Spatio-temporal behaviour of cruise passengers at the destination: a big data approach using mobile location events

Abstract

Purpose The purpose of this paper is to provide a deeper understanding of the spatio-temporal behaviour of cruise passengers at a given destination using the city of Hamburg as a use case. Design/methodology/approach Big data in the form of passive location events from smartphones were analysed to determine the spatio-temporal behaviour of cruise tourists. The data were filtered using a definition created specifically for determining the signals of cruise passengers and were analysed using spatial statistics and network analysis methods. Findings In Hamburg, cruise passengers have a relatively small area of activity that is concentrated in the city's core tourist area. Foreign cruise passengers are less spatially concentrated than German passengers. Foreign passengers generate most of their visits at the airport and in the city's shopping areas, while German passengers are most frequently seen at the railway station and at the city's maritime experience locations. Originality/value Although numerous publications have examined the spatio-temporal behaviour of cruise passengers at the destination, to the best of the authors’ knowledge, no studies have used big data sources for this purpose. This paper uses passive location events from smartphones to determine the routes taken by cruise tourists in Hamburg, shows the strengths and weaknesses of this data source and suggests how cruise tourists can be defined from the data.