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Dynamic structural comparison of BRICS national innovation systems based on machine learning techniques

机译:基于机器学习技术的金砖国家创新系统的动态结构比较

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摘要

This study aims at investigating the structural differences of NISs among BRICS countries to reveal the different functional patterns of these systems. Different Machine learning techniques are used of a set of variables that represent the main NISs dimensions. This study covers 50 countries, for 26 years. The results show that BRICS's NISs have different functional patterns in terms of economic, educational and infrastructural dimensions, where all BRICS countries, except India, perform well in comparison with other studied countries. On the other hand, all NISs of BRICS countries have the same functional patterns in terms of innovation and institutional dimensions, where all BRICS's NISs suffer from a low performance. The results also show that the performance of BRICS's NISs tends to diverge over time. This study introduces a novel approach to analyse and compare NISs structurally and dynamically enabling policy makers to identify the strengths and weaknesses of their NISs.
机译:本研究旨在调查金砖国家中南部的结构差异,以揭示这些系统的不同功能模式。 不同的机器学习技术用于一组变量,该变量代表主要的NIS尺寸。 本研究涵盖了50个国家,26年。 结果表明,金砖石的尼森在经济,教育和基础设施维度方面具有不同的功能模式,除印度除印体外,与其他研究国家相比,所有金砖国家表现得很好。 另一方面,所有NIS的金色国家在创新和机构维度方面具有相同的功能模式,所有金砖石的南都患有低性能。 结果还表明,金砖公司的NIS的表现随着时间的推移往往倾向于发散。 本研究介绍了一种新颖的分析和比较Niss结构和动态支持政策制定者,以确定他们NIS的优势和劣势。

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