National Innovation Systems Archetypal Analysis

Joseph Gogodze

doi:doi:10.11648/j.ajtas.20180706.13

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National Innovation Systems Archetypal Analysis

Joseph Gogodze

Published in American Journal of Theoretical and Applied Statistics (Volume 7, Issue 6)

Received: 7 September 2018 Accepted: 18 September 2018 Published: 31 October 2018

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Abstract

The national innovation system (NIS) determines the innovation capability of a country, and its economic development. However, recently, very little is known regarding the determinants of NIS functioning in various countries. Probably the easiest way to obtain such an understanding is to begin with the structural representation of the NIS. Particularly, it is quite natural to assume that there exists several ‘cornerstone type NIS’ or ‘archetypal NIS’, and all the other types can be considered a mixture of them. The aim of this paper is to somewhat study the advances in the structural understanding of the NIS. For this purpose we conducted our study based on the data set from the Global Innovation Indexes’ (GII) seven pillars and using archetypal analysis. It is also important to note that the concept of entropy was also naturally determined under archetypal analysis. We demonstrate that each NIS can be considered a mixture of three archetypical NISs, which are as follows: The first one is a prototype of a highly developed NIS (with a high level GII score and a low level of entropy); the second one is a prototype of an underdeveloped NIS (with a low level GII score and a low level of entropy); and the third one is an intermediate form of NIS (with a medium level GII score and a high level of entropy). Hence, we establish that such a multidimensional phenomenon, such as the NIS (described in this study as the 7-dimensional vector – GII pillars), with an acceptable level of the accuracy, essentially can be considered a 2-dimensional object; and the corresponding barycentric coordinates are a convenient means of describing NISs. We also introduce an important indicator – the NIS entropy – which characterises the level of the disorder or randomness in the NIS.

Published in	American Journal of Theoretical and Applied Statistics (Volume 7, Issue 6)
DOI	10.11648/j.ajtas.20180706.13
Page(s)	215-221
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2018. Published by Science Publishing Group

Keywords

Statistical Data Analysis, Archetypal Analysis, National Innovation System

References

[1]	Verspagen, B., 2005. Innovation and economic growth, in: Fagerberg, J., Mowery, D. C., Nelson R. R. (Eds.), The Oxford Handbook of Innovation, Oxford University Press, pp. 487–513.
[2]	Fagerberg, J., Srholec, M., 2008. National innovation systems, capabilities and economic Development. Research Policy, 37, 1417–1435.
[3]	Acemoglu, D., 2015. Localised and biased technologies: Atkinson and Stiglitz's new view, induced innovations, and directed technological change. The Economic Journal, 125 (583), 2015, pp.443-463.
[4]	Kogan, L., Papanikolaou, D., Seru, A. and Stoffman, N., Technological innovation, resource allocation, and growth. The Quarterly Journal of Economics, 132 (2), 2017, pp.665-712.
[5]	Hidalgo, C. A., Economic complexity: From useless to keystone. Nature Physics, 2018, 14 (1), p.9.
[6]	Thompson, M., Social capital, innovation and economic growth. Journal of behavioral and experimental economics, 73, 2018, pp.46-52.
[7]	Cutler A., Breiman L., 1994. Archetypal Analysis. Technometrics, 36(4), 338–347.
[8]	Eugster, M. J. and Leisch, F., Weighted and robust archetypal analysis. Computational Statistics & Data Analysis, 55 (3), 2011, pp.1215-1225.
[9]	Kaufmann, D., Keller, S. and Roth, V., Copula archetypal analysis. In German Conference on Pattern Recognition, Springer, 2015, pp. 117-128.
[10]	Vinué, G., Anthropometry: An R package for analysis of anthropometric data. Journal of Statistical Software, 77 (6), 2017, pp.1-39.
[11]	INSEAD. Global innovation index 2011; Global innovation index 2012; Global innovation index 2013; Global innovation index 2014; Global innovation index 2015. Fontainebleau: INSEAD.

