Agent-Based Models (ABM) are becoming more relevant in computational
social science (CSS) due to the potential to model complex phenomena that emerge
from individual-based interactions. Most tourism theoretical models recognize the
complex nature of the tourism system, and complexity is a subject of growing interest
among researchers. Geosimulation models (GM) are presented as potential tools to
address tourism in a complex systems lens. Particularly ABM, has a GM tool, as
captured growing interest by tourism researchers, however there is little empirical
application as a tool to explore and predict tourism patterns. The purpose of the chapter
is to frame ABM in GM following a complex systems theoretical approach, in order to
increase knowledge by (i) considering the complex nature of tourism, (ii) providing
tools to explore the interactions between system components, (iii) discussing the
potential for coupling ABM and Geographical Information Systems (GIS) in tourism
research, and (iv) giving insights on the functioning of the tourist behaviours and
decision-making process through an ABM approach. Also a theoretical ABM is
developed to improve knowledge on tourist decision-making in the selection of a
destination to vacation. Tourists’ behaviour, such as individual motivation and social
network influence in the vacation decision-making process are presented. On-going
work on loose coupling of ABM and GIS is discussed.
Keywords: Agent-Based Models, Cellular Automata, Complexity, Computational
social science, Decision-making process, Distribution patterns, Exploratory
analysis, Geosimulation, Geographical Information Systems, Heterogeneity, Ifthen
rules, Individual-based, Interaction, Non-linearity, Scenario development,
Simulation, Tourism, Tourist behaviour, Tourism system.
