JOURNAL OF NATURAL RESOURCES ›› 2021, Vol. 36 ›› Issue (7): 1792-1810.doi: 10.31497/zrzyxb.20210712

• Special Feature on "Innovation and Development of Red Tourism Resources of China" • Previous Articles     Next Articles

Spatio-temporal evolution and influencing factors of Chinese red tourism classic scenic spots network attention

TANG Hong1,2(), XU Chun-xiao1()   

  1. 1. College of Tourism, Hunan Normal University, Changsha 410081, China
    2. School of Economic and Management, Tongren College, Tongren 554300, Guizhou, China
  • Received:2021-02-18 Revised:2021-04-20 Online:2021-07-28 Published:2021-09-28
  • Contact: XU Chun-xiao;


The network attention of red tourism classic scenic spots in 31 provinces (autonomous regions and municipalities) of China from 2011 to 2019 was obtained by means of "Baidu Index". The spatio-temporal evolution characteristics and the preference degree of the network attention of the red tourism classic scenic spots were analyzed through coefficients of scenic spot preference. The influence mechanism of the changes in the network attention of the red tourism classic scenic spots was revealed by using panel data regression model and geographic detector model. The research found that: (1) In terms of time series, the network attention of red tourism classic scenic spots continuously increased from 2011 to 2019, with obvious seasonal differences, showing an "M"-shaped variation form. (2) From the regional perspective, network attention of red tourism classic scenic spots in the eastern-central-western regions showed obvious gradient-descending characteristics. The regional differences show a decreasing trend from east, west to center, with a relatively balanced spatial structure. The majority of eastern provinces are located in hot spots, central provinces are mostly at an average level, and western provinces are in cold spots. The eastern and western regions have relatively stable order series, the central region mostly showed an upward trend, and there are certain seasonal differences between provinces, but the time series do not change greatly. (3) From the perspective of scenic spots, the inter-monthly variations of scenic spots are divided into three types, namely, unimodal type, bimodal type and multimodal type. The seasonal difference of unimodal type is significant, but the seasonal difference between bimodal type and multimodal type is small. The preference of scenic spots with a "pyramid" structure is characterized by "multi-center" distribution with a relatively stable pattern on the whole. (4) Regarding influencing factors, the contribution is listed in the order of the development level of the tourist source network>population size>education level>economic development level. But the influence of the tourism Engel coefficient is not significant. The number of star-rated hotels in the destination and tourist level and the transportation accessibility outside the city are important influencing factors. The informatization level, air quality, travel agency and public management ability are the primary influencing factors.

Key words: red tourism classic scenic spots, network attention, spatio-temporal evolution, influencing factor