Simulation of tourists’ spatiotemporal behaviour and result validation with social media data

Abstract

This study explores the pattern and formation mechanism of tourists’ spatiotemporal behaviour by modelling, which is crucial for tourism transportation planning and management. The tourism utility maximization principle and tourism demand spillover effect are introduced to explain personal spatiotemporal behaviour. Based on the mathematical description of agent behaviour and simulation environment, an Agent Based Tourist Travel Simulation Model (ABTTSM) is systematically established to include an evaluation of the impact of a new high-speed rail operation in a region of high tourist attraction. Novel spatiotemporal data from social media is employed to test the simulation results. It is found that the transfer probability matrices of the simulation results and social media data are highly correlated and, as a consequence, the tourism circle division is almost unanimous. This means the ABTSM can effectively simulate tourists’ spatiotemporal behaviour and be applied in the planning and management of tourism and transportation.

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