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The MOBIS dataset: a large GPS dataset of mobility behaviour in Switzerland

Molloy, Joseph and Castro, Alberto and Götschi, Thomas and Schoeman, Thomas and Tchervenkov, Christopher and Tomic, Uros and Hintermann, Beat and Axhausen, Kay W.. (2022) The MOBIS dataset: a large GPS dataset of mobility behaviour in Switzerland. Transportation, 50. pp. 1983-2007.

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Official URL: https://edoc.unibas.ch/93143/

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Abstract

This article presents the MOBIS dataset and underlying survey methods used in its collection. The MOBIS study was a nation-wide randomised controlled trial (RCT) of transport pricing in Switzerland, utilising a combination of postal recruitment, online surveys, and GPS tracking. 21,571 persons completed the first online survey, and 3680 persons completed 8 weeks of GPS tracking. Many continued tracking for over a year after the study was completed. In the field experiment, participants participated through the use of a GPS tracking app, Catch-my-Day, which logged their daily travel on different transport modes and imputed the trip segments and modes. The experiment lasted 8 weeks, bookended by two online surveys. After the first 4-week control phase, participants were split into two different treatment groups and a continued control group. An analysis of the survey participation shows that the technology is capable of supporting such an experiment on both Android and iOS, the two main mobile platforms. Significant differences in the engagement and attrition were observed between iOS and Android participants over the 8-week period. Finally, the attrition rate did not vary between treatment groups. This paper also reports on the wealth of data that are being made available for further research, which includes over 3 million trip stages and activities, labelled with transport mode and purpose respectively.
Faculties and Departments:06 Faculty of Business and Economics > Departement Wirtschaftswissenschaften > Professuren Wirtschaftswissenschaften > Public Economics / Public Finance (Hintermann)
UniBasel Contributors:Hintermann, Beat and Schoeman, Beaumont
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:Springer
ISSN:0049-4488
e-ISSN:1572-9435
Note:Publication type according to Uni Basel Research Database: Journal article
Language:English
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Last Modified:11 Sep 2023 06:37
Deposited On:11 Sep 2023 06:37

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