Jan Kinne has been a member of the ZEW Research Department “Economics of Innovation and Industrial Dynamics” since June 2016. He studied geoinformatics at Heidelberg University and Loughborough University, UK. In the context of his dissertation (Dr. rer. nat.) at the University of Salzburg, which he successfully completed in September 2020, he developed web-based innovation indicators for microgeographic analyses. He continues to conduct method-oriented research on the use of (text-based) web data for innovation research
Selected Publications
Articles in Refereed Journals
Kinne, Jan and Janna Axenbeck (2020), Web Mining for Innovation Ecosystem Mapping: A Framework and a Large-scale Pilot Study, Scientometrics. Download
Mirtsch, Mona, Jan Kinne and Knut Blind (2020), Exploring the Adoption of the International Information Security Management System Standard ISO/IEC 27001: A Web Mining-Based Analysis, IEEE Transactions on Engineering Management. Download
Rammer, Christian, Jan Kinne and Knut Blind (2019), Knowledge Proximity and Firm Innovation: A Microgeographic Analysis for Berlin, Urban Studies 57(5), 996-1014. Download
Kinne, Jan and Resch Bernd (2018), Generating Big Spatial Data on Firm Innovation Activity from Text- Mined Firm Websites, GI_Forum 1, 82-89. Download
Kinne, Jan and Bernd Resch (2018), Analyzing and Predicting Micro-Location Patterns of Software Firms, ISPRS International Journal of Geo-Information 7, 1. Download
Monographs, Contributions to Edited Volumes
Kinne, Jan (2017), Standortmustermodellierung der deutschen Softwarebranche, in: Kolbe, Thomas H.; Bill, Ralf; Donaubauer, Andreas Wichmann, Berlin, Offenbach, 24-28.
Discussion and Working Papers
Kinne, Jan, Miriam Krüger, David Lenz, Georg Licht and Peter Winker (2020), Corona Pandemic Affects Companies Differently, Daily updated website analysis on the reaction of companies to the Corona pandemic in Germany, ZEW expert brief No. 20-05, Mannheim. Download
Krüger, Miriam, Jan Kinne, David Lenz and Bernd Resch (2020), The Digital Layer: How Innovative Firms Relate on the Web, ZEW Discussion Paper No. 20-003, Mannheim. Download
Kinne, Jan and David Lenz (2019), Predicting Innovative Firms Using Web Mining and Deep Learning, ZEW Discussion Paper No. 19-001, Mannheim. Download
Kinne, Jan and Janna Axenbeck (2018), Web Mining of Firm Websites: A Framework for Web Scraping and a Pilot Study for Germany, ZEW Discussion Paper No. 18-033, Mannheim. Download
Kinne, Jan and Bernd Resch (2017), Analysing and Predicting Micro-Location Patterns of Software Firms, ZEW Discussion Paper No. 17-063, Mannheim. Download
Rammer, Christian, Jan Kinne and Knut Blind (2016), Microgeography of Innovation in the City: Location Patterns of Innovative Firms in Berlin, ZEW Discussion Paper No. 16-080, Mannheim. Download
Expertises
Koch, Tobias, Jürgen Egeln, Josefine Diekhof, Jan Kinne, Friedemann Koll, Jan-Philipp Kramer, Marion Neumann, Christian Rammer, Melanie Reisch and Hinrich Schwarze (2018), Regionale Innovationssysteme in Baden-Württemberg – Bestandsaufnahme und Schlussfolgerungen, Ministerium für Wirtschaft, Arbeit und Wohnungsbau Baden-Württemberg, Stuttgart/Mannheim. Download
Gottschalk, Sandra, Jürgen Egeln, Jan Kinne, Annegret Hauer, Detlef Keese and Marie Oehme (2017), Die volkswirtschaftliche Bedeutung der Familienunternehmen, Stiftung Familienunternehmen, München. Download
Research Reports
- JUNGE UNTERNEHMEN
- JUNGE UNTERNEHMEN
Projects
Current Projects
- Project Duration 01.09.2020 - 28.02.2022Preparing the CIS 2022
- Project Duration 01.10.2019 - 30.09.2021Networks of Innovative Firms (NETINU)
- Project Duration 01.07.2019 - 30.06.2022Business and Economic Research Data Center (BERD-Center)
- Project Duration 01.01.1992 - currentThe Mannheim Enterprise Panel
Finished Projects
- Project Duration 01.04.2020 - 31.07.2020Medium-sized Companies in the Corona Crisis Reflected in their Website Contents
- Project Duration 01.05.2019 - 29.02.2020Innovation Activities of Firms in East Germany
- Project Duration 01.08.2018 - 31.01.2019The Economic Contribution of Family Firms
- Project Duration 01.10.2017 - 30.09.2020Text Data Based Output Indicators as Base of a New Innovation Metric
- Project Duration 01.01.2017 - 31.07.2017The Economy of Baden-Wuerttemberg: Analysis of Structural Features and Future Perspectives in a National and International Comparison
- Project Duration 01.12.2016 - 31.08.2018Regional Innovation Systems in Baden-Wuerttemberg – State of Play and Conclusions
- Project Duration 01.09.2016 - 31.08.2019InnovationStudio Leibniz: Development of Innovation Capabilities of Research Organisations and Integration of SMEs in Research Projects (Science4KMU)
- Project Duration 01.08.2016 - 30.11.2016The Economic Importance of Family Enterprises 2016
- Project Duration 01.05.2016 - 30.11.2016Increasing the R&D Intensity of Firms in Saxony-Anhalt
- Project Duration 01.07.2015 - 30.06.2019Innovation Indicator 2015 to 2018
Events
Expert Seminars
More Information
Teaching Activities and Stand-in Professors
-
SS 2020:
Seminar
"Data Science with Python",
Hochschule Darmstadt, Germany -
11.2020:
"Web Mining of Firm Websites",
Aalborg University, Denmark
more information -
SS 2019:
"Text Mining with Python",
University of Salzburg, Austria -
05.2018:
Seminar
"Geographische Informationssysteme",
Centre for European Economic Research , Mannheim, Germany
more information
-
SS 2020:
Seminar
"Data Science with Python",
Research Stays
Referee-Reports for Scientific Journals, Public Trusts etc.
