Social Capital as Antecedents of Knowledge Sharing: A Social Network Approach

AHRD 2017 paper testing how task interdependence, trust, friendship, and awareness of expertise predict knowledge-sharing ties.
Presentation & Talk
Conference Paper
Published

January 1, 2017

Keywords

knowledge sharing, social capital, social network analysis, QAP regression, community of practice

Overview

This paper, led by Caleb Seung-hyun Han with Seung Won Yoon and me, studies knowledge sharing as a relationship between two people rather than as an individual attribute. Drawing on social capital theory, social network theory, and the Community of Practice, we examined how different kinds of relationships predict whether one person shares knowledge with another.

Participants were 29 undergraduate students in a leadership course at a public university who worked through five problem-solving cases in changing groups. Each relationship was recorded as a 29 x 29 matrix. Because network observations are not independent, we used network logistic regression with the Quadratic Assignment Procedure (QAP), run in R.

Key points

  • The proposed model correctly predicted about 81% of the existence of knowledge-sharing ties.
  • Among the three dimensions of social capital, the structural dimension, measured as task interdependence, had the strongest influence.
  • Trust and friendship networks also had significant effects on knowledge sharing.
  • The study shows how network regression can handle interdependent relational data in HRD research.

Event

AHRD 2017.

Citation

Han, S.-H., Chae, C., & Yoon, S. W. (2017). Social capital as antecedents of knowledge sharing: A social network approach. Paper presented at AHRD 2017.