Manufacturing Industry Agglomeration Research Articles

Synergistic industrial agglomeration, new quality productive forces and high-quality development of the manufacturing industry

This study analysed the impact of the mechanism of the synergistic agglomeration of manufacturing and modern service industries on the high-quality development of the manufacturing industry using the entropy value method, coupling coordination degree, and E-G index. We utilised panel data of 30 provinces and cities in China from 2012 to 2022. The study found that synergistic agglomeration significantly promotes the high-quality development of the manufacturing industry, in which ‘new quality productive forces’ play a key intermediary effect, while the innovation ecosystem has direct and indirect moderating effects on the relationship between the two. Simultaneously, industrial synergistic agglomeration, development of new productivity, construction of innovation ecosystems, and high-quality development of the manufacturing industry in all provinces and cities showed a steady increase; however, there were significant differences between regions. Based on the findings of the study, policy recommendations are suggested to further promote the synergistic development of the manufacturing industry and modern service industry. At the policy level, the government should strengthen the guidance and support of industrial synergistic agglomeration and formulate differentiated policies to promote industrial synergistic agglomeration; simultaneously, it should pay attention to the cultivation of new productivity and the construction of innovation ecosystems, optimise the allocation of innovation resources, and stimulate the vitality of innovation. At the industrial level, manufacturing enterprises should actively cooperate with modern service enterprises to achieve resource sharing and technological complementation; modern service industries should improve service quality and efficiency to meet the needs of manufacturing transformation and upgrading; and close cooperation between the industry, academia, and research institutes should be established to promote technological innovation and industrial upgradation.

Impact of Low-Carbon City Pilot Policies on Regional Green Total Factor Productivity: A Study

Based on data from 246 prefecture-level cities in China spanning the years 2006 to 2019, this paper employs a multi-temporal double-difference model to empirically examine the effects of low-carbon pilot policies implemented since 2010 on green total factor productivity. Furthermore, the paper conducts a mechanism analysis and heterogeneity analysis to explore the policys impact mechanisms and effects on different regions. The study reveals that low-carbon pilot policies have enhanced Chinas green total factor productivity. Results from the mechanism analysis indicate that these policies increase green total factor productivity by promoting the agglomeration of productive service industries and the innovation of green technologies, with the mechanism test for manufacturing industry agglomeration showing non-significant effects. Heterogeneity analysis results suggest that the impact of low-carbon pilot policies on the improvement of green total factor productivity is significant in Chinas eastern and western regions as well as in non-resource-based cities.

Research on the Impact of Digital Finance on the Quality of Manufacturing Industry Agglomeration

In the new era of deep global economic integration and industrial structure transformation and upgrading, high-quality industrial agglomeration has become the core driving force leading the development trend. Manufacturing is the most obvious industry of industrial agglomeration. The promotion effect of digital finance on high-quality manufacturing agglomeration is mainly reflected in the scale, economic efficiency, innovation, green and industrial structure upgrading of manufacturing agglomeration. The development of digital finance plays an important role in promoting high-quality manufacturing agglomeration.

Spatial spillover effects of manufacturing agglomeration on China's total factor carbon productivity: evidence from the regulatory role of fiscal decentralization.

Based on the theory of new economic geography, this paper used panel data from 284 cities in China from 2006 to 2019 to determine the effects of spatial spillover and heterogeneity of manufacturing agglomeration (MA) on urban total factor carbon productivity (TFCP) and the regulatory effect of fiscal decentralization on the outcome. The results showed that (1) MA shifted from the eastern region of China to the central and western regions, with the center of gravity moving towards the south. The spatial pattern of urban TFCP displayed the solidifying characteristics of "low-level agglomeration and high-level dispersion," with technological progress being the primary driver. (2) The MA had a significant U-shaped effect on the TFCP of local and nearby cities, promoting the improvement of urban TFCP through Jacobs' and Porter's externalities but not MAR externalities. (3) Regarding regional differences, MA had a significant U-shaped impact on urban TFCP in the eastern and central regions. At different levels of manufacturing development, there was an inverted U-shaped relationship in both manufacturing and non-manufacturing metropolitan areas. For varying degrees of manufacturing industry agglomeration, increasing the level of MA improved urban TFCP in low agglomeration areas, but inhibited it in high agglomeration areas. (4) The implementation of fiscal decentralization nationwide and in the eastern and central regions significantly weakened the impact of MA on TFCP. Furthermore, fiscal decentralization significantly enhanced the influence of MA on TFCP in cities exhibiting high levels of economic development, advanced industrial structure and strict environmental regulations. Therefore, based on the unique developmental characteristics of the manufacturing industry in various cities, fiscal policies ought to be tailored to local circumstances to support key areas. This strategy should facilitate the high-quality development of manufacturing industry and low-carbon development of cities.

