Summary
Human resource development (HRD) research has relied mainly on attribute data: perceptions, attitudes, and behaviors of individuals. Relationships among people, which shape learning, problem solving, and the generation of new ideas in organizations, are harder to study with conventional methods. This methods paper introduces social network analysis (SNA) to HRD researchers as a way to study those relationships.
The article explains the methodological basics of analysing social networks and the main concepts of social capital theory from a network perspective. It then works through a practical case with hypothetical knowledge-sharing network data, using R and packages such as igraph and sna, with the code shown step by step.
The case illustrates two routes to social capital. Some actors build it through strong, supportive relations within a closed group, while others gain brokerage advantages by occupying structural holes between groups. The paper is written as a brief guide for beginners who want to use SNA with R in HRD research.
Why it matters
It lowers the entry barrier to relational analysis for a field that has mostly used attribute-based survey designs.
Citation
Han, S.-H., Chae, C., & Passmore, D. L. (2019). Social network analysis and social capital in human resource development research: A practical introduction to R use. Human Resource Development Quarterly, 30(2), 219–243. https://doi.org/10.1002/hrdq.21341
Indexed in: SSCI
Citation
@online{2019,
author = {},
title = {Social {Network} {Analysis} and {Social} {Capital} in {Human}
{Resource} {Development} {Research:} {A} {Practical} {Introduction}
to {R} {Use}},
date = {2019-06-01},
url = {https://chadchae.github.io/posts_publication/2019-06-01-social-network-analysis-social-capital-hrd-r/social-network-analysis-social-capital-hrd-r.html},
langid = {en}
}