Study on the Correlation Characteristics between Scenic Byway Network Accessibility and Self-Driving Tourism Spatial Behavior in Western Sichuan
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Published:2023-09-25
Issue:19
Volume:15
Page:14167
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ISSN:2071-1050
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Container-title:Sustainability
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language:en
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Short-container-title:Sustainability
Author:
Zhang Bo1, Zhou Liangyu2, Yin Zhiwen1, Zhou Ao2, Li Jue2ORCID
Affiliation:
1. School of Civil Engineering, Chongqing Jiaotong University, Chongqing 400074, China 2. School of Traffic & Transportation, Chongqing Jiaotong University, Chongqing 400074, China
Abstract
The scenic byways in Western Sichuan are some of the most popular self-driving tourism destinations in China. However, the current network of scenic byways in the region is not well-coordinated with the level of regional tourism development. This paper, based on travel digital footprints, uses methods such as spatial design network analysis, GIS spatial analysis, social network analysis models, and spatial econometric models to analyze the accessibility and self-driving tourism spatial behavior characteristics in Western Sichuan. The main research results are as follows: (1) the accessibility level of scenic byways in Western Sichuan exhibits significant spatial variation, with the majority of areas demonstrating moderate to poor accessibility; (2) the network structure of self-driving tourism spatial behavior displays characteristics of low overall network density, but with a high clustering coefficient and relatively short average path length, indicating a significant small-world phenomenon. All network node indicators exhibit significant heterogeneity, with the core nodes displaying clear clustering characteristics; (3) the accessibility of scenic byways and self-driving tourism spatial behavior exhibit significant spatial spillover effects. This study analyzes the relationship between the accessibility of scenic byways and self-driving tourism spatial behavior in Western Sichuan, providing valuable insights for the planning and construction of scenic byways and the development of self-driving tour routes.
Funder
National Social Science Fund of China
Subject
Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Building and Construction
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