Spatiotemporal Dynamics and Driving Factors of the Urban Tourismification–Transportation Quality–Ecological Resilience System: A Case Study of 80 Cities in Central China
Within China’s “Central China Rising” strategy, urban tourismification operates as a production mode that reconfigures spatial, economic, and ecological systems—mirroring global overtourism challenges seen in Barcelona and Venice, where rapid infrastructure development often prioritizes economic gai...
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MDPI AG
2025-06-01
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| author | Hexiang Zhang Yechen Zhang Ruxing Wang Xuechang Zhang |
| author_facet | Hexiang Zhang Yechen Zhang Ruxing Wang Xuechang Zhang |
| author_sort | Hexiang Zhang |
| collection | DOAJ |
| description | Within China’s “Central China Rising” strategy, urban tourismification operates as a production mode that reconfigures spatial, economic, and ecological systems—mirroring global overtourism challenges seen in Barcelona and Venice, where rapid infrastructure development often prioritizes economic gains over ecological resilience (cf. Lines 43–46). This study examines 80 central Chinese cities (2010–2021), proposing the Urban Tourismification–Transportation Quality–Ecological Resilience System (UTTES) framework. Using entropy weighting, improved coupling coordination degree (CCD), GM (1,1) forecasting, and spatial Durbin models, we analyze coordination relationships, driving factors, and mechanisms. Key findings reveal the following: (1) UTTES coordination peaked in 2019 (pre-COVID), showing a spatial “center-periphery” gradient with provincial capitals leading. (2) Projections indicate transportation efficiency as a critical bottleneck—most cities will achieve good coordination post-2026. (3) Economic activity, social restructuring, and policy support drive the system, with spatial spillovers creating dual-path mechanisms (economic growth vs. manufacturing/environmental barriers). The UTTES framework advances a replicable methodology for diagnosing Tourism–Transportation–Ecology synergies in rapidly developing regions, integrating multidimensional indicators to balance environmental governance and tourism dynamics. |
| format | Article |
| id | doaj-art-a3d19243677f4a20ab47dc94c73aa3d7 |
| institution | OA Journals |
| issn | 2073-445X |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Land |
| spelling | doaj-art-a3d19243677f4a20ab47dc94c73aa3d72025-08-20T02:21:13ZengMDPI AGLand2073-445X2025-06-01146126310.3390/land14061263Spatiotemporal Dynamics and Driving Factors of the Urban Tourismification–Transportation Quality–Ecological Resilience System: A Case Study of 80 Cities in Central ChinaHexiang Zhang0Yechen Zhang1Ruxing Wang2Xuechang Zhang3College of Tourism and Exhibition, Hefei University, Hefei 230601, ChinaCollege of Tourism and Exhibition, Hefei University, Hefei 230601, ChinaCollege of Tourism and Exhibition, Hefei University, Hefei 230601, ChinaCollege of Tourism and Exhibition, Hefei University, Hefei 230601, ChinaWithin China’s “Central China Rising” strategy, urban tourismification operates as a production mode that reconfigures spatial, economic, and ecological systems—mirroring global overtourism challenges seen in Barcelona and Venice, where rapid infrastructure development often prioritizes economic gains over ecological resilience (cf. Lines 43–46). This study examines 80 central Chinese cities (2010–2021), proposing the Urban Tourismification–Transportation Quality–Ecological Resilience System (UTTES) framework. Using entropy weighting, improved coupling coordination degree (CCD), GM (1,1) forecasting, and spatial Durbin models, we analyze coordination relationships, driving factors, and mechanisms. Key findings reveal the following: (1) UTTES coordination peaked in 2019 (pre-COVID), showing a spatial “center-periphery” gradient with provincial capitals leading. (2) Projections indicate transportation efficiency as a critical bottleneck—most cities will achieve good coordination post-2026. (3) Economic activity, social restructuring, and policy support drive the system, with spatial spillovers creating dual-path mechanisms (economic growth vs. manufacturing/environmental barriers). The UTTES framework advances a replicable methodology for diagnosing Tourism–Transportation–Ecology synergies in rapidly developing regions, integrating multidimensional indicators to balance environmental governance and tourism dynamics.https://www.mdpi.com/2073-445X/14/6/1263urban tourismificationspatiotemporal dynamicsdriving factorsurban agglomerations |
| spellingShingle | Hexiang Zhang Yechen Zhang Ruxing Wang Xuechang Zhang Spatiotemporal Dynamics and Driving Factors of the Urban Tourismification–Transportation Quality–Ecological Resilience System: A Case Study of 80 Cities in Central China Land urban tourismification spatiotemporal dynamics driving factors urban agglomerations |
| title | Spatiotemporal Dynamics and Driving Factors of the Urban Tourismification–Transportation Quality–Ecological Resilience System: A Case Study of 80 Cities in Central China |
| title_full | Spatiotemporal Dynamics and Driving Factors of the Urban Tourismification–Transportation Quality–Ecological Resilience System: A Case Study of 80 Cities in Central China |
| title_fullStr | Spatiotemporal Dynamics and Driving Factors of the Urban Tourismification–Transportation Quality–Ecological Resilience System: A Case Study of 80 Cities in Central China |
| title_full_unstemmed | Spatiotemporal Dynamics and Driving Factors of the Urban Tourismification–Transportation Quality–Ecological Resilience System: A Case Study of 80 Cities in Central China |
| title_short | Spatiotemporal Dynamics and Driving Factors of the Urban Tourismification–Transportation Quality–Ecological Resilience System: A Case Study of 80 Cities in Central China |
| title_sort | spatiotemporal dynamics and driving factors of the urban tourismification transportation quality ecological resilience system a case study of 80 cities in central china |
| topic | urban tourismification spatiotemporal dynamics driving factors urban agglomerations |
| url | https://www.mdpi.com/2073-445X/14/6/1263 |
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