旅游区经济影响域界定研究——以八达岭长城旅游区为例

文章提出了旅游区经济影响域的概念和关键指标、界定模型,并选取八达岭旅游区作为典型案例区,旅游区周围的6个村落为样本点,进行现场问卷调查和深入访谈,从而获取了旅游经济指标的实测值以及样本空间坐标。然后运用旅游区经济影响指数模型和旅游区经济影响域域值模型对样本数据进行总体趋势和范围的分析。结果发现,基于户均旅游直接就业和收入标准化值的八达岭旅游区旅游经济影响域域值为2.84千米,该值代表了八达岭旅游区经济辐射范围核心部分。在此基础上,刻画出旅游经济影响域的空间结构,并探讨了空间分异的原因。

Quantitative Analysis on the Tourism Economic Impact Domain:A Case Study of the Great Wall Tourism Area at Badaling

Domain of impact is a widely used concept, mainly in meteorology, disasters, environmental protection, forest ecology, numerical calculation, network analysis, and urban studies. It refers to the spreading range of the impacts from a place or event. In this paper, the authors apply the concept to the study of the economic impact of tourism. We introduce the concept and metrics of tourism economic impact domain, which refers to those tourism areas directly affected by tourism-related economic activities, depicting an interrelated space between a tourists＇ area and surrounding communities, and can be measured in terms of tourism employment and tourism revenue. After selecting six sample villages around the Great Wall tourism area at Badaling, the authors conducted detailed data collection and site surveys in the sample villages and processed the data on the tourism economy and spatial coordinates of samples by SPSS. By using the method of tourism impact index and tourism domain value, the authors were able to analyse the tourism domain value of the Badaling tourism area, anatomized the spatial characteristics of tourism impact and described the spatial model of the tourism economic impact domain. Case study results show that, the value of economic impact domain at the Badaling tourism area is 2.84 km, meaning that the boundary of Badaling tourism area＇ s direct economic impact is 2.84 km. There are two villages within this range. The results from the tourism economic impact domain analysis basically reflect the high-intensity radiation of economic activities in the Badaling tourism area. The mechanism of the tourism domain is also presented to illustrate how those various sample villages grow under tourism impacts. First, characterized by sight-seeing oriented tourism products, the tourism resources of the Badaling Great Wall play a key role in attracting tourists, serving as the core tourism radiation source with a significant distance decay effect. Second, significant differences in the value-added aspects of primary, secondary and tertiary industries near the tourism area also result in spatial differentiation of the tourism impact domain. Third, the traffic location factors should never be neglected, because sample villages far away from the main traffic lines lose the opportunities of attracting investments in tourism and the leisure tourist market. Forth, the externalities of tourism industry agglomeration drive the formation of the tourism economic impact domain, which gradually declines with the change from the direct impact domain to the indirect influence areas. However, the quantitative analysis in the article is only an approximate assessment, due to huge differences in the population structure, tourism employment, and tourism revenue. In addition, selection of the indicators and sample villages can be further improved in the future. Perhaps the potential for tourism impact domain research should be explored via a more systematic and scientific use or the domain index system. More models should also be established, including tourism domain models of different types of tourism areas, the dynamic mechanism model of tourism impact domain and the spatial differentiation model.