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Identifizierung von Technologie- und Innovationstrends der Berliner Wirtschaft auf Basis von Webseiten-Analysen: Ergebnisbericht

Author

Listed:
  • Rammer, Christian
  • Kinne, Jan

Abstract

Der vorliegende Bericht fasst die Ergebnisse eines explorativen Forschungsprojekts zusammen, das im Auftrag der Technologiestiftung Berlin vom Leibniz-Zentrum für Europäische Wirtschaftsforschung (ZEW) und istari.ai durchgeführt wurde. Ziel des Projekts war es, auf Basis von Webseiten-Analysen Innovations- und Technologietrends in der Berliner Wirtschaft zu identifizieren und Netzwerke von Unternehmen und anderen Organisationen in Berlin zu untersuchen, die diese Trends aufgreifen und vorantreiben. Die Webseiten-Analysen wurden von istari.ai unter Einsatz von Analysetools vorgenommen, die mittels Methoden der künstlichen Intelligenz Inhalte von Webseiten in Bezug auf die Relevanz bestimmter Themen und Aktivitäten bewerten. Diese Analysetools können sowohl die Relevanz von vorgegebenen Themen untersuchen als auch in explorativer Form das Auftreten neuer Themen identifizieren. Hierzu wurden auch Änderungen in den Webseiten-Inhalten über die Zeit betrachtet. Über die bestehenden Verlinkungen zu anderen Webseiten (Hyperlinks) wurde ausgewertet, zu welchen anderen Akteuren der Berliner Wirtschaft Beziehungen bestehen. Das Forschungsprojekt umfasste vier analytische Teile: - 1. Identifikation von Akteuren, die in ausgewählten Technologietrends aktiv sind, wobei die Technologietrends gemeinsam von der Technologiestiftung Berlin, Vertreter:innen der Senatsverwaltung für Wirtschaft, Energie und Betriebe des Landes Berlin sowie istari.ai und ZEW vorab festgelegt wurden. - 2. Identifikation von neu aufkommenden Technologie- und Innovationsthemen (Themenclustern) auf Basis einer explorativen Topic-Analyse. - 3. Analyse von Netzwerken der identifizierten Akteure, die zu den ausgewählten Technologietrends aktiv sind. - 4. Analyse von Strukturmerkmalen und Innovationsaktivitäten der Akteure, die zu den festgelegten Technologietrends und den identifizierten Themenclustern aktiv sind. Hierfür wird auf Datenbasen des ZEW (Mannheimer Unternehmenspanel, Mannheimer Innovationspanel) zurückgegriffen.

Suggested Citation

  • Rammer, Christian & Kinne, Jan, 2025. "Identifizierung von Technologie- und Innovationstrends der Berliner Wirtschaft auf Basis von Webseiten-Analysen: Ergebnisbericht," ZEW Expertises, ZEW - Leibniz Centre for European Economic Research, number 334907.
    • Handle: RePEc:zbw:zewexp:334907
    Note: Studie im Auftrag der Technologiestiftung Berlin
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    References listed on IDEAS

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    1. Dorian Arifi & Bernd Resch & Jan Kinne & David Lenz, 2023. "Innovation in hyperlink and social media networks: Comparing connection strategies of innovative companies in hyperlink and social media networks," PLOS ONE, Public Library of Science, vol. 18(3), pages 1-28, March.
    2. Dahlke, Johannes & Beck, Mathias & Kinne, Jan & Lenz, David & Dehghan, Robert & Wörter, Martin & Ebersberger, Bernd, 2024. "Epidemic effects in the diffusion of emerging digital technologies: evidence from artificial intelligence adoption," Research Policy, Elsevier, vol. 53(2).
    3. Bettina Peters & Christian Rammer, 2023. "Innovation panel surveys in Germany: the Mannheim Innovation Panel," Chapters, in: Handbook of Innovation Indicators and Measurement, chapter 5, pages 54-87, Edward Elgar Publishing.
    4. Milad Abbasiharofteh & Miriam Krüger & Jan Kinne & David Lenz & Bernd Resch, 2023. "The digital layer: alternative data for regional and innovation studies," Spatial Economic Analysis, Taylor & Francis Journals, vol. 18(4), pages 507-529, October.
    5. Jan Kinne & David Lenz, 2021. "Predicting innovative firms using web mining and deep learning," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-18, April.
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