Wenjing Feng

Ms. Wenjing Feng


Research Focus & Metrics

Academic Career Length

4Years (2023-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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2 March 2023 in Sustainability
Verified
Journal Article
Open access
PDF file
HGHuixin Gong
Huixin Gong
YZYaomin Zheng
Yaomin Zheng
JSJinlian Shi
Jinlian Shi
WFWenjing Feng
Wenjing Feng
HGHuixin Gong
Huixin Gong
XHXiankai Huang
Xiankai Huang
Tourism is linked to multiple dimensions, such as the economy, society, and environment, and the relationships among its influencing factors are complex, diverse, and overlapping. This study constructed an evaluation index system to measure the degree of coordinated development of tourism, transportation, and the regional economy, then built a tourism-transportation-based Spatial Durbin Model (SDM) regarding the process of the coordinated development of tourism in the Beijing-Tianjin-Hebei region (BTHR) from 2010 to 2020. This paper explains the current status of sustainable tourism development in the BTHR and the impact and spillover effects of transportation on tourism development. The results show that the normalized tourism coordinated development index (NTCDI) of the BTHR increased from 13.61 in 2010 to 18.75 in 2019, then decreased to 14.45 in 2020. The results of SDM show that different transportation modes have different spillover effects on tourism. Specifically, civil aviation transportation has a positive impact and significant spillover on a city’s tourism revenue (TR), while high-speed railway transportation has a negative spillover effect. The model results also show that the degree of openness of the city and city economic development level have significant positive effects and spillover effects on tourism development. Finally, the implications of related variables are discussed, and some suggestions are put forward on tourism development in the BTHR. However, there are some limitations in this study. In the future, international cooperation and data sharing will be strengthened, and multivariate methods such as social network analysis, artificial intelligence, and machine learning will be further integrated to achieve accurate simulation and prediction of the spatial spillover effects of tourism transportation.