Comprehensive knowledge of the building stock is considered essential for the implementation of climate and resource protection policy objectives. In contrast to residential buildings, data on the stock dynamics in the non-residential building sector are scarce in Germany. With publication of the construction statistics via Scientific Use File (SUF) by the research data centres of the statistical offices of Germany, for the first time, in-depth analyses of the stock dynamics in the non-residential buildig sector are possible. The dataset contains Information on on the spatial distribution down to municipality level, the date of completion of the construction measure, the predominantly used building material, information on the building owner as well as information on the number of full storeys, the volume, the floor space before and after construction completion. This dataset enables spatially detailed analyses of stock dynamics and allows an analysis of the underlying causes - or cause-effect relationships - that are responsible for these construction dynamics.

The aim of this work is to identify factors that influence changes in the non-residential building stock and to quantify their influence. Based on a suitable typology of non-residential buildings, a pre-selection of influencing factors will be obtained through an expert survey. The analysis will focus on the use classes of warehouse buildings, office buildings, factory buildings and agricultural buildings. For each of these use classes within the non-residential building stock, individual influencing factors were identified. These factors are then correlated on the change in the non-residential building stock within pre-selected submarkets at the district level. For the selection of suitable districts, a cluster analysis is carried out. A factor analysis is used to reveal the interdependence between influencing factors and the respective use classes. As a result, this work can contribute to a more informed discussion on the future development of the non-residential building stock. It can be seen that comprehensive building activity statistics are essential for validating and updating future building cadastres.