Abstract
Public transport systems – especially demand responsive transport – lack a direct feedback possibility for customers. Contemporary approaches allow post-mortem feedback, where the consumer has to input detailed data of past travel experiences. Hence, it is hard to detect the location and time when and where the feedback was submitted, and in particular it is hard to trace the location of the incident that leads to the feedback (e.g. on which line/route, on which exact train the incident happened). Therefore we propose an approach for submitting feedback, that utilizes the current position of the customer. The approach draws on Volunteered Geographic Information (VGI), which is a special case of user–generated content coupled with participatory approaches in Geoinformation. Thus, the approach followed in this paper presents a concept that allows instant feedback, including the current position and timestamp. This approach allows the instant detection “where” an incident happened leading to costumer feedback (e.g. on which train, on which bus). A pilot implementation is tested and critically evaluated in a test region located in the municipality of Gratwein–Straßengel (Province of Styria, Austria). The experiment is conducted in a demand responsive transport system, where we monitor the feedback behavior of the customers using a smart-phone feedback application. The results show, that the concept utilizing VGI–methodologies was successfully applied to a demand responsive transport system. In addition, the results show that the approach provides instant feedback on problems and incidents for decision makers and transport managers, including the crucial information “where” and “when” something happened. In the first two weeks of operation, we received 55 customer feedbacks – of 175 ordered trips – of which the majority was positive and requested the transport service to be expanded in future.
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Dienstl, B., Scholz, J. (2019). A Concept for Smart Transportation User-Feedback Utilizing Volunteered Geoinformation Approaches. In: Nathanail, E., Karakikes, I. (eds) Data Analytics: Paving the Way to Sustainable Urban Mobility. CSUM 2018. Advances in Intelligent Systems and Computing, vol 879. Springer, Cham. https://doi.org/10.1007/978-3-030-02305-8_65
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DOI: https://doi.org/10.1007/978-3-030-02305-8_65
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