Exploring regional innovation capacities of PR China: Toward the study of knowledge divide

While the Chinese innovation system has achieved some promising developments at the aggregate level over the past few years, looking at the breakdown by regions unveils a different story behind the success. This study is a modest attempt to shed light on the issue of 'knowledge divide' in the Chinese context, as existing regional inequalities have appeared in conjunction with the production of knowledge and innovation in its transformation into an innovation-driven economy. In order to understand the major reasons for this new trend in regional divergence, the study explores the different levels of innovation activities among the provincial-level regions of China and analyzes underlying factors leading to the regional disparity in innovation performance.;Much of the analysis is concerned with an empirical and comparative exploration of the determinants of regional innovation capacity, employing a comprehensive and unified framework of a regional innovation system which can capture a dynamic process of building regional innovation capacity. Combining both quantitative (e.g., regression and factor analyses) and qualitative (e.g., comparative case analysis) methods, the research examines the relationship between regional innovative output (e.g., domestic patenting) and the explanatory variables associated with the regional innovative capacity as well as explore how innovation capacities are built in different regional contexts.;The quantitative empirical results show that the development of innovation infrastructure has been the most important factor that contributes to the enhancement of the capacities of the regional innovation systems. Accumulated knowledge stocks and overall level of research and development (R&D) resources have the prominent and positive impacts on the level of the regional innovation productivity. Regional government policies also play a significant role in determining the innovation productivity but they have the distinctive effects on the different qualities of the innovation outputs. The public investments in human capital play a considerable role in technologically intensive innovation process, whereas the impact of government S&T supports is limited to the production of marginal innovation. This implies the inefficiency of public S&T support systems which lower the quality level of innovation outputs. However, the knowledge spillover effects of the foreign direct investment (FDI) inflow and international trade on the regional innovations are mostly insignificant and negative.;The results also suggest that the cluster innovation environment, measured by private S&T funding, is a critical determinant of advanced technological innovations. In fact, this is reflected in a rapid increase in the firms' share of institutional invention patent grants over the past decade. While industry becomes a major source of technologically intensive innovation, the knowledge spillovers from the science sector play a favorable role in generating marginal innovation. Given that the interactions or linkages between the private and science sectors have a limited effect on the regional innovation outputs, this indicates that the efficiency and quality of R&D productivity can be low in most regional innovation systems in China.;The detailed comparative case study of Hubei and Fujian complements the above empirical results, highlighting the importance of the government's policies and the interactions or links between private and science sectors. The contrasts between the two regional innovation systems reveal that the establishment of the strong knowledge base and learning culture for innovation, along with the effective government intervention is a determinant factor leading to differences in the innovation performance of the two regions. Specifically, it suggests that the effective government intervention policies, institutional incentive systems, science and technology (S&T) capabilities of industry, and research-oriented academic culture are crucial to induce the active learning trends which can contribute to the development of the regional innovation capacity.