<p>Variable definitions and calculation method.</p>

Using multi‑source geospatial data and an integrated framework combining XGBoost, SHAP, Partial Dependence Plots (PDP), Interpretive Structural Modeling (ISM), and Bayesian Networks (BN), we quantify nonlinear effects, interaction patterns, and probabilistic association pathways. Results reveal distinct locational logics: light‑asset retail thrives through widespread penetration, responding strongly to competition intensity, service‑function proximity, and perceptual synergies; capital‑intensive retail concentrates in high‑yield hubs, driven by facility networks, accessibility, and high‑quality aesthetic environments above defined thresholds.

Human perception emerges as a core determinant, accounting for up to 28.95% of explanatory importance, often exerting threshold‑dependent effects. The ISM–BN analysis uncovers multi‑entry vs. sequential pathways to spatial clustering across formats. Findings advance retail location theory by linking built‑environment metrics with street-level perceptual attributes, offering actionable guidance for urban planners to tailor format‑specific, perception‑oriented, and threshold‑sensitive strategies for sustainable retail ecosystems.</p></div>