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[journal article]

dc.contributor.authorKoster, Sierdjande
dc.contributor.authorBrunori, Claudiade
dc.date.accessioned2022-11-16T12:47:33Z
dc.date.available2022-11-16T12:47:33Z
dc.date.issued2021de
dc.identifier.issn0143-7720de
dc.identifier.urihttps://www.ssoar.info/ssoar/handle/document/83099
dc.description.abstractPurpose: Ongoing automation processes may render a fair share of the existing jobs redundant or change their nature. This begs the question to what extent employees affected invest in training in order to strengthen their labour market position in times of uncertainty. Given the different national labour market regimes and institutions, there may be an important geographical dimension to the opportunities to cope with the challenges set by automation. The purpose of this study is to address both issues. Design/methodology/approach: Using data from the 2016 European labour Force Survey, the authors estimate with logit and multi-level regression analyses how the automation risk of a worker's job is associated with the propensity of following non-formal education/training. The authors allow this relationship to vary across European countries. Findings: The results show that employees in jobs vulnerable to automation invest relatively little in training. Also, there are significant differences across Europe in both the provision of training in general and the effect of automation on training provision. Originality/value: While there is quite a lot of research on the structural labour market effects of automation, relatively little is known about the actions that employees take to deal with the uncertainty they are faced with. This article aims to contribute to our understanding of such mechanisms underlying the structural macro-level labour-market dynamics.de
dc.languageende
dc.subject.ddcSoziologie, Anthropologiede
dc.subject.ddcSociology & anthropologyen
dc.subject.ddcWirtschaftde
dc.subject.ddcEconomicsen
dc.subject.otherEU-LFSde
dc.titleWhat to do when the robots come? Non-formal education in jobs affected by automationde
dc.description.reviewbegutachtet (peer reviewed)de
dc.description.reviewpeer revieweden
dc.source.journalInternational Journal of Manpower
dc.source.volume42de
dc.publisher.countryGBRde
dc.source.issue8de
dc.subject.classozIndustrie- und Betriebssoziologie, Arbeitssoziologie, industrielle Beziehungende
dc.subject.classozSociology of Work, Industrial Sociology, Industrial Relationsen
dc.subject.classozArbeitsmarktforschungde
dc.subject.classozLabor Market Researchen
dc.subject.thesozAusbildungde
dc.subject.thesoztrainingen
dc.subject.thesozArbeitsmarktde
dc.subject.thesozlabor marketen
dc.subject.thesozAutomatisierungde
dc.subject.thesozautomationen
dc.subject.thesozArbeitsplatzde
dc.subject.thesozjoben
dc.subject.thesozWeiterbildungde
dc.subject.thesozfurther educationen
dc.identifier.urnurn:nbn:de:0168-ssoar-83099-1
dc.rights.licenceCreative Commons - Namensnennung 4.0de
dc.rights.licenceCreative Commons - Attribution 4.0en
ssoar.contributor.institutionFDBde
internal.statusformal und inhaltlich fertig erschlossende
internal.identifier.thesoz10037045
internal.identifier.thesoz10036392
internal.identifier.thesoz10037519
internal.identifier.thesoz10036501
internal.identifier.thesoz10038335
dc.type.stockarticlede
dc.type.documentZeitschriftenartikelde
dc.type.documentjournal articleen
dc.source.pageinfo1397-1419de
internal.identifier.classoz10204
internal.identifier.classoz20101
internal.identifier.journal784
internal.identifier.document32
internal.identifier.ddc301
internal.identifier.ddc330
dc.identifier.doihttps://doi.org/10.1108/IJM-06-2020-0314de
dc.description.pubstatusVeröffentlichungsversionde
dc.description.pubstatusPublished Versionen
internal.identifier.licence16
internal.identifier.pubstatus1
internal.identifier.review1
internal.pdf.validfalse
internal.pdf.wellformedtrue
internal.pdf.encryptedfalse


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