Measurement and spatial statistical analysis of green science and technology innovation efficiency among Chinese Provinces

Wu, Mingran

doi:10.1007/s10651-021-00491-7

Cited by 23 publications

(10 citation statements)

References 10 publications

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“…Wu MR measured the green technology innovation efficiency of 30 provinces in China from 2008 to 2017 by constructing a three-stage super-efficiency DEA model including undesired output. e study found that the overall performance of regional green technology innovation efficiency in China was poor in the past decade, and there was still a lot of room for improvement [19]. In addition, other methods such as cluster analysis, technique for order preference by similarity to an ideal solution model, and translogarithmic random boundary analysis model are also shown in the literature about green economic efficiency [20][21][22][23][24][25][26].…”

Section: Literature Reviewmentioning

confidence: 99%

[Retracted] How to Evaluate the Efficiency of Green Economy and Its Regional Differences: Evidence from China

Duan

Tang

Kui

2022

Discrete Dynamics in Nature and Society

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Green economy is environmentally friendly economy, which is important for the sustainable economic development and environmental protection. Based on the panel data of 30 provinces and cities in China, a three-stage super-efficient SBM-DEA (slack-based model-data envelopment analysis) model is constructed to evaluate the efficiency of green economy and analyze its regional differences. The results show that, first, the random error factor and external environmental conditions significantly affect the efficiency of green economy. Second, the green economic efficiency in China from 2010 to 2019 is stable and needs to be further improved. Third, through regional comparison, it is found that the green economy efficiency in eastern China is higher than those in central and western China and the green economy efficiency in northeast China is the lowest. Finally, green economy efficiency does not simply depend on the economic development, the regional differences of green economy efficiency results from the combined effects of different geographical resources endowment, different economic development characteristics, and different environmental protection policies in different regions of China. Based on the research findings, corresponding policy suggestions are put forward to improve the efficiency of green economy.

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Section: Literature Reviewmentioning

confidence: 99%

[Retracted] How to Evaluate the Efficiency of Green Economy and Its Regional Differences: Evidence from China

Duan

Tang

Kui

2022

Discrete Dynamics in Nature and Society

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“…In (13), is the spherical distance between two provincial capitals, R is the radius of the earth, (θ 1 , ϕ 1 ) is the latitude and longitude of the provincial capital of region i, and (θ 2 , ϕ 2 ) is the latitude and longitude of the provincial capital of region j.…”

Section: Methodsmentioning

confidence: 99%

“…Ordering T(W) = (I N − ρW) −1 and C M (W) = T(W)•(I N ψ M + θ M W), (13) can be simplified to the following by multiplying both sides by T(W):…”

Section: Methodsmentioning

confidence: 99%

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Causes and Evolution Characteristics of Green Innovation Efficiency Loss: The Perspective of Factor Mismatch under Local Government Competition

2022

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The objective of this paper is to measure the efficiency loss of green innovation caused by local government competition and explore its causes and evolution characteristics. Based on the equimarginal principles such as the deviation of the allocation of green innovation output factors, this paper uses the panel data of China’s provinces (excluding Tibet, Hong Kong, Macao and Taiwan) from 2000 to 2020 and employs the spatial panel measurement model and the Kernel density estimation. The study finds that first, local government competition causes the mismatch of local innovation factors not only locally but also in neighboring regions. Second, the mismatch of innovative talents and capital caused by local government competition lowers the green innovation efficiency. Third, the shortage of innovative talents caused by local government competition is the main reason for the loss of green innovation efficiency in Beijing, Tianjin, and Shanghai. Fourth, the degree of efficiency loss of green innovation at the provincial level in China is heterogeneous in government competition strategies, and the loss due to tax competition is the most significant. Fifth, although the loss of green innovation efficiency generally decreases yearly, in the future, the institutional competition will still hinder the improvement of green innovation efficiency in the eastern, central and western regions of China. Our policy suggestions include promoting regional cooperation and cultivating innovative talents to further improve the efficiency of green innovation.

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“…However, scholars believe that the next focus must be on management practices (Adu & Kumarasamy, 2020). They think that the new industrialization mode emphasizes the high efficiency and sustainable utilization of resources through the enhancement of management ability, so that industry development will change from resource-consuming to technology-oriented, including the establishment of scientific and technological innovation system (Wu, 2021), vigorously develop circular economy (Wang & Feng, 2018), formulate and improve laws and regulations (Kuznetsov & Kuznetsova, 2019), explore new regional development pattern , etc. Since the reform and opening-up, China's industrial economy has experienced several rounds of rapid growth and has now formed a mature system that is in a period of transformation, rising with great potential.…”

Section: Introductionmentioning

confidence: 99%

Archives of Environmental Protection

Wu¹,

Huang²

2022

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Based on China's provincial panel data from 2009 to 2019, this paper empirically tests and analyzes the effects of industrial agglomeration and other important economic variables on industrial green technology innovation efficiency from the perspective of spatial statistical analysis. The results show that the efficiency of China's industrial green innovation has not changed much during the study period, exhibiting an obvious polarization phenomenon. Moreover, the improvement of the degree of industrial agglomeration is conducive to the regional green innovation efficiency level. This means that industrial agglomeration produces effective environmental and innovation benefits. In addition, the influence coefficient of enterprise-scale is negative, indicating that for Chinese industrial enterprises, the enlargement of the production scale weakens the promotion effect of R&D activities. The influence coefficient of human capital is negative, mainly because the direct effect has a small and positive value, while the indirect effect (spillover effect) has a negative and large value, indicating that the spillover effect of human capital between regions in China is deficient.

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Measurement and spatial statistical analysis of green science and technology innovation efficiency among Chinese Provinces

Cited by 23 publications

References 10 publications

[Retracted] How to Evaluate the Efficiency of Green Economy and Its Regional Differences: Evidence from China

[Retracted] How to Evaluate the Efficiency of Green Economy and Its Regional Differences: Evidence from China

Causes and Evolution Characteristics of Green Innovation Efficiency Loss: The Perspective of Factor Mismatch under Local Government Competition

Archives of Environmental Protection

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