Research on the Development Mechanism and Practical Path of Digital Tourism Economy Under Environmental Constraints<b></b>

Against the backdrop of the global digital transformation of tourism and the growing urgency of ecological protection, digital technology has become a crucial link in balancing tourism economic growth and sustainable environmental development. This study comprehensively adopts the literature research method, multi-case comparative analysis, and field investigation. It systematically integrates theories of digital tourism, environmental economics, and sustainable development to construct a "Digital Technology-Environmental Management-Tourism Economy-Educational Empowerment" Four-Dimensional Interactive Theoretical Model. Taking three empirical cases—Sanjiangyuan World Heritage Site in Yunnan (ecologically sensitive scenic area), Xixi National Wetland Park in Hangzhou (mature tourist scenic area), and Huangshan Geological Study Tour Base in Anhui (study tour scenario)—the research deeply analyzes the application mechanisms and effects of digital technology in environmental monitoring, passenger flow regulation, experience enhancement, and educational empowerment. The results show that through the progressive action path of "intelligent monitoring-dynamic regulation-immersive experience-educational collaboration," digital technology can increase the efficiency of ecological early warning responses by over 40%, reduce tourist flow in core ecological areas by 30%, and lower energy consumption per tourist in scenic areas by 26%. However, issues such as insufficient technological adaptability (e.g., a 23% failure rate of IoT devices in remote areas), cross-departmental data sharing barriers (less than 30% data utilization rate), and long investment return cycles (an average of 3.5 years) still significantly restrict development effectiveness. The conclusions of this study provide differentiated practical paths for constructing an environmentally friendly digital tourism economic system in different types of scenic areas and offer empirical support for improving the theory of sustainable tourism.