SSOAR Logo
    • Deutsch
    • English
  • English 
    • Deutsch
    • English
  • Login
SSOAR ▼
  • Home
  • About SSOAR
  • Guidelines
  • Publishing in SSOAR
  • Cooperating with SSOAR
    • Cooperation models
    • Delivery routes and formats
    • Projects
  • Cooperation partners
    • Information about cooperation partners
  • Information
    • Possibilities of taking the Green Road
    • Grant of Licences
    • Download additional information
  • Operational concept
Browse and search Add new document OAI-PMH interface
JavaScript is disabled for your browser. Some features of this site may not work without it.

Download PDF
Download full text

(external source)

Citation Suggestion

Please use the following Persistent Identifier (PID) to cite this document:
https://doi.org/10.13152/IJRVET.5.3.4

Exports for your reference manager

Bibtex export
Endnote export

Display Statistics
Share
  • Share via E-Mail E-Mail
  • Share via Facebook Facebook
  • Share via Bluesky Bluesky
  • Share via Reddit reddit
  • Share via Linkedin LinkedIn
  • Share via XING XING

The 'Future of Employment' on the Shop Floor: why Production Jobs are Less Susceptible to Computerization than Assumed

[journal article]

Pfeiffer, Sabine

Abstract

Context: Germany is seen as one of the major players in developing what is known as “Industry 4.0.” Especially in the manufacturing and the automotive sector, the vocational training is seen as a precondition and consequence alike for the global success of these sectors. Current research though char... view more

Context: Germany is seen as one of the major players in developing what is known as “Industry 4.0.” Especially in the manufacturing and the automotive sector, the vocational training is seen as a precondition and consequence alike for the global success of these sectors. Current research though characterizes production work, especially machine-related tasks, as dull routine work and therefore of high probability of computerization. Approach: Based on qualitative research perspectives and sociological results that reveal the importance of experience and implicit capabilities, this study quantifies what is mostly seen as “non-routine” work. To measure these dimensions of living labouring capacity, an index is introduced that is developed from 18 items of one of the biggest German task-based, representative surveys. Findings: The contribution challenges the widespread prognosis that production workers face high susceptibility. Comparing data on non-routine share in production and of vocational trained workers with those of Frey and Osborne, the findings stress the mostly neglected importance of non-routine work, even in production and especially with vocational trained, machine-related occupations. Conclusion: The results draw on how much more employees on the shop floor are apt to handle change, complexity, and imponderabilities than often assumed. If their work will or will not be susceptible to novel approaches in robotics or algorithms, therefore, is not a question of routine.... view less

Keywords
employment; employment trend; manufacturing area; digitalization; skilled worker; machine work; work organization; computer; occupational distribution

Classification
Sociology of Work, Industrial Sociology, Industrial Relations
Occupational Research, Occupational Sociology

Document language
English

Publication Year
2018

Page/Pages
p. 208-225

Journal
International journal for research in vocational education and training, 5 (2018) 3

Issue topic
Social Dimension and Participation in VET-System

ISSN
2197-8646

Status
Published Version; peer reviewed

Licence
Creative Commons - Attribution-Noncommercial-No Derivative Works 4.0


GESIS LogoDFG LogoOpen Access Logo
Home  |  Legal notices  |  Operational concept  |  Privacy policy
© 2007 - 2025 Social Science Open Access Repository (SSOAR).
Based on DSpace, Copyright (c) 2002-2022, DuraSpace. All rights reserved.
 

 


GESIS LogoDFG LogoOpen Access Logo
Home  |  Legal notices  |  Operational concept  |  Privacy policy
© 2007 - 2025 Social Science Open Access Repository (SSOAR).
Based on DSpace, Copyright (c) 2002-2022, DuraSpace. All rights reserved.