Dynamic capabilities perspective on innovation ecosystem of China’s universities in the age of artificial intelligence: Policy-based analysis

Abstract

Universities play a key role in university-industry-government interactions and are important in innovation ecosystem studies. Universities are also expected to engage with industries and governments and contribute to economic development. In the age of artificial intelligence (AI), governments have introduced relevant policies regarding the AI-enabled innovation ecosystem in universities. Previous studies have not focused on the provision of a dynamic capabilities perspective on such an ecosystem based on policy analysis. This research work takes China as a case and provides a framework of AI-enabled dynamic capabilities to guide how universities should manage this based on China’s AI policy analysis. Drawing on two main concepts, which are the innovation ecosystem and dynamic capabilities, we analyzed the importance of the AI-enabled innovation ecosystem in universities with governance regulations, shedding light on the theoretical framework that is simultaneously analytical and normative, practical, and policy-relevant. We conducted a text analysis of policy instruments to illustrate the specificities of the AI innovation ecosystem in China’s universities. This allowed us to address the complexity of emerging environments of innovation and draw meaningful conclusions. The results show the broad adoption of AI in a favorable context, where talents and governance are boosting the advance of such an ecosystem in China’s universities.

– The IAFOR International Conference on Arts & Humanities – Hawaii 2024 Official Conference Proceedings

“…Innovation development always needs a national strategy to support technology innovation and development from policies (Lundvall, 2007). Therefore, as AI has been recognised as a national strategy in many nations, such as China, the US, the UK, Japan, and the European Union (Qu & Kim, 2022), it is important to consider how policy context can play an active role in researching and developing AI in innovation for industries. The trend and characteristics of AI policy inclination may prove a country's innovation focus and development clusters.…”

The Kyoto Conference on Arts, Media & Culture 2023: Official Conference Proceedings

“…Following the issuance of these national policies, a total of 33 regional policies were released, constituting a significant majority at 91.67% of the policies issued during this stage. This phase is categorized as the "environmental side" of policy implementation, signifying a crucial step in setting the desired objectives and outcomes, as highlighted by Qu & Kim (2022). The second phase covers the period from 2018 to 2019, during which a greater number of AI-related policies were issued.…”

“…In 2020, the MOST issued 6 supportive regional AI pilot zones, enhancing collaborations with universities to promote the integration of disciplines and expedite the training of graduate students in the field of AI. This shift implies that AI policy instruments have transitioned to a "supply side" approach, which includes a focus on "cultivating talents" (Qu & Kim, 2022). In 2022, China entered a new stage.…”

“…In recent articles, with the release of reports, plans, and policy documents, an increasing number of countries worldwide are focusing on this area. More than 30 countries have released national AI policy strategies so far (Schiff, 2022) (Qu and Kim, 2022). These policy documents and reports provide informative content on the development and future directions of AI research.…”

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“…Moreover, the strategic approach towards AI, as outlined in China’s New Generation AI Development Plan, aims to establish China as a global leader in AI by 2030 (Nguyen & Hekman, 2022; Roberts et al, 2020). This ambition is mirrored in the robust AI innovation ecosystems within Chinese universities and the corporate sector, especially within the digital technology giants Baidu, Alibaba, and Tencent (BAT) (Qu & Kim, 2022; Su & Flew, 2020). However, despite these strides, certain challenges such as business risks, ethical concerns, and the potential adverse impact on the environment and certain economic sectors persist (Lv et al, 2022; Mao & Shi-Kupfer, 2021; Wang, 2022; Wu et al, 2020).…”