Modeling space preferences for accurate occupancy prediction during the design phase

Seunghyun Cha, Koen Steemers, Tae Wan Kim

Research output: Journal article publicationJournal articleAcademic researchpeer-review

13 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)135-147
Number of pages13
JournalAutomation in Construction
Publication statusPublished - 1 Sept 2018


  • Building simulation
  • Occupancy prediction
  • Occupant behavior
  • Space utilization
  • Spatial choice behavior

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Civil and Structural Engineering
  • Building and Construction


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