| 摘要: |
| 本文以陕西省乡村民宿为对象，
运用多尺度地理加权回归（Multiscale
Geographically Weighted Regression，
MGWR）模型，探讨其空间异质性特征。
结果表明：第一，乡村民宿不同价格的数
量规模呈“金字塔”结构，空间分布具有
明显差异。低价位民宿分布范围最广，中
等价位民宿集聚在西安周边，高价格民宿
主要集中在秦岭北麓，少数位于陕南。第
二，乡村民宿价格影响因素存在空间尺度
效应，人均GDP 和活动设施完备度是全
局性因素，客房面积和是否免押金是局部
变量，高等级公路密度、基础设施完备度
和建筑特色等作用范围适中。第三，民宿
本体特征对价格影响程度最大，其中硬件
设施配套大于民宿软性服务。第四，县域
高等级公路密度、人均GDP、是否免押
金等与乡村民宿价格负相关，而客房面
积、基础设施完备度、活动设施完备度对
价格具有积极作用。文章可为陕西省乡村
旅游健康高效发展和陕西省乡村全面振兴
提供理论支撑和实践指导意义。 |
| 关键词: 乡村民宿 空间分异 价格特
征 陕西省 |
| DOI：10.13791/j.cnki.hsfwest.20241227001 |
| 分类号: |
| 基金项目:陕西省社会科学基金项目（2023J038）；西北农林科技大学基本科研业务费人文社科项目（2452024346） |
|
| Spatial heterogeneity analysis and influencing factors of rural residential accommodationin Shaanxi Province |
|
YANG Huan,QI Yu,MIAO Xuan,CHAI Haoran
|
| Abstract: |
| Rural homestays serve as a pivotal component of rural tourism, and their healthy development
plays a crucial role in revitalizing idle rural resources and optimizing the rural industrial structure. In
Shaanxi Province, the development of rural homestays has achieved remarkable results. This paper takes
rural homestays in Shaanxi Province as the object and uses the Multiscale Geographically Weighted
Regression (MGWR) model to explore the influencing factors and spatial scale effects on their prices.
The results show that: 1) The spatial distribution of rural homestays in Shaanxi Province exhibits
significant imbalance, characterized by localized clustering and a “one core, one sub-core, and three
nodes”. In the Guanzhong region, the Greater Xi’an area serves as the primary agglomeration hub,
radiating to neighboring counties such as Lantian, Lintong, and Mei County. Weinan City has a relatively
independent secondary agglomeration nucleus of rural homestays surrounding the Huashan Scenic Area.
Additional clusters of homestays are observed in Linyou County, Liquan County, and Baota District,
though at a smaller scale. The quantity and scale of rural homestays at different price levels follows a
“pyramid” structure, with significant differences in spatial distribution. Low-priced homestays have the
widest distribution range, showing a continuous and extensive distribution pattern. Medium-priced ones
are concentrated in the areas surrounding Xi’an, forming a certain scale of agglomeration. High-priced
ones are mainly located in the northern foothills of the Qinling Mountains, with only a few scattered
points in southern Shaanxi. 2) The influencing factors of rural homestay prices exhibit spatial scale
effects. The bandwidths of per capita GDP and the completeness of activity facilities are 567 and 568,
respectively, indicating that they are global factors with almost no spatial heterogeneity. The intensity of
their influence on rural homestay prices generally shows a pattern of being higher in the south and lower
in the north. The bandwidths of room area and whether a deposit is required are 49 and 43, respectively,
suggesting that they are local variables with significant spatial heterogeneity in their impact on prices.
Their influence is mainly concentrated in the northern foothills of the Qinling Mountains and some areas
in southern Shaanxi. The bandwidths of factors such as the density of high-grade highways, the
completeness of infrastructure, and architectural features range from 100 to 130. These factors have a
moderate influence range, mainly concentrated in Xi’an, Baoji, and other places, and there is no obvious
spatial distribution pattern in the magnitude of their influence coefficients. 3) An analysis from the three
dimensions of the regional macro-background, neighbourhood environmental characteristics, and the
physical characteristics of homestays, it can be seen that the physical characteristics of homestays have
the greatest impact on rural homestay prices, with hardware facilities having a more significant effect
than soft services. The macro-regional characteristics also have a relatively high impact on rural
homestay prices, among which the density of high-grade highways and per capita GDP are particularly
influential. However, neighbourhood environmental characteristics have no significant influence on theprices of rural homestays. 4) At the county level, the density of high-grade highways, per capita GDP, and whether a deposit is required are negatively
correlated with the prices of rural homestays. On the other hand, factors such as room size, the completeness of infrastructure, and the completeness of activity
facilities have a positive promoting effects on rural homestay prices. The conclusions of this paper provide theoretical support and practical guidance for the
healthy and efficient development of rural tourism and the overall revitalization of rural areas in Shaanxi. Based on the spatial distribution pattern of rural
homestay prices and the spatial heterogeneity of influencing factors, this paper proposes several recommendations from two aspects: enhancing the physical
characteristics of homestays and optimizing their spatial layout. For instance, in terms of improving the physical characteristics of homestays, in line with the
market positioning of rural homestays, different price rural homestays should offer differentiated activity facilities. Moreover, the spatial layout should be
optimized following the logical approach of “driven by homestay clusters and connected by major axes”. These suggestions aim to provide useful support for
local governments in guiding the scientific pricing of rural homestays, optimizing homestays layout, improving service quality, and enhancing the
competitiveness of the rural tourism market. The conclusions of this paper provide theoretical support and practical guidance for the healthy and efficient
development of rural tourism and the overall revitalization of rural areas in Shaanxi Province. The research findings also provide valuable insights for other
regions facing similar challenges in rural tourism development, serving as a reference for policy-making and practical applications in the fields of rural
homestay management and rural tourism promotion. |
| Key words: rural homestay spatial heterogeneity price characteristics Shaanxi Province |
