@article{ref1,
title="Spatial differentiation characteristics of regional self-driving tourism flow: a case study of central Yunnan urban agglomeration",
journal="Heliyon",
year="2023",
author="Ji, Xiaofeng and Huang, Haiqin and Chen, Fang and Li, Mingjun",
volume="9",
number="11",
pages="e21814-e21814",
abstract="The aim of this study was investigate the spatial effects of A-class scenic spots and the spatial distribution of highway networks on the influence of self-driving tour behavioral patterns in China at the urban agglomeration scale, based on big data of road traffic during three holidays. A spatial analysis method and a geographically weighted regression model were used to analyze the spatial distribution differences and influencing factors of self-driving tourism flows in the central Yunnan urban agglomeration. The results showed that holiday self-driving tourism in the central Yunnan urban agglomeration presented a typical core-edge spatial pattern. The mean value of the spatial autocorrelation coefficient was 0.54, indicating significant spatial autocorrelation. The influence of tourism resources and traffic conditions on self-driving tourism flow showed a decreasing trend from the center of the high positive value to the periphery of the main urban area of Kunming. This study reveals the spatial differentiation characteristics of self-driving tourism flows in urban agglomerations and lays a theoretical foundation for understanding flow pattern.<p /> <p>Language: en</p>",
language="en",
issn="2405-8440",
doi="10.1016/j.heliyon.2023.e21814",
url="http://dx.doi.org/10.1016/j.heliyon.2023.e21814"
}