443
Views
7
CrossRef citations to date
0
Altmetric
Original Articles

The dialectics between boundaryless career and competence development findings among Finnish ICT and paper managers

Pages 181-196 | Published online: 27 Jan 2011
 

Abstract

The aim of this study is to examine how boundaryless career relates to competence development of managers in Finnish information and communication business sector (ICT) and paper business sector. The research was qualitative by nature and the used research method was a focused interview. The research group included 15 managers from three ICT companies in the field of software and 15 managers from three paper companies specialising in pulp, paper and paperboard manufacture. Managers were themselves responsible for updating their competence; continuous development of skills and knowledge enabled managers to make their own career decisions and manage their career. Career decisions directed the managers' further training needs. High competence level created shelter and self-confidence to managers. Managers were more committed to their competence related to the business sector than any particular organisation, and they wanted to combine work, family and hobbies in their lives as well. Only two Finnish business sectors were included in this study and the target was in the middle management level in organisations. Therefore, the study is not comprehensive. However, the results of the study give information concerning the relation between boundaryless career research and competence research in changing work environments.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 352.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.