Tourism has become a dominant economic activity in coastal, historical, and mountainous locations. To address the negative impacts of mass tourist arrivals, this study presents an approach for promoting Sustainable Tourism Development in small, vulnerable destinations. Specifically, we focus on mitigating the adverse effects of short-stay tourism, which often leads to peak tourist densities and safety concerns. We propose a novel touristic trip design model, aiming to reduce peak tourist demand by optimizing scheduling in strategic destinations. This approach considers three critical aspects: maximizing tourist satisfaction, optimizing transport resource usage, and respecting maximum carrying capacities. Methodologically, we adopt a Network Flow Problem formulation solved using a Time Expanding Network. A Time Expanding Network provides a static representation of the network for each discrete time interval, ensuring travelers' satisfaction and the overall duration of their visit. We conducted a case study in Liguria Region, Italy, comparing our model's performance with an innovative heuristic approach. Results show the superiority of our approach in managing tourist flows and promoting sustainability. This research contributes valuable insights for achieving Sustainable Tourism Development in vulnerable touristic areas, assisting policymakers and stakeholders in making informed decisions for harmonizing tourism and environmental preservation.

Optimal Travel Planning of Short Stays in Mass Tourist Destinations

Chiara Bersani;Roberto Sacile;Enrico Zero
2023-01-01

Abstract

Tourism has become a dominant economic activity in coastal, historical, and mountainous locations. To address the negative impacts of mass tourist arrivals, this study presents an approach for promoting Sustainable Tourism Development in small, vulnerable destinations. Specifically, we focus on mitigating the adverse effects of short-stay tourism, which often leads to peak tourist densities and safety concerns. We propose a novel touristic trip design model, aiming to reduce peak tourist demand by optimizing scheduling in strategic destinations. This approach considers three critical aspects: maximizing tourist satisfaction, optimizing transport resource usage, and respecting maximum carrying capacities. Methodologically, we adopt a Network Flow Problem formulation solved using a Time Expanding Network. A Time Expanding Network provides a static representation of the network for each discrete time interval, ensuring travelers' satisfaction and the overall duration of their visit. We conducted a case study in Liguria Region, Italy, comparing our model's performance with an innovative heuristic approach. Results show the superiority of our approach in managing tourist flows and promoting sustainability. This research contributes valuable insights for achieving Sustainable Tourism Development in vulnerable touristic areas, assisting policymakers and stakeholders in making informed decisions for harmonizing tourism and environmental preservation.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1144318
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