Overtourism to Equilibrium: A System Dynamics & Multi-Objective Model for Sustainable Destinations

TL;DR

This paper presents a comprehensive decision-making model combining system dynamics and multi-objective optimization to promote sustainable tourism, balancing economic, environmental, and social factors in destinations facing overtourism.

Contribution

It introduces an integrated framework using system dynamics and NSGA-II, validated through case studies on Juneau and Iceland, with sensitivity analysis for policy insights.

Findings

Optimal solutions achieve up to $1.64B revenue with high sustainability indices.

Carbon fees and capacity limits significantly influence environmental and economic outcomes.

Scenario simulations show targeted policies can reduce congestion and improve sustainability.

Abstract

Overtourism poses severe challenges to popular destinations worldwide, threatening natural environments and local communities. This paper develops a decision-making model integrating system dynamics with multi-objective evolutionary algorithms (NSGA-II) to balance economic returns, environmental protection, and social satisfaction. We collect multi-source data from 2008-2024 including visitor arrivals (up to 3.1M), government revenue/expenditure (up to $10.3M), glacier retreat (220-350 ft), CO2 emissions (77K-105K tons), and social satisfaction (0.29-0.48), and establish a dynamic system with four modules: tourist behavior, government finance, environmental evolution, and social well-being. We optimize three objectives via NSGA-II: cumulative net revenue, final environmental index, and final social satisfaction. Experiments on Juneau show optimal solutions yield net revenue up to $1.64B with environmental index 0.93 and social satisfaction 0.86. Extending to Iceland reveals Pareto fronts spanning revenues $150M-$200M, environment indices up to 0.92, and social satisfaction above 0.80. Sobol and Morris sensitivity analyses indicate carbon fees and price elasticity account for over 60% of environmental outcome variance, while capacity limits explain around 90% of net revenue variability. Scenario simulations demonstrate how capacity limits and dynamic pricing on crowded attractions, combined with marketing and infrastructure investment in lesser-known sites, mitigate congestion and enhance sustainability. This work contributes: (i) an integrated system-dynamics and NSGA-II framework for sustainable tourism management; (ii) demonstrated portability via case studies on Juneau and Iceland; and (iii) global sensitivity analysis highlighting influential policy levers for decision makers.