Agent-Based Modelling: An Approach to Integrate Emerging Tourism Interactions with the Environment

Jillian Student*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

2 Citations (Scopus)

Abstract

This chapter introduces agent-based modelling (ABM), a useful approach for looking at complex interactions between humans and their environment. Tourism is such a complex industry involving many stakeholders like tourists, accommodation providers, travel agencies, etc., working together to create a single tourism experience. Moreover, as tourism is both a global and local phenomenon, ABM helps to improve the understanding of how individual interactions result in larger phenomena. Individual decisions, such as where to go on vacation, influence the state of the destination as well as local and global transportation flows, and these feedbacks are often non-linear. Simultaneously, tourism and its ecosystem are changing through their interactions. ABM can capture heterogeneities in agent characteristics, types, and decisions as well as variations in the environmental context, providing it with the potential to assist researchers in understanding complex tourism challenges, explore potential future scenarios, and support decision-making. In this chapter, tourism as a complex system and the relevance of ABM for studying such emerging challenges will be described. In the practical demonstration, the main steps for developing an agent-based model will also be explained, and the model Coasting will illustrate the process of model building, key components of the model, and analysis tools.

Original languageEnglish
Title of host publicationTourism on the Verge
EditorsR. Egger
PublisherSpringer
Pages481-511
Number of pages31
ISBN (Electronic)9783030883898
ISBN (Print)9783030883881
DOIs
Publication statusPublished - 31 Jan 2022

Publication series

NameTourism on the Verge
VolumePart F1051
ISSN (Print)2366-2611
ISSN (Electronic)2366-262X

Keywords

  • Agent-based modelling (ABM)
  • Agents
  • Complex adaptive systems
  • Human-environment systems

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