Spatiotemporal analysis of regional tourism development: A semiparametric Geographically Weighted Regression model approach

《Spatiotemporal analysis of regional tourism development: A semiparametric Geographically Weighted Regression model approach》

打印

关键字: Regional tourism development; Semiparametric GWR; Spatiotemporal modelling; Local; Spatiotemporal lag; Jiangsu province; HIGH-SPEED RAIL; SPATIAL-DISTRIBUTION; ECONOMIC-GROWTH; INBOUND TOURISM; BIG DATA; CHINA; IMPACT; URBANIZATION; DETERMINANTS; ASSOCIAT

作者单位: [Jin, Cheng; Huang, Zhenfang] Nanjing Normal Univ, Sch Geog Sci, Nanjing 210023, Jiangsu, Peoples R China. [Jin, Cheng; Huang, Zhenfang] Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Jiangsu, Peoples R China. [Jin, Cheng; Huang, Zhenfang] Nanjing Normal Univ, Minist Educ, Key Lab Virtual Geog Environm, Nanjing 210023, Jiangsu, Peoples R China. [Xu, Jing] Nanjing Xiaozhuang Univ, Tourism & Social Adm Coll, Nanjing 211171, Jiangsu, Peoples R China. Xu, J (reprint author), Nanjing Xiaozhuang Univ, Tourism & Social Adm Coll, Nanjing 211171, Jiangsu, Peoples R China. E-Mail: xujing@njxzc.edu.cn; huangzfang@njnu.edu.cn

摘要: Tourism development is an important topic within tourism and regional studies. However, previous studies have lacked focus regarding the coexistence of spatial and temporal effects, where the mixed analysis of global and local influencing factors has been limited. This paper employs a semiparametric GWR model to explore the spatiotemporal relationships between regional tourism economy and influencing variables. Results indicate that in the areas of better tourism economic development, spatiotemporal lag factors play a key promotion role, while in the areas of lower tourism economic development, spatiotemporal lag factors play a restraining role. In comparison with traditional analysis methods, semiparametric GWR was found to be superior in analyzing regional tourism economies as it accounts for spatiotemporal relationship at both global and local scales.