Open innovation and innovative performance of universities: Evidence from China

Abstract

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.

Network Proximity Evolution of Open Innovation Diffusion: A Case of Artificial Intelligence for Healthcare

“…Organizational proximity positively affected open innovation diffusion, while temporal proximity had a negative effect. The result interprets why transferring technology from universities to enterprises is difficult, which supplements the theory based on the prior literature [21,22]. Enterprises tend to learn advanced technology from other enterprises, especially the competitors, and the situation is the same for universities.…”

“…Proximity performance determines whether the entity can adapt to the external environment. In addition, proximity reduces the uncertainty of entities in industrial strategic decision-making [22], thus promoting open innovation diffusion.…”

How do university‐industry collaborations benefit innovation? Direct and indirect outcomes of different collaboration types

“…However, the contemporary understanding sees innovation as an interactive process where learning occurs inside and outside the organization. It has increasingly been recognized that innovation is a highly social process requiring increased interactions among people, which has led to the introduction of concepts such as ‘open innovation’ (Chesbrough, 2003; Ye et al., 2020). R&D collaborations with universities and other knowledge‐generating organizations have been emphasised to stimulate firm innovation (Doloreux et al., 2020; Fitjar & Rodríguez‐Pose, 2013).…”

Triple helix relationship research on China's regional university–industry–government collaborative innovation: Based on provincial patent data

“…Since the 1990s, 90% of research institutes of the original planned economy system have completed the restructuring of enterprises and become innovative enterprises operating independently and responsible for their own profits and losses (Xing et al., 2019). With the strong support of the government, the existing public scientific research institutions such as the Chinese Academy of Sciences and provincial scientific research institutes are engaged in scientific research and public welfare technology development related to the national economy and the people's livelihood and accept the guidance of government initiatives (Ye et al., 2020). In addition, scientific research institutions are established and supervised by the government in order to pursue public interests.…”