Background to the research project

As a result of the amendment to the Passenger Transportation Act, bus companies have been permitted to operate long-distance passenger services within Germany in addition to rail companies since January 1, 2013. Since that time, the long-distance bus market has grown continuously. However, the long-distance bus market is also highly competitive, as demonstrated by various market exits. One response to the high intensity of competition is to improve supply planning in order to exploit the demand for long-distance bus connections in a targeted manner. Travel-intensive events such as festivals, city festivals, fairs, and demonstrations increase the demand for passenger transport capacity. Targeted analysis of demand would enable long-distance bus companies to adjust the supply of long-distance bus connections according to demand in order to generate additional revenue and secure and expand their market position.

Research project

The research project addresses a current problem in the economy. Small and medium-sized long-distance bus companies need to exploit additional revenue potential in order to compete with large companies. Opportunities are offered by travel-intensive events, which create a large demand for long-distance bus capacity. To exploit demand for long-distance bus capacity, it is necessary to analyze demand with an eye to the future. Information about future demand is available in Web 2.0 - especially in social media platforms. However, specific software solutions are required to use complex Web 2.0 data generated and analyzed in real time. SMEs in particular need a tool that can be used immediately to prepare and use relevant data with limited experience and resources. Therefore, the central research question was: how can long-distance bus companies' service planning for travel-intensive events be improved by applying Big Data technologies to analyze Web 2.0 data?

Research Objective

The goal of the research project was to develop a software application for analyzing Web 2.0 data that can be used to plan long-distance bus services for travel-intensive events and test them for profitability. In this context, the term "Web 2.0" refers to the changing use of Internet content in recent years. In the context of "Web 1.0", Internet users still used Internet content purely to obtain information and were passive recipients of information. Today, in the context of "Web 2.0," Internet users are active co-creators of Internet content, act independently and produce information for other Internet users.

Benefits, innovation contribution and possible applications of the results obtained

The results enable the low-effort integration of future-oriented demand information from Web 2.0 into business practice. The prototypical software application is based on an open source software package, is freely available, independent of the operating system used and can be used without licensing costs. With the help of the research results, long-distance bus companies can secure and expand their competitive position. This is especially true for SMEs with limited experience, capacity and financial resources. For long-distance bus companies, the research result provides the following innovations: The integration of future-oriented demand information for travel-intensive events into service planning, a general improvement of service planning by using Web 2.0 data, and a profitability analysis for long-distance bus services considering future-oriented demand data for travel-intensive events.

Project partners, funding and data

The AIF-funded research project was a collaboration between the Chair of Information Systems, Processes and Systems at the University of Potsdam and the International Performance Research Institute gemeinnützige GmbH (IPRI).
Funding: 2015 - 2017