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Joseph Gogodze. (2018). National Innovation Systems Archetypal Analysis. American Journal of Theoretical and Applied Statistics, 7(6), 215-221. https://doi.org/10.11648/j.ajtas.20180706.13

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Joseph Gogodze. National Innovation Systems Archetypal Analysis. Am. J. Theor. Appl. Stat. 2018, 7(6), 215-221. doi: 10.11648/j.ajtas.20180706.13

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Joseph Gogodze. National Innovation Systems Archetypal Analysis. Am J Theor Appl Stat. 2018;7(6):215-221. doi: 10.11648/j.ajtas.20180706.13

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@article{10.11648/j.ajtas.20180706.13,
  author = {Joseph Gogodze},
  title = {National Innovation Systems Archetypal Analysis},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {7},
  number = {6},
  pages = {215-221},
  doi = {10.11648/j.ajtas.20180706.13},
  url = {https://doi.org/10.11648/j.ajtas.20180706.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20180706.13},
  abstract = {The national innovation system (NIS) determines the innovation capability of a country, and its economic development. However, recently, very little is known regarding the determinants of NIS functioning in various countries. Probably the easiest way to obtain such an understanding is to begin with the structural representation of the NIS. Particularly, it is quite natural to assume that there exists several ‘cornerstone type NIS’ or ‘archetypal NIS’, and all the other types can be considered a mixture of them. The aim of this paper is to somewhat study the advances in the structural understanding of the NIS. For this purpose we conducted our study based on the data set from the Global Innovation Indexes’ (GII) seven pillars and using archetypal analysis. It is also important to note that the concept of entropy was also naturally determined under archetypal analysis. We demonstrate that each NIS can be considered a mixture of three archetypical NISs, which are as follows: The first one is a prototype of a highly developed NIS (with a high level GII score and a low level of entropy); the second one is a prototype of an underdeveloped NIS (with a low level GII score and a low level of entropy); and the third one is an intermediate form of NIS (with a medium level GII score and a high level of entropy). Hence, we establish that such a multidimensional phenomenon, such as the NIS (described in this study as the 7-dimensional vector – GII pillars), with an acceptable level of the accuracy, essentially can be considered a 2-dimensional object; and the corresponding barycentric coordinates are a convenient means of describing NISs. We also introduce an important indicator – the NIS entropy – which characterises the level of the disorder or randomness in the NIS.},
 year = {2018}
}

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TY  - JOUR
T1  - National Innovation Systems Archetypal Analysis
AU  - Joseph Gogodze
Y1  - 2018/10/31
PY  - 2018
N1  - https://doi.org/10.11648/j.ajtas.20180706.13
DO  - 10.11648/j.ajtas.20180706.13
T2  - American Journal of Theoretical and Applied Statistics
JF  - American Journal of Theoretical and Applied Statistics
JO  - American Journal of Theoretical and Applied Statistics
SP  - 215
EP  - 221
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20180706.13
AB  - The national innovation system (NIS) determines the innovation capability of a country, and its economic development. However, recently, very little is known regarding the determinants of NIS functioning in various countries. Probably the easiest way to obtain such an understanding is to begin with the structural representation of the NIS. Particularly, it is quite natural to assume that there exists several ‘cornerstone type NIS’ or ‘archetypal NIS’, and all the other types can be considered a mixture of them. The aim of this paper is to somewhat study the advances in the structural understanding of the NIS. For this purpose we conducted our study based on the data set from the Global Innovation Indexes’ (GII) seven pillars and using archetypal analysis. It is also important to note that the concept of entropy was also naturally determined under archetypal analysis. We demonstrate that each NIS can be considered a mixture of three archetypical NISs, which are as follows: The first one is a prototype of a highly developed NIS (with a high level GII score and a low level of entropy); the second one is a prototype of an underdeveloped NIS (with a low level GII score and a low level of entropy); and the third one is an intermediate form of NIS (with a medium level GII score and a high level of entropy). Hence, we establish that such a multidimensional phenomenon, such as the NIS (described in this study as the 7-dimensional vector – GII pillars), with an acceptable level of the accuracy, essentially can be considered a 2-dimensional object; and the corresponding barycentric coordinates are a convenient means of describing NISs. We also introduce an important indicator – the NIS entropy – which characterises the level of the disorder or randomness in the NIS.
VL  - 7
IS  - 6
ER  -

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Author Information

Joseph Gogodze

Institute of Control Systems, Techinformi, Georgian Technical University, Tbilisi, Georgia

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Joseph Gogodze. (2018). National Innovation Systems Archetypal Analysis. American Journal of Theoretical and Applied Statistics, 7(6), 215-221. https://doi.org/10.11648/j.ajtas.20180706.13

