With business today relying increasingly more on collaboration, new product development is also on a network base. The concept of innovation ecosystem is built upon knowledge creating and sharing across companies, knowledge institutions, policy regimes, business enterprises and industry boundaries. China as the largest emerging market has witnessed innovation with interaction among government, university, industry and research. Though government plays an important role in promoting innovation, not many studies have covered the detailed dynamic process and impact of policy on forming innovation ecosystem, especially in places where initial knowledge resources such as universities and research institutes are limited. Therefore, our article aims to fill in this research gap. Through document review and case study on Changzhou region of China, 1 we map out the local government policy concerns and changes during each stage of innovation ecosystem formation, development and expansion from 2001 to 2015. The interaction mechanism among government, university, industry and research is summarised with a proposed framework to highlight the key policy making areas. Further research areas are recommended with implication and conclusion.

High-tech zones are an important platform for local governments in China to carry out regional collaborative innovation and an important carrier for the construction of a regional innovation ecosystem. The evolution path of innovation ecosystem in a high-tech zone is divided into three stages: enterprise collection, industrial cluster, and system integration. The innovation subjects form a complex network system that transcends the physical boundary. This paper studies the relationship between innovation input, innovation output, and innovation environment from the perspective of cluster innovation ecosystem structure. Using data mining technology, this paper establishes an index variable system of the innovation ecosystem in a high-tech zone, which includes innovation input, innovation output, and innovation environment. Based on the data of the Nanning National High-tech Zone in China, empirical tests were carried out, using factor analysis and regression analysis to analyze the quantitative relationship between the input, output, and innovation environment of the Nanning High-tech Zone’s innovation ecosystem, and to explain the relationship between each other and the overall innovation of the high-tech zone. This research has certain practical significance for enriching and perfecting the theory of industrial clusters and studying the evolution of the innovation ecosystem of high-tech zones from a micro level. It has important, enlightening significance as a reference for the construction of innovative high-tech zones and the enhancement of high-tech zones’ independent innovation capabilities.

We studied the formation of leaders' habitual behaviors and the impact of leaders' existing and potential capabilities on ambidextrous (i.e., exploitative and exploratory) innovation activities. Leadership habitual domain (LHD) theory was applied from an endogenous perspective to analyze the impact mechanism of LHD on ambidextrous innovation via the mediating role of dynamic capabilities. We used structural equation modeling to test data collected from 205 team leaders in East China. Results showed that LHD was positively associated with both exploitative and exploratory innovation, and that dynamic capabilities mediated these relationships. Thus, team leaders should renew, reconfigure, and expand their LHD by sensing and seizing opportunities when implementing ambidextrous innovation.