2026-10-12T22:22:00Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33955663 2026-09-21T17:23:53Z category_21 category_272 category_39 category_45 category_734 category_106 portal_5 item_type_3 month_year_09_2026

<p>Comparative analysis of model effectiveness.</p> Yueyi Tan (22278553) Jusheng Song (22278556) Guangying Zhao (10504034) Yunxi Bai (22278559) Yan Li (23143) Xuren Wei (25084375) Biotechnology Environmental Sciences not elsewhere classified Ecology Sociology Biological Sciences not elsewhere classified Science Policy threshold &# 8209 source geospatial data service &# 8209 perception &# 8209 partial dependence plots offering actionable guidance neglecting nonlinear dynamics human perception emerges high &# 8209 changing consumer behavior quantify nonlinear effects quality aesthetic environments probabilistic association pathways ism &# 8211 shopping malls ), level perceptual attributes light &# 8209 capital &# 8209 china &# 8217 intensive retail concentrates asset retail thrives ism ), retail formats urban environments sequential pathways dependent effects perceptual synergies perceptual dimensions bn ), yield hubs widespread penetration urban redevelopment urban planners study investigates spatial density sensitive strategies scale supermarkets responding strongly machine learning linear assumptions interaction patterns intensive formats increasingly shaped function proximity facility networks <div><p>Understanding spatial competition between retail formats is vital for sustaining urban commercial vitality. In China’s rapidly evolving urban economy, the contrast between light‑asset and capital‑intensive formats within traditional retail has been increasingly shaped by urban redevelopment and changing consumer behavior. However, prior studies largely confine themselves to linear assumptions, neglecting nonlinear dynamics and complex interdependencies. They also lack systematic comparisons between light-asset and capital-intensive formats, especially when attempting to integrate objective urban features with perceptual dimensions. This study investigates how objective urban environment indicators and human perception jointly shape the spatial density of two traditional retail formats, light‑asset (convenience stores) and capital‑intensive (large-scale supermarkets and shopping malls), in Shenzhen, China. 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> 2026-09-21T17:23:24Z Dataset Dataset 10.1371/journal.pone.0358597.t002 https://figshare.com/articles/dataset/_p_Comparative_analysis_of_model_effectiveness_p_/33955663 CC BY 4.0