Predicting Travel Volumes for Long-Distance Coach Services Through Big Data Analytics -- A Case Study on German Public Viewing Events During the UEFA EURO 2016

Capacity planning is a key challenge for long-distance coach vendors due to the competitive market pressure. Travel-intensive events have the potential to increase the capacities for existing routes or to offer new connections. Actually, planning activities of vendors are mainly based on past-data. To improve the quality of predictions about future capacities, information from different data sources e.g. social media, geo-based information or websites has to be considered. Technologies to collect structured and unstructured information from different data sources are available. This paper presents an approach to use these technologies for capacity predictions and pricing of coach vendors in terms of travel-intensive events. To verify the approach, a case study, focused on the UEFA EURO 2016, is described. The case study is necessary to demonstrate the value of the research and to give a deeper understanding about data sources and the discussion culture of travelers in social networks.