The Influence of Street-Scene Emotional Perception on Commercial Satisfaction: A Study Based on Random Forest Model and SHAP Algorithm

In cross-disciplinary research on urban planning and service marketing, the street landscape is seen as an extended service environment. However, most studies focus on the link between a single business type and one emotional dimension. This leaves the complex mechanisms between streetscape emotional perception and commercial satisfaction unrevealed. This study combines street-view imagery, Dianping point-of-interest (POI) data, and online ratings to build a dataset. It covers four main commercial categories (Catering Services, Retail and Trade Locations (RTL), In-store Service Sectors, Leisure and Experience Venues) and six emotional perceptions (Safety, Aesthetics, Wealth, Vibrancy, Depression, Boring). The study uses Random Forest (RF) regression and SHapley Additive exPlanations (SHAP) to examine how streetscape emotions influence businesses. Results show catering services are mostly affected by the Depression and Vibrancy (Dpr–Vib) link. In-store services and leisure venues are shaped by the synergy of Aesthetics and Wealth (Aes–Wth). Retail trade reveals a tension between Aesthetics and Depression. The study proposes a business-type-specific "emotion-customized" spatial intervention framework to guide urban renewal and management of mixed-use streets.