Paper
8 May 2022 An analysis of the influencing factors of tourist experience in Xinjiang self-driving campsites: taking Jiadengyu as an example of a car campsite
Yanjun Li, Dan Wang, Liyue Wu
Author Affiliations +
Proceedings Volume 12249, 2nd International Conference on Internet of Things and Smart City (IoTSC 2022); 122493I (2022) https://doi.org/10.1117/12.2637096
Event: 2022 2nd International Conference on Internet of Things and Smart City (IoTSC 2022), 2022, Xiamen, China
Abstract
In recent years, due to the rapid increase in private car ownership in China, the number of people traveling by car has doubled. This has also greatly increased the market demand for self-driving campsites and the rapid rise of the industry but the development of self-driving campsites has not as expected. Therefore, the author conducted field research and analysis on Shaanxi, Gansu, Ningxia, Qinghai, and Xinjiang along the Silk Road by reading and browsing a large number of documents and tourism websites. Among them, the most distinctive Xinjiang region is selected as the research object of this article, focusing on the preliminary construction of the factors that affecting the tourist experience of Xinjiang self-driving campsites. At the same time, the questionnaire was revised, designed and distributed to relevant experts, tourists and industry operators. SPSS23.0 software was used to perform factor analysis on the collected data. After the analysis, it is concluded that the main influencing factors and the level of influence on the experience of self-driving campsites which provides a favorable implementation basis and theoretical foundation for the reasonable developing and planning of the construction of self-driving campsites in Xinjiang.
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Yanjun Li, Dan Wang, and Liyue Wu "An analysis of the influencing factors of tourist experience in Xinjiang self-driving campsites: taking Jiadengyu as an example of a car campsite", Proc. SPIE 12249, 2nd International Conference on Internet of Things and Smart City (IoTSC 2022), 122493I (8 May 2022); https://doi.org/10.1117/12.2637096
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KEYWORDS
Analytical research

Factor analysis

Reliability

Statistical analysis

Safety

Climatology

Roads

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