Rate My Professor Martin Edwards

Professor Martin Edwards is a Professor in Management in the UQ Business School at the University of Queensland, serving as Deputy Head of the School and head of the Management, International Business, Strategy and Entrepreneurship portfolio. He joined the University of Queensland in 2019, having previously held the position of Reader in HRM and Organisational Psychology at King's College London. Before embarking on his academic career, Edwards worked for several years as an HR consultant in London. His academic qualifications include a Bachelor of Social Psychology from the University of Kent, a Master's (Coursework) in Industrial Relations from the London School of Economics and Political Science, and a Doctor of Philosophy in Industrial and Organisational Psychology from King's College London.

Edwards' research focuses on HR analytics and people analytics, organisational identification and employee-organisational linkages, social and multiple identities in the workplace, employee responses to mergers and acquisitions, employer branding, gendered employer brands, and the effects of monitoring and performance metrics on employees. His publications include the co-edited book Workforce Analytics: A Global Perspective (Routledge, 2025), Using R in HR Analytics: A Practical Guide to Analysing People Data (Kogan Page, 2024, with Kirsten Edwards and Daisung Jang), and Predictive HR Analytics: Mastering the HR Metric (3rd edition, Kogan Page, 2024). Recent articles feature "Managerial control or feedback provision: How perceptions of algorithmic HR systems shape employee motivation, behavior, and well-being" (Human Resource Management, 2024), "Do pre-merger loyalties help or hinder post-merger retention? A longitudinal study" (British Journal of Management, 2024), and "Anticipated organizational identity change, job anxiety and affective commitment during macro-level turbulence: a cross-lagged study in the shifting sands of Brexit" (European Journal of Work and Organizational Psychology, 2024). His research explores how organizations use statistics and data science modelling to answer important people-related questions at work.