Tropical Geography ›› 2020, Vol. 40 ›› Issue (1): 154-163.doi: 10.13284/j.cnki.rddl.003208

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Relationship between Tourism Industry Agglomeration and Regional Tourism Economic Growth: Based on China’s Provincial Panel Data during 2001-2017

Zhang Shuwen, Chen Qinchang, Wang Kai()   

  1. Tourism College of Hunan Normal University, Changsha 410081, China
  • Received:2019-05-06 Revised:2019-10-21 Online:2020-01-10 Published:2020-02-24
  • Contact: Wang Kai E-mail:kingviry@163.com

Abstract:

Due to the comprehensive effect of a number of factors, the interaction mechanism between tourism industry agglomeration and regional tourism economic growth is becoming increasingly complex. It is thus crucial to explore the relationship between them from a spatial dimension so as to promote the coordinated development of the regional tourism economy. This study used composite location quotient to judge the level of regional tourism industry agglomeration to bring the variable of tourism industry agglomeration into the spatial lag term. Using the spatial autocorrelation analysis method, the spatial correlation characteristics regarding tourism economic growth of China’s 30 provinces from 2001 to 2017 was comprehensively researched. A spatial Durbin model was constructed to explore the influencing factors of regional tourism economic growth and categorically analyze the spatial spillover effect of tourism industry agglomeration on regional tourism economic growth. The results showed that: 1) The agglomeration of the tourism industry in Beijing, Tianjin, Shanghai, Hainan and Yunnan has always been at a high level, while the opposite applies to Qinghai, Jilin, Ningxia, Inner Mongolia and Xinjiang, which are essentially at a low level. The agglomeration of China’s overall tourism industry shows a fluctuating upward trend and the gap among provinces is gradually decreasing. 2) Tourism economic growth has a significant spatial correlation in China. Local spatial distribution is dominated by H-H and L-L types. The provinces of Yangtze River Delta, Pearl River Delta and Bohai-sea Rim basically belong to the “H-H” and “H-L” types, while the northwest and northeast provinces are mostly distributed in the “L-L” category. The central and southwest provinces are mainly distributed in the first and second quadrants. Some southwest provinces have transformed from “L-H” to “H-H,” while the provinces of Anhui, Jiangxi and Hainan always fall into the “L-H” category. 3) The level of regional economic development, urbanization, industrial structure, and regional innovation capability in the province and its adjacent provinces are important factors to promote tourism economic growth. Although the agglomeration of tourism industry significantly promotes the growth of tourism economy in the province, it negatively affects the adjacent provinces. Transport facilities have a negative effect on tourism economic growth in the province but have no significant effect on adjacent provinces. The effect of regional openness on tourism economic growth is not significant. According to the research results, some targeted recommendations are proposed to promote the coordinated and symbiotic development of the regional tourism industry. This study avoids the limitations of traditional panel models in spatial analysis and strengthens the influencing of regional spatial correlation and spatial “spillover effect” on the research results. However, due to space constraints, only some factors that affect the economic growth of tourism are discussed and the paper fails to specifically consider the differences in tourism development among provinces. Due to the spatial heterogeneity of the tourism industry, it is recommended that the spatial spillover effect and the differences of influencing factors in different types of tourism economic growth regions are further explored in the future.

Key words: tourism economic growth, tourism industry agglomeration, spatial Durbin model, spillover effect

CLC Number: 

  • F592.99