Using innovations to understand tourist mobility in national parks

Abstract

Technological advances have had profound impacts upon tourists’ mobility. However, until recently, there has been a gap between technological advances and their integration into tourism research methods. This paper addresses this gap by presenting a research method that utilised an application (app) equipped with a synthesised demographic survey and Global Navigation Satellite System (GNSS) technology. This enabled automated tracking of tourists’ behaviour for their entire stay within the island state of Tasmania, Australia. This paper focuses on tourists’ movement within the well-known Freycinet National Park. The highly detailed granular data were assessed in three phases, revealing segments of tourists more likely to use the walking tracks, those more and less likely to visit during peak crowding times and finally, the development of an automated spatio-temporal dependence model via a machine-based learning environment, designed to operate in real time. The paper details the implications that innovative methodologies such as this may offer natural resource managers and tourism authorities, particularly in terms of locating, assessing and ultimately alleviating crowding and overtourism.

Keywords:

• Visitor mobility
• GNSS technology
• national parks
• tourist movement
• visitor tracking
• crowding

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Anne Hardy

Associate Professor Anne Hardy is the Director of the Tourism Research and Education Network (TRENd) at the University of Tasmania. She is currently undertaking research in three areas: the neo-tribal behaviour of tourists; sustainable tourism; and tracking tourists’ movement using integrated GPS tracking and survey technology. She is the lead investigator on the Tourism Tracer project (www.tourismtracer.com) that has received international acclaim and won numerous awards; it is the first research project to track tourists across an entire destination for the duration of their stay. Her research has been published widely in academic journals, books and via a variety of media channels. Her approach to research seeks to extend knowledge in a two way direction between the tourism industry and academia.

Jagannath Aryal

Dr. Jagannath Aryal is a Senior Lecturer in Spatial Sciences at the University of Tasmania. His current research focus is on application of spatial and temporal analysis in understanding various processes within data analytics environment. The application areas are tourist behaviour, and information extraction in hierarchy from Earth observation images with an emphasis on environmental management. His research has been published widely in high impact spatial sciences and highly technical IEEE academic journals. He is the investigator on the Tourism Tracer project overseeing the spatial and temporal aspects. His research contributes towards advancing knowledge in Geographic Information (GI) Science and Earth Observation data modelling.