Staff Profile

Dr. Kiu Chun Tung Thomas 喬振東博士

BSc (Hons) SBS UK, MSc DBS UK, PhD DBS UK, PGCert GBS UK

Senior Lecturer
Lee Shau Kee School of Business and Administration

Biography

Thomas Kiu is a Senior Lecturer of HRM at Hong Kong Metropolitan University. His research explores the dynamic relationship between technology, organizations, and employees (i.e., human resource management) in the 21st century.

Drawing on theories of Strategic Human Resource Management (SHRM), Technology-Organization-Environment (TOE), and leadership, Thomas investigates how organizations develop, leverage, and respond to significant technological transformations. He utilizes a combination of quantitative and qualitative techniques to unravel the dynamics of innovation at both individual and organizational levels.

In addition, Thomas's research places a specific focus on artificial intelligence (AI) and analytics, with an emphasis on understanding the potential benefits and risks for organizations and individuals. This includes mapping the utilization of AI and analytics in promoting sustainable development and considering any associated harms throughout the entire technology value chain. Notably, Thomas is currently investigating the implications and impacts of artificial intelligence, big data, and HR analytics within the European Union.

Prior to joining Hong Kong Metropolitan University, Thomas taught at Greenwich University in London and successfully obtained his PhD from Durham University - a prestigious institution ranked right after Oxford, Cambridge, LSE and Imperial College, Thomas has also amassed invaluable practical experience as a business analyst in the United Kingdom.

Teaching Areas & Research Interests

HRM
Analytics
Artificial Intelligence
Motivation
Well-being

Selected Publications

Journal Articles

Kiu, C.T.T. and Chan, J.H. (2024), "Firm characteristics and the adoption of data analytics in performance management: a critical analysis of EU enterprises", Industrial Management & Data Systems, Vol. 124 No. 2, pp. 820-858. https://doi.org/10.1108/IMDS-07-2023-0430

Modified Date: 20 Jun, 2024
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