Pendler Mobil: Die Verwendung von Mobilfunkdaten zur Unterstützung der amtlichen Pendlerstatistik: Können Mobilfunkdaten die amtliche Pendlerrechnung unterstützen?

The availability of small-scale and real-time commuting patterns is of great importance for political as well as communal decision-marking processes. From commuting behaviour, conclusions can be drawn about labour market regions and the distribution of the resident population, which contributes, among other things, to the ongoing improvement of the public transport infrastructure. The data required for this purpose is published by the official commuter statistics. However, it shows potential for improvement with respect to the temporal and spatial representation of commuting patterns of employed persons as well as a technical extension with respect to educational commuters. This article describes the possibilities for extending the official commuter statistics based on origin-destination matrices from mobile network data, which were investigated by the project Pendler Mobil. Due to their temporal timeliness and spatially fine resolution, mobile network data provide a robust data basis for the flexible mapping of potential and regular commuter movements. The potential performance of mobile network data thus enables an external validation of existing commuter calculations or commuter statistics, as well as a two-way complement to identify and represent other forms of commuting by the employed population. Using the state of North Rhine-Westphalia as a case study, we discuss similarities and differences between corresponding commuting patterns based on mobile network data and the official commuter statistics. In this context, we address the challenges of processing and defining suitable mobile network data by the data provider as well as other influences, such as the distance covered or dwell times of mobile activities on them. Especially the underestimation of mobile commuter flows compared to the official commuter statistics suggests to discuss modification approaches of the mobile network data. As a result, the available mobile network data can potentially support the official commuter statistics by providing small-scale commuter flows in cities as an extended destination determination and enables the identification of highly frequented potential work locations in cities.