Digital economy, industrial agglomeration and high-quality development

ABSTRACT This study examines the impact of the digital economy on high-quality economic development in 283 Chinese cities from 2011 to 2020, focusing on manufacturing industry agglomeration. The results show that the digital economy significantly enhances economic efficiency, particularly in larger cities, while smaller cities see less pronounced effects. The research highlights a pathway from digital economy development to industrial agglomeration, underscoring the critical role of manufacturing industry agglomeration in promoting high-quality economic development in Chinese cities.

Study on the impact of digital economy on industrial collaborative agglomeration: Evidence from manufacturing and productive service industries.

In the digital era, digital economy has a far-reaching impact on the collaborative agglomeration of manufacturing and service industries. This research aims to examine the economic relationship between digital economy and industrial collaborative agglomeration. Based on a panel data set of 286 Chinese cities, this research employs Tobit model, moderating effect model, and mediating effect model to conduct data analysis. It is found that digital economy has a nonlinear relationship with industrial collaborative agglomeration, and this relationship is a U-shape. Moderating effect analysis reveals that government intervention significantly regulates the role of digital economy in industrial collaborative agglomeration. Mediating effect analysis indicates that digital economy promotes industrial collaborative agglomeration through entrepreneurial activity. Heterogeneity analysis shows that the facilitating effect of digital economy on collaborative agglomeration in high-end industries comes earlier than in middle- and low-end industries. Moreover, this research finds that digital economy plays a significant role in industrial collaborative agglomeration in central and western regions of China but not in the eastern region. To enhance the impact of digital economy on industrial collaborative agglomeration, it is crucial to strengthen the engagement of the government and ensure the availability of digital technology.

The impact of collaborative agglomeration of manufacturing and producer services on carbon emission intensity: Influence mechanism and spatial effect.

Under the goal of " carbon peaking and carbon neutrality," how to create a low-carbon and green development path for cities is an urgent problem in China. One of the effective ways to solve this problem is through industrial collaborative agglomeration. In this paper, panel data of 276 prefecture-level cities in China from 2010 to 2020 was selected to investigate the relationship between the collaborative agglomeration of manufacturing and producer service and carbon emission intensity by using a fixed-effects model, intermediary model, and SDM in multiple dimensions. The study found that the collaborative agglomeration of manufacturing and producer service industries significantly influences carbon emission intensity with an inverted U-shaped curve, and the agglomeration of manufacturing and producer service industries can influence carbon emission intensity through technological progress. In addition, the inverted U-shaped impact of collaborative agglomeration of manufacturing and producer services on carbon emission intensity has a spatial spillover effect, and the spatial spillover effect generated is stronger than the impact on the local area. Moreover, from the perspective of industry heterogeneity, compared with low-end producer services, the agglomeration of manufacturing and high-end producer services can play a better role in carbon emission reduction. Regarding regional heterogeneity, compared with the central and western regions, the impact of manufacturing and production services agglomeration on carbon intensity is far more obvious in the more economically developed eastern regions.

Collaborative agglomeration level and spatial correlation of intercity manufacturing industry: An empirical study based on the cities of the Yangtze River Delta.

Taking 27 cities in the Yangtze River Delta as an example, the time section data from 2009 to 2019 are selected, and the location entropy index and the modified E-G index are introduced to measure the collaborative agglomeration level of intercity manufacturing industry in the Yangtze River Delta. The spatial weight matrix is constructed based on the highway mileage between cities. Using Moran's index and Local Moran's index, this article analyzes the spatial correlation of the collaborative agglomeration level of intercity manufacturing industry in the Yangtze River Delta. The results show that: Firstly, the overall agglomeration degree of manufacturing industry of cities in the Yangtze River Delta shows a fluctuating downward trend. The agglomeration degree of manufacturing industry in Jiangsu and Zhejiang Provinces has decreased, that of most cities in Anhui Province has increased steadily. Secondly, the collaborative agglomeration level of manufacturing industry between Shanghai, Nanjing, Hangzhou and other cities in Jiangsu and Zhejiang Provinces showed a downward trend, while the collaborative agglomeration level with Anhui cities increased steadily. The collaborative agglomeration level of manufacturing industry between Wuxi, Suzhou, Nanjing and cities with obvious advantages in manufacturing industry agglomeration degree shows an upward trend, while the collaborative agglomeration level with other cities has declined. The collaborative agglomeration level of intercity manufacturing industry in Hefei has generally improved, especially the collaborative agglomeration quality and depth of manufacturing industry between Hefei and other cities in Anhui Province have significantly improved. Thirdly, the regions with high collaborative agglomeration level of intercity manufacturing industry in the Yangtze River Delta are still mainly concentrated in Jiangsu and Zhejiang Provinces. Although there has been a trend of westward transfer in the past decade, the overall change range is small, and the spatial correlation of the collaborative agglomeration level of intercity manufacturing industry shows a weakening trend as a whole.

