A dyadic perspective on knowledge exchange
by Sheng-Hsun Hsu, Shiou-Fen Tzeng
International Journal of Technology Management (IJTM), Vol. 49, No. 4, 2010

Abstract: This study provides insights into the relational characteristics of internal knowledge markets. Many knowledge initiatives are still based on the incorrect assumption that knowledge flows without friction and that people are willing to share knowledge with no concern about what they may gain or lose by doing so. However, such one-sided transactions seldom occur in real life. As a result, this study attempts to develop a sender-receiver (dyadic) framework to recognise the existence of knowledge markets and understand the mechanisms of knowledge markets. It is important to note that the unit of analysis in this study is the relationship between pairs of individuals and, thus, all of the variables are dyadic. To analyse the data at the dyadic level, we employ social network analysis and the Multiple Regression Quadratic Assignment Procedure (MRQAP). However, as research that is based on dyadic-level analysis is relatively scant, this raises some concerns about the reliability of the results. To address these concerns, we also analysed our data at the nodal (individual) level using the Partial Least Square (PLS) technique.

Online publication date: Sat, 06-Apr-2013

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Technology Management (IJTM):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com