Agent-based modelling for tourism research
Aarash Baktash,
Arthur Huang,
Efrén de la Mora Velasco,
Melissa Farboudi Jahromi and
Frida Bahja
Current Issues in Tourism, 2023, vol. 26, issue 13, 2115-2127
Abstract:
Managing tourism destinations has become increasingly challenging due to the tourism ecosystem’s complex nature. Tourism destinations can be seen as complex systems consisting of interactive agents such as tourists, tourism attractions, service providers, destination marketing organizations (DMOs), and the local communities. These agents have various types of interactions with each other in real-time. This paper introduces how the Agent-Based Modelling (ABM) approach can be used in tourism research. ABM is a computational modelling approach that examines the tourism system’s dynamic behaviour based on the agents’ interactions and simulates how the microscopic interactions lead to macroscopic phenomena. ABM can be leveraged with existing behavioural theories and various types of data to address complex topics such as sustainability and social equity. This study reviewed existing literature that adopts ABM throughout tourism planning, development, and management stages. We identified seven themes where ABM would be appropriate for studying tourism: sustainable tourism, tourist decision-making behaviour, tourist flow management, crisis management, cultural tourism management, natural tourism management, and transportation management. We further propose an agent-based modelling framework with key agents and attributes to guide the modelling process for tourism researchers and practitioners.
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:taf:rcitxx:v:26:y:2023:i:13:p:2115-2127
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DOI: 10.1080/13683500.2022.2080648
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