Building a Sustainable Yangtze River Delta: Spatiotemporal Evolution and Obstacle Factor Analysis of Coupling Coordination

Achieving the coordinated development of the digital economy (DE), the tourism industry (TI) and the ecological environment (EE) is of great significance for regional sustainable development. This paper constructs a comprehensive evaluation index system for the digital economy–tourism industry–ecological environment (DTE) complex system. Indicator weights are determined via the entropy method, and the comprehensive development levels of the three subsystems in the Yangtze River Delta (YRD) region from 2010 to 2023 are systematically assessed. Based on this, the coupling coordination degree model is applied to measure the coordination of the DTE system, and the obstacle degree model is employed to identify the key factors restricting its coupling coordinated development. The results show the following: (1) From 2010 to 2023, the overall level of comprehensive development of the DE and EE in the YRD showed an upward trend, while the TI declined significantly during 2020–2022 due to the COVID-19 pandemic. (2) In terms of temporal evolution, the coupling coordination degree rose from 0.434 to 0.676 between 2010 and 2019, steadily improving from near disorder to primary coordination; although there were fluctuations between 2020 and 2023, it remained stable at a primary coordination level. Spatially, the region exhibited a “higher in the east, lower in the west” pattern. (3) From 2010 to 2019, the primary bottleneck in coordinated development stemmed from the DE subsystem; after 2020, the degree of constraints in the TI rose rapidly, creating a dual-system constraint pattern where the DE and the TI coexist. This study provides theoretical insights and practical recommendations for fostering positive DTE interactions in the YRD and offers valuable experience for other regions. This study has limitations regarding its research scale and indicator system, and it does not account for external influencing factors. Future research could adopt municipal or county-level analyses, apply causal inference methods such as panel Granger causality and system GMM, refine the evaluation index system, integrate internal and external factors, and thoroughly analyze the underlying mechanisms governing interactions within the DTE system.