Sustainable Tourism Analysis Based on System Dynamics Model

Abstract

In recent years, the global tourism industry has grown rapidly, but over-tourism has led to environmental degradation, increased pressure on infrastructure, and a decline in residents’ quality of life. This paper takes Juneau, Alaska, USA as an example to build a model to balance the relationship between economic benefits, ecological protection and social equity, so as to promote tourism from simple ”quantitative expansion” to ”sustainable development” . In Requirement 1, we develop a system dynamics model which aims to achieve sustainable tourism and address the issues caused by over-tourism. The model optimizes tourism economic benefits, environmental quality, and residents’ happiness, overcoming the limitations of single-objective approaches. By setting constraints such as maximum visitor numbers, minimum environmental quality and maximum taxes, the model ensures that indicators remain within reasonable limits, preventing negative impacts of over-tourism. Additionally, we develop recursive equations using dynamically linked variables (such as visitor numbers, environmental quality, and infrastructure) to simulate the complexity of the real system. To further optimize the outcomes, we also create a spending plan that allocates additional tax revenues to three core areas: environmental restoration, infrastructure upgrades, and community development projects. These spending plans directly influence environmental quality, residents’ happiness, and economic gains through the dynamic equations in the model. Based on the above analysis, we use NSGA-II algorithm to solve the model and obtain the Pareto optimal solution.Finally, we conduct sensitivity analysis to identify the most critical factors under different objectives, ensuring the model’s practicality and accuracy. Finally, we analyze the advantages and disadvantages of the model. The model’s strength lies in its comprehensive consideration of multiple factors, enabling more accurate predictions in a dynamic environment, and its operability, offering personalized optimization solutions for different tourist destinations. However, the model also has limitations, such as its dependence on data quality and quantity, which could constrain its application in real-world scenarios.