Land supply and industrial agglomeration: Extension of the new economic geography model with land elements incorporated

Many countries and regions have adopted various incentive land policies to promote industrial agglomeration, but the effect of these policies is limited. This paper extends the new economic geography model, introduces the guiding role of land policy on industrial agglomeration, and explores the rules of land supply affecting industrial agglomeration based on the four cases of Chengdu, Beijing, Shandong, and Shenzhen in China. The study shows that (1) A stable equilibrium for the manufacturing industry agglomeration may still be formed for enterprises not highly dependent on land without incentive land policies. (2) For enterprises with moderate dependence on the land, elastic adjustment of the land supply according to the land demand has a positive effect on the stable equilibrium of industrial agglomeration. (3) For enterprises highly dependent on land, the effect of incentive land supply policies to promote industrial agglomeration may not be significant. (4) Small-scale agricultural land expropriation can, to a certain extent, promote the agglomeration of manufacturing industries. However, suppose the cost of manufacturing land reduced by agricultural land expropriation cannot compensate for the increase in the cost of agricultural products due to the reduction of agricultural land. In that case, the market crowding effect that promotes the dispersion of enterprises still exists. Therefore, the government should fully examine the degree of dependence on the land of various enterprises and formulate targeted land policies, measure the scope of land expropriation that does not disturb the agricultural market, stabilize the cost of agricultural products required by the manufacturing industry, and realize the stable agglomeration for the manufacturing industry from a comprehensive perspective with agriculture incorporated.

Synergistic Agglomeration of Manufacturing and Logistics Industries and Urban Green Economy Efficiency: Influence and Upgrading

Synergistic industrial agglomeration has an impact on green economy. In this research, the evaluation index system of urban green economic efficiency (GEE) is constructed; the superefficiency SBM model, Malmquist index method, location entropy method, and Tobit regression analysis are used to analyse the static and dynamic GEE, the industrial agglomeration level of manufacturing and logistics industries, the synergistic agglomeration level of the two, and the influencing factors of GEE of 41 cities and four provinces in the Yangtze River Delta (YRD) region from 2010 to 2019. The results show that the urban GEE in the YRD region is generally not high, and the annual change trend of efficiency is U‐shaped. In the YRD region as a whole and in each province, the relationship between the synergistic agglomeration level of the two industries and the GEE presents regional heterogeneity and GEE is influenced by various factors. Synergistic alignment and integrated development of the two industries are good ways to optimize and upgrade industrial structure transformation. The government can improve urban GEE by adjusting the horizontal and vertical intergovernmental relations as well as adjusting the talent support mechanism to promote integration of technologies with industry and optimizing the upgrading and transformation of industrial structure to achieve sustainable industry development.

Factor crowding effect of marine manufacturing industry agglomeration

Factor crowding effect of marine manufacturing industry agglomeration

Influence Mechanism of Industrial Agglomeration and Technological Innovation on Land Granting on Green Total Factor Productivity

The influence of land granting on green total factor productivity (GTFP) and its mechanisms remain under-explored. Based on dynamic spatial panel data of 30 provincial administrative regions in China from 2007 to 2017, this study attempts to establish the framework of a transmission mechanism among land granting, manufacturing agglomeration and technological innovation, and green total factor productivity, and measures their interactions by the mixed directional distance function and Global Malmquist–Luenberger index model containing undesirable output. Then, this paper empirically estimates the impacts of land granting, industrial agglomeration and technological innovation on green total factor productivity in China with a dynamic spatial mediating effect model. The results show that the development paradigm of China’s industrial green economy is characterized by path dependence, and industrial GTFP has a significant spatial effect. Local governments rely on low-price competition to obtain cost advantages and facilitate the agglomeration of local manufacturing industries, and promote the impact of negotiation on industrial GTFP through the mediating effect of manufacturing agglomeration. There exists a non-linear relationship between manufacturing agglomeration and industrial GTFP. The land acquired through negotiation has a promoting effect on green technology innovation, and will foster industrial GTFP through the intermediary effect of technological innovation. No obvious non-linear relationship is observed between technological innovation and industrial GTFP. The grant of “Tender, Auction and Listing” has no significant influence on the industrial GTFP, and the mediating conduction effect on the GTFP of industry is not established. Industrial structure, government management and infrastructure will significantly promote the improvement of industrial GTFP, while the level of transportation will inhibit the improvement of industrial GTFP. Through administrative intervention in low-production capacity departments, local governments can integrate regional resource endowments, give play to the comparative advantages of industries, and achieve industrial structure upgrades and core competitiveness, which will be conducive to the improvement of industrial GTFP. High-level transportation conditions increase energy consumption and greenhouse gas emissions in transportation operation, which makes no contribution to the enhancement of industrial GTFP.

