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Journal of Letters

A Study of Tourist Behavior in Destination Selection and Distribution of Tourists Using an Agent-Based Model: A Case Study of Chon Buri Province

Publication Date

2023-11-15

Abstract

This research aims to investigate the selection of travel destinations by tourists using an agent-based model (ABM) as well as the distribution of tourists at destinations in Chon Buri Province. The ABM was developed using the NetLogo program and operated on a geographic information system (GIS). This study examined tourist behaviors via 3,200 agents that proportionally represent the number of excursionists in Chon Buri Province in 2019. The tourist agents were classified into 12 groups according to sex and age range, each having different levels of interest in destination types. In this study, we define six types of tourist destinations, with 59 destinations in total. The agents started their decision-making by randomly choosing a destination type, given a probability function representing the chances of each destination type being selected based on each agent group’s rank of interests. The agents only selected destinations from the type that they had chosen in a range of 50 kilometers from the agent's current location. Agents were released to the study area on an hourly basis, traveled at a constant speed of 60 km/h, and stayed at the chosen destination for two hours. The agents were allowed to choose destinations from 8:00 a.m. to 4:30 p.m. Based on 45 model simulations, the types of destinations that were most selected by tourist agents were natural (48%), followed by recreational (30%) and cultural and religious (17%). The largest number of tourists was at historical and shopping destinations, as these types of destinations are few in number in the study area. Model results correspond to the most observed tourist groups at five surveyed destinations. It was also found that tourists were not evenly distributed over the province but concentrated at Pattaya City and Saen Suk Municipality, where there are a large number of destinations of different types. Results from this study can be employed for tourism planning and development at a local and national scale.

First Page

1

Last Page

30

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