This paper analyzes how positional and relational data in 186 regions of Germany influence the location choices of knowledge-based firms. Where firms locate depends on specific local and interconnected resources, which are unevenly distributed in space. This paper presents an innovative way to study such firm location decisions through network analysis that relates exponential random graph modeling (ERGM) to the interlocking network model (INM). By combining attribute and relational data into a comprehensive dataset, we capture both the spatial point characteristics and the relationships between locations. Our approach departs from the general description of individual location decisions in cities and puts extensive networks of knowledge-intensive firms at the center of inquiry. This method can therefore be used to investigate the individual importance of accessibility and supra-local connectivity in firm networks. We use attributional data for transport (rail, air), universities, and population, each on a functional regional level; we use relational data for travel time (rail, road, air) and frequency of relations (rail, air) between two regions. The 186 functional regions are assigned to a three-level grade of urbanization, while knowledge-intensive economic activities are grouped into four knowledge bases. This research is vital to understand further the network structure under which firms choose locations. The results indicate that spatial features, such as the population of or universities in a region, seem to be favorable but also reveal distinct differences, i.e., the proximity to transport infrastructure and different valuations for accessibility for each knowledge base.

This paper challenges the traditional perspective of a territorial core–periphery pattern as an organizing principle of space by introducing a relational perspective through an empirical approach. We study spatial processes of knowledge creation among advanced producer services in Germany between 2009 and 2019. We use a unique longitudinal dataset to analyse if German regions have become more integrated into the intra-firm location networks nationally and globally, and how this translates into the processes of centralization and peripheralization. The current conceptualization of core–periphery in Germany is too static and does not reflect the economic development of the regions. We find that there is no trend of urban areas becoming more integrated and peripheral areas less integrated into these networks. Instead, our research finds a discrepancy between the federal territorial classification and the functional orientation of German regions. Regions classified as peripheral have not generally decreased in connectivity to other regions. In contrast, some have increased their connectivity and have become more central in relational terms. Overall, we identified peripheralization and centralization as a relational process with dynamic, overlapping and trans-scalar networks.

A profound appraisal framework has been developed and refined in transport economics and planning literature for decades, mainly characterised by welfare economic theory, cost–benefit analysis, and transport demand modelling. In summary, the appraisal methodology and its applications have concentrated on single infrastructure measures, marginal impacts identified through ceteris paribus comparisons, forecasts based on trends from the past, and monetary assessments of all quantifiable impacts. However, this framework has been continuously contested in transport planning literature, for instance, for its focus on travel demand and short-term travel time savings. Therefore, we suggest a novel approach for planning and assessing transport schemes in city regions, combining accessibility analyses, quantitative target indicators, and cost-effectiveness analysis. We develop and test this approach by assessing a proposed underground rail project in the Munich city region, the U5 southeast extension. In this case, we define an accessibility target level and estimate the potential for push measures along with the U5 project. We find modest impacts on quantitative targets in the Munich city region: Even when the U5 southeast extension is bundled with push measures in selected transport cells, the contribution to passenger transport-related carbon dioxide emission targets and primary energy consumption targets is low. Nevertheless, we demonstrate that the proposed assessment framework can support strategic transport planning in city regions. We argue for a change in perspective towards supply-side-oriented urban transport planning. Our proposed methodology is a first step in a different direction towards a sustainable mobility planning paradigm.

In Germany, employment is becoming increasingly concentrated in urban areas, largely driven by knowledge-intensive firms competing to attract the most qualified and appropriate labour. Therefore, this paper addresses where knowledge workers relocate to and how relocation patterns vary across spatial distances. Using an innovative origin-destination analysis, we examine job-related employment relocations across 186 functional urban areas in Germany from 2012 to 2021, using official employment data for 480 multi-locational firms, classified into one of three knowledge bases: analytical, synthetic and symbolic. This classification helps explain how firms create and use knowledge in their innovation process and allows us to differentiate workers’ relocation patterns. Our findings reveal a nuanced, multi-scalar perspective on the German knowledge economy. Between 2012 and 2021, knowledge-intensive employment has primarily relocated towards the largest functional urban areas, such as Munich or Frankfurt. However, relocation patterns diverge by knowledge base, and we can reveal the underlying dynamics driving this concentration. Workers in synthetic knowledge bases predominantly relocate on a large scale to and between these largest functional areas and between more decentralised functional areas, suggesting that spatial proximity plays a subordinate role in job-related relocations. In contrast, workers in analytical and symbolic knowledge bases exhibit less frequent relocations to other functional urban areas, instead relocating on a regional scale, mostly between neighbouring or spatially closer functional urban areas.