The role of green innovations, environmental policies and carbon taxes in achieving the sustainable development goals of carbon neutrality

Wang, Xinyu; Khurshid, Adnan; Qayyum, Sumaira; Călin, Adrian Cantemir

doi:10.1007/s11356-021-16208-z

Cited by 52 publications

(11 citation statements)

References 68 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Wireless Communications and Mobile Computing relationship between green innovation and economic growth is analyzed by constructing a VAR model, etc. [17].…”

Section: Related Workmentioning

confidence: 99%

A Model-Driven Analysis of the Relationship between Innovation and Growth in a Green Low-Carbon Economy Based on Open Public Data

2022

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

In the new era, China’s economic development is in the offensive period of transforming the development mode, green development is an inevitable requirement to accelerate the transformation of economic development mode and optimize the industrial structure, and we should adhere to the concept of ecological priority and green development to promote high-quality economic development. The 19th Party Congress clearly proposed to “promote green development, establish a sound economic system of green low-carbon cycle development, and build a market-oriented green technology innovation system.” Green technology is the technology to save resources, reduce pollution, and achieve sustainable development. Green technology innovation continues to promote green development, which will become an important support to promote the progress of ecological civilization, adhere to pollution prevention and control, and promote high-quality development. Promoting green technology innovation, taking the road of sustainable development, enhancing the awareness of environmental protection, and promoting high-quality economic development are also inevitable choices to promote the conversion of economic development mode. Carrying out research on the impact of green technological innovation on regional economic growth is of great significance to alleviate the shortage of innovation resources in China, guide enterprises to change to a green way of development, and promote the sustainable development of China’s economy and population, resources, and environment. This paper provides publicly available data from 2015-2021, takes fixed asset investment as the variable, introduces control variables, and analyzes the relationship between technological innovation and economic growth using fixed-effects model and intermediate-effects model. The results show that innovation contributes significantly to regional economic growth and is influenced by the mediating role of fixed asset investment. In order to boost China’s economic growth, specific policy recommendations are proposed in terms of optimizing the regional innovation layout, improving the intellectual property rights system, cultivating high-quality talents, optimizing the structure of fixed assets, and attracting the inflow of foreign capital.

show abstract

“…Wireless Communications and Mobile Computing relationship between green innovation and economic growth is analyzed by constructing a VAR model, etc. [17].…”

Section: Related Workmentioning

confidence: 99%

A Model-Driven Analysis of the Relationship between Innovation and Growth in a Green Low-Carbon Economy Based on Open Public Data

2022

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

show abstract

“…In the fourth global climate assessment, the Intergovernmental Panel on Climate Change (IPCC) pointed out that human activities and greenhouse gas emissions are the main causes of global warming [3]. Therefore, reduction in greenhouse gas emissions has become an important mission for all humankind to cope with the challenge of global warming, and countries around the world have dedicated numerous efforts to achieving this [4,5].…”

Section: Introductionmentioning

confidence: 99%

The Carbon Emission Reduction Effect of Tourism Economy and Its Formation Mechanism: An Empirical Study of China’s 92 Tourism-Dependent Cities

Tong

Zhang

2022

IJERPH

View full text Add to dashboard Cite

The tourism economy is regarded as an effective way to realize regional sustainable development. Hence, it is of great significance to explore whether and how tourism economy can alleviate regional carbon emission intensity. To this end, a structural equation model (SEM) reflecting the multiple pathways of the carbon emission reduction effect of tourism economy was constructed based on 92 tourism-dependent cities in China, and the existence and formation mechanism of the carbon emission reduction effect of tourism economy were empirically tested. The main findings are as follows: (1) The tourism economy has a significant carbon emission reduction effect in China. Although the direct impact of tourism economy on carbon emission intensity is significantly positive, the indirect impact is significantly negative and stronger than the direct impact. (2) The carbon emission reduction effect of tourism economy presents multiple pathways characteristics. There are single intermediary pathways such as Tourism Economy → Environmental Regulation → Carbon Emission Intensity, Tourism Economy → Opening-Up → Carbon Emission Intensity, and dual intermediary pathways such as Tourism Economy → Opening-Up → Industrial Development → Carbon Emission Intensity, Tourism Economy → Opening-Up → Innovation Capacity → Carbon Emission Intensity. (3) The formation mechanism of the carbon emission reduction effect of tourism economy presents obvious spatial heterogeneity.

show abstract

“…Prior empirical data has shown that special prices react nonlinearly to price changes and that bidirectional causality pricing exists [44], [45]. This link was confirmed further [46]- [48].…”

Section: Iiliterature Reviewmentioning

confidence: 56%

Comparison of Machine Learning Algorithms for Predicting Diamond Prices Based on Exploratory Data Analysis

Basysyar¹,

Dwilestari²

2022

IJEAST

View full text Add to dashboard Cite

Diamonds are a unique commodity whose socially generated notions significantly influence perceived value. To study how a diamond's physical attributes might predict its price, a massive dataset of loose diamonds scraped from an online diamond store is subjected to data mining, which reveals that diamond weight, color, and clarity are the most influential determinants of diamond pricing. Therefore, submit a proposal for an Exploratory Data Analysis that includes a component that analyses various parts of news articles using LASSO Regression, ElasticNet Regression, and Random Forest Regression. This system is trained on past data to forecast diamond prices while retaining an easily interpretable trading approach concerning rule complexity. The suggested strategy beats cutting-edge methods for prediction accuracy and interpretability, such as extreme learning machines using deep learning. Our data indicate that the news impact factor is crucial for forecasting. Demonstrate that the suggested system outperforms the average yearly return while offering a set of language trading rules that are interpretable. This has substantial repercussions for investors. A significant degree of subjectivity in diamond pricing may result from diamond dealers' price concealment techniques.

show abstract

The role of green innovations, environmental policies and carbon taxes in achieving the sustainable development goals of carbon neutrality

Cited by 52 publications

References 68 publications

A Model-Driven Analysis of the Relationship between Innovation and Growth in a Green Low-Carbon Economy Based on Open Public Data

A Model-Driven Analysis of the Relationship between Innovation and Growth in a Green Low-Carbon Economy Based on Open Public Data

The Carbon Emission Reduction Effect of Tourism Economy and Its Formation Mechanism: An Empirical Study of China’s 92 Tourism-Dependent Cities

Comparison of Machine Learning Algorithms for Predicting Diamond Prices Based on Exploratory Data Analysis

Contact Info

Product

Resources

About