benefits by improving the productivity of the primary industry labour force, increasing the level of fixed asset construction, and optimizing the industrial structure in poverty-stricken counties. Additionally, this study also conducted a heterogeneity analysis. In summary, this study concludes that the FCSP is a climate change mitigation measure worthy of promotion in impoverished regions.

The Impact of the Digital Economy on China's Economic Development

Abstract: This paper explores the impact of the digital economy on China's economic development. The digital economy, as a new form of the economy following the agricultural and industrial economies, centres on data resources and modern information networks, driving the digital transformation of all factors of production. The Chinese government places great importance on the development of the digital economy, clarifying its direction and key tasks through policy documents such as the "14th Five-Year Plan for Digital Economic Development". This paper analyses the current state of development of the digital economy in e-commerce, digital payments, and big data applications, and discusses its impact on industrial structure, employment, and consumption patterns. The study shows that the digital economy has promoted the upgrading of traditional industries and the growth of emerging industries, while also bringing about changes in employment structure and innovation in consumption methods. However, it also poses challenges to the job market, which need to be addressed through skills training and educational reform.

Risk Analysis of Financing Structure in Theme Park Industry and Optimization Using Blockchain Finance -- Based on Shanghai Disney Company

Abstract: In recent years, with the passing of the epidemic period, the theme park industry has rapidly developed and heated up. On the basis of favorable development conditions, the financing model of theme parks will become a key consideration factor for ensuring their sustainable development, that is, how to ensure sufficient capital injection. This research mainly studies the risk analysis of the existing financing structure of the theme park industry, as well as how to further optimize the structure and whether new technology blockchain technology can be applied to it. Through this study, business managers will further understand the shortcomings and risks of the current theme park financing model, how to optimize it in the future, and how to combine new technologies such as blockchain in supply chains to gain competitiveness in complex market environments. This research uses a combination of case analysis and data analysis to select Shanghai Disneyland as the target object. The capital data in its annual report is analyzed, as well as companies that use new technologies in their financing structure as case studies. This research analyzes the shortcomings and risks of the existing financing structure of Disneyland, proposes new financing models that will benefit the future development of Disney Company, and combines blockchain technology to propose new plans.