Event Overview

Forced migration is one of today’s most urgent global grand challenges. Supporting refugee livelihoods requires more than good intentions — it calls for finely tuned, evidence-based solutions.

This session explores how engaged, collaborative research can create sustainable pathways to employment and economic inclusion for displaced populations.

Drawing on multi-stakeholder applied research with refugees, employers, community groups, and policymakers, we will showcase how partnerships grounded in real-world practice can deliver:

High-impact insights
Actionable policy tools
Scalable programs for lasting change

Key Topics

The challenges and opportunities of refugee employment
Building partnerships that drive impact
Research dissemination that bridges academia and practice

Through real-world case studies, the session will highlight successes, challenges, and lessons learned, illustrating how engaged research connects academic knowledge with meaningful social impact.

Speaker Profiles

Eun Su Lee
Lecturer in Management, University of Melbourne (Australia)

Research in international HRM & migrant integration journeys
Published in leading journals including Academy of Management Perspectives, Human Resource Management Journal, and International Journal of Management Reviews
Recipient of global awards: AIB Insights Award for Actionable Insights (2022), NBS Research Impact on Practice Award, and International HRM Scholarly Award

Betina Szkudlarek
Professor of International Management & Strategic Consultant, United Nations Alliance of Civilizations (UNAOC)

Global expert on inclusive workplaces; lead editor of the SAGE Handbook of Contemporary Cross-Cultural Management
Insights featured in Wall Street Journal, Harvard Business Review, BBC
Honours include the 2022 Academy of Management Research Impact on Practice Award and the 2023 UN PRME Award for Excellence in SDG Integration

Useful Links

Contact the host of From Research to Impact: Collaborative Solutions for Refugee Employment

There were 0 errors found in the information you submitted: