This study aimed to examine the spatial structure of the tourist attraction cooperation network in the Yangtze River Delta, from the perspective of tourist flow. This study conducted spatial and social network analyses of 470 popular tourist attractions in the Yangtze River Delta region of China, accounting for the occurrence and co-occurrence of tourist attraction information in tourist travel notes. The analyzed tourist attractions show an obvious spatial agglomeration effect, including four high-density agglomeration areas and two medium-density agglomeration areas. Degree centrality, closeness centrality, and betweenness centrality were used to examine the tourism function, distribution function, and connection function of nodes in the network; nodes were divided into various types of roles according to their function. There are eight condensed subgroups, but their scales are unbalanced. In these condensed subgroups, several tourist attractions with an intermediate function can be selected as transit and stopover points on tourist routes. This study can contribute to the understanding of tourists’ spatial behavior, clarify the role and status of nodes in the cooperation network of tourist attractions based on tourism flow, and help them to formulate measures for the joint marketing of tourist attractions, and promote the development of tourism in the Yangtze River Delta region.
Based on the data of high-level scenic spots in Inner Mongolia, the methods of the nearest neighbor index, kernel density, accessibility, and spatial autocorrelation are used to systematically sort out the spatial distribution pattern, accessibility, and influencing factors of various types of scenic spots. The following conclusions are drawn from the analysis. The spatial distribution of different types of tourist attractions in Inner Mongolia is in a state of “small agglomeration and large dispersion”. The spatial accessibility of different types of tourist attractions in Inner Mongolia is generally poor, and the temporal accessibility presents an inverted U-shaped distribution over time. The county-level accessibility of different types of scenic spots in Inner Mongolia is relatively poor, basically showing an oblique distribution pattern of low in the west and high in the east. The influencing factors of the spatial distribution pattern and accessibility of various scenic spots in Inner Mongolia mainly include the natural environment, transportation network, resource endowment, and economic level. This study proposes an optimal path for accessibility according to the aspects of the design of tourism scenic areas in a circle and the construction of tourist traffic and facilities, as well as the linkage design of tourist routes.
This study explores the spatial structure of regional tourism cooperation networks among 27 cities in the Yangtze River Delta from the perspective of supply and demand. Data from the supply network were collected from official news released by the Chinese government and quotations for tour routes published by travel agencies. Travel notes published on tourists’ blog community platforms about their travel experiences were used as source data for the demand network. The degree of cooperation between the cities was analyzed based on the frequency of occurrence and co-occurrence of information on tourist attractions or cities in the Yangtze River Delta region in tourist notes, tourist route quotes, and official news. This study divides 27 cities in the Yangtze River Delta region into three categories: those where supply matches demand (e.g., Shanghai and Nanjing), nine cities where there is a demand lag (e.g., Zhenjiang), and 16 cities where there is a supply lag (e.g., Wuxi). Investigating the differences between the supply and demand networks is helpful to understand the effectiveness of regional tourism cooperation mechanisms and government policies, which is crucial for the sustainability and good governance of regional tourism.
BackgroundTourism eco-efficiency is a performance basis for evaluating green total factor productivity and sustainable development.ObjectiveThe objective of this study was to measure tourism eco-efficiency in Inner Mongolia and explore its influencing factors. The aim was to provide an accurate reference for improving the quality and efficiency of tourism in Inner Mongolia and promoting the sustainable development of the regional economy and society.MethodsTourism eco-efficiency in Inner Mongolia from 2009 to 2019 was calculated using a super-slacks-based measure (SBM) model with an undesirable output. The spatial variation function was used to explore the spatial evolution pattern of tourism eco-efficiency in Inner Mongolia, and the influencing factors of the spatial evolution were analyzed by geographically weighted regression.ResultsTourism eco-efficiency in Inner Mongolia is relatively low. Eco-efficiency values among cities in Inner Mongolia vary, and their distribution is not balanced. The structural eco-efficiency of tourism in Inner Mongolia has been consistent from 2009 to 2019. The degree of homogenization in the overall direction is relatively good. Furthermore, its spatial distribution form and internal structure evolution show a certain regularity and continuity. The pattern evolution of tourism eco-efficiency in Inner Mongolia is jointly driven by the economic level, environmental regulation, industrial structure, traffic conditions, resource endowment, and tourism reception facilities. These influencing factors show obvious spatial heterogeneity.ConclusionFrom the perspective of Inner Mongolia, the difference in the tourism eco-efficiency value from 2009 to 2019 was relatively large, but the number of effective areas in the efficiency frontier generally showed a fluctuating growth trend. The range parameters of tourism eco-efficiency showed a decreasing trend, and the spatial correlation effect of tourism eco-efficiency in Inner Mongolia showed a decreasing trend under the influence of structural and spatial differentiation.
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