Schmidt, Sebastian, Jan Kinne, Sven Lauterbach, Thomas Blaschke, David Lenz and Bernd Resch (2022), Greenwashing in the US metal industry? A novel approach combining SO2 concentrations from satellite data, a plant-level firm database and web text mining,, Science of The Total Environment Volume 835, 155512, ISSN 0048-9697.

Dörr, Julian Oliver, Jan Kinne, David Lenz, Georg Licht and Peter Winker (2022), An integrated data framework for policy guidance during the coronavirus pandemic: Towards real-time decision support for economic policymakers, PLOS ONE 17(2), e0263898.

Kinne, Jan and David Lenz (2021), Predicting Innovative Firms using Web Mining and Deep Learning, PLoS One 16 (4).

Kinne, Jan and Janna Axenbeck (2020), Web Mining for Innovation Ecosystem Mapping: A Framework and a Large-scale Pilot Study, Scientometrics.

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.

Rammer, Christian, Jan Kinne and Knut Blind (2019), Knowledge Proximity and Firm Innovation: A Microgeographic Analysis for Berlin, Urban Studies 57(5), 996-1014.

Kinne, Jan and Resch Bernd (2018), Generating Big Spatial Data on Firm Innovation Activity from Text- Mined Firm Websites, GI_Forum 1, 82-89.

Kinne, Jan and Bernd Resch (2018), Analyzing and Predicting Micro-Location Patterns of Software Firms, ISPRS International Journal of Geo-Information 7, 1.

Kinne, Jan (2017), Standortmustermodellierung der deutschen Softwarebranche, in: Kolbe, Thomas H.; Bill, Ralf; Donaubauer, Andreas Wichmann , Berlin, Offenbach, 24-28

Eugenidis, Dania, Jan Kinne and David Lenz (2022), Analysing Gender Equality at the Firm Level, MAGKS Papers on Economics 14-2022 , Marburg.

Schmidt, Sebastian, Jan Kinne, Sven Lautenbach, Thomas Blaschke, David Lenz and Bernd Resch (2022), Greenwashing in the US Metal Industry? A Novel Approach Combining SO2 Concentrations From Satellite Data, a Plant-Level Firm Database and Web Text Mining, ZEW Discussion Paper No. 22-006, Mannheim

Dörr, Julian Oliver, Jan Kinne, David Lenz, Georg Licht and Peter Winker (2021), An Integrated Data Framework for Policy Guidance in Times of Dynamic Economic Shocks, ZEW Discussion Paper No. 21-062, Mannheim

Abbasiharofteh, Milad, Jan Kinne and Miriam Krüger (2021), The Strength of Weak and Strong Ties in Bridging Geographic and Cognitive Distances, ZEW Discussion Paper No. 21-049, Mannheim

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

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

Kinne, Jan and David Lenz (2019), Predicting Innovative Firms Using Web Mining and Deep Learning, ZEW Discussion Paper No. 19-001, Mannheim

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

Kinne, Jan and Bernd Resch (2017), Analysing and Predicting Micro-Location Patterns of Software Firms, ZEW Discussion Paper No. 17-063, Mannheim

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

Rammer, Christian, Marius Berger, Patrick Breithaupt, Sandra Gottschalk and Jan Kinne (2022), KI-Startups in Deutschland, Bundesministerium für Wirtschaft und Klimaschutz, Berlin

Dörr, Julian Oliver, Sandra Gottschalk, Jan Kinne, David Lenz and Georg Licht (2020), Mittelständische Unternehmen in der Corona - Krise im Spiegel ihrer Webseiten, Bundesministerium für Wirtschaft und Energie (BMWi), Mannheim

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

Gottschalk, Sandra, Jürgen Egeln, Jan Kinne, Annegret Hauer, Detlef Keese and Marie Oehme (2017), Die volkswirtschaftliche Bedeutung der Familienunternehmen, Stiftung Familienunternehmen, München

JUNGE UNTERNEHMEN Jahrgang 16, Nr.6, Dezember 2016

JUNGE UNTERNEHMEN Jahrgang 16, Nr. 5, August 2016

01.2022: Zeitschrift "Journal of Evolutionary Economics"

01.2021: Zeitschrift "Applied Spatial Analysis and Policy"

09.2020: Zeitschrift "Research Policy"

01.2020: Zeitschrift "ISPRS International Journal of Geo-Information"

10.2018: Zeitschrift "Environment and Planning B"

2022: Machine Learning Meets Economic Geography, Global Conference on Economic Geography, Dublin, Irland

2021: DGPF Jahrestagung, Webbasierte Innovationsindikatoren für mikrogeographische Analysen, Online, Deutschland more information

2021: Daily updated website analysis on the reaction of companies to the Coronavirus pandemic in Germany, CONFERENCE ON NEW TECHNIQUES AND TECHNOLOGIES FOR STATISTICS, Online, Belgien more information

2021: Webbasierte Innovationsindikatoren für mikrogeographische Analysen, Runder Tisch GIS, Technische Universität München, Deutschland more information

2021: Predicting Innovative Firms using Web Mining and Deep Learning, Advancing Indicators of Regional Structural Change, Online, Deutschland

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

SS 2021: Seminar "Data Science with Python", Hochschule Darmstadt, Germany

WS 2021/2021: Seminar "Web Data Science", Justus Liebig University Giessen, Gießen, Germany

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

11. – 11.2020 KOF Konjunkturforschungsstelle, ETH Zürich, Zurich, Switzerland

06. – 08.2019 Harvard University, Cambridge, United States of America (USA) Institute for Quantitative Social Sciences