The evolution of government sponsored collaboration network and its impact on innovation: A bibliometric analysis in the Chinese solar PV sector

Liang, Xinning; Liu, Anita M. M.

doi:10.1016/j.respol.2018.04.012

Cited by 82 publications

(58 citation statements)

References 61 publications

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“…To examine result sensitivity, we perform two robustness checks (see Appendix B for details in ). First, to avoid potential endogeneity problems, a one‐year time window is lagged, expecting that the output effects of independent and control variables will occur after one year (Liang & Liu, 2018) or more. Second, we carry out a robustness check on a subsample of universities.…”

Section: Resultsmentioning

confidence: 99%

Open innovation and innovative performance of universities: Evidence from China

Zeng

Cao

2020

Growth and Change

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University–industry interactions have been extensively discussed by economic geographers. However, while universities increasingly engage in local and nonlocal interactions with the industry, there is a lack of evidence concerning the consequences of universities becoming involved in these open innovation processes. Therefore, this study empirically examines the effects of local and nonlocal knowledge interactions on the innovative performance of universities by utilizing a large panel database constructed from a sample of 185 universities in China. First, we observe that both local and nonlocal interactions have an inverted U‐shaped relationship with university innovative performance. Second, local interactions combined with nonlocal interactions have a negative effect on the innovative performance of universities. Finally, we find that a balance is required between local and nonlocal interactions to enhance university performance. These results have important implications for policy design.

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Section: Resultsmentioning

confidence: 99%

Open innovation and innovative performance of universities: Evidence from China

Zeng

Cao

2020

Growth and Change

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“…In addition, since the application date represents the earliest point when new firm capabilities can be identified [12] and is a more accurate representation of the date of firm innovation [14], we use the patent applications to measure innovation performance. Therefore, in this study, firm innovation performance is measured as the annual number of successful patent applications by a firm [56,57]. Besides, we also adopt an alternative measurement for innovation performance when performing robustness checks.…”

Section: Dependent Variablementioning

confidence: 99%

The Impact of Industry–University–Research Alliance Portfolio Diversity on Firm Innovation: Evidence from Chinese Manufacturing Firms

Zhang¹,

Yuan²,

Wang³

2019

Sustainability

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Innovation is a key factor for the sustainable development of firms. Although it has been a prevalent phenomenon that firms maintain multiple industry–university–research (I–U–R) alliances simultaneously to generate innovation, there is a lack of explorations in this phenomenon in extant literature. In this study, we introduce a new construct, I–U–R alliance portfolio, and investigate the impact of its diversity on a focal firm’s innovation performance. Hypotheses are proposed and examined using datasets of 176 listed firms in the Chinese manufacturing industry. We find that I–U–R alliance portfolio diversity exerts a positive effect on a focal firm’s innovation performance and a firm’s absorptive capacity positively moderates this relationship. Furthermore, we contend that with increasing levels of government financial support, the positive relationship between I–U–R alliance portfolio diversity and firm innovation performance is strengthened. Finally, our findings provide several theoretical and practical implications for the I–U–R alliance portfolio and firm innovation.

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“…For catch-up nations like China, universities are the main sources of knowledge, they are funded by government, so that their R&D abilities are much powerful than companies. In fact, it is not a bad thing like some scholars said [64], because enterprises have got progress with the help of universities; on the other hand, we discover that geographical proximity is the initial energy of innovation evolution, cognitive proximity puts a positive effect on it, and organizational proximity is the motivation in rapid development stage. Guangzhou's biological industry is weak at the budding time, it is not particular in China [65].…”

Section: Discussionmentioning

confidence: 86%

Evolution of Guangzhou Biomedical Industry Innovation Network Structure and Its Proximity Mechanism

Zhang

Qian

Zhao³

2020

Sustainability

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The topological structure and multidimensional proximity evolution mechanism of Guangzhou biomedical industry innovation network are studied by using cooperative patents and cooperative papers from 1998 to 2018 with Ucinet and PLS-SEM. Research shows: ① The evolution of the Guangzhou Biomedical Industry Innovation Network can be divided into three stages, which are the primary budding stage of 1998–2005, the steady development stage of 2006–2012, and the rapid development stage of 2013–2018; ② the number of subjects in the innovation network is increasing, and the types of subjects are constantly increasing. The innovation network has gone from small to large, from closed to open, and from simple to complex. Patents and papers cooperation networks show different characteristics at various stages; ③ the relationship between geographical proximity, cognitive proximity, organizational proximity, and innovation network differs in stages. The interaction of proximity varies with the content of innovation cooperation. Based on this result, we have put forward policy recommendations for different innovative content.

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The evolution of government sponsored collaboration network and its impact on innovation: A bibliometric analysis in the Chinese solar PV sector

Cited by 82 publications

References 61 publications

Open innovation and innovative performance of universities: Evidence from China

Open innovation and innovative performance of universities: Evidence from China

The Impact of Industry–University–Research Alliance Portfolio Diversity on Firm Innovation: Evidence from Chinese Manufacturing Firms

Evolution of Guangzhou Biomedical Industry Innovation Network Structure and Its Proximity Mechanism

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