BOSSA: A multidimensional post-occupancy evaluation tool

Research findings point to three methodological shortcomings of current post-occupancy evaluation (POE) tools: (1) contextualizing results, (2) adding instrumental data side by side to survey results and (3) producing meaningful feedback to its key stakeholders. This paper introduces the holistic BOSSA (Building Occupants Survey System Australia) and tools developed under this project's scope in close collaboration with industry. It aims to present and discuss the statistical analysis used in the BOSSA tool, distilling the survey results down to nine indoor environmental quality (IEQ) dimensions and their association with four overall indices. Principal component analysis (PCA) extracted nine IEQ dimensions that were uncorrelated with each other: spatial comfort, indoor air quality, personal control, noise distraction and privacy, connection to the outdoor environment, building image and maintenance, individual space, thermal comfort, and visual comfort. Four separate multiple regression analyses were conducted, one for each global evaluation item as an independent variable: work area comfort, building satisfaction, productivity and health. This statistical analysis provided the rational basis of BOSSA's scoring system, designed to simplify how occupant survey results are communicated to key stakeholders from the property industry and researchers.;Research findings point to three methodological shortcomings of current post-occupancy evaluation (POE) tools: (1) contextualizing results, (2) adding instrumental data side by side to survey results and (3) producing meaningful feedback to its key stakeholders. This paper introduces the holistic BOSSA (Building Occupants Survey System Australia) and tools developed under this project's scope in close collaboration with industry. It aims to present and discuss the statistical analysis used in the BOSSA tool, distilling the survey results down to nine indoor environmental quality (IEQ) dimensions and their association with four overall indices. Principal component analysis (PCA) extracted nine IEQ dimensions that were uncorrelated with each other: spatial comfort, indoor air quality, personal control, noise distraction and privacy, connection to the outdoor environment, building image and maintenance, individual space, thermal comfort, and visual comfort. Four separate multiple regression analyses were conducted, one for each global evaluation item as an independent variable: work area comfort, building satisfaction, productivity and health. This statistical analysis provided the rational basis of BOSSA's scoring system, designed to simplify how occupant survey results are communicated to key stakeholders from the property industry and researchers.;