Impacts of human and spatial factors on user satisfaction in office environments
Abstract Post Occupancy Evaluation (POE), as an architectural design decision tool, utilizes data concerning multiple users' satisfaction in conjunction with indoor environmental components to develop a better quality of human life. However, one of the limitations of POE that is frequently pointed out is its excessive reliance on surveys and general solutions, without a full understanding of the occupants' physiological characteristics and pertinent environmental performance/conditions. This lack of awareness may lead to irrelevant modifications and the occupants' dissatisfaction with indoor environmental quality (IEQ). Therefore, this study suggested an integrated POE, that combined a quantifiable environmental dataset to indicate each individual occupant's satisfaction with each IEQ element. At 411 workstations in modern offices located in Southern California of the U.S., on-site IEQ measurements and user satisfaction surveys were conducted. Statistical analyses of the collected data were also conducted within specific categories of building types, spatial attributes, and human factors. These analyses revealed significant relationships that exist between human factors and IEQ satisfaction, as well as environmental conditions, including gender, age, workstation location, etc. These relationships could be ranked in accordance with the impact that sensitivities of individual IEQ elements using a decision tree algorithm, have on human physiological conditions. These findings suggested a hierarchical approach as an optimal design solution to maximize the occupants' well-being in their workplace environments. Therefore, these results reinforced the necessity for an integrated POE with consideration of human and environmental factors in order to provide enhanced/optimal IEQ design solutions for specifically-targeted population and spatial conditions. Highlights This study showed significant relationships existing between IEQ satisfaction and human factors. The relationships appear to be ranked in accordance with the sensitivity of IEQ to human factors. Females seem to prefer higher air velocities within a moderate range, as compared to males. A classification analysis supports the necessity for a POE to focus on a specifically-targeted IEQ solution. Human factors, and lighting and air quality were found to be key parameters in considering IEQ control and design.
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