We used cluster analysis to build the SGCC’s co-publications networks and compare these results with its patent portfolio co-ownership. The SGCC’s publications11 were retrieved from the Web of Science and applied and granted patents from the Derwent Innovation databases.
As in the previous chapters of this section, we proxied innovation networks by constructing co-publications’ network maps. To that end, we performed a cluster analysis of SGCC’s co-authors’ affiliations to map the institutions that are more frequently publishing with SGCC. If SGCC is an intellectual monopoly, it should build innovation networks integrated by multiple organizations, and be capable of capturing most of their potential intellectual rents. Hence, it would not share most of the ownership of resulting patents neglecting the role of other participating organizations. This may be the case of universities because the SGCC’s innovation strategy has heavily relied on them (Yi-chong, 2017, Chapter 7).
We retrieved every SGCC’s publication until 2018 included (4,192 publications). This corpus was split into two periods (2003-10 and 2011-18) to have a sense of the evolution of SGCC’s innovation networks. Data were processed with the CorText platform. We built co-occurrence maps12 that associated SGCC and its co-authors according to their frequency of cooccurrence. To draw these maps, we followed the work of Tancoigne et al. (2014), including their proposed methodology for corpuses cleaning. Nodes sizes represented co-authorship frequency with SGCC. To focus on the SGCC’s innovation networks - thus its systematically privileged partners -, we prioritized the top 101 research organizations for each period (SGCC plus its top 100 partnering organizations). In the first period, SGCC coauthored papers with only 79 institutions. The corresponding map depicts only the 76 institutions that surpassed a minimum proximity threshold (0.1). Overall, these network analyses provided information on: (i) the variety of stakeholders, (ii) their place in the SGCC’s innovation networks, and (iii) the geographic scope of the SGCC’s innovation networks.
In addition, to provide evidence on the topics being researched by the SGCC’s different innovation networks, each one proxied as a cluster on its co-publications’ network map, we also plotted for each cluster its most frequent research fields.
To determine to what extent SGCC shared potential intellectual rents with the organizations that participate in its innovation networks, we retrieved and analysed the SGCC’s applied and granted patents from every patent office until and including 2017 (122,296 records). Our access to Derwent Innovation provided access to 25 different patent offices. However, in the SGCC corpus, 99% (120,937) of applied and granted patents corresponded to the China National Intellectual Property Administration, followed by WIPO (758, representing 0.62%) and USPTO (295, representing 0.24%). We will further discuss these figures later.
We compared results between both data sets in terms of the SGCC’s partners and their countries of origin. Results are presented and discussed in the next section.
SGCC: on the way to becoming a transnational intellectual monopoly
SGCC’s scientific publications
We analyse the SGCC’s co-publications’ network as a proxy of its corporate innovation system integrated by multiple innovation networks. It shows that while the SGCC’s innovation networks initially relied mostly on local actors (Figure 9.2), in the more recent period, they are expanding beyond China (Figure 9.3) (foreign organizations are highlighted with a rectangle in both figures). By building diverse innovation networks, SGCC was also complying with Chinese government policies. In 2009, the central government launched the Technological Innovation Project, which fostered strategic
Figure 9.2 Network map. SGCC scientific publications’ co-authorships (2003-10). Source: Author’s analysis based on Web of Science data extraction.
Figure 9.3 Network map. SGCC scientific publications’ co-authorships (2011-18). Source: Author’s analysis based on Web of Science data extraction.
alliances and technological cooperation with universities and other research institutions (Yi-chong, 2017, Chapter 7).
In the first period (2003-10), SGCC was connected to 12 foreign institutions, including two multinationals (Siemens and Areva) and ten universities. These institutions came from seven different countries and represented 16% of the SGCC’s partners. In the second period (2011-18), the number of foreign institutions among its top co-authors grew to 26 (117% increase), all of them are universities, from ten different countries. These results show that, over time, SGCC is broadening its innovation networks beyond China, not only to closer countries but also to core Western countries. Beyond the direct establishment of partnerships with foreign universities and those collaborations that initially took place connected by a Chinese university or PRO, another mechanism that has also contributed to expanding the SGCC’s innovation network was its Foreign Direct Investment strategy. As it purchases other countries’ local companies that have established collaboration with local universities, SGCC inherits those collaborations.
