Introduction Understanding responsible tourism behavior in high-density urban destinations is critical for sustainable tourism development. However, limited research has examined how tourists’ psychological evaluations are situated within objectively measured urban visual environments. Methods This study adopted a multimodal design combining survey-based behavioral modeling and street-level visual analysis in Macao. Survey data from 519 non-local visitors were analyzed using covariance-based structural equation modeling to examine relationships among destination image, perceived value, perceived risk, satisfaction, attitude, and responsible tourism behavioral intention. Street-level visual indicators, including the Green View Index, Sky View Factor, and Building Enclosure Index, were derived from street view imagery using deep learning–based semantic segmentation and summarized at the functional zone level. Results Destination image, perceived value, and satisfaction were positively associated with attitudes toward responsible tourism behavior, whereas perceived risk is negatively associated with satisfaction and attitude. A zone-level descriptive comparison further suggested that visually open and green environments tended to coincide with more favorable destination evaluations, while visually enclosed environments aligned with higher perceived risk. Discussion These findings highlight the importance of environmental context in understanding responsible tourism behavior in high-density urban destinations. The observed relationships should be interpreted as contextual alignment rather than evidence of independent environmental effects or formal cross-zone causal inference.
Building similarity graph...
Analyzing shared references across papers
Loading...
Wang et al. (Thu,) studied this question.
www.synapsesocial.com/papers/69ca1280883daed6ee094e91 — DOI: https://doi.org/10.3389/fpsyg.2026.1783451
Youcheng Wang
Haoran Lyu
Yin Wu
Frontiers in Psychology
SHILAP Revista de lepidopterología
Nanfang Hospital
City University of Macau
Sustainable Development Institute
Building similarity graph...
Analyzing shared references across papers
Loading...