Does Manufacturing Industry Agglomeration Aggravate Regional Pollution? -- Evidence from 271 Prefecture-level Cities in China

<p>To find out the relationship between industrial agglomeration and environmental pollution, this paper carried out empirical research on the panel data collected from 271 prefecture-level cities in China from 2004 to 2017 through a spatial panel econometric model. It reviewed the influence of agglomeration externality on environmental pollution. The results detected an inverted "U"-shaped relationship between manufacturing industry agglomeration and environmental pollution nation-wide. The manufacturing industry agglomeration level at the inflection point was 0.652, suggesting that prefecture-level cities suffered severe environmental pollution problems. At the regional level, the manufacturing industry agglomeration in eastern and western China had a significant adverse effect on environmental pollution. In the central China, the relationship between manufacturing industry agglomeration and pollution was "N" -shaped. The manufacturing industry agglomeration levels in most prefecture-level cities were between the two inflection points. The environmental pollution aggravated as the manufacturing industry agglomeration level rose in the range. As for cities in the northeastern region, manufacturing industry agglomeration has no direct causal relationship with environmental pollution.</p>

Spatial-Temporal Evolution and Influencing Factors of Urban Green Innovation Efficiency in China.

Promoting green urban development has become a common consensus to address environmental pollution and ecological damage, but we know little about the measurement and drivers of urban green innovation efficiency (GIE). In this article, firstly, we established a framework for assessing urban green innovation efficiency through multidimensional data, then used the spatial econometric model to reveal the spatiotemporal evolutionary characteristics of urban GIE, and, finally, analyzed the influencing factors and spatial spillover effects of urban GIE. The results show the following: (1) The overall urban GIE in China was low and had significant spatial agglomeration, mainly concentrated in the Yangtze River Delta and Pearl River Delta regions with spatial locking characteristics, while the GIE of cities in undeveloped regions does not change much. (3) There was much room for improvement in the input-output system of green innovation, considering that the sources of inefficiency in most cities were insufficient investment in scientific and technological innovation personnel and innovation environment, excessive environmental pollution, and limited technological output. (4) Foreign direct investment, financial development, and manufacturing industry agglomeration had positive effects on urban GIE. These research findings and policy implications are of certain reference value for other emerging developing countries to implement urban governance and green development.

An Intelligent Analysis Model in the Environment of Regional Economic Development and Regional Economic Differences in China Using Big Data Analysis Technology.

The current and long-term regional economic imbalance in China requires ongoing attention. To ensure the balanced development of China's renewable energy, it is therefore important to examine the causes of the differences in China's renewable energy from a variety of perspectives. The spatial distribution pattern and characteristics of China's per capita GDP (gross domestic product) from 2012 to 2021 were examined in this study using the exploratory spatial data analysis tool. In addition, it conducts an empirical investigation into the spatial spillover effect of RED and the manufacturing agglomeration in China (regional economic development). The findings indicate that in the eastern region, the total backward link value of the feedback effect of 17 industrial sectors is 0.8524, and in the central region, the value is 0.8139. The real per capita GDP of neighboring provinces will increase by 0.118% for every 1% increase in manufacturing agglomeration level. According to the overall ranking, China's RED level is very uneven due to a number of factors. We should direct and encourage the manufacturing industry to congregate in various regions, optimize the spatial pattern of manufacturing industry agglomeration, and fully exploit SSE in order to promote China's RED and reduce the difference in RE.

