Mining mobile application usage data to understand travel planning for attending a large event


Information and communication technology can play a crucial role in advertising large events and in making information available for the attendance experience to be attractive, easy to plan, pleasant and engaging, and to promote the other tourist attractions of the hosting place. Few studies have focused on understanding the role of mobile applications in supporting travellers’ information needs while attending an event onsite and during the preceding travel planning stage. Starting from a concrete case study, this paper discusses the utility of mining usage data collected by a mobile application to identify patterns of adoption and context-dependent usages (in time and space) that characterize different categories of large event attendees. The findings highlight the existence of classes of users with varied travel planning behaviour, ranging from users who start looking for practical information quite in advance, to users who look for information at the very last minute or just when arrived onsite. The outcomes of the study provide useful information and guidelines for designers and developers of information systems as well as for event organizers and tourism stakeholders. Suggestions include how to prepare information sources and adapt them to different classes of users, when to launch and advertise bespoke mobile services, what interaction aspects to trace to gather insights on visitors’ behaviour before and during the event. Benchmarking measures are proposed to evaluate the popularity of mobile applications for events. The research demonstrates the contribution that user behaviour analysis can provide to the field of electronic tourism management and marketing, for a deeper understanding of consumers’ behaviour and preferences that goes beyond standard analytics.

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Availability of data and material

The log data used for the research presented in the paper is owned by the two ICT companies Suggesto and Interline (Trento, Italy), which developed the information systems considered for the case study and provided access for research purposes. Availability of data is subject to their consent and to compliance with the General Data Protection Regulation in force in Italy.


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    Also here the Kruskal–Wallis test was used in place of ANOVA since the data was not normally distributed, as indicated by the skewness and kurtosis check.


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The research described in this paper was partially funded by the Suggesto Marketspace and Destinazione 4.0 projects. Suggesto Marketspace (2016-2018) was funded by the Autonomous Province of Trento under the work programme for industrial research (art. 5, L.P. n.6/1999). Destinazione 4.0 (2018–2019) was funded by the Autonomous Province of Trento under the FESR 2014-2020 work programme. We thank the two ICT companies Suggesto and Interline involved in the projects who kindly provided access to the log data and provided feedback on the research work.

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Correspondence to Elena Not.

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Not, E. Mining mobile application usage data to understand travel planning for attending a large event. Inf Technol Tourism (2021).

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  • Mobile applications
  • Data mining
  • Interaction analysis
  • Travel planning
  • Large events
  • Tourism