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Regional Patterns and Hierarchical Tendencies: Analysis of the Network Connectivity of 63 Service-Oriented Tourist Cities in China
Previous studies of service-oriented tourist city networks have often focused on the analysis of the geographical distributions and service roles of important cities instead of the connections and hierarchical tendencies between different types of cities within a whole region. The current study uses big data approaches for the regional connections of 38 tourism organizations, including famous hotels, air passenger transport services, and tourism service agencies, across 63 of the most important tourist cities in China. Fuzzy c-means clustering analysis is used to define eight city arena clusters. According to the distributions of connectivity between the 63 cities, these eight clusters play different functional service roles in the urban tourism network in four hierarchies. With their “center–edge” memberships, these arena clusters are formed by the interweaved process of regional and hierarchical tourism service connections. The results here include analysis of the various service-oriented tourist cities in China and point out the geographical “gap” faced by networks. Service-oriented tourist cities need to find their hierarchies and positioning in the network, scientifically speaking, to avoid blind development and to support sustainable regional tourism development in urban areas.
Regional Patterns and Hierarchical Tendencies: Analysis of the Network Connectivity of 63 Service-Oriented Tourist Cities in China
Previous studies of service-oriented tourist city networks have often focused on the analysis of the geographical distributions and service roles of important cities instead of the connections and hierarchical tendencies between different types of cities within a whole region. The current study uses big data approaches for the regional connections of 38 tourism organizations, including famous hotels, air passenger transport services, and tourism service agencies, across 63 of the most important tourist cities in China. Fuzzy c-means clustering analysis is used to define eight city arena clusters. According to the distributions of connectivity between the 63 cities, these eight clusters play different functional service roles in the urban tourism network in four hierarchies. With their “center–edge” memberships, these arena clusters are formed by the interweaved process of regional and hierarchical tourism service connections. The results here include analysis of the various service-oriented tourist cities in China and point out the geographical “gap” faced by networks. Service-oriented tourist cities need to find their hierarchies and positioning in the network, scientifically speaking, to avoid blind development and to support sustainable regional tourism development in urban areas.
Regional Patterns and Hierarchical Tendencies: Analysis of the Network Connectivity of 63 Service-Oriented Tourist Cities in China
Hongjiu Tang (author)
2020
Article (Journal)
Electronic Resource
Unknown
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