Science parks and innovation policies have a major mission in driving innovative resources and nurturing emerging industries, while the government-academia-industry collaborations and the establishment of an ecosystem are essentials. To investigate the key driving forces for sustainable development of the collaborative ecosystem, this article evaluates the technological innovations and the ecosystem of Science Parks in Shanghai based on historical data obtained from Shanghai Zhangjiang Science Park (Zhangjiang Park in short). Systems thinking and causal loop analysis are adopted to explore the structure of the collaborative ecosystem and reflections of the policy impact on the science park. The role of the government in science parks and innovation ecosystems is identified with systems mapping and empirical study. The economic impact of Zhangjiang Park policies and the performance of innovation activities in Shanghai are further evaluated. Lessons learnt from the benchmarked science parks and policy implications for facilitating the innovation ecosystem are addressed.

In an environment marked with phenomena such as globalization and creation, open innovation is critical for universities to cooperate with external resources and meet the requirements of the era. To investigate open innovation ecosystem of higher education, we use secondary data and interviews to analysis interactive model of Zizhu International Education Park from both internal and external perspectives. The analysis result suggests that the open innovation ecosystem could have positive effects on the development of higher education. It can contribute to deepening the integration of production, teaching, and research; improve the efficiency of scientific research transformation; and use this part of the income to supplement school funding. While the university–industry collaborative relationship could also be a limiting factor for it.

Given the growing importance of system dynamics (SD) in solving increasingly complex and dynamic problems in any country, we believe SD education will become an imperative leverage point in helping us deal with our uncertain future. This study tries to understand the causal relationships in proliferating SD education by a system dynamics group modelling approach in China. Based on a questionnaire survey and a group model building (GMB) workshop, we aim to explore the interactions of feedback loops in the constructed causal loop diagram (CLD). This uncovers insights into what constitutes the growth of SD education in China and helps to guide the design and implementation of policies to achieve this growth. We conclude that it is important and relevant to find ways to improve, including the construction of an SD teaching platform to integrate normative resources, providing opportunities for teacher training, enhancing the availability and accessibility of SD education, and building networks with international partners. The results of our study may set the foundation for further research to extend the generalizability of our insights and methodological approaches to other countries.