Site selection of self-driving and recreational vehicle camps in China: An investigation using analytic hierarchy process and entropy

Abstract

Self-driving and recreational vehicle (RV) camps are a new form of industry module with the integration of transportation and tourism in China, thus the scientific and reasonable site selection plays an important role in the success of camps’ construction and operation. In terms of relying resources and development factors, camps can be divided into five categories: scenic-spot-based, transportation-based, environment-based, project-based and leisure and vacation-based. According to whether it is of excludability and competitiveness, the camps in China mainly embody the attribute of private products. Based on the combination of subjective evaluation and objective calculation, the evaluation model of spatial site selection is constructed and the weight of each index is calculated by using analytic hierarchy process (AHP) method and entropy coefficient method. The results show that traffic condition factor is the priority to the selection of campsite, and whether it is on the popular main self-driving route and the grade of trunk roads are the dominant indices. The second factor taken into consideration is the social factors, in which government policy supports and land cost play a key role. The third factor is the market, in which the urban economic level, partnership with the government and tourist resource conditions are of great importance. The fourth factor of the campsite selection includes natural elements, in which the quality of ecological environment and water source conditions are mostly considered. In the future, it is suggested that a camp pattern of “public goods” plus “private goods” should be built and the construction of camps in underdeveloped areas should be highly developed so as to form camp spatial network from individual points to a series of campsite and finally the campsite group in China will be set up.

Keywords

• Self-driving
• RV camp
• Product attribute
• Site selection
• Evaluation model
• AHP