While public transportation networks are becoming more integrated and convenient, they are also turning more stakeholder-intensive and complicated to manage, with ticketing revenue allocation (revenue sharing) being one of the major complexities. Do you want to eliminate the following challenges to split ticket revenue more effectively?
- Inaccuracy of data due to human errors and biases.
- Limited knowledge of passenger behavior.
- Significant manual effort to collect and analyze the data that is time-consuming and resource-intensive.
- Inefficient data sharing.
If the answer is “yes,” let us explain how by starting with an example of a recent experience in Germany: the 9-Euro-Ticket.
In response to rising consumer goods and gasoline prices, the German government introduced a 9-Euro-Ticket for public transport. Anyone could purchase a monthly ticket for summer 2022 for only 9 Euros. Moreover, the 9-Euro-Ticket was valid throughout Germany for public transportation except for Intercity and Intercity Express trains.
It has been an unprecedented experiment for the German transportation system due to the scope of implementation and the parties involved. Logically, one of the upcoming challenges was allocating ticket revenues between all public transport operators accepting this ticket. Accurate cost and revenue estimation are among the most significant issues associated with revenue allocation due to fluctuations in ridership, changes in operating costs, and other variables, especially when several public transit agencies are involved.
Apart from the country-wide regional and suburban trains operator, Deutsche Bahn, Germany has more than 60 local public transport companies operating in 16 regions. The challenge of calculating each operator’s profit share is significant, given that Germany is the second-largest European country in terms of passenger flow after France and has a yearly revenue of about 10 billion Euros. As a result, a minor inaccuracy in the passenger flow calculations can lead to significant losses for some companies.
The 9-Euro-Ticket is considered a success from the demand point of view. However, it took the German government almost a year to introduce the 9-Euro-Ticket successor, a 49-Euro-Ticket. Partially, this is because the country has never adopted the revenue allocation practice on such a scale before.*
An unclear and unreliable calculation system can lead to conflicts, especially when one agency is more successful or profitable than others.
Data sharing and reporting are additional challenges when agencies use different data systems or reporting methods. The mentioned complications can make it difficult to estimate the revenue generated by each public transport operator accurately and reach a fair and equitable revenue allocation agreement.
Traditional transportation data collection methods, such as surveys or ticketing information, are not only restrained in overcoming the challenges of revenue allocation but also add complications to an already challenging system.
Precise transportation data provided by MOTIONTAG can play a critical role in solving your challenges associated with revenue allocation. Apart from eliminating the errors and biases mentioned earlier, our technology can also:
- Ensure the revenue allocation is fair and equitable based on precise passenger kilometer data.
- Help to improve the integration of services provided by multiple public transit agencies. This data can identify areas where services overlap and help coordinate the scheduling and routing of services to provide the best possible service for users.
- Be used to develop standardized data systems and reporting methods, which can help to eliminate disputes over data quality and accuracy. This can also ensure that data is shared and reported consistently and transparently, which helps to build trust between the different public transit agencies.
- Be used to monitor and evaluate the performance of the public transit system, which can help identify improvement areas and ensure that the revenue sharing remains fair and equitable over time. This data can also track individual agencies’ performance and identify areas where performance can be improved.
Providing accurate and detailed information about each agency’s revenue generated on public transport lines can help ensure that the revenue allocation is fair, equitable, and consistent with the goals and priorities of all parties involved.
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“MOTIONTAG’s technology is one of the most interesting new tools for mobility surveys. New, digital survey methods simplify data collection and facilitate access for young, technology-oriented target groups.
MOTIONTAG’s technology convinces with an elaborate data privacy and security approach, high precision and fast data availability. Integrating this technology in our market research app gave us the possibility to collect better data for longer timeframes in a more economic and customer-friendly way.”
– Robert Follmer – Head of Mobility and Regional Research at Infas.
MOTIONTAG generates detailed, real-time data on how individuals travel – no matter the mode of transportation. Data is collected through apps, where our technology runs in the background in full transparency for the end users as they accept the tracking (opt-in). By anonymizing this data, we provide aggregated mobility insights into travel demands. Our technology is already a basis for mobility data collection for GfK, BVG, Deutsche Bahn, Swisscom, Infas, and ETH Zurich.