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Modeling the relative efficiency of national innovation systems

机译：对国家创新系统的相对效率进行建模

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Although a large amount of past research has theorized about the character of national innovation systems (NISs), there has been limited process-oriented empirical investigation of this matter, possibly for methodological reasons. In this paper, we first propose a relational network data envelopment analysis (DEA) model for measuring the innovation efficiency of the NIS by decomposing the innovation process into a network with a two-stage innovation production framework, an upstream knowledge production process (KPP) and a downstream knowledge commercialization process (KCP). Although the concept of innovation efficiency is a simplification of the innovation process, it may be a useful tool for guiding policy decisions. We subsequently use a second-step partial least squares regression (PLSR) to examine the effects of policy-based institutional environment on innovation efficiency, considering statistical problems such as multicollinearity, small datasets and a small number of distribution assumptions. The hybrid two-step analytical procedure is used to consider 22 OECD (Organisation for Economic Co-operation and Development) countries. A significant rank difference, which indicates a non-coordinated relationship between upstream R&D (research and development) efficiency and downstream commercialization efficiency, is identified for most countries. The evidence also indicates that the overall innovation efficiency of an NIS is mainly subject to downstream commercial efficiency performance and that improving commercial efficiency should thus be a primary consideration in future innovation policy-making in most OECD countries. Finally, the results obtained using PLSR show that the various factors chosen to represent the embedded policy-based institutional environment have a significant influence on the efficiency performance of the two individual component processes, confirming the impact of public policy interventions undertaken by the government on the innovation performance of NISs. Based on these key findings, some country-specific and process-specific innovation policies have been suggested.
机译：尽管过去的大量研究都对国家创新系统（NIS）的特征进行了理论化，但可能出于方法论的原因，对此问题的面向过程的实证研究有限。在本文中，我们首先提出了一种关系网络数据包络分析（DEA）模型，用于通过将创新过程分解为具有两阶段创新生产框架，上游知识生产过程（KPP）的网络来衡量NIS的创新效率。以及下游知识商业化流程（KCP）。尽管创新效率的概念是创新过程的简化，但它可能是指导政策决策的有用工具。随后，我们考虑了多重共线性，小数据集和少量分配假设等统计问题，使用第二步偏最小二乘回归（PLSR）检验了基于政策的制度环境对创新效率的影响。混合两步分析程序用于考虑22个OECD（经济合作与发展组织）国家。对于大多数国家而言，存在明显的等级差异，这表明上游研发（研究与开发）效率与下游商业化效率之间存在不协调的关系。证据还表明，国家创新体系的总体创新效率主要取决于下游的商业效率绩效，因此，在大多数经合组织国家中，提高商业效率应成为未来创新政策制定的主要考虑因素。最后，使用PLSR获得的结果表明，选择用来代表基于政策的嵌入式制度环境的各种因素对两个单独组成部分过程的效率绩效都有重大影响，从而确认了政府采取的公共政策干预对政策制定的影响。 NIS的创新表现。基于这些关键发现，提出了一些针对特定国家和特定过程的创新政策。

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