Impact and threshold effect of Internet technology upgrade on forestry green total factor productivity: Evidence from China

Lin, Wu; Zhang, Zhiguang

doi:10.1016/j.jclepro.2020.122657

Cited by 63 publications

(41 citation statements)

References 9 publications

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“…According to the above research, we find some interesting phenomena: Firstly, in 2008 to 2017, the development focus of forestry industry gradually shifted from the eastern China to the central and western, which shows the transfer of total factor productivity (TFP) and technical efficiency change (EC) of forestry industry. However, it is worth mentioning that the areas with high efficiency of technical progress (TC) are still mainly concentrated in Shanghai, Jiangsu, Fuzhou and other eastern regions, which is also consistent with the research of Wu and Zhang 39 . In addition to giving full play to its own resource advantages, promoting the technological progress of forestry industry in the central and western regions is also a key factor for its industrial development 20 .…”

Section: Resultssupporting

confidence: 78%

The effect of total factor productivity of forestry industry on CO2 emissions: a spatial econometric analysis of China

Zhong

Wang

2021

Sci Rep

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Forestry plays an essential role in reducing CO2 emissions and promoting green and sustainable development. This paper estimates the CO2 emissions of 30 provinces in China from 2008 to 2017, and uses Global DEA-Malmquist to measure the total factor productivity of the forestry industry and its decomposition index. On this basis, by constructing a spatial econometric model, this paper aims to empirically study the impact of forestry industry's total factor productivity and its decomposition index on CO2 emissions, and further analyze its direct, indirect and total effects. The study finds that the impact of forestry industry's total factor productivity on CO2 emissions shows an "inverted U-shaped" curve and the inflection point is 0.9395. The spatial spillover effect of CO2 emissions is significantly negative. The increase of CO2 emissions in adjacent areas will provide a "negative case" for the region, so that the region can better address its own energy conservation and emission reduction goals. TFP of forestry industry also has positive spatial spillover effect. However, considering the particularity of forestry industry, this effect is not very significant. For other factors, such as foreign direct investment, urbanization level, industrial structure and technology market turnover will also significantly affect regional CO2 emissions.

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Section: Resultssupporting

confidence: 78%

The effect of total factor productivity of forestry industry on CO2 emissions: a spatial econometric analysis of China

Zhong

Wang

2021

Sci Rep

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“…Whether digital economy can promote green development is controversial at present, with most scholars believing that digital economy promotes green development. Wu and Zhang [17] found that China's technological Internet and platform Internet have significantly improved the green total factor productivity of forestry in the short term. As the Chinese government speeds up the 'Internet+' development plan, the integrative development of energy and Internet has become a new way of green urban development.…”

Section: Literature Reviewmentioning

confidence: 99%

The Impact of Digital Economy on Industrial Carbon Emission Efficiency: Evidence from Chinese Provincial Data

Xie

Zhang

2022

Mathematical Problems in Engineering

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Digital economy has become an important driving force for green economic growth in China. Based on the province-level data of China from 2003 to 2018, this paper constructed the Total-factor Nonradial Directional Distance Function (TNDDF) model to measure the carbon emission efficiency of industrial sector and discussed the impact of digital economy on carbon emission efficiency. Empirical analysis shows that the carbon emission efficiency of China’s industrial sector is low, and there is obvious regional heterogeneity where the carbon emission efficiency of eastern China is higher than that of central and western China. Areas with high level of digital economy development have higher carbon emission efficiency, and digital economy is conducive to promoting energy conservation and pollution reduction in China’s industrial sector. The optimal threshold interval of digital economy for promoting carbon emission efficiency is explored by means of threshold model. In view of this, the Chinese government should vigorously develop the digital economy, promote industrial enterprises to networking and digital evolution, and improve the efficiency of carbon emission as well.

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“…This paper mainly studies the influence of green credit policy on the green transformation and upgrading of heavy pollution enterprises, and the green transformation and upgrading of enterprises is the dependent variable of this paper. Some scholars ( Shi and Li, 2019 ; Wu et al, 2020 ; Xia and Xu, 2020 ) study green total factor productivity ( Gtfp ), but all focus on the macro level and green innovation ( Wu and Zhang, 2020 ; Fang et al, 2021 ; Wang et al, 2021 ). Gtfp integrated assessment of changes in social welfare and economic development performance ( Cao et al, 2021 ).…”

Section: Methodsmentioning

confidence: 99%

Green credit and enterprise green operation: Based on the perspective of enterprise green transformation

Niu

Zhao²,

Luo³

et al. 2022

Front. Psychol.

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This paper uses panel data of listed heavily polluting enterprises from 2007 to 2021, based on the perspective of transformation and upgrading of heavy polluters, innovatively studies the impact of green credit on the green operation of enterprises. At the micro level, the research results of this paper verify the effectiveness of green credit policy on the transformation of green enterprises. It is also found that the two intermediary paths of debt cost and government subsidy play a partial intermediary role in the process of green credit promoting green enterprise transformation and upgrading. Green credit policy also moderates the green transformation of enterprises through debt cost and government subsidies. Based on the research results, this paper puts forward targeted policy suggestions from the aspects of financing constraints, government subsidy policies, enterprise technological innovation and green operation, and provides empirical support for the current expansion of green credit policies in China.

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Impact and threshold effect of Internet technology upgrade on forestry green total factor productivity: Evidence from China

Cited by 63 publications

References 9 publications

The effect of total factor productivity of forestry industry on CO2 emissions: a spatial econometric analysis of China

The effect of total factor productivity of forestry industry on CO2 emissions: a spatial econometric analysis of China

The Impact of Digital Economy on Industrial Carbon Emission Efficiency: Evidence from Chinese Provincial Data

Green credit and enterprise green operation: Based on the perspective of enterprise green transformation

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