Professor Stephen Teo is a Professorial Research Fellow in the School of Business and Law.
Dr Stephen Teo is a Professor of Work and Performance and Professorial Research Fellow at Edith Cowan University, Australia. Prior to this appointment, he was the Interim Director of the Global Business Innovation Research Platform at RMIT University. He is recognised as one of the leading scholars in the field of human resource management, as shown by the outcome of the 2012 New Zealand Performance-based Research Funding evaluation.
He has published in leading refereed journals such as Human Resource Management (USA), Human Resource Management Journal, Journal of Vocational Behavior, the International Journal of Human Resource Management, International Business Review, Asia Pacific Journal of Management, and others such as the Journal of Advanced Nursing. His most recent projects examined the impact of organizational change on the well-being and performance of public sector employees in Australia, New Zealand, the United Kingdom, the USA and Italy. He is currently undertaking research into workplace ill-treatment and psychological capital. In addition to research, Prof Teo is passionate about learning and teaching, in particular the use of group assessment in the diverse, multicultural classroom.
- Fellow, Australian Human Resources Institute
- Chartered Fellow, Chartered Institute of Personnel andDevelopment
- Fellow, UK Royal Society of Arts
- Senior Associate, Financial Services Institute ofAustralasia
- Member, Australia and New Zealand Academy of Management
- Member, Academy of Management
- Member, Asia Academy of Management
- International Affiliate, USA Society for Industrial andOrganizational Psychology
- Member, US Society of Human Resource Management
Awards and Recognition
National and International Awards
- 2014 - Best Research Paper Award (authors: Ho, Teo, Bentley, Verreynne, & Galvin), Paper presented at the 4th Annual International Conference on Human Resource Management & Professional Development for the Digital Age, Singapore - winner of Best Research Paper Award
- 2014 - Nominated for Best Paper Award (authors: Nguyen & Teo), Paper presented at the First International Conference of the Human Resources Division, US Academy of Management, Beijing
- 2013 - Best Research Paper Award (authors: Ho, Lo & Teo), Paper presented at the 3rd Annual International Conference on Human Resource Management & Professional Development for the Digital Age, Singapore
- 2013 - Highly Commended Award for “Generic skills development and satisfaction with groupwork among business students: Effect of country of permanent residency” published in Education + Training
- 2012 - Best Paper Award, Human Resource Management Track, Irish Academy of Management Conference
University and National Teaching Awards
- 2007 - The Carrick Institute for Learning and Teaching in Higher Education Citation for Outstanding Contributions to Student Learning (For sustained contributions in practise-based, research-led curriculum and assessment design to provide Business graduates with work ready competencies in HRM)
- 2006 - Commendation, UTS Team Teaching Award (with K Redfern) for coordinating the Bachelor of Business (Shanghai) program
- 2004 - Recipient of the University of Technology, Sydney 2004 Teaching Award
- 2004 - Commendation, UTS Vice Chancellor’s Human Rights and Social Justice Award for using group work assessment task to enhance human rights and social justice
National and International Research Positions
Research Mentor, Australia and New Zealand Academy of Management (2015-17)
- 2015 - Winner, AUT Faculty of Business & Law Dean’s Premier Publication Award
- 2013 - AUT Vice Chancellor’s Award for Research Excellence
- 2012 - AUT Faculty of Business and Law Research Excellence Award
Research Areas and Interests
Stephen’s research focuses on Strategic HRM (including HRRoles Effectiveness); Change Management; Job Stress and Wellbeing; NegativeWorkplace Behaviors; and Public Management. He has a preference forquantitative research methods, utilising techniques such as multivariateanalyses, structural equations modelling (AMOS, SmartPLS, Mplus),meta-analysis, and multi-level modelling.