Based on the panel data of 41 cities in the Yangtze River Delta from 2008 to 2017, this paper constructs an evaluation indicators system for urban tourism eco-efficiency. By measuring the tourism eco-efficiency in the Yangtze River Delta urban agglomeration, we analyze its spatial-temporal evolution characteristics. Furthermore, the modified gravity model and social network analysis are introduced to explore the spatial network structure of tourism eco-efficiency and its evolution trend.The results show that:(1) The overall eco-efficiency of tourism in the Yangtze River Delta region presents a fluctuating downward trend, among which Jiangsu and Zhejiang have high eco-efficiency, Shanghai and Anhui are relatively low. The gap within the region first increased and then decreased. (2) During this decade, the spatial network structure of tourism eco-efficiency in the Yangtze River Delta has become increasingly loose. The weakening of the network connection strength has led to a decrease in the regional tourism eco-efficiency to a great extent. (3) The network centrality of cities such as Zhoushan, Huzhou, and Huangshan has always maintained a high level, and these cities have firmly occupied the core position of network. (4) The spatial association network of tourism eco-efficiency can be divided into four blocks: “two-way spillover”, “net spillover”, “net benefit” and “agent”. The synergy and spillover effect between various blocks are significant, and there is a spatial polarization trend centered on a few cities. Based on this, this paper puts forward optimization suggestions for the spatial network structure of the Yangtze River Delta urban agglomeration, in anticipation of promoting the improvement of regional tourism eco-efficiency.
The research on the coupling coordination of regional urbanization is of great significance for achieving sustainable urbanization. Based on the theories of coordinated development, this paper constructs an index system for comprehensive evaluation of the three sub-systems of urbanization (population, economy and land urbanization). Then, the entropy method, coupling coordination degree model and spatial autocorrelation analysis are used to explore the spatiotemporal characteristics of overall and pairwise coordination among population, land and economy urbanization. Finally, the geographic detector model is used to analyze the influencing factors in the urbanization process. The results show that: (1) the levels of population, land and economy urbanization in the Yangtze River Delta have been improved from 2001 to 2016. The overall and pairwise coupling coordination degrees among them also continue to improve and the stage characteristics are presented. (2) The spatial distribution of low-level and high-level coupling coordination cities shows a certain spatial dependence and a Z-shaped pattern, respectively. The spatiotemporal characteristics of pairwise coupling coordination indicate regional imbalance of the urbanization. (3) The overall coupling coordination degree of urbanization has an apparent spatial autocorrelation, with its local spatial correlation patterns dominated by the High–High and Low–Low type agglomeration. Significant differences in local spatial correlation patterns of the pairwise coupling coordination suggest that regional synergy should not be neglected. (4) The economic development level is the main factor influencing the spatiotemporal differentiation of the coupling coordination of urbanization. Location traffic conditions and population agglomeration effect are the second most influencing factors. The evolution mechanisms of coupling coordination of urbanization are affected by factors in change. The findings highlight the importance of dealing with the relationship among population, land and economy in the process of regional urbanization and have implications for promoting the integration of urban agglomerations.
On the background of climate change, studying tourism eco-efficiency of cities is of great significance to promote the green development of tourism. Based on the panel data of the three major urban agglomerations in China’s Yangtze River Delta, Pearl River Delta, and Beijing–Tianjin–Hebei region from 2008 to 2017, this paper constructed an evaluation index system and measured the tourism eco-efficiency of 63 cities by using a hybrid distance model called Super-EBM (epsilon-based measure). We compared the spatial and temporal evolution characteristics of tourism eco-efficiency in the three urban agglomerations. Furthermore, the internal factors influencing tourism eco-efficiency were explored through input–output redundancy, and the external factors were analyzed by a panel regression model. The results indicate that the tourism eco-efficiency of the three urban agglomerations in China generally shows a decreasing-rising-declining trend. Among them, the Yangtze River Delta has the highest eco-efficiency, followed by the Pearl River Delta, and the lowest in the Beijing–Tianjin–Hebei region. Moreover, there is a certain gap within each urban agglomeration. The redundancy input of labor and capital is the main internal cause of low eco-efficiency. Among the external factors, the status of the tourism industry and the level of urbanization have a positive effect on eco-efficiency, while the level of tourism development, technological innovation and investment have a negative impact on it. In the future, we must attach great importance to the development quality and overall benefit value of the tourism industry so as to achieve green and balanced development of the three major urban agglomerations in eastern China. Based on the above conclusions, this paper puts forward targeted policy implications to improve the tourism eco-efficiency of cities.
11 August 2025 in Journal of Environmental Management
Catering and urban elements have a strong spatial association. The spatial clustering and dispersal patterns of catering can effectively influence cities’ economic and socio-spatial reconfiguration. This research first introduced the concept of the ARTR (the attractiveness of residential areas to restaurants) and measured its value as well as its spatial and temporal evolutionary patterns using global and local colocation quotients. The DBSCAN algorithm and spatial hot-spot analysis were used to analyze their spatial evolution patterns. On this basis, a multiscale geographically weighted regression (MGWR) model was used to analyze the scale of and spatial variation in the drivers. The results show that (1) Nanjing’s ARTR is at a low level, with the most significant decline in ARTR occurring from 2005 to 2020 for MRs and HRs, while LRs did not significantly respond to urban regeneration. (2) The spatial layout of the ARTR in Nanjing has gradually evolved from a circular structure to a semi-enclosed structure, and the circular structure has continued to expand outward. At the same time, the ARTR for different levels of catering shows a diverse distribution in the margins. (3) Urban expansion and regeneration have led to increasingly negative effects of the clustering level, commercial competition, economic level and neighborhood newness, while the density of the road network has been more stable. (4) The road network density has consistently remained a global influence. Commercial diversity has changed from a local factor to a global factor, while economic and locational factors have strongly spatially non-smooth relationships with the ARTR. The results of this study can provide a basis for a harmonious relationship between catering and residential areas in the context of urban expansion and regeneration.