Differences in tourism economic development and its influencing factors among three major city clusters along the middle reaches of the Yangtze River

PLoS One. 2024 May 2;19(5):e0299773. doi: 10.1371/journal.pone.0299773. eCollection 2024.

Abstract

An in-depth study of the mechanisms governing the generation, evolution, and regulation of differences in tourism economics holds significant value for the rational utilization of tourism resources and the promotion of synergistic tourism economic development. This study utilizes mathematical statistical analysis and GIS spatial analysis to construct a single indicator measure and a comprehensive indicator measure to analyze tourism-related data in the research area from 2004 to 2019. The main factors influencing the spatial and temporal differences in the tourism economy are analyzed using two methods, namely, multiple linear regression and geodetector. The temporal evolution, overall differences and differences within each city group fluctuate downwards, while the differences between groups fluctuate upwards. Domestic tourism economic differences contribute to over 90% of the overall tourism economic differences. Spatial divergence, the proportion of the tourism economy accounted for by spatial differences is obvious, the comprehensive level of the tourism economy can be divided into five levels. The dominant factors in the formation of the pattern of spatial and temporal differences in the tourism economy are the conditions of tourism resources based on class-A tourist attractions and the level of tourism industry and services based on star hotels and travel agencies. This study addresses the regional imbalance of tourism economic development in city clusters and with the intent of promoting balanced and high-quality development of regional tourism economies.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • China
  • Cities*
  • Economic Development* / trends
  • Humans
  • Rivers*
  • Tourism*
  • Travel / economics
  • Travel / statistics & numerical data

Grants and funding

This paper received funding support from the following grants during the research process, as detailed below. 1. China Scholarship Council, China; Grant No.202306770014; The full name of each funder is Xiangqiang Li; URL of each funder website is https://sa.csc.edu.cn/verification; The funders had some roles in study design, data collection and analysis, decision to publish of the manuscript. 2. Central University Basic Scientific Research Operating Expenses Funding (Excellent Innovation Project), China; Grant No.2023CXZZ027; The full name of each funder is Xiangqiang Li; URL of each funder website is http://gs.ccnu.edu.cn/info/1039/2944.htm; The funders had some roles in study design, data collection and analysis, decision to publish of the manuscript. 3. National Natural Science Foundation of China (Youth Project); Grant No.42201266; The full name of each funder is Yingying Wang, URL of each funder website is https://kd.nsfc.cn/fundingProjectInit; The funders had a role in decision to publish of the manuscript. 4. Natural Science Foundation of Shandong Province, China (Youth Project); Grant No. ZR2021QD151; The full name of each funder is Yingying Wang, URL of each funder website is http://cloud.kjt.shandong.gov.cn/nsf; The funders had a role in decision to publish of the manuscript. 5. Guangdong Provincial Education Science Planning Project, China; Grant No.2021GXJK367; The full name of each funder is Ying Huang, URL of each funder website is https://edu.gd.gov.cn/zwgknew/gsgg/content/post_3919846.html; The funders had some roles in study design, data collection and analysis, decision to publish of the manuscript. 6. Guangdong Philosophy and Social Science "13th Five-Year Plan" 2020 Discipline Co-construction Program, China; Grant No.GD20XSH03; The full names of each funder are Ying Huang and Liangfu Long, URL of each funder website is http://www.gdpplgopss.org.cn/tzgg/content/post_608987.html; The funders had a role in decision to publish of the manuscript.