Author(s):
Rongxu Qiu* - University of Lethbridge
Wei Xu -
Shan Li -
Abstract:
Modeling and predicting the tourist flow pattern can generate important information for tourism management and infrastructure development. The tourism destination and visit duration are decided by individual tourists whose available time and money as well as preferences vary greatly. Individual tourism decisions at micro level often lead to complex tourist flow direction and scale. Such macro-scale complexity emerged from simple microscopic personal activity proves to be difficult to model using traditional statistical methods. Agent-based Modeling is especially suited to address this problem as it is essentially using a bottom-to-top modelling approach. This paper presents an Agent-based model that simulates tourist flow diffusion process in a defined spatial and temporal space. The model starts at building simple tourist agents, whose main activates are selecting tourism destinations and organizing tourism schedule under the limitation of available money and time. The destination manager agents are created, whose responsibilities are to alert tourists about the crowdedness of the tourism destinations and or to post advertisements to attract tourists. A regional tourism flow model was developed to simulate the decisions and behaviours of these agents and predict tourist flow direction and distribution. The model was applied to Sichuan province, China, where there are 41 class A tourism destinations. Under different decision making scenarios, the results of model simulations show that NW, NE, SE and SW are three main directions of tourist flows and crowd-alert would help regulate the tourist flow and tourism distribution pattern effectively except when long-distance tourists dominate.
