Impact of Information and Communication Technologies Development on the Labor Market in the Russian Federation

Magomedov, M.D.; Карабанова, О.В.; Stroev, V. V.

doi:10.2991/aebmr.k.201205.049

Cited by 1 publication

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“…The authors highlight the need to connect the demand for work to the university and vocational training of Russian workers as a strategy to increase the digitization of the labor market. [20] consider the role of ICT specialists in promoting a digitization-oriented labor market in Russia. The possibility for ICT workers to participate in the wide phenomenon of digitization essentially depends on the complex of training tools made available to Russian students and workers through the university system and through training within companies.…”

Section: Introductionmentioning

confidence: 99%

ICT Specialists in Europe

Leogrande¹,

MAGALETTI²,

Cosoli³

et al. 2022

Preprint

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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%.

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Section: Introductionmentioning

confidence: 99%