我国区域性生物医药创新集群演化动力与可持续发展策略研究*——基于长三角系统动力学的仿真分析

Study on the Evolutionary Dynamics and Sustainable Development Strategies of Biomedical Innovation Clusters in Yangtze River Delta Region-Simulation analysis based on system dynamics

摘要:

依据生物医药产业创新集群特征设计长三角生物医药创新集群系统动力学模型,分析系统动力机制、演化路径和关键变量作为可持续发展决策的杠杆作用点,基于2012-2021年长三角生物医药创新集群面板数据对关键要素推动创新集群产值的影响进行仿真模拟分析,探究长三角生物医药创新集群发展的动力系统及各子系统要素对集群演化产生的影响。实证发现,市场需求子系统为创新集群演化提供根本性动力,国内市场需求影响尤为显著；创新能力子系统是集群演化的内生动力,但研发投入持续高速增长可能不利于集群发展；政府支持子系统是推动集群演化的外生动力,且影响显著。建议实施长三角区域高质量发展统一大市场策略；构建江浙沪皖四方资源组合的新型创新链；实施区域政府公共价值创造合作策略,形成创新集群可持续发展支持体系。

Abstract:

It designs a system dynamics model of biopharmaceutical innovation clusters in the Yangtze River Delta, uses the key variables in the system as leverage points for sustainable development decisions, and conducts simulation analysis of the impact of key elements driving the output value of innovation clusters based on panel data of biopharmaceutical innovation clusters in the Yangtze River Delta from 2012 to 2021 to explore the dynamics system of biopharmaceutical innovation cluster development and the impact of each subsystem element on the evolution of the clusters. The empirical evidence finds that market demand subsystem provides fundamental driving force for innovation cluster evolution, and the influence of domestic market demand is particularly significant. Innovation capability subsystem is the endogenous driving force for cluster evolution, but continued high growth in R D investment may not be conducive to cluster development. Government support subsystem is the exogenous driving force for cluster evolution, and the influence is significant. It is suggested to implement a unified large market strategy for high-quality development in the Yangtze River Delta region. To construct an innovation chain with the combination of resources from four sides of Jiangsu, Zhejiang, Shanghai and Anhui. To implement a regional governmental public value creation cooperation strategy to form a sustainable development support system for innovation clusters.