LABOR ECONOMIC ASPECT OF AN AUTOMATION: A PROPOSED STUDY USING ADVANCED MACHINE LEARNING ALGORITHMS

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F22%3A63553098" target="_blank" >RIV/70883521:28140/22:63553098 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/70883521:28120/22:63553098

Výsledek na webu

<a href="http://dx.doi.org/10.7441/dokbat.2022.28" target="_blank" >http://dx.doi.org/10.7441/dokbat.2022.28</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.7441/dokbat.2022.28" target="_blank" >10.7441/dokbat.2022.28</a>

Jazyk výsledku

angličtina

Název v původním jazyce

LABOR ECONOMIC ASPECT OF AN AUTOMATION: A PROPOSED STUDY USING ADVANCED MACHINE LEARNING ALGORITHMS

Popis výsledku v původním jazyce

This proposed research study aims to examine the effect of automation and robotization on theemployment situation in Europe. The study will evaluate and analyze by identifying the risk ofsubstitution of job classification along with a proposed empirical analysis by using advancedtechnologies such as machine learning (ML), robotics, and automated processing units. Thestudy will employ the advanced methodology of modeling and prediction to evaluate the riskof substitution of the classified jobs by automation while focusing on the task-based structure.The advanced prediction tools, primarily Artificial Intelligence (AI) and Machine Learning(ML), will contribute to the evaluation of the latent relationship between automation and thetasks performed by jobs. This research study will contribute to scientific works by providingsignificant results for understanding the true effects of automation on classified jobs,particularly in manufacturing sectors.

Název v anglickém jazyce

LABOR ECONOMIC ASPECT OF AN AUTOMATION: A PROPOSED STUDY USING ADVANCED MACHINE LEARNING ALGORITHMS

Popis výsledku anglicky

This proposed research study aims to examine the effect of automation and robotization on theemployment situation in Europe. The study will evaluate and analyze by identifying the risk ofsubstitution of job classification along with a proposed empirical analysis by using advancedtechnologies such as machine learning (ML), robotics, and automated processing units. Thestudy will employ the advanced methodology of modeling and prediction to evaluate the riskof substitution of the classified jobs by automation while focusing on the task-based structure.The advanced prediction tools, primarily Artificial Intelligence (AI) and Machine Learning(ML), will contribute to the evaluation of the latent relationship between automation and thetasks performed by jobs. This research study will contribute to scientific works by providingsignificant results for understanding the true effects of automation on classified jobs,particularly in manufacturing sectors.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

50201 - Economic Theory

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název statě ve sborníku

DOKBAT 2022 - 18th International Bata Conference for Ph.D. Students and Young Researchers

ISBN

978-80-7678-101-6

ISSN

—

e-ISSN

—

Počet stran výsledku

9

Strana od-do

287-295

Název nakladatele

Fakulta managementu a ekonomiky, UTB ve Zlíně

Místo vydání

Zlín

Místo konání akce

Zlín

Datum konání akce

14. 9. 2022

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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