Mapping the pulse of urban nighttime economy: spatial patterns and behavioral insights in Kunming, China

The nighttime economy has become a crucial component of urban vitality and consumption growth, yet a comprehensive understanding of its spatial organization and consumer behavior patterns remains limited, particularly in developing cities. This study proposes a dual-perspective framework integrating spatial analysis and behavioral mechanisms to examine nighttime economy activities. Using multi-source heterogeneous data including nighttime light imagery, Points of Interest (POI), and questionnaire surveys, this research investigates the spatial differentiation characteristics of Kunming’s nighttime economy and its influencing factors through Geodetector and Geographically Weighted Regression (GWR) models. The findings reveal a distinctive “large aggregation, small dispersion, and multiple centers” spatial pattern, where commercial shopping plazas, school agglomeration areas, residential clusters, and tourism-leisure areas form interconnected economy cores. Land-use mix, public service facilities, and transportation accessibility emerge as primary drivers, with interaction effects among factors significantly amplifying their explanatory power. The dual-perspective approach uncovers important discrepancies between spatial patterns and behavioral preferences: while urban spatial quality factors show limited geographical impact, questionnaire results indicate strong consumer preferences for these elements. Behavioral analysis reveals significant demographic heterogeneity, with women prioritizing accessibility and service diversity while younger groups favor functional intensity. These findings underscore that creating vibrant nighttime economies requires balancing spatial optimization with diverse consumer preferences. The integrated framework provides empirical evidence for developing nighttime economy strategies that optimize urban spatial configurations while responding to differentiated demographic needs.