For instance, when SGCC bought a controlling stake in CPFL Energia, Brazil’s largest power distributor, the latter already had R&D cooperation with the University of Campinas. SGCC inherited this link.13
Besides SGCC, in both periods, some institutions occupy bridging positions in the network. The Chinese Academy of Science connects its cluster with that of SGCC and with other Chinese institutions’ clusters. Shandong University has also been a key partner for SGCC in a twofold way: as a co-author of 8.6% of SGCC’s papers, and as a bridging institution, among others connecting SGCC with two clusters with foreign institutions in each period. As explained by Choi et al. (2011, p. 768), “(b)ridging organizations promote new connections to catalyse information flows and to create innovation opportunities”. Even some foreign universities became bridging institutions in the second period, such as the Technical University of Dortmund connecting SGCC with Oak Ridge National Laboratory, the University of Texas and Washington University.
A difference between periods is that the total number of research institutions co-authoring with SGCC went from 79 to 864. This, in part, responded to the general increase of the SGCC’s R&D reflected in its publications’ growth (see Figure 9.1 in Section 3), but it also shows an expansion of its innovation networks. Additionally, between 2011 and 2018, there is no single institution co-authoring more than 8.5% of the SGCC’s papers. In contrast, in the first period, its two main partners - Shandong University and Wuhan University-co-authored 14.8% and 13.9%, respectively. This happened even if total publications with these institutions increased around ten times. Hence, they are less important in relation to the whole set of the SGCC’s co-authors but not in absolute terms. Being less dependent on single institutions is a sign of the larger scope of the SGCC’s innovation networks within and beyond China. It also contributes to reduce the influence that a single organization can exercise over the content and distribution of profits from the research projects undertaken by SGCC, thus potentially strengthening its intellectual monopoly.
A final aspect to consider in the comparison between both periods is the place of Siemens and Areva. Their joint publications with SGCC refer to general power supply technologies, thus not related to the SGCC’s main innovative aims. Considering also that they disappear from top partners and in line with Yi-chong (2012, Chapter 6) and Yi-chong (2017, Chapter 7), we consider these publications as the result of technical assistance provided by Siemens and Areva. Different multinationals were initially contacted by SGCC to develop new core technologies for UHV DC lines. However, these corporations wanted to keep the property of resulting patents. Hence, SGCC committed to innovating in UHV DC lines without them. It succeeded two years later (Yi-chong, 2017, Chapter 7). This experience is evidence of wannabe intellectual monopolies as still not prepared to establish technological cooperation with already incepted intellectual monopolies. By rejecting their offers, SGCC won the chance to become itself an intellectual monopoly.
The whole publications’ corpus also evidences strong state support. Thirty percent of the SGCC’s publications declared being funded by the National Natural Science Foundation of China, which was the SGCC’s most frequently declared funding source, and 7% enjoyed funds from China’s National Key Technology Research and Development Program. Other less frequent Chinese state funding sources declared in the SGCC’s publications were the “National Program for Science and Technology 863” (5%) and the “National Basic Research Program of China 973” (4%).
Finally, the variety of fields covered by the SGCC’s publications, especially in the second period where it even researched medical topics, is reflected in the diversity of clusters’ most frequent topics. The SGCC’s publications corroborate its continuous multi-technology and multi-product strategy, as it was observed for the cases of Amazon and Apple in the two previous chapters. Moreover, it is quite clear that the second period becomes more aligned to ecological transition matters with the SGCC’s central cluster dealing with environmental and ecological research and other clusters focusing on water resources.
All in all, SGCC seems to be relying on its national innovation system to develop more transnational innovation networks on topics aligned to the ecological transition. Still, this transnationalization is not as developed as in recognized global intellectual monopolies; and considering China’s specificities, it may never be. For instance, Roche and Novartis have less than 5% of its top 150 co-authors in Switzerland, whilst Pfizer (originally from the United States where this industry’s innovations mostly take place) has around 50% of its top 150 co-authors in the United States (Rikap, 2019).