Comparing the International Knowledge Flow of China’s Wind and Solar Photovoltaic (PV) Industries: Patent Analysis and Implications for Sustainable Development

Abstract

Climate-relevant technologies, like wind and solar energy, are crucial for mitigating climate change and for achieving sustainable development. Recent literature argues that Chinese solar firms play more active roles in international knowledge flows, which may better explain their success in international markets when compared to those of Chinese wind firms; however, empirical evidence remains sparse. This study aims to explore to what extent and how do the international knowledge flows differ between China's wind and solar photovoltaic (PV) industries? From a network perspective, this paper develops a three-dimensional framework to compare the knowledge flows in both explicit and tacit dimensions: (i) inter-country explicit knowledge clusters (by topological clustering of patent citation network); (ii) inter-firm explicit knowledge flow (patent citation network of key firms); and, (iii) inter-firm tacit knowledge flow (by desktop research and interviews). The results show that China's PV industry has stronger international knowledge linkages in terms of knowledge clustering and explicit knowledge flow, but the wind power industry has a stronger tacit knowledge flow. Further, this study argues that the differences of global knowledge links between China's wind and solar PV industries may be caused by technology characteristics, market orientation, and policy implementation. This suggests that these industries both have strong connections to global knowledge networks, but they may involve disparate catch-up pathways that concern follower-modes and leader-modes. These findings are important to help us understand how China can follow sustainable development pathways in the light of climate change.

How Knowledge Acquisition Diversity Affects Innovation Performance during the Technological Catch-Up in Emerging Economies: A Moderated Inverse U-Shape Relationship

“…These studies have considerably advanced our understanding of domestic enterprises' choice of technology sourcing channels. However, the anecdotal evidence also highlights that domestic enterprises develop their technology capability using a combination of technology sourcing channels [17,18,34]. Different types of technology sourcing channels are appropriate in different situations, such as the attributes of the technology being pursued and the degree of technical change and uncertainty [24,34,35].…”

“…However, the anecdotal evidence also highlights that domestic enterprises develop their technology capability using a combination of technology sourcing channels [17,18,34]. Different types of technology sourcing channels are appropriate in different situations, such as the attributes of the technology being pursued and the degree of technical change and uncertainty [24,34,35]. For example, Zhou, Pan, and Urban (2018) found that technology sourcing channels such as equipment acquisition and knowledge transfer from other manufactures take a very different form in China's solar PV sector than the wind energy sector [34].…”

“…Different types of technology sourcing channels are appropriate in different situations, such as the attributes of the technology being pursued and the degree of technical change and uncertainty [24,34,35]. For example, Zhou, Pan, and Urban (2018) found that technology sourcing channels such as equipment acquisition and knowledge transfer from other manufactures take a very different form in China's solar PV sector than the wind energy sector [34]. Van de Vrande, Vanhaverbeke, and Duysters (2009) found that the benefits of using a particular type of external technology sourcing are contingent on environmental turbulence, emerging technologies, and the technological distance between partners [24].…”

Exploring the Future Development of Research, Technology and Business of Machine Tool Domain in New-Generation Information Technology Environment Based on Machine Learning

“…Scientific literatures have been considered as a valuable and rich source of knowledge or a key proxy about technology development, reflecting the current technological focuses in their respective disciplines and the trend of technology development in both theory and practice [14,15]. Bibliometric or patent analysis method have been widely employed by many researchers to analyze scientific literatures quantitatively, which was regarded as a more systematic, objective, and effective method compared to qualitative literature review approach to explore the evolution trend of specific discipline [16][17][18][19]. For example Ernst analyzed the patent data in the machine tool industry to explore the future development trend of CNC technology [20].…”

A novel method to identify emerging technologies using a semi-supervised topic clustering model: a case of 3D printing industry

“…We refer to these methods, collectively, as technological topic segmentation in this paper. These literatures usually use word/citation-based methods that include topic trends (Watts and Porter 2003;Guo et al 2011;De Rassenfosse et al 2013), co-word (Furukawa et al 2015) or term-clumping (Zhang et al 2014), citation or co-citations (Leydesdorff and Rafols 2009;Zhou et al 2019;Kajikawa and Takeda 2008;Shibata et al 2011;Cho and Shih 2011;Kong et al 2017;Zhou et al 2016Zhou et al , 2018, and combinations of these methods (Zhang et al 2010;Wang et al 2018b;Small et al 2014;Breitzman and Thomas 2015). However, these methods have some limitations, depicted as follows: (1) The methods are word-or citation-based, and they have limited capability to utilize the semantic information that is embedded in the publications and patents.…”