Next Article in Journal
Cultural Distance and Entry Modes in Emerging Markets: Empirical Evidence in Vietnam
Next Article in Special Issue
Mainstreaming Global Sustainable Development Goals through the UN Global Compact: The Case of Visegrad Countries
Previous Article in Journal
QE versus the Real Problems in the World Economy
Open AccessArticle

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

Faculty of Philosophy and Science in Opava, Silesian University in Opava, Bezručovo nám. 14, 746 01 Opava, Czechia
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;
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
Show Figures

Figure 1

MDPI and ACS Style

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.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Back to TopTop