This study aims to explore the influence of user behavior on sustainable design strategies and proposes a framework for optimizing design interventions. User behavior data regarding energy use, resource consumption, and waste management were collected through surveys, in-depth interviews, and virtual reality simulations. K-means clustering and Principal Component Analysis (PCA) were employed to systematically identify user behavior patterns. The findings reveal three distinct user groups: environmentally conscious, economically driven, and neutral/passive. Experimental results validated the effectiveness of various design intervention strategies—such as behavioral incentives, interactive feedback, and visual prompts—in increasing the frequency of energy-saving actions and reducing energy consumption. The behavioral incentive strategy showed the most significant impact, reducing energy consumption by 20% and achieving the highest user satisfaction. Through multiple regression analysis and ANOVA, the statistical significance of the behavioral incentive strategy was further confirmed. The innovation of this study lies in optimizing user behavior through customized strategies and proposing a combination of interventions to achieve greater energy savings. This provides new theoretical and practical support for sustainable design practices.
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Zhou et al. (2024) studied this question.
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