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

Kód výsledku v 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>

Nalezeny alternativní kódy

RIV/47813059:19520/20:A0000182

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

50803 - Information science (social aspects)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2020

Kód důvěrnosti údajů

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

Název periodika

Journal of Risk and Financial Management

ISSN

1911-8066

e-ISSN

1911-8074

Svazek periodika

13

Číslo periodika v rámci svazku

13

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

39

Strana od-do

1-39

Kód UT WoS článku

000511892200016

EID výsledku v databázi Scopus

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