Modeling space preferences for accurate occupancy prediction during the design phase
Automation in Construction
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Cha, S., Steemers, K., & Kim, T. (2018). Modeling space preferences for accurate occupancy prediction during the design phase. Automation in Construction, 93 135-147. https://doi.org/10.1016/j.autcon.2018.05.001
The accurate prediction of occupancy during the design phase of a building helps architects to improve space efficiency by eliminating the possible under-utilization and over-crowding of space during the design use phase. However, existing models exhibit limited accuracy in occupancy prediction. A major reason for this limitation is that spatial-choice behavior is ignored or oversimplified. We therefore developed a space-preference model to explain spatial-choice behavior, with a particular focus on individual work-related activities. For this purpose, we conducted a discrete-choice experiment: 2048 observations of spatial choices were collected, and a conditional logit model was used to model space preferences. The application of the space-preference model was illustrated by two case examples, with which the merits of the model were highlighted. It was then validated in a predictive success test and a case study. The model will help architects to assess potential over-crowding and under-utilization of space according to different design options.
This work was supported by the Hong Kong Polytechnic University: [grant number 1-ZVHW]. This work was also supported by Incheon National University Research Grant in 2017.
External DOI: https://doi.org/10.1016/j.autcon.2018.05.001
This record's URL: https://www.repository.cam.ac.uk/handle/1810/283265