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Characterizing visitor engagement behavior at large-scale events: Activity sequence clustering and ranking using GPS tracking data

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References

2008Service Quality, Satisfaction, and Intent to Return in Event Sport Tourism337 cited
2016The use of tracking technologies in tourism research: the first decade271 cited
2007Sequence Alignment as a Method for Human Activity Analysis in Space and Time231 cited
2016Understanding the tourist mobility using GPS: Where is the next place?185 cited
2013Temporal Activity Patterns of Theme Park Visitors122 cited
2013The Application of a Sequence Alignment Method to the Creation of Typologies of Tourist Activity in Time and Space90 cited
2019Spatiotemporal tourist behaviour in urban destinations: a framework of analysis80 cited
2008Activity patterns in space and time: calculating representative Hagerstrand trajectories64 cited
2018Spatiotemporal Contingencies in Tourists’ Intradiurnal Mobility Patterns51 cited
2003Managing Travel for Planned Special Events51 cited
2014Assessing Activity Pattern Similarity with Multidimensional Sequence Alignment Based on a Multiobjective Optimization Evolutionary Algorithm44 cited
2013Special events travel surveys and model development25 cited

Cited by

2022Identifying Tourist Spatial and Temporal Patterns Using GPS and Sequence Alignment Method22 cited
2025A Comparison of Tourists’ Spatial–Temporal Behaviors Between Location-Based Service Data and Onsite GPS Tracks

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13 cited

2025Deep learning to segment first-time and repeat travelers: Analyzing GPS data4 cited