Spatial and temporal modelling of tourist movements using Semi-Markov processes

Abstract

Tourist movement is a complex process. It can be modelled from a number of different perspectives; for example, Tourism, Geography, Economics, Mathematics, Computer Sciences and Psychology. This paper aims to establish a sound methodology, using Semi-Markov processes to model the spatial and temporal movement of tourists. The objective is to understand, predict, control for, and optimise the decisions made by tourists in their choice of attractions. Semi-Markov processes have a Markov chain and a renewal process embedded within their structure, and as such, can be used to provide a wide variety of practical models. One of the outcomes of this approach is the introduction of a measure to assess the attractiveness of particular tourist attractions based on spatial and temporal interactions between the attractions. A case study conducted at Phillip Island Nature Park, Victoria, Australia is used to validate the model. The study’s results support the proposed model’s efficiency. The results are also practical and useful for assisting park managers and tourist operators with park planning and marketing decisions: for example, knowing which attractions are the most popular, how long tourists will spend at any one site; and what the likely routes are that they will follow.