Version 1
: Received: 4 March 2022 / Approved: 7 March 2022 / Online: 7 March 2022 (04:17:02 CET)
How to cite:
Leogrande, A.; Magaletti, N.; Cosoli, G.; Giardinelli, V.; Massaro, A. ICT Specialists in Europe. Preprints2022, 2022030088. https://doi.org/10.20944/preprints202203.0088.v1
Leogrande, A.; Magaletti, N.; Cosoli, G.; Giardinelli, V.; Massaro, A. ICT Specialists in Europe. Preprints 2022, 2022030088. https://doi.org/10.20944/preprints202203.0088.v1
Leogrande, A.; Magaletti, N.; Cosoli, G.; Giardinelli, V.; Massaro, A. ICT Specialists in Europe. Preprints2022, 2022030088. https://doi.org/10.20944/preprints202203.0088.v1
APA Style
Leogrande, A., Magaletti, N., Cosoli, G., Giardinelli, V., & Massaro, A. (2022). ICT Specialists in Europe. Preprints. https://doi.org/10.20944/preprints202203.0088.v1
Chicago/Turabian Style
Leogrande, A., Vito Giardinelli and Alessandro Massaro. 2022 "ICT Specialists in Europe" Preprints. https://doi.org/10.20944/preprints202203.0088.v1
Abstract
The following article estimates the value of ICT Specialists in Europe between 2016 and 2021 for 28 European countries. The data were analyzed using the following econometric techniques, namely: Panel Data with Fixed Effects, Panel Data with Random Effects, WLS and Pooled OLS. The results show that the value of ICT Specialists in Europe is positively associated with the following variables: "Desi Index", "SMEs with at least a basic level of digital intensity", "At least 100 Mbps fixed BB take-up" and negatively associated with the following variables: "4G Coverage","5G Coverage", "5G Readiness", "Fixed broadband coverage", "e-Government", "At least Basic Digital Skills", "Fixed broadband take-up", "Broadband price index", "Integration of Digital Technology". Subsequently, two European clusters were found by value of "ICTG Specialists" using the k-Means clustering algorithm optimized by using the Silhouette coefficient. Finally, eight different machine learning algorithms were compared to predict the value of "ICT Specialists" in Europe. The results show that the best prediction algorithm is ANN-Artificial Neural Network with an estimated growth value of 12.53%. Finally, "augmented data" were obtained through the use of the ANN-Artificial Neural Network, through which a new prediction was made which estimated a growing value of the estimated variable equal to 3.18%.
Keywords
innovation, and invention: processes and incentives; management of technological innovation and R&D; diffusion processes; open innovation
Subject
Business, Economics and Management, Economics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
