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Industrial and Corporate Change
Article . 2021 . Peer-reviewed
License: OUP Standard Publication Reuse
Data sources: Crossref
EconStor
Research . 2019
Data sources: EconStor
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Digital technologies, employment, and skills

Authors: Jelena Reljic; Rinaldo Evangelista; Mario Pianta;

Digital technologies, employment, and skills

Abstract

Abstract This article investigates the relationship between the diffusion of digital technologies, employment, and skills. The empirical analysis is carried out on industry-level data of six major European economies (Germany, France, Spain, Italy, the Netherlands, and the UK) over the 2009–2014 period. We analyze two dimensions of digitalization: industries’ consumption of intermediate inputs from digitally intensive sectors and investment in Information and Communication Technology (ICT) tangible and intangible assets, considering also patterns of demand, education, technological change, and offshoring. The results show that job creation in industries is positively associated with an increasing share of digital goods and services in total intermediate inputs and is negatively linked with processes of ICT capital deepening. We then explore how these two different patterns of digitalization are related to the evolution of four occupational groups—managers, clerks, craft, and Manual workers, defined on the basis of International Standard Classification of Occupations classes—finding a positive link between ICT consumption and managerial jobs, and negative ones between digital variables and mid-skill occupations.

Country
Italy
Keywords

Employment, ddc:330, J21, Skills, J23, J24, O3, European industries, Digital technology, Innovation, digital technology; innovation; employment; skills; european industries

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    24
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
24
Top 10%
Top 10%
Top 10%
Green
bronze