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

(1.015Mb)

Citation Suggestion

Please use the following Persistent Identifier (PID) to cite this document:
https://nbn-resolving.org/urn:nbn:de:0168-ssoar-77103-2

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

Robot Acceptance at Work: A Multilevel Analysis Based on 27 EU Countries

[journal article]

Turja, Tuuli
Oksanen, Atte

Abstract

Robots are increasingly being used to assist with various tasks ranging from industrial manufacturing to welfare services. This study analysed how robot acceptance at work (RAW) varies between individual and national attributes in EU 27. Eurobarometer surveys collected in 2012 (n = 26,751) and 2014 ... view more

Robots are increasingly being used to assist with various tasks ranging from industrial manufacturing to welfare services. This study analysed how robot acceptance at work (RAW) varies between individual and national attributes in EU 27. Eurobarometer surveys collected in 2012 (n = 26,751) and 2014 (n = 27,801) were used as data. Background factors also included country-specific data drawn from the World Bank DataBank. The study is guided by the technology acceptance model and change readiness perspective explaining robot acceptance in terms of individual and cultural attributes. Multilevel studies analysing cultural differences in technological change are exceptionally rare. The multilevel analysis of RAW performed herein accounted for individual and national factors using fixed and random intercepts in a nested data structure. Individual-level factors explained RAW better than national-level factors. Particularly, personal experiences with robots at work or elsewhere were associated with higher acceptance. At a national level, the technology orientation of the country explained RAW better than the relative risk of jobs being automated. Despite the countries’ differences, personal characteristics and experiences with robots are decisive for RAW. Experiences, however, are better enabled in countries open to innovations. The findings are discussed in terms of possible mechanisms through which the technological orientation and social acceptance of robots may be related.... view less

Keywords
robot; industrial robot; acceptance; technology; technological change; mechanization; Europe; multi-level analysis

Classification
Sociology of Science, Sociology of Technology, Research on Science and Technology
Sociology of Work, Industrial Sociology, Industrial Relations

Free Keywords
Change readiness; ICT exports; Robot acceptance at work; Technology acceptance; Special Eurobarometer 382: Public Attitudes towards Robots; ZA5933: Eurobarometer 82.4 (2014)

Document language
English

Publication Year
2019

Page/Pages
p. 679-689

Journal
International Journal of Social Robotics, 11 (2019) 4

DOI
https://doi.org/10.1007/s12369-019-00526-x

ISSN
1875-4805

Status
Published Version; peer reviewed

Licence
Creative Commons - Attribution 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.