Spatial Distribution Pattern and Influencing Factors of Bed-and-breakfasts (B&Bs) from the Perspective of Urban-rural Differences: A Case Study of Jiaodong Peninsula, China

Abstract

There are significant differences between urban and rural bed-and-breakfasts (B&Bs) in terms of customer positioning, economic strength and spatial carrier. Accurately identifying the differences in spatial characteristics and influencing factors of each type, is essential for creating urban and rural B&B agglomeration areas. This study used density-based spatial clustering of applications with noise (DBSCAN) and the multi-scale geographically weighted regression (MGWR) model to explore similarities and differences in the spatial distribution patterns and influencing factors for urban and rural B&Bs on the Jiaodong Peninsula of China from 2010 to 2022. The results showed that: 1) both urban and rural B&Bs in Jiaodong Peninsula went through three stages: a slow start from 2010 to 2015, rapid development from 2015 to 2019, and hindered development from 2019 to 2022. However, urban B&Bs demonstrated a higher development speed and agglomeration intensity, leading to an increasingly evident trend of uneven development between the two sectors. 2) The clustering scale of both urban and rural B&Bs continued to expand in terms of quantity and volume. Urban B&B clusters characterized by a limited number, but a higher likelihood of transitioning from low-level to high-level clusters. While the number of rural B&B clusters steadily increased over time, their clustering scale was comparatively lower than that of urban B&Bs, and they lacked the presence of high-level clustering. 3) In terms of development direction, urban B&B clusters exhibited a relatively stable pattern and evolved into high-level clustering centers within the main urban areas. Conversely, rural B&Bs exhibited a more pronounced spatial diffusion effect, with clusters showing a trend of multi-center development along the coastline. 4) Transport emerged as a common influencing factor for both urban and rural B&Bs, with the density of road network having the strongest explanatory power for their spatial distribution. In terms of differences, population agglomeration had a positive impact on the distribution of urban B&Bs and a negative effect on the distribution of rural B&Bs. Rural B&Bs clustering was more influenced by tourism resources compared with urban B&Bs, but increasing tourist stay duration remains an urgent issue to be addressed. The findings of this study could provide a more precise basis for government planning and management of urban and rural B&B agglomeration areas.