The contradiction between ecological protection and tourism development in ecotourism is a common challenge in the field of global sustainable development. As an important ecological barrier in the Guangdong-Hong Kong-Macao Greater Bay Area, a certain scenic area was selected as a "National Ecotourism Demonstration Zone" in 2023, but its tourist satisfaction rate was only 3.2/5 in 2024, highlighting the structural imbalance between protection and development. Based on the theory of externality, this study constructs an economic policy modeling framework of "quantifying the positive externality of ecological protection-pricing the negative externality of tourism development", and through network comment sentiment analysis, policy text coding, and ecological data assessment, combined with the calculation of elasticity coefficients (such as the correlation between rainforest coverage and tourism revenue) and marginal cost accounting (such as the impact of tourist overload on ecological restoration), it reveals the core issues: tourists' "value-for-money anxiety" regarding tickets and services, insufficient transparency of ecological compensation in policy implementation, and overloading of ecological pressure in high-density areas. Through this economic policy model, the balance between protection and development is transformed into calculable policy parameters, and based on this, a four-dimensional collaborative governance system of "policy-technology-community-enterprise" is innovatively constructed, and targeted countermeasures such as an ecological access negative list and dynamic compensation standards based on model calculations are proposed. This research provides a localized solution for karst landscape scenic areas to break through the "protection-development-value-added" dilemma. The economic policy modeling logic has been verified through cross-border case comparisons with Costa Rica and Zhangjiajie, demonstrating cross-regional adaptability. It responds to the United Nations' "Technology Empowering Sustainable Tourism" initiative and provides a quantifiable decision-making tool for the sustainable development of global ecotourism.
Jundi Chen (Mon,) studied this question.