Artikel

Local extremes of selected Industry 4.0 indicators in the European space: Structure for autonomous systems

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.

Language
Englisch

Bibliographic citation
Journal: Journal of Risk and Financial Management ; ISSN: 1911-8074 ; Volume: 13 ; Year: 2020 ; Issue: 1 ; Pages: 1-37 ; Basel: MDPI

Classification
Wirtschaft
Subject
indicators
Industry 4.0
precedence analysis

Event
Geistige Schöpfung
(who)
Botlíková, Milena
Botlík, Josef
Event
Veröffentlichung
(who)
MDPI
(where)
Basel
(when)
2020

DOI
doi:10.3390/jrfm13010013
Handle
Last update
10.03.2025, 11:42 AM CET

Data provider

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Object type

  • Artikel

Associated

  • Botlíková, Milena
  • Botlík, Josef
  • MDPI

Time of origin

  • 2020

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