Social network analysis and social capital in human resource development research: A practical introduction to R use

• Author: Chungil Chae,David L. Passmore,Seung‐hyun Han
• Published date: 01 June 2019
• DOI: http://doi.org/10.1002/hrdq.21341
• Date: 01 June 2019

METHODS PAPER

Social network analysis and social capital in human

resource development research: A practical

introduction to R use

Seung-hyun Han

1

| Chungil Chae

2

| David L. Passmore

3

1

Learning, Leadership and Organization

Development, University of Georgia, Athens,

Georgia

2

Applied Cognitive Science Lab, Pennsylvania

State University, University Park, Pennsylvania

16802

3

Learning and Performance Systems University

Park, Pennsylvania State University, PA

Correspondence

Chungil Chae, Applied Cognitive Science Lab,

Pennsylvania State University, University Park,

Pennsylvania 16802.

Email: czc176@psu.edu

Social network analysis (SNA) has become increasingly popular in

many scientific applications and is applied widely in human

resource development (HRD) research. Leveraging social networks

can influence learning processes within organizations and provide

opportunities for problem-solving and the generation of new ideas.

This article offers a look at the methodological basics of analyzing

social networks and the major concepts in social capital theory from

the social network perspective. A practical case is made to use SNA

in the HRD context. After an analysis of hypothetical network data

and application of social capital theory, the case shows how some

actors in the network can create social capital from strong support-

ive relations, whereas others might expect to gain brokerage advan-

tages by playing a role in structural holes. This article also serves as

a brief guide for beginners using SNA with R in HRD research.

KEYWORDS

HRD relationships, R applications, social capital, social network

analysis

1|INTRODUCTION

In recent decades, scholars have devoted considerable attention to the concept of social networks as a method for

analyzing social relations and structures (Hanneman & Riddle, 2011; Kadushin, 2012; Knoke & Yang, 2008). Research

trends have shown social network analysis (SNA) to be one of the most useful ways of identifying relationships

among socially relevant units (most commonly persons or organizations), revealing relational patterns and explicating

complicated connections (Cross, Parker, & Sasson, 2003; Kilduff & Tsai, 2003; Scott, 2012). This analytic approach is

used to examine social phenomena and the patterns formed by social entities (Borgatti, Everett, & Johnson, 2013).

Foundational work in human resource development (HRD) research has focused on learning and performance as

either a cognitive process or a function of behavioral change occurring through HRD interventions and applications

in workplace practices (Holton, 2002; Marsick & Watkins, 1994). Although social relations and interactions are funda-

mental dimensions sustaining groups within purposeful organizations (Storberg, 2002), the focus on the attributes of

DOI: 10.1002/hrdq.21341

© 2019 Wiley Periodicals, Inc.

Human Resource Development Quarterly. 2019;30:219–243. wileyonlinelibrary.com/journal/hrdq 219

participants in social networks has precluded a deep consideration of how social context in HRD can be furthered by

the notion of SNA (Hatala, 2006; Kilduff & Brass, 2010; Yamkovenko & Hatala, 2015). To date, most HRD research

has been dominated by frameworks that focus primarily on attribute datasets that record participant perceptions,

attitudes, and behaviors regarding specific interests, with little inquiry into relational or social views in HRD as a func-

tion of relationships (Akinci & Saunders, 2015; Stewart & Harte, 2015). Conventional research methods used in quan-

titative research often fail to properly account for phenomena derived from intertwined social relationships, even

though these relationships influence individual choice and opportunity, group formation, and the structure of behav-

iors and attitudes (Carolan, 2013).

Given the importance of social relationships and interactions embedded in workplace learning (Nakamura &

Yorks, 2011; Storberg-Walker & Gubbins, 2007), it is necessary to employ tools that measure the dynamics between

individuals and the forces that impact relations between them. HRD research has stressed the social environment

and context in specific ways of considering, for example, whether the organizational structure affects individual or

group performance (Lines, 2005), whether individuals in certain social positions produce different learning outcomes

(Korte & Lin, 2013; Watkins & Marsick, 2014), and how individual performance and group systems are intertwined

(Hatala, 2006). In using SNA to improve the empirical rigor of conducting HRD research, Hatala (2006) provided a

comprehensive introduction to the methodological advantage of SNA in HRD studies. Hatala's literature review

highlighted the origins and implications of social network theory and pointed to possible directions for HRD research,

including social capital analysis, HRD theory-building, and organizational change. Yamkovenko and Hatala (2015) pro-

vided a brief explanation of network indicators and SNA’s statistical applications. Storberg-Walker and Gubbins

(2007) explained the deeply connected relationships between contemporary HRD and SNA. HRD practitioners

should take a look at SNA, because an understanding of social structure would steer researchers toward tools that

enable detection of opportunities or constraint factors for individual performance and learning.

Despite descriptions of these efforts in the existing literature, SNA has been infrequently used in practice-

oriented HRD research. This lack of emphasis might be due to the debate about whether SNA is an analysis tech-

nique or a domain of research (Mische, 2011). Wellman (1988) noted that SNA is “a comprehensive paradigmatic

way of taking social structure by studying directly how patterns of ties allocate resources in a social system”

(p. 20). Rather than just reintroducing the basic concepts of SNA, we devote special attention in this article to its

applicability in the HRD context. In particular, social capital theory is adopted here to provide novel insights; we

focus on how SNA can produce particular answers into HRD research questions and identify meaningful interpre-

tations of SNA that can be integrated with findings shared in the HRD literature. Social capital has been regarded

as a key concept that can add value to the study of social networks (Tsai & Ghoshal, 1998). Well-established liter-

ature underscores the ways in which social capital is embedded in social interactions, and influences organiza-

tional behaviors and performance (Cross & Cummings, 2004; Hatala, 2006; Inkpen & Tsang, 2005; Nakamura &

Yorks, 2011). However, a gap remains in the research methodology where a systematic analysis of social capital

and social networks intersect.

The significance of this study lies in stimulating new lines of thinking and streams of research that provide

insightful applications into the role of social capital as a force that may accentuate the HRD research. By examining

social capital from the network perspective, HRD may be able to support organizations with better-informed deci-

sions and design more efficient training and work systems (Storberg, 2002). By integrating some of the possible inter-

ests around SNA and social capital, HRD research acknowledges the opportunities and constraints arising from the

social context where actors are embedded (Yamkovenko & Hatala, 2015). This could generate a more diverse pool of

knowledge, ultimately leading to a better understanding of social capital and more effective HRD practices.

This article is organized into three parts. First, foundational concepts of SNA are described, focusing on the social

capital theory that undergirds SNA. Then, we look at the ways in which SNA provides HRD researchers with a differ-

ent way of evaluating an array of processes and outcomes to explicitly account for the importance of one's relation-

ships with others as well as for structural patterns in which these relationships are embedded. To stress the use of

SNA in practice, step-by-step instructions for SNA are provided that include examples of code in R and easily applied

220 HAN ET AL.