Decoupling research of tourism economic efficiency and tourism transport carbon intensity in Yangtze River Delta urban agglomeration

This study examines whether carbon intensity in tourism transport is decoupling from improvements in tourism economic efficiency within the context of regional transportation–tourism integration. Using the Yangtze River Delta urban agglomeration as a case study, we apply the Tapio decoupling model to quantify decoupling coefficients, classify decoupling types, and trace their spatiotemporal evolution. Spatial autocorrelation and dynamic diffusion trends are further explored using ESDA and spatial kernel density methods. The geographic detector is employed to identify key factors shaping decoupling patterns. Results show that: (1) Temporally, the number of strong decoupled cities in the urban agglomeration gradually increases; while spatially, the strong decoupled areas tend to concentrate in the southwest and southeast directions. (2) Decoupling patterns are spatially polarized and path dependent, rather than evenly spread across the region. (3) Spatiotemporal factors significantly contribute to the upward convergence of the decoupling effect in urban agglomeration. (4) The level of integration not only serves as the primary factor influencing the decoupling effect but also exhibits significant explanatory power in its interaction with other influencing factors. These findings contribute to the understanding of low-carbon tourism transitions at the urban-agglomeration scale and provide actionable insights for advancing sustainable, high-quality tourism development. • Investigated the decoupling relationship between tourism transport carbon intensity and tourism economic efficiency in urban agglomeration. • Decoupling effects are not evenly distributed but exhibit spatial polarization and trajectory dependence • Spatiotemporal drivers significantly contribute to the overall improvement of decoupling performance • Examined the single and interactive factors influencing the decoupling effect over time using the geographic detector.