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How to improve the innovation level of a country? A Bayesian net approach

机译:如何提高一个国家的创新水平?贝叶斯网络方法

摘要

This study aims to provide strategic guidelines to policy makers who are developing strategies to improve their country’s innovativeness. In this paper, we claim that innovation cannot be related only to some factors inherent in the environment of a country, nor is it a single entity to be managed without any linkages to the rest of the actors comprising the competitiveness of a country. Hence, a comprehensive study on innovation should cover the interaction between competitiveness indicators and innovation. For this purpose, the innovation performance of 148 countries is analyzed using an integrated cluster analysis and a Bayesian network framework. These countries are first clustered based on the average values of their competitiveness indicators representing 12 pillars and several sub-pillars adopted from the Global Competitiveness Reports of World Economic Forum for the 2009-2012 period. As a result, five appropriate clusters emerge: Leaders, Followers, Runners Up, Developing Ones, and Laggers. A factor analysis is then conducted to reveal the main characteristics of each cluster in terms of competitiveness indicators. Subsequently, a Bayesian network is constructed and sensitivity analyses are performed to reveal important policies for each cluster.
机译:这项研究旨在为正在制定战略以提高本国创新能力的决策者提供战略指导。在本文中,我们主张创新不能仅与一国环境中固有的某些因素相关,也不可以是一个单一的实体进行管理,而与构成国家竞争力的其他参与者没有任何联系。因此,对创新的全面研究应涵盖竞争力指标与创新之间的相互作用。为此,使用集成聚类分析和贝叶斯网络框架对148个国家的创新绩效进行了分析。这些国家首先根据其竞争力指标的平均值进行分组,这些指标代表了《世界经济论坛2009-2012年全球竞争力报告》中采用的12个支柱和几个子支柱。结果,出现了五个合适的集群:领导者,追随者,亚军,发展中的人和匕首。然后进行因素分析,以根据竞争力指标揭示每个集群的主要特征。随后,构建贝叶斯网络并进行敏感性分析以揭示每个群集的重要策略。

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