Organisational Network Analysis

Revealing the invisible structure of organisations

Organisational Network Analysis (ONA) is the application of social network methods to the study of relationships, information flows, and influence structures within and between organisations. My research in this area extends beyond traditional single-layer network studies by employing multiplex network frameworks that simultaneously examine five distinct relationship types:

  • Work Advice — Who do people turn to for task-related guidance?
  • AI Support — Who helps colleagues navigate AI tools?
  • Trust — Whom do people trust with sensitive information?
  • Information — Who shares timely organisational information?
  • Collaboration — Who actively collaborates on projects?

By overlaying these network layers, we can identify structural patterns invisible to conventional surveys: knowledge silos, informal leaders, redundant communication paths, and critical bridging nodes whose departure would fragment organisational knowledge.

Deep-dive: What is ONA? →

AI Champion Programs

Grass-roots AI adoption through network-identified influencers

A central contribution of my work is the development of an evidence-based framework for designing AI champion programs — initiatives that identify and empower key individuals within an organisation to champion AI adoption among their peers.

Using betweenness centrality and Infomap community detection algorithms applied to ONA data, I have identified three distinct AI champion archetypes:

Oracle

High betweenness centrality across all network layers. Oracles are the go-to experts — their AI endorsement carries the most credibility and reach.

Broker

High betweenness between community clusters. Brokers are the cross-boundary connectors who bridge departments and translate AI insights across silos.

Silo Buster

Low internal centrality but high inter-community ties. Silo Busters prevent knowledge hoarding and ensure AI best practices spread beyond isolated teams.

Deep-dive: What are AI Champions? →

Information Security Governance

Understanding and improving security behaviours in organisations

A significant strand of my research investigates the human and organisational dimensions of information security. Rather than focusing solely on technical controls, I examine why individuals comply with — or deviate from — security policies, and how organisations can cultivate a security-positive culture.

Key themes include:

  • Security policy compliance and non-compliance drivers among employees
  • The role of organisational culture in shaping security behaviour
  • Social influence and peer pressure in information security contexts
  • Enterprise security governance frameworks in Vietnamese SMEs and MNCs
  • Phishing susceptibility and security awareness training effectiveness
  • Privacy concerns and digital literacy in Vietnamese online populations

This work draws on theories including Protection Motivation Theory, Theory of Planned Behaviour, and Social Cognitive Theory, often combined with survey-based structural equation modelling (PLS-SEM, CB-SEM) and qualitative methods.

Digital Transformation

Navigating large-scale technology change in emerging markets

My digital transformation research examines how individuals and organisations navigate profound technology-driven change — and the social, cognitive, and structural factors that determine whether transformation initiatives succeed or stall.

Key topics include:

  • Technology acceptance and adoption in Vietnamese enterprise contexts
  • Change management strategies for enterprise system implementations (ERP, CRM)
  • Knowledge transfer and organisational learning during digital transitions
  • AI readiness assessment frameworks for Vietnamese SMEs
  • Leadership and culture as enablers (or barriers) of digital change

Research methods

I employ a pluralistic methodological approach, combining quantitative, qualitative, and computational methods depending on the research question:

Quantitative

Survey-based structural equation modelling (PLS-SEM, CB-SEM), regression analysis, multi-group analysis

Network Science

Social network analysis, multiplex ONA, betweenness centrality, Infomap community detection, network visualisation

Qualitative

Semi-structured interviews, case studies, thematic analysis, grounded theory

Mixed Methods

Sequential and concurrent mixed-methods designs combining survey data with interview insights and network metrics