Data-Driven Design Framework for Hybrid Workspaces

The modern office is a complex system that involves dynamic interactions between the design of physical environments and its occupants, serving diverse functionalities and expectations. Office design is shaped by social, economic and technological transformations, as well as organisational interests and individual preferences. The COVID-19 pandemic has accelerated the evolution of office design through a forced large-scale ‘work from home’ experiment. In the post-pandemic time, the conventional ‘office’ concept is being reconsidered as advanced digital technologies have eased location constraints of working, while the term ‘workspace’ has gained prevalence, representing a broader idea of physical and virtual work environments that accommodate hybrid working models. The shift towards hybrid working, as documented in many studies and reports, reflects employees’ desires for flexible work arrangements and employers’ interest in boosting productivity and fostering a positive organisational culture. These evolving dynamics are expected to drive a transformation in workspace design, raising critical questions about the future role of offices and the need for design strategies that emphasise flexibility, occupant well-being and sustainability. This doctoral project investigates the workspace design and space planning for the hybrid working setup. It integrates multi-source datasets, including occupancy levels, environmental conditions, spatial structures, human preferences and subjective comfort votes, to develop an evidence-based data-driven design framework. The framework aims to support the creation of physical workspace design strategies that align with emerging demands. A flexible co-working space in London is applied as a contextualised case study. The project is delivered in three parts: 1) analysing the shifts in work pattern, workspace preference and design for the future; 2) exploring the contextualised quantitative evidence collected from an experimental hybrid flexible workspace; and 3) formulating a data-driven framework to analyse and predict occupants’ seat preference and inform user-centric space design and planning of offices. This work was developed from 2020 to 2023, during the COVID-19 pandemic and the subsequent period of its long-lasting impacts. This thesis presents a review of the evolution of workspace design, archetypes of modern knowledge workers and their design preferences, as well as a set of empirical chapters based on the case study. The experimental works involve extensive data collection over more than a year, demonstrating the application of data-driven workflows. Key findings reveal that spatial and environmental design features such as the number of other seats in visual field (‘Degree’), access to facilities and air temperature significantly impact occupancy levels. Intriguingly, mismatches between the human-indicated preferences and actual occupancy patterns, highlighting the importance of embedding multi-source evidence-based insights in optimising workspace design. This thesis offers unique insights for designing and retrofitting modern workspaces in the novel context of hybrid working.

Name dc:type.qualificationname

Doctor of Philosophy (PhD)

Level dc:type.qualificationlevel

Doctoral

Grantor dc:publisher.institution

University of Cambridge

Year dc:date.issued

2024

Author dc:creator

• Pan, Jiayu

Advisor dc:contributor.advisor

• Bardhan, Ronita

• Architecture
• Future of work
• Hybrid working
• Interior design
• Office
• Space planning

Licence

• https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/b278e072-13eb-408c-8e4b-53fd9f7f6701/download
• https://www.rioxx.net/licenses/all-rights-reserved/

Language dc:language

eng

Author Identifier

0000-0003-2011-6206

OAI identifier oai:identifier

oai:www.repository.cam.ac.uk:1810/373701