Changes in Ecotourism Flow in Hunan Province of China in the Context of COVID-19

Abstract

This study analyzed the changes in ecotourism flow in Hunan Province before and after the COVID-19 epidemic by obtaining the ecotourism route data for 2019 and 2020 from online tourism platforms such as wasp nest, poor travel, Ctrip, tuniu and qunar, and determining geographical distribution characteristics, node characteristics and network characteristics with the help of software such as UCINET, Netdraw and ArcGIS. The results revealed major changes in spatial distribution, the roles of nodes, and the structure and composition of the flow network. (1) COVID-19 has changed the spatial distribution pattern of ecotourism flows in Hunan Province. Under the influence of the epidemic, the spatial geographical concentration trend in Hunan Province decreased from 30.42 in 2019 to 28.94 in 2020, the flow in the North weakened, and the hot spots shifted to the south. In order to promote the development of global tourism in Hunan Province, we should focus on how to correctly handle the differences in tourism resources and the imbalance in tourism development between the Xiangxi region and other tourism regions. (2) The COVID-19 epidemic triggered changes of the roles of some nodes in the ecotourism flow network in Hunan Province. The comprehensive efficiency value of the node decreased from 266 to 222, indicating that crisis events such as the epidemic have caused damage to the ecotourism flow in Hunan Province, and the surrounding low-density ecotourism sites with good natural scenery have become more favored by tourists after the COVID-19 epidemic. (3) The COVID-19 situation has affected the structure and composition of the ecotourism flow network in Hunan Province. The overall network density of ecotourism flow in Hunan Province increased from 0.18 to 0.14, the degree of separation between ecotourism destinations increased, and tourists' demand for health and safety has driven the development of ecotourism flow in Hunan Province towards multinode and multiregional characteristics.