Simulation of regional knowledge creation in EU and China

The creation of new knowledge is an imperative condition for generating innovation and thus of central importance in a global innovation competition context. However, new knowledge is generally not equally distributed and accessible in geographical space, emphasizing the importance of interactive, collaborative learning processes among organizations of different types located in different geographical spaces (regions) to prevent possible technological lock-ins by tapping region- external knowledge. In this project, we propose an empirically driven Multi-Agent-Based Model for simulating regional knowledge creation in EU and China from a comparative perspective, going beyond empirical studies predominantly employing different types of input-output inspired econometric models. We specifically shift attention to modelling the role of networks and policy interventions for regional knowledge creation dynamics in the two innovation systems. Generally, Applying Multi-Agent-Based Simulation (MABS) in regional science has great potential that is quite under-exploited so far: first, it can reflect spatial heterogeneity (e.g. size, economic characteristics, connectivity) that is ubiquitous in a regional background and second, it enables to depict the behaviors of agents in technology innovation and diffusion. Specifically, the proposed model is designed on a micro level where knowledge creation processes are determined by heterogeneous research agents (e.g. firms, universities or research institutes) each located within a European/Chinese region following certain research strategies, and on a macro level with different R&D network types (e.g. patenting and research collaboration networks) determining the creation and diffusion of knowledge as well as the collaboration behavior of the R&D organizations. With an application of the simulation model to the EU and China, we selected two highly interesting geographical areas, each showing completely different development paths, different overall socio-economic characteristics and conditions, different approaches in policy making and societal systems as a whole, etc. A comparative perspective on the European and Chinese regional knowledge creation mechanisms promises interesting insights in differences in certain impact dimensions. The significance of the proposed research is manifold and can be distinguished in substantive, methodological and policy relevant contributions: The model will be implemented using advanced ICT tools and, will break new ground in the design of such models for concrete real-world applications. Moreover, simulation results will provide a more comprehensive, micro-based understanding of determinants affecting regional knowledge creation and diffusion, and, by this, provides important insights not only in scientific terms, but also in a policy context.

The project "Simulation of regional knowledge creation in EU and China" sheds light on the spatial dynamics of knowledge creation and innovation in EU and China. Recognizing new knowledge as a catalyst for innovation and socio-economic growth, the project investigates drivers of inter-regional disparities in the two study areas. On the one hand, China's development to an innovation-driven economy resulted in a comparably strong spatial concentration of innovative activities only recently shifted attention to R&D collaborations facilitating access to new - geographically more distant - knowledge; potentially decreasing regional socio-economic disparities. On the other hand, in countries of the European Union (EU), inter-regional R&D collaborations are well-established vehicles of spatial knowledge diffusion and are an integral part of the national and regional innovation systems. Against this background, the research offers a comparative perspective, revealing insights into regional knowledge creation mechanisms and the impact of policy interventions. Specifically, the objectives of the project have been to i) to develop an empirical agent-based model (ABM) for regional knowledge creation in China and the EU, allowing us to ii) assess the influence of determinants on quantity and quality of regional knowledge creation in the two systems, specifically shifting attention to the role of R&D collaborations. The project significantly advances the geography of innovation literature by establishing an empirically grounded agent-based model (ABM) as a novel approach for analyzing knowledge creation within regional contexts. The ABM's unique properties capture non-linear and non-stationary mechanisms of knowledge creation, especially regarding increased R&D collaboration. This pioneering research showcases the model's successful empirical transfer from Europe to China underscoring its adaptability and potential generalizability. For China, the data collection and creation of a novel database for over 280 Chinese prefecture-level cities is groundbreaking. This rich dataset facilitates empirical initialization, calibration, and validation in the developed simulation model, offering also future research opportunities. The project's exploration of China's transformation into an innovation-driven economy fills significant research gaps, emphasizing micro-dynamics and bottom-up perspectives. Simulation results from the ABM reveal policy-relevant drivers of regional knowledge dynamics, emphasizing the impact of cross-region collaboration on knowledge gains for Europe and China. For instance, it is shown that a higher cross-region collaboration intensity indeed leads to higher knowledge gains at the system level, both in Europe and China, but that the potential for such gains is higher in China than in Europe as cross-region collaboration links are less developed.