A Data-as-an-Asset Facility Management Framework to Support Hybrid Workplaces and Advance Sustainable Development: Case Studies at Hospitals in China
Year: 2025
Type: conference-paper
Abstract: Hybrid working that combines home, remote, and in-office working has surged after the COVID-19 pandemic. This working model is disrupting existing facility management practices to (re)shape people-centered hybrid workplaces and advance sustainable development. Collecting, integrating, processing, sharing and analyzing volume and variety of facilities and workspaces data, behavioral and activity data of occupants, environmental data and operational analytics insights remains a major challenge for stakeholders to leverage emerging technologies and digital solutions including digital twin and artificial intelligence to enhance the productivity, operational intelligence, and sustainability of hybrid workplaces. This research proposed a data-as-an-asset facility management framework to support the management and decision-making of hybrid facilities and workplaces. The framework consists of a digital twinning methodology for encoding, processing and managing static and dynamic data and domain knowledge; a service-oriented, asset-based mechanism to share and exchange hybrid workplaces data; a method to evaluate the value of collected data assets; and a cloud-based software reference architecture. The framework is developed through desktop research; interview and focus group meetings with industry leaders, facility managers and professionals; field trips; prototype development; and pilot projects. Case studies are being conducted at the hybrid workplaces of two hospitals to verify the practicality and limitations of the framework. The preliminary results show that the proposed framework can assist the stakeholders in harvesting data essentials for improving the total performance and productivity of hybrid workplaces and facilitate the engagement and contribution of various industries for achieving the UN’s Sustainable Development Goals.
Source: CIB Conferences
Authors: S. Thomas Ng, Jun Frank Xu, Cheng Zhang, Guanying Huang, Jiajian Zhang
Institution: City University of Hong Kong
Language: English
Subfield: Social Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W4411472820