Analysis of Tourists' Route Selection in Scenic Areas Based on Game Theory Model

Ruimin Ma, Lifei Yao

2023

Abstract

This paper focuses on analysing the game behaviour of tourists within the scenic area sightseeing system. It examines how tourists’ decision-making in choosing routes is influenced by their perception of crowds and guidance information. A game pay-off matrix is constructed, taking into account the impact of guidance information, to understand the decision-making process and optimal choices under different strategies. Additionally, a replication dynamic equation is established to study the evolution of route choice behaviour over time. Numerical simulations are conducted to assess the effects of guidance information on tourists’ route choices. The findings indicate that the uniqueness of the Evolutionarily Stable Strategy (ESS) depends on the magnitude of payoffs loss resulting from congestion, as conveyed through the guidance information.

Paper Citation

in Harvard Style

Ma R. and Yao L. (2023). Analysis of Tourists' Route Selection in Scenic Areas Based on Game Theory Model. In Proceedings of the 2nd International Seminar on Artificial Intelligence, Networking and Information Technology - Volume 1: ANIT; ISBN 978-989-758-677-4, SciTePress, pages 344-349. DOI: 10.5220/0012283300003807

in Bibtex Style

@conference{anit23,
author={Ruimin Ma and Lifei Yao},
title={Analysis of Tourists' Route Selection in Scenic Areas Based on Game Theory Model},
booktitle={Proceedings of the 2nd International Seminar on Artificial Intelligence, Networking and Information Technology - Volume 1: ANIT},
year={2023},
pages={344-349},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012283300003807},
isbn={978-989-758-677-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Seminar on Artificial Intelligence, Networking and Information Technology - Volume 1: ANIT
TI - Analysis of Tourists' Route Selection in Scenic Areas Based on Game Theory Model
SN - 978-989-758-677-4
AU - Ma R.
AU - Yao L.
PY - 2023
SP - 344
EP - 349
DO - 10.5220/0012283300003807
PB - SciTePress