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

Authors: Ibrahim Alnafrah

Addresses: Department of Intellectual Property and Innovation Management, Faculty of Technological Management and Innovation, ITMO University, Kronverkskiy Prospekt, 4, Saint Petersburg, 197101, Russia

Abstract: 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.

Keywords: national innovation system; BRICS; machine learning techniques; classification; clustering; functional patterns comparison; innovation policy; innovation strategy; structural comparison.

DOI: 10.1504/IJTLID.2019.102681

International Journal of Technological Learning, Innovation and Development, 2019 Vol.11 No.3, pp.265 - 290

Received: 03 Apr 2019
Accepted: 29 Jul 2019

Published online: 01 Oct 2019 *

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