Abstract
Despite the multidimensionality of knowledge and technology transfer (KTT), existing quantitative evaluations predominantly focus on a limited range of channels, often resulting from the availability of data rather than theoretical considerations. To address this gap, we leverage unstructured data from university websites to develop indicators that provide a comprehensive view of universities’ KTT activities. Applying large-language-transformers to scraped websites of German universities, we identify five distinct KTT dimensions: engagement in collaborative research consortia with industry, technical consulting activities, start-up activities, the development of regional tech transfer hubs, as well as technology transfer offices. Based on exploratory regression analyses, we find that the intensity of the type of KTT activities varies with the regional environment as well as university characteristics. Moreover, our regressions unveil a synergistic relationship between KTT and basic research, where this finding again seems to depend strongly on the type of KTT activity.
| Original language | English |
|---|---|
| Article number | 102333 |
| Number of pages | 15 |
| Journal | Socio-Economic Planning Sciences |
| Volume | 102 |
| DOIs | |
| Publication status | Published - 2025 Dec |
Subject classification (UKÄ)
- Economics and Business
Free keywords
- Knowledge-transfer
- Large-language transformers
- Semantic-search
- Technology-transfer
- Topic modeling
- Topic-modeling
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