Mixed-methods study examines how smart technologies improve manpower outcomes in Hong Kong's property management sector, suggesting transformative implications.
Purpose This study aims to examine how smart facilities management (FM) technologies contribute to mitigating manpower shortages and improving operational efficiency in Hong Kong’s property and facilities management (PFM) sector. It focuses on identifying the conditions, constraints and mechanisms through which digital transformation translates into realised manpower outcomes in real-world building contexts. Design/methodology/approach A mixed-methods research design was adopted, combining semi-structured interviews with nine PFM practitioners and four in-depth case studies across private residential estates, serviced apartments and public rental housing in Hong Kong. Interview insights were triangulated with case evidence, documentary review and on-site walkthroughs to assess the feasibility, adoption conditions and manpower implications of smart FM technologies. Findings Smart FM technologies yield indicative manpower savings of around 0.5–1.0 full-time positions in security, cleaning and administration. These outcomes are context-dependent, influenced by estate scale, demographics, organisational readiness and user adoption. Rather than direct labour substitution, they mainly reconfigure tasks, support predictive decision-making and strengthen artificial intelligence (AI)–human collaboration. Key barriers include high costs, privacy concerns, technical integration issues and the need for ongoing human oversight, especially in estates with more elderly residents. Originality/value This study contributes a mechanism-based perspective on digital transformation in PFM by moving beyond technology adoption and efficiency claims to explain how smart FM technologies reshape work practices and manpower structures in operational settings. By identifying and empirically validating three cross-cutting mechanisms: task reconfiguration, predictive decision-making and AI–human collaboration. The paper offers a theoretically grounded explanation of how digital transformation translates into context-dependent manpower outcomes.
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Chan et al. (2026) studied this question.
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