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This dataset is based on the interlocking network model developed by the Globalization and World Cities Study Group (GaWC) at Loughborough University (Taylor 2004). It provides one specific way to address the question how inter‐city relations can be empirically measured despite the chronic lack of data on inter‐city information flows. The model uses a proxy – intra‐firm networks of multi‐branch, multi‐location enterprises – to estimate potential flows of knowledge‐creating information between cities and towns. The method was originally developed to measure the connectivity between global cities based on multi‐branch advanced producer services (APS) firms as they organize business activities across their offices worldwide. In this dataset, the model is adapted to measure relations between functional urban areas (FUAs) within and beyond the German and Swiss space economy, for both APS and High-Tech firms. In contrast to the original methodology, in this dataset the company locations were localized by the exact, georeferenced address, not only on the level of FUAs. The present dataset is created as part of the SNF research project “Knowledge-intensive firms, connectivity and spatial restructuring: dynamics and differences in Germany and Switzerland”.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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