Overtourism to Equilibrium: A System Dynamics & Multi-Objective Model for Sustainable Destinations
Huanzhu Lyu, Xiao Yang, Xintong Ji
TL;DR
The paper tackles overtourism by proposing an integrated framework that couples system dynamics with NSGA-II to optimize three objectives—cumulative net revenue, final environmental quality, and final social satisfaction—across dynamic, interlinked subsystems of tourism, environment, and governance. Using 2008–2024 multi-source data, the JST model is calibrated for Juneau and Iceland, demonstrating Pareto-optimal policy blends and revealing how capacity constraints, carbon pricing, and environmental investment steer outcomes. Global sensitivity analyses (Morris and Sobol) identify carbon fees, price elasticity, and capacity limits as key levers for environmental and revenue variability, while scenario analyses illustrate trade-offs among environmental protection, infrastructure, community welfare, and marketing. The work provides a portable, data-driven decision-support tool for sustainable destination management, offering actionable guidance for balancing economic benefits with ecological integrity and social tolerance in diverse settings.
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.