Abstract:

Tourism resource endowment, traffic accessibility, and regional economic development are widely acknowledged as key factors shaping the spatial distribution of homestays. However, it remains uncertain whether the dominant influence and relative importance of these factors vary significantly across different regional contexts. In regions with distinct development stages, unique resource endowments, and diverse market conditions, whether the core mechanisms driving homestay agglomeration undergoes fundamental changes require further empirical investigation. To address this gap, this study examines Gansu Province—a less economically developed region in western China experiencing rapid growth in the homestay industry—as a case study. Utilizing the nearest neighbor index, kernel density estimation, spatial autocorrelation analysis, and geographical detector methods, this study analyzes the spatial distribution patterns and driving mechanisms of homestays under heterogeneous development conditions, based on POI data from 2667 homestays and 14 influencing factors. The results indicate that: (1) Homestays in Gansu Province exhibit a highly clustered spatial distribution, characterized by denser concentrations in the east and sparser distributions in the west, dual-core leadership, spoon-shaped layout, and peripheral rarity. Lanzhou and Dunhuang serve as primary agglomeration centers, with development axes along the Hexi Corridor and southeastern Gansu. Ecological barrier zones, alpine pastoral areas, desert Gobi regions, and mountainous valleys are largely devoid of homestays. (2) At the macro-municipal (county) scale, the global Moran’s I index suggests a random distribution, while at the micro scale (5-10 km), a significant short-distance agglomeration effect is observed, which has weak correlation with administrative divisions, demonstrating both agglomeration dependence and scale sensitivity. (3) Hotspots cluster in Dunhuang and along the Lanzhou-Longnan-Gannan belt, with sub-hotspots distributed peripherally. Anomalous zones, including Tianshui urban districts, Kongtong District, Xifeng District (high-low type), and Zhouqu County, Aksay County, and Min County (low-high type), surrounded by high or low values, show unbalanced development and strong growth potential. Coldspots are mainly found in central and eastern Gansu, anchored by Tongwei County and Zhuanglang County, forming a pattern of decreasing confidence from the core to the periphery. (4) Among influencing factors, non-homestay hotel density (q=0.375), scenic spot kernel density (q=0.264), and cultural/intangible cultural heritage density (q=0.188) are most significant, indicating that homestay locations depend heavily on existing accommodation infrastructure and high-quality tourism resources. While climate comfort has a limited independent impact, it acts as a latent amplifier notably enhancing the effects of other drivers (e.g., interaction q-value with non-homestay hotel density reaches 0.548). (5) In less economically developed regions with abundant ecological and cultural resources, such as Gansu, homestay development follows a synergistic logic of facility-resource-environment interaction rather than relying solely on market demand or capital input. This study offers empirical insights into the unique development patterns of the homestay industry in underdeveloped areas and provides guidance for optimizing regional homestay layout and formulating differentiated policy approaches.

Key words: homestay, spatial analysis, clustering characteristics, Gansu Province