Investigate the role of technology innovation and renewable energy in reducing transport sector <scp>CO<sub>2</sub></scp> emission in China: A path toward sustainable development
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- Danish I. Godil
- Business Studies Department, Bahria Business School Bahria University Karachi Campus Karachi Pakistan
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- Zhang Yu
- School of Economics and Management Chang'an University Xi'an China
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- Arshian Sharif
- Othman Yeop Abdullah Graduate School of Business Universiti Utara Malaysia Malaysia
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- Rimsha Usman
- Business Studies Department, Bahria Business School Bahria University Karachi Campus Karachi Pakistan
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- Syed Abdul Rehman Khan
- School of Management and Engineering Xuzhou University of Technology Xuzhou China
書誌事項
- 公開日
- 2021-02-03
- 権利情報
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- http://onlinelibrary.wiley.com/termsAndConditions#vor
- DOI
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- 10.1002/sd.2167
- 公開者
- Wiley
この論文をさがす
説明
<jats:title>Abstract</jats:title><jats:p>The objective of this research is to examine the role of economic growth, technology innovation, and renewable energy in reducing transport sector CO<jats:sub>2</jats:sub> emission in China by using the annual data of 1990–2018. An application of the QARDL approach discloses that economic growth, technology innovation, and renewable energy significantly influence CO<jats:sub>2</jats:sub> emission in the transportation sector in China. Both renewable energy consumption and innovation show a negative impact on emissions of CO<jats:sub>2</jats:sub> related to transport. It depicts that due to the increase in renewable energy and innovation, the CO<jats:sub>2</jats:sub> emission in the transport sector is likely to decrease; however, an increase in the GDP of a country will upsurge the emission of CO<jats:sub>2</jats:sub> in the transportation sector. However, China should make new policies to introduce innovation in the transportation sector to minimize the emission of CO<jats:sub>2</jats:sub>.</jats:p>
収録刊行物
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- Sustainable Development
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Sustainable Development 29 (4), 694-707, 2021-02-03
Wiley
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詳細情報 詳細情報について
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- CRID
- 1360302870945199488
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- DOI
- 10.1002/sd.2167
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- ISSN
- 10991719
- 09680802
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- データソース種別
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- Crossref

