Urban agglomeration is the core area of not only regional economic development and urbanization but also human–land contradiction. Based on the population–economy–society–spatial model and the pressure–state–response model, this study develops an evaluation index system for the urbanization and eco-environment of 13 urban agglomerations in China. The urbanization index and eco-environment index are determined using the coefficient of variation method. The coupled coordination of the two indices is measured with the coupled coordination model, and the influence of the indicator factors is calculated with a geographical detector. The results reveal the following: (1) The urbanization indices of the 13 urban agglomerations in China increase year by year, and the spatial distribution pattern is high in the east and low in the west. (2) The eco-environment index shows an “S-shaped” variation trend, and the spatial difference between urban agglomerations gradually decreases. (3) The coupled coordination is mainly characterized as a mild imbalance, and the spatial distribution pattern is “balance in the east and imbalance in the west”. (4) The coupled coordination degree between urbanization and eco-environment is affected by many factors. Among such factors, economic urbanization, social urbanization, spatial urbanization, and eco-environment response are the main controlling factors. The impact of population urbanization, eco-environment pressure, and eco-environment state presents a gradual increase.
Strengthening research on urban tourism competitiveness is vital in evaluating the current situation and potential of urban tourism, maintaining the sustainable development of the tourism economy and assisting in the regional macro decision making. In this study, an index system evaluation of urban tourism competitiveness in city agglomerations across the Guanzhong Plain is established by collecting cross-section data from the years 2017 and 2010. The entropy value method is adopted to determine the index weight. Cluster analysis is performed and the spatial-temporal pattern and evolution laws of urban tourism competitiveness among city agglomerations in the Guanzhong Plain are analyzed and the geographic detector utilized to discuss the influencing factors. Results show that the spatial gradient difference of urban tourism competitiveness of agglomerations in the Guanzhong Plain is significant. In 2010, it presented the characteristic of ‘the high and middle levels having a zonal distribution from east to west, and the low level was distributed along the north and south wings’. In 2017, the characteristic of ‘polarization’ became highly prominent, that is, the scope of high-level and low-level cities expanded and the scope of medium-level cities decreased. Urban tourism competitiveness in city agglomerations across the Guanzhong Plain exhibited a trend of ‘strengthening in the east, weakening in the west’. The competitiveness of resources and management shifted aggressively and supporting factors competitiveness underwent a slight change. The urban tourism competitiveness of city agglomerations in the Guanzhong Plain is generally low, while the urban tourism competitiveness of Xi’an had an absolute advantage in city agglomerations of the Guanzhong Plain. According to the cluster analysis results, resources and management competitiveness, supporting factors competitiveness, demand conditions competitiveness, situational conditions competitiveness and urban tourism competitiveness of Xi’an in 2010 and 2017 were all at an extremely high level, which was relatively higher than the index values of other cities in the city agglomerations of the Guanzhong Plain. Tourism resources, service support capacity, infrastructure support capacity, tourism income scale, tourism reception scale and economic development power are the core influencing factors of urban tourism competitiveness among city agglomerations in the Guanzhong Plain. The single factor explanatory power of destination management indicates a downward trend while the single factor explanatory power of the ecological environment condition shows an upward trend. Tourism resources are the leading interactive factor of urban tourism competitiveness, and destination management and ecological environment condition are the most significant indicators for the collaborative effect.
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