Influence of Information Technologies on Production Efficiency: Estimation on the Basis of Algorithms for Machine Learning

O. V. Bakanach (), N. V. Proskurina (), N. P. Persteneva () and M. Yu. Karyshev ()
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O. V. Bakanach: Samara State University of Economics
N. V. Proskurina: Samara State University of Economics
N. P. Persteneva: Samara State University of Economics
M. Yu. Karyshev: Samara State Transport University

A chapter in Sustainable Growth and Development of Economic Systems, 2019, pp 195-205 from Springer

Abstract: Abstract This contribution illustrates a brief description of information technologies as a factor of economic production. This issue is important today because there are no unequivocally recognized priority methodological approaches to estimate them against the background of the constant influence of information technologies on the economy. A methodology for obtaining a quantitative estimation of the impact of information technologies on economic production was developed and tested in the course of this study (using the example of statistical data on economic entities in Russia for the period from 2005 to 2016). This technique is based on principles of statistics and machine learning algorithms, which allow obtaining reliable results of estimates. The result of the contribution was classification models based on such machine learning algorithms as the nearest neighbors (k-nearest neighbors), logistic regression, and decision trees. This composite algorithm is able to make a decision on efficiency of one or another surveyed unit (enterprise of any type of economic activity) from the standpoint of its characteristics in the field of information technologies.

Keywords: Economic efficiency; Information technology; Statistics; Programming languages; Machine learning; Artificial intelligence (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:spr:conchp:978-3-030-11754-2_15

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DOI: 10.1007/978-3-030-11754-2_15

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