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ACS Style

Joseph Gogodze. National Innovation Systems Archetypal Analysis. Am. J. Theor. Appl. Stat. 2018, 7(6), 215-221. doi: 10.11648/j.ajtas.20180706.13

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AMA Style

Joseph Gogodze. National Innovation Systems Archetypal Analysis. Am J Theor Appl Stat. 2018;7(6):215-221. doi: 10.11648/j.ajtas.20180706.13

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@article{10.11648/j.ajtas.20180706.13,
  author = {Joseph Gogodze},
  title = {National Innovation Systems Archetypal Analysis},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {7},
  number = {6},
  pages = {215-221},
  doi = {10.11648/j.ajtas.20180706.13},
  url = {https://doi.org/10.11648/j.ajtas.20180706.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20180706.13},
  abstract = {The national innovation system (NIS) determines the innovation capability of a country, and its economic development. However, recently, very little is known regarding the determinants of NIS functioning in various countries. Probably the easiest way to obtain such an understanding is to begin with the structural representation of the NIS. Particularly, it is quite natural to assume that there exists several ‘cornerstone type NIS’ or ‘archetypal NIS’, and all the other types can be considered a mixture of them. The aim of this paper is to somewhat study the advances in the structural understanding of the NIS. For this purpose we conducted our study based on the data set from the Global Innovation Indexes’ (GII) seven pillars and using archetypal analysis. It is also important to note that the concept of entropy was also naturally determined under archetypal analysis. We demonstrate that each NIS can be considered a mixture of three archetypical NISs, which are as follows: The first one is a prototype of a highly developed NIS (with a high level GII score and a low level of entropy); the second one is a prototype of an underdeveloped NIS (with a low level GII score and a low level of entropy); and the third one is an intermediate form of NIS (with a medium level GII score and a high level of entropy). Hence, we establish that such a multidimensional phenomenon, such as the NIS (described in this study as the 7-dimensional vector – GII pillars), with an acceptable level of the accuracy, essentially can be considered a 2-dimensional object; and the corresponding barycentric coordinates are a convenient means of describing NISs. We also introduce an important indicator – the NIS entropy – which characterises the level of the disorder or randomness in the NIS.},
 year = {2018}
}

Copy | Download

TY  - JOUR
T1  - National Innovation Systems Archetypal Analysis
AU  - Joseph Gogodze
Y1  - 2018/10/31
PY  - 2018
N1  - https://doi.org/10.11648/j.ajtas.20180706.13
DO  - 10.11648/j.ajtas.20180706.13
T2  - American Journal of Theoretical and Applied Statistics
JF  - American Journal of Theoretical and Applied Statistics
JO  - American Journal of Theoretical and Applied Statistics
SP  - 215
EP  - 221
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20180706.13
AB  - The national innovation system (NIS) determines the innovation capability of a country, and its economic development. However, recently, very little is known regarding the determinants of NIS functioning in various countries. Probably the easiest way to obtain such an understanding is to begin with the structural representation of the NIS. Particularly, it is quite natural to assume that there exists several ‘cornerstone type NIS’ or ‘archetypal NIS’, and all the other types can be considered a mixture of them. The aim of this paper is to somewhat study the advances in the structural understanding of the NIS. For this purpose we conducted our study based on the data set from the Global Innovation Indexes’ (GII) seven pillars and using archetypal analysis. It is also important to note that the concept of entropy was also naturally determined under archetypal analysis. We demonstrate that each NIS can be considered a mixture of three archetypical NISs, which are as follows: The first one is a prototype of a highly developed NIS (with a high level GII score and a low level of entropy); the second one is a prototype of an underdeveloped NIS (with a low level GII score and a low level of entropy); and the third one is an intermediate form of NIS (with a medium level GII score and a high level of entropy). Hence, we establish that such a multidimensional phenomenon, such as the NIS (described in this study as the 7-dimensional vector – GII pillars), with an acceptable level of the accuracy, essentially can be considered a 2-dimensional object; and the corresponding barycentric coordinates are a convenient means of describing NISs. We also introduce an important indicator – the NIS entropy – which characterises the level of the disorder or randomness in the NIS.
VL  - 7
IS  - 6
ER  -

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