A Method for Evaluating the Architectural Quality of Storefronts Using Statistical Methods

Abstract

Due to the complexity and long-life cycle of architectural projects, the evaluation of architectural performance is an irreplaceable part of design. Existing systematic building evaluation methods mainly focus on structural, environmental, and economic factors, while ignoring the establishment of evaluation systems for subjective factors such as aesthetics and context. This is partly due to the multidisciplinary complexity of human behavior studies and partly due to the difficulty of quantifying subjective data. It leads to the fact that designers and design review boards have to pay extra time and capital costs to deal with these unclear criteria. This thesis aims to establish an architectural evaluation system based on qualitative and quantitative research into different features of architectural facades, such as color, geometry, etc. Focusing on one building type, small-scale commercial storefronts, and using statistical methods, we build mathematical models to describe and predict people’s aesthetic preferences for key design criteria. We plan to leverage quantitative methods to help establish a system for evaluating aesthetic choices that design review boards can use to make their decisions more consistent across projects and jurisdictions, and to fill the gap between them and designers.