Does industrial agglomeration affect the regional environment? Evidence from Chinese cities

This study examines the impact of industrial agglomeration on the regional environment using panel data of 13 prefecture-level cities in the Beijing-Tianjin-Hebei region from 1998 to 2018. The empirical results show a strong spatial autocorrelation and a strong spatial lag and spatial error effect on the environmental pollution level in the Beijing-Tianjin-Hebei region. The results further show that the manufacturing agglomeration significantly aggravates the regional pollution; service agglomeration significantly alleviates the regional environmental pollution; the synergistic agglomeration of manufacturing and service industry has a significant inverted "U" type relationship on the regional environmental pollution. More specifically, the development of synergistic agglomeration intensifies regional environmental pollution at the early stage, and after reaching the inflection point, synergistic agglomeration alleviates regional environmental pollution. The inflection point occurs when the level of synergistic agglomeration is around 2.85. At the same time, there is no significant spillover effect of synergistic agglomeration on neighboring regions after calculating the feedback effect. Study findings provide insights for promoting the strategy of "two-wheel-drive development" and alleviating the contradictory relationship between industrial development and environmental pollution.

Rapid Transportation and Green Technology Innovation in Cities—From the View of the Industrial Collaborative Agglomeration

This research uses a two-way fixed effect model to examine the correlation between the development of high-speed rail and the growth of green technology innovation by adopting the panel data of 284 Chinese cities between 2004 and 2013. The empirical results show that the supply of high-speed rail services has a significant promoting influence on the advance of urban green technology innovation capabilities. In particular, cities located in central and western China, along with those cities with relatively little government support or relatively backward public cultural infrastructure, have more chances to benefit from the supply of high-speed rail services. In addition, by employing a mediating effect model, this article finds that the industrial collaborative agglomeration plays an important mediating role between high-speed rail and regional green technology innovation. Therefore, this article suggests that the Chinese central government should continue to accelerate the construction of the rapid transportation network and expand the coverage of high-speed rail services in China to increase the growth of green technology innovation and achieve steady and sustained economic growth in China. Meanwhile, local governments should actively guide the collaborative agglomeration of manufacturing and related producer service industries under local conditions to stimulate the expansion of the green technology innovation market.

Analysis of the agglomeration of Chinese manufacturing industries and its effect on economic growth in different regions after entering the new normal

Abstract Entering the new normal of economy symbolises the innovation of growth mode and continuous optimisation and upgradation of economic structure. Using EG index, this paper measures the agglomeration degree of 31 provinces and cities and 31 manufacturing industries in China from 2012 to 2016; the results show that under the new normal, the degree of industrial agglomeration in China's manufacturing industry remains basically stable, but the overall situation is still in a state of moderate agglomeration, the regions with higher degree of concentration continue to present the pattern of ‘one pole, two domains’. To further reveal the relationship between the concentration of Chinese manufacturing industry and regional economic growth, the GMM method of dynamic panel two-stage system was used, and the results showed that industrial agglomeration and economic growth do not have simple linear relationship, but inverted U-type relationship. There was a dynamic continuation effect of regional economic growth, and external factors such as fixed asset investment and government financial expenditure can promote regional industrial economic growth. Finally, the enlightenment of the complete article is given.

The Impacts of Urban Manufacturing Agglomeration on the Quality of Water Ecological Environment Downstream of the Three Gorges Dam

As an important way to promote economic growth and to improve ecological environment quality, industrial agglomeration strategy has been widely accepted and implemented in various regions of China. In theory, industrial agglomeration is conducive to reducing pollution emissions. However, this needs to be tested in reality. The purpose of this paper is to test the impacts of manufacturing industry agglomeration on the quality of water ecological environment in 17 prefecture-level cities downstream of the Three Gorges Dam. Therefore, a theoretical model was established to test the direct and indirect effects. Empirically, results show that the direct effect of manufacturing agglomeration on the quality of water ecological environment is −0.426, which provides statistical evidence for the important role of manufacturing agglomeration in improving the quality of water ecological environment. The indirect effect of manufacturing agglomeration on ammonia nitrogen (NH3-N) is 0.118% through technological innovation, the indirect effect on NH3-N is 0.114% through economic growth, and the indirect effect on NH3-N is 0.254% through industrial structure. Due to the low overall level of the manufacturing industry and its reliance on dirty technologies, the indirect effects of industrial agglomeration are not conducive to improving the quality of the water ecological environment. Therefore, it is necessary to establish a long-term mechanism to promote the evolution of the regional economy along a path that is conducive to the improvement of the water ecological environment.

Spatiotemporal change characteristics and differences of manufacturing industry agglomeration in the Beijing-Tianjin-Hebei region

Spatiotemporal change characteristics and differences of manufacturing industry agglomeration in the Beijing-Tianjin-Hebei region