implementation effect

  • 文章类型: Journal Article
    鉴于技术转让为促进国民经济发展提供了重要的推动力,技术转移政策(TTP)越来越受到学术界和工业界的关注。政府出台了许多政策。然而,TTP的实施效果仍有待明确。本研究是从“文本内容-影响路径-实施效果”的渐进层面进行的。\'\'旨在采用系统分析方法,分析政策工具和政策实施阶段,然后构建了TTP影响路径的概念框架。然后阐明了定性模型中变量之间的关系,并利用系统动力学(SD)模型建立了具有四个反馈回路的定量模型。最后,以辽宁为例,以中国为例,在VensimPLE中实现了系统仿真和主要参数的灵敏度分析。不同的政策工具在TTP影响研究阶段具有不同的作用,转让,和工业化。基于2013-1019年的数据,本文构建的SD模型可用于预测2020-2015年TTP的实施效果。仿真和敏感性分析结果为政府部门提高现有TTP的实施效果提供了实践启示。本研究也为其他研究者通过“文本内容-影响路径-实施效果”传导链提高TTP的实施效果提供了系统的理解,为TTP的进一步研究提供了新的见解。
    Given that technology transfer provides an important boost for promoting national economic development, technology transfer policy (TTP) has attracted more and more attention from academia and industry. The government issued many policies. However, the implementation effect of TTP still needs to be clarified. This study is carried out from the progressive level of \"text content-influence path-implementation effect.\'\' It aims to adopt a systematic analysis method to analyze policy tools and policy implementation stages, then builds a conceptual framework of the influence path of TTP. Then the relationship between variables in the qualitative model was clarified, and the system dynamics (SD) model was used to build a quantitative model with four feedback loops. Finally, taking Liaoning, China as an example, the system simulation and sensitivity analysis of the main parameters are implemented in Vensim PLE. Different policy tools have different roles in the TTP impact stages of research, transfer, and industrialization. Based on the data of 2013-1019, the SD model constructed in this paper can be used to predict the implementation effect of TTP during 2020-2015. Simulation and sensitivity analysis results provide practical enlightenment for government departments to improve the implementation effect of the existing TTP. This study also provides other researchers with a systematic understanding for improving the implementation effect of TTP with a \"text content-influence path-implementation effect\" conduction chain and provides new insights for further research on TTP.
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