JOURNAL ARTICLE
Exploring the Patent Collaboration Network of Bioenergy Technology: Evidence from Provinces along the Belt and Road in China.
Published In: International Journal of Innovation & Technology Management, 2024, v. 21, n. 1. P. 1 1 of 3
Database: Business Source Ultimate 2 of 3
Authored By: Liu, Weiwei; Li, Fangye; Bi, Kexin 3 of 3
Abstract
Bioenergy is a significant renewable energy source with great potential for addressing global environmental challenges. This study aims to construct and analyze the patent collaboration network of bioenergy in Chinese provinces along the Belt and Road (BR) initiative. By collecting and analyzing co-patents from the China National Intellectual Property Administration (CNIPA) between 1993 and 2017, this research investigates the network's structure, evolution, and the provincial differences in bioenergy technology development. The results reveal an increasing number of co-patents since 2006. I-I, E-E, E-R, and E-U are common types of collaboration, and this paper believes that E-E will be the most important type in the future. The network is relatively sparse and in its early development stage. However, the cohesion of the network is gradually increasing, and it has good development potential. From the perspective of IPC, the scope of patents for bioenergy is relatively narrow, and the breadth and depth of research need to be improved. Moreover, the study highlights Guangdong as a promising province for bioenergy and emphasizes the close collaboration between provinces along the Belt and Road and those not along it, such as Guangdong and Jiangsu. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:International Journal of Innovation & Technology Management. 2024/02, Vol. 21, Issue 1, p1
- Document Type:Article
- Subject Area:Science
- Publication Date:2024
- ISSN:0219-8770
- DOI:10.1142/S021987702450007X
- Accession Number:175573034
- Copyright Statement:Copyright of International Journal of Innovation & Technology Management is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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