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Open AccessArticle

Local Extremes of Selected Industry 4.0 Indicators in the European Space—Structure for Autonomous Systems

1
Faculty of Philosophy and Science in Opava, Silesian University in Opava, Bezručovo nám. 14, 746 01 Opava, Czechia
2
School of Business Administration in Karvina, Silesian University in Opava, Univerzitní nám. 1934/3, 733 40 Karviná, Czechia
*
Author to whom correspondence should be addressed.
J. Risk Financial Manag. 2020, 13(1), 13; https://doi.org/10.3390/jrfm13010013
Received: 1 December 2019 / Revised: 3 January 2020 / Accepted: 4 January 2020 / Published: 7 January 2020
(This article belongs to the Special Issue International Trends and Economic Sustainability on Emerging Markets)
In the past, the social and economic impacts of industrial revolutions have been clearly identified. The current Fourth Industrial Revolution (Industry 4.0) is characterized by robotization, digitization, and automation. This will transform the production processes, but also the services or financial markets. Specific groups of people and activities may be replaced by new information technologies. Changes represent an extreme risk of economic instability and social change. The authors described available published sources and selected a group of indicators related to Industry 4.0. The indicators were divided into five groups and summarized by negative or positive impact. The indicators were analyzed by precedence analysis. Extremes in the geographical dislocation of factor values were found. Furthermore, spatial dependencies in the distribution of these extremes were found by calculating multiple (long) precedencies. European countries were classified according to individual groups of indicators. The results were compared with the real values of the indicators. The indicated extremes and their distribution will allow to predict changes in the behavior of the population given by changes in the socio-economic environment. The behavior of the population can be described by the behavior of autonomous systems on selected infrastructure. The paper presents research related to the creation of a multiagent model for the prediction of spatial changes in population distribution induced by Industry 4.0. View Full-Text
Keywords: Industry 4.0; indicators; precedence analysis Industry 4.0; indicators; precedence analysis
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Botlíková, M.; Botlík, J. Local Extremes of Selected Industry 4.0 Indicators in the European Space—Structure for Autonomous Systems. J. Risk Financial Manag. 2020, 13, 13.

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