- 09.2020: Zeitschrift "Research Policy"
- 01.2020: Zeitschrift "ISPRS International Journal of Geo-Information"
- 10.2018: Zeitschrift "Environment and Planning B"
Lectures
-
2020:
The digital layer: How innovation firms relate on the web,
5th Geography of Innovation Conference,
Stavanger, Norwegen
more information -
2020:
Web-based innovation indicators,
Research Seminar,
Scuola Superiore Sant’Anna, Pisa, Italien -
2020:
Web-based innovation indicators,
KOF ETH Zurich Seminar,
KOF ETH Zürich, Schweiz
more information -
2020:
Predicting Innovative Firms using Web Mining and Deep Learning,
G-Forum 2020,
KIT Karlsruhe, Deutschland -
2020:
Text Data Based Output Indicators as Base of a New Innovation Metric (TOBI),
Workshop "New Innovation Indicators - From Research to Policy Application" ,
Berlin, Deutschland -
2020:
Web Mining COVID-19,
Online NESTI workshop on the “Statistical monitoring and analysis of Science, Technology and Innovation in times of crisis”,
Online, Frankreich -
2020:
Web-based innovation indicators,
Technis Webinar,
Mannheim, Deutschland
more information -
2020:
Web-based innovation indicators,
ifo Research Seminar Online,
Online, Deutschland -
2019:
Web Mining von Unternehmenswebseiten,
BAM Abteilungsseminar,
Berlin, Deutschland -
2019:
Predicting Innovative Firms using Web Mining and Deep Learning,
LISH Harvard University Seminar,
Cambridge, Massachusetts, Vereinigte Staaten von Amerika (USA) -
2019:
Predicting Innovative Firms using Web Mining and Deep Learning,
IGL Global Conference 2019,
Berlin, Deutschland
more information -
2019:
Web Mining for Innovation Research: A Framework and an Open Source Web Scraping Tool,
Workshop Machine Learning and AI for Science, Technology, and (Eco-)System Mapping and Forecasting,
Peking, China - Volksrepublik -
2019:
Predicting Innovative Firms using Web Mining and Deep Learning,
New Data for Innovation Policy,
London, Vereinigtes Königreich -
2019:
Predicting Innovative Firms using Web Mining and Deep Learning,
CGA/IQSS Harvard University Seminar,
Cambridge, Vereinigte Staaten von Amerika (USA) -
2019:
Predicting Innovative Firms using Web Mining and Deep Learning,
9th ZEW/MaCCI Conference on the Economics of Innovation and Patenting,
ZEW, Deutschland -
2019:
Predicting Innovative Firms using Web Mining and Deep Learning,
Deutsche Bundesbank Seminar,
Deutsche Bundesbank in Frankfurt am Main, Deutschland -
2019:
Predicting Product Innovator Firms using Website Texts and Deep Learning,
STI Working Group at Eurostat,
Eurostat, Luxemburg -
2019:
The Digital Layer: How innovative firms relate on the Web,
PhD Seminar,
Salzburg University, Österreich -
2019:
Predicting Product Innovator Firms using Website Texts and Deep Learning,
ZEW-FDZ-Data User Workshop,
ZEW, Deutschland -
2019:
Web Mining von Unternehmenswebseiten,
Weiterentwicklung der Indikatorik für Forschung und Innovation,
Berlin, BMBF, Deutschland -
2019:
Predicting Innovative Firms using Web Mining and Deep Learning,
CIS Task Force Meeting,
Luxemburg, Luxemburg -
2018:
Web Mining for firm-level Innovation Indicators,
Research Seminar,
KOF ETH Zürich, Schweiz -
2018:
A Framework for Web Scraping Firm Websites to Generate Innovation Indicators,
CISS - Competition and Innovation Summer School,
Ulcinj, Montenegro
more information -
2018:
Microgeographic Innovation Processes in Urban Agglomerations,
Dissertation Proposition Defense,
Salzburg University, Österreich -
2018:
Web Mining for Geodata on Firm-level Innovation Activity,
GI_Forum,
Salzburg, Österreich -
2018:
Web Mining of Firm Websites,
EURITO New Data for R&I Policy Workshop,
European Commission, Brüssel, Belgien -
2017:
Förderpreis Geoinformatik,
Münchner GI-Runde,
TU München, Deutschland
more information -
2017:
Innovation Related Topics: Neartime Innovation Indicators from Text Mining of Firm Websites,
CISS - Competition and Innovation Summer School (2096),
Cala Liberotto, Italien -
2017:
Urban Innovative Neighbourhoods: Micro-Location Patterns of Innovative Firms in Berlin,
57th ERSA Congress,
Groningen, Niederlande -
2016:
Analysing and Predicting Location Patterns of Software Firms,
Brown Bag Seminar Department of Geoinformatics – Z_GIS, Salzburg University,
Salzburg, Österreich
-
2020:
The digital layer: How innovation firms relate on the web,
Function
Researcher
Prices, Awards and Distinctions
-
2017:
Beste Abschlussarbeit (Diplom- / Masterarbeit),
Master Thesis, Technische Universität München, Munich, Germany
Doctoral degree/habilitation
-
Doctoral degree/PhD
(9.2020),
University of Salzburg, Austria,
Thesis title: Web-based innovation indicators for microgeographic economic analysis
