A study of validation on the current POE method by using a case study in southern California
ABSTRACT: Post-occupancy evaluation (POE) is an architectural building evaluation tool that aims to improve indoor environmental quality and building performance using comparative metrics. POE has been performed to develop a better quality of human life through improving user satisfaction, productivity, and better matching of building design functions and occupants’ needs. Despite the limitations of POE research due to its significant dependence on subjective user satisfaction surveys. researchers have developed methods that combine environmental datasets that integrate an occupant's satisfaction with real IEQ data. While these efforts have enhanced POE methodology, it still is limited by one-time data collection that is unlikely to adequately take varying degrees of human environmental perceptions into consideration in a manner that is consistant and reliable. Nevertheless, what distinguishes this study is the use of advanced POE testing, which uses multiple data collection methodologies to validate the current POE method and identify the potential necessity of an improved method. A modern office in Southern California was chosen as a testbed office to conduct plural occupant satisfaction surveys and on-site measurements were simultaneously made during two months. A statistical analysis of the aggregated data was conducted with consideration of various categories such as time differences and human factors. The result of this analysis revealed that the occupants experienced different levels of environmental satisfaction at different times even though environmental conditions at their workstations remained consistent, or only marginally changed. In addition, human factors, such as age and gender, indicated a significant relationship between occupant satisfaction and changes in human IEQ perceptions. These findings suggest a comprehensive approach is recommended to diagnose current space diagnostics and to provide optimal design solutions that boost users’ well-being in a working environment.
KEYWORDS: Environmental comfort; Occupant well-being; Data acquisition; Healthy environment; Human factor