Spatial-temporal differentiation of high-quality industrial development level in the Yellow River Basin based on ecological total factor productivity

Ju, Hong; Li, Tongsheng; ZHAI, Zhouyan

doi:10.18402/resci.2020.06.08

Cited by 3 publications

(4 citation statements)

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“…It was found that the high values of land use benefits in the Yellow River Basin were concentrated in the nationally approved urban agglomerations such as the Central Plains, Guanzhong, hubao'e, and Shandong Peninsula. As the focus areas of economic development, high-density population gathering areas, and key areas in the comprehensive treatment of environmental pollution and ecological protection [52], these urban agglomerations had a large proportion of cropland and built-up land, rapid economic development, dense population, and industry [53]. Their technological development levels were also higher than that of other regions.…”

Section: Spatial Difference Of Land Use Benefitmentioning

confidence: 99%

Comprehensive Evaluation of Land Use Benefit in the Yellow River Basin from 1995 to 2018

Chen

Zhang

et al. 2021

Land

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Land resources are the basis of human survival and development. Land use benefit is the embodiment of land input-output ability. As an important economic zone and ecological barrier in China, it is important to calculate the land productivity in the Yellow River Basin. Using the center of gravity model and other methods, this study evaluated the land use benefit of the Yellow River Basin from 1995 to 2018 based on the selected indicators of geographic grid-scale and analyzed the regional disparity. The results revealed that the comprehensive benefits, economic benefits, and social benefits of land use were on the rise, but the ecological benefits changed in volatility. Land circulation had a great impact on the change of land use benefits. So reasonable land transfer policy should be particularly significant for land use in the Yellow River Basin. In addition, there were obvious spatial differences and agglomeration effects in land use benefit. The high values of benefits were concentrated in urban groups, which showed that areas with better economic and social development had better land use benefits. To narrow land use benefits’ spatial differences between regions, the less developed areas deserve more preferential policies to improve their economic and social levels. Besides, ecological benefits are generally not high. Thus, the land policy in the Yellow River Basin should take ecological priority as the basic principle while considering economic factors.

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Section: Spatial Difference Of Land Use Benefitmentioning

confidence: 99%

Comprehensive Evaluation of Land Use Benefit in the Yellow River Basin from 1995 to 2018

Chen

Zhang

et al. 2021

Land

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“…Gansu, Guizhou, Heilongjiang, Henan, Hubei, Jilin, Ningxia, Qinghai, Shaanxi, Shandong, Shanxi, Sichuan, Xinjiang, Yunnan (14) High-Low Beijing, Chongqing, Guangdong, Liaoning, Inner Mongolia (5) https://doi.org/10.1371/journal.pone.0259845.t007…”

Section: Low-lowmentioning

confidence: 99%

“…The literature using total factor productivity as measurement standard include: Yang et al improved the method of Fare et al [12] by using the Global-Malmquist-Luenberger model and the fixed effect model [13]; Ju et al [14] using the super efficiency DEA and Malmquist index model to produce the ETFP (Ecological Total Factor Productivity) as the industrial development level of major cities and urban clustering in the Yellow River Basin; and Zhao and Gu [15] integrating total factor productivity, GVC economic status index and export technology complexity, and comparing China with the United States. Since this method covers limited dimensions and is unable to measure the high-quality development of industry comprehensively, other studies construct index systems taking account of: the Five Concepts of Development [16][17][18]; economic performance, technological innovation, green development, quality, brand, integration of industrialization and informatization and high-end development as in Jiang et al [19]; efficiency, structure optimization, innovation drive and mode transformation as in Li and Wang [20]; input and output, environment, innovation, market factor and government factor as in Han and Ren [21]; talent accumulation as in Fu and Chu [22]; and energy security as in Hou et al [23].…”

Section: Introductionmentioning

confidence: 99%

Measurement and spatiotemporal analysis of high-quality development of China’s industry

