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

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F47813059%3A19240%2F20%3AA0000642" target="_blank" >RIV/47813059:19240/20:A0000642 - isvavai.cz</a>

Alternative codes found

RIV/47813059:19520/20:A0000182

Result on the web

<a href="https://www.mdpi.com/1911-8074/13/1/13" target="_blank" >https://www.mdpi.com/1911-8074/13/1/13</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/jrfm13010013" target="_blank" >10.3390/jrfm13010013</a>

Result language

angličtina

Original language name

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

Original language description

In the past, the social and economic impacts of industrial revolutions have been clearly identified. The current Fourth Industrial Revolution (Industry 4.0) is haracterized 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 actor 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.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

50803 - Information science (social aspects)

Project

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Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2020

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Journal of Risk and Financial Management

ISSN

1911-8066

e-ISSN

1911-8074

Volume of the periodical

13

Issue of the periodical within the volume

13

Country of publishing house

CH - SWITZERLAND

Number of pages

39

Pages from-to

1-39

UT code for WoS article

000511892200016

EID of the result in the Scopus database

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