Modelling the complex nature of regional knowledge creation is high on the research agenda. It deals with the identification of drivers for regional knowledge creation of different kinds, among them inter-regional networks and agglomeration factors, as well as their interplay; i.e. in which way they influence regional knowledge creation and accordingly, innovation capabilities—in the short- and long-term. Complementing a long line of tradition—establishing a link between regional knowledge input indicators and knowledge output in a regression framework—we propose an empirically founded agent-based simulation model that intends to approximate the complex nature of the multi-regional knowledge creation process for European regions. Specifically, we account for region-internal characteristics, and a specific embedding in the system of region-internal and region-external R&D collaboration linkages. With first exemplary applications, we demonstrate the potential of the model in terms of its robustness and empirical closeness. The model enables the replication of phenomena and current scientific issues of interest in the field of geography of innovation and hence, shows its potential to advance the scientific debate in this field in the future.

中文翻译：

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基于经验主体的欧洲区域知识创造模型

对区域知识创造的复杂性进行建模是研究工作的重中之重。它探讨了不同类型区域知识创造的驱动因素，包括区域间网络和集聚因素，以及它们之间的相互作用。即，它们以何种方式在短期和长期内影响区域知识的创造以及相应的创新能力。作为长期的传统的补充（在回归框架中建立区域知识输入指标和知识输出之间的链接），我们提出了一个基于经验的基于主体的模拟模型，旨在模拟欧洲多区域知识创造过程的复杂性。地区。具体来说，我们考虑了区域内部特征，并特别嵌入到区域内部和区域外部R＆D合作链接的系统中。在第一个示例性应用程序中，我们从模型的鲁棒性和经验接近性方面证明了该模型的潜力。该模型能够复制创新地理学领域中感兴趣的现象和当前的科学问题，因此显示了其在未来推动该领域的科学辩论的潜力。