Yang

Ren

et al. 2021

PLoS ONE

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Background China’s economy has been transitioning from a phase of rapid growth to high-quality development. The high-quality development of industry is the foundation of a sustainable and healthy growth of national economy, and is of great significance to improve people’s living standards, and to meet people’s needs for a better life. Methods We develop an evaluation index system of high-quality development of industry from the perspectives of industrial benefit, innovation ability, coordination ability, green ability, opening ability and sharing ability. Based on a panel data of 30 provinces in China during 1999–2018, we evaluate the level of high-quality development of industry using the entropy-weight method and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method. Meanwhile we select six specific years and adopt the Natural Breaks method to classify the provinces according to their levels. At last, Moran’s I index is used to analyze the spatial correlation among the provinces. Results Opening ability and innovation ability are found to have greater impacts on industrial high-quality development than other indices, and their influence has been increasing in recent years. There are large spatial and temporal differences among different provinces. Municipalities and coastal provinces are found to be at constantly high levels. The levels in the central region dropped first and then increased, however it was the opposite in the western region. In the northeast region, the levels fluctuated greatly. Overall, the high-quality development of industry among China’s provinces shows positive spatial correlation. Most provinces in China are in High-High and Low-Low clustering States. The High-High clustering type is mainly distributed in the eastern region and the Low-Low clustering type is mainly distributed in the western and central regions. Conclusion (1) Innovation ability and open ability are the most important factors. (2) Green ability has not sufficiently contributed to China’s industrial development. (3) Regional and time evolution differences are significant. (4) There is a significant and stable spatial clustering effect in the high-quality development of industry among China’s provinces.

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“…Research on industrial agglomeration in the YRB is comparatively rare (Geng et al, 2020;Hu et al, 2021). In terms of industrial agglomeration in the YRB, using environmental total factor productivity (ETFP) as the measurement standard, Ju et al (2020) calculated and analyzed the industrial development level of major cities and urban agglomerations in the YRB from 2006 to 2016 via the super-efficiency data envelopment analysis (DEA) and Malmquist index models. Based on the measurement of the level and types of industrial structure transformation in provinces and regions in the YRB, Geng et al (2020) used econometric models to discuss the spatial and temporal characteristics of industrial structure transformation in cities and regions in the YRB and its response to spatial agglomeration models such as specialization and diversification.…”

Section: Introductionmentioning

confidence: 99%

The spatiotemporal effects and drivers of industrial agglomeration—A case study of counties in the Yellow River basin

Duan

Zhao

Zhang

et al. 2022

Front. Environ. Sci.

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While the research on industrial agglomeration has received more attention, there has been little research on its spatial effect and impact mechanism from the micro perspective. On the basis of the industrial cluster data of 600 counties in the Yellow River basin (YRB) from 2010 to 2020, this article investigates the spatial effect of industrial agglomeration in the YRB from the two aspects of time and space via center of gravity analysis and exploratory spatial data analysis and uses the spatial econometric method to research the drivers of county-level industrial agglomeration. The results reveal the following. During the study period, the industrial center of gravity in the YRB presented a moving tendency from east to west, and 2016 was an important turning point. The county-level industrial distribution in the YRB showed an unbalanced trend, but its unbalanced degree exhibited a weakening trend. In terms of the temporal dimension, the county-level industrial agglomeration degree in the YRB presented a significant downward trend and emerged an evolution process of “diffusion–agglomeration–re-diffusion.” Specifically, it gradually diffused from Shandong and Henan to southern Shanxi and Shaanxi. In the spatial dimension, the county-level industrial agglomeration in the YRB was found to have conspicuous spatial autocorrelation, and the spatial spillover effect was prominent. The number of counties with high–high cluster gradually increased and shifted to the west, while the number of counties with low–low agglomeration exhibited a decreasing trend. The degree of government intervention restrains county-level industrial agglomeration, while the external industry level, regional market demand, and urbanization level promote county-level industrial agglomeration. In terms of river basins, in the upstream, the degree of government intervention and industrial structure adjustment inhibit industrial agglomeration, while the regional market demand and urbanization level promote industrial agglomeration. In the midstream, the degree of government intervention inhibits industrial agglomeration, while the external industry level, regional market demand, and industrial structure adjustment promote industrial agglomeration. In the downstream, the external industry level and industrial structure adjustment restrain industrial agglomeration, while the regional market demand and urbanization level promote industrial agglomeration. The conclusions provide a significant reference for the industrial transformation and high-quality economic development of the YRB.

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Spatial-temporal differentiation of high-quality industrial development level in the Yellow River Basin based on ecological total factor productivity

Cited by 3 publications

References 0 publications

Comprehensive Evaluation of Land Use Benefit in the Yellow River Basin from 1995 to 2018

Comprehensive Evaluation of Land Use Benefit in the Yellow River Basin from 1995 to 2018

Measurement and spatiotemporal analysis of high-quality development of China’s industry

The spatiotemporal effects and drivers of industrial agglomeration—A case study of counties in the Yellow River basin

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