By Topic

Exploratory Study of Intra-Organizational Learning from Social Network Perspective within a Spanish Knowledge Intensive Company

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
de Pablo Gonzalez del Campo, J.D.S. ; Univ. of Castilla-La Mancha, Ciudad Real, Spain ; Skerlavaj, M. ; Gomez, F.G. ; Dimovski, V.

Organizational learning is a research topic very relevant in strategic studies. Nevertheless, the way in which learning takes place in the firm constitutes one of the main gaps in research. For this reason, this paper wants to explain how learning occurs in a company. A case study of a Spanish high-tech company is used to explore the network perspective on intra-organizational learning. It expands the generalization of the network perspective to intra-organizational learning, as proposed by Skerlavaj and Dimovski (2006). We formulated four propositions based on an exploratory social network analysis. We provide additional arguments for the generalization of the research findings related to the importance of industry experience and company tenure as determinants of the key players in learning networks. The novel contribution of this study relates to the complementarity of knowledge as a tie generator and shows the importance of cross-departmental knowledge flows in projects. Moreover, similarity in terms of experiential level and physical proximity creates opportunities to learn. From a practice-oriented perspective, this study offers tools for detecting the most important employees in a firm from a learning viewpoint.

Published in:

Social Network Analysis and Mining, 2009. ASONAM '09. International Conference on Advances in

Date of Conference:

20-22 July 2009