Prof. Dr. Patrick Cato

MENDEN, Christian, Ulrich MÜLLER-STEINFAHRT, Philipp GÖLZER und Patrick CATO, 2025. Forecasting the Demand for Recycled Plastics using a Digital Twin for Regional Plastic Cycles. In: WEHNER, Rainer und Emin AKÇAOĞLU, Editors Conference Proceedings: Würzburg International Business Forum, 8th International Business Conference 2025, Balancing Innovation and Resilience in International Business, Special Focus: Tourism & Hospitality. Würzburg: Würzburg International Business Press, Page 65-68. ISBN 978-3-949864-10-0. Available at: https://wibf.thws.de/publications/conference-proceedings-books/

KAISER, Carolin, Michael JUNGBLUTH, Anna ULRICHSHOFER, Lucas KAMES und Patrick CATO, 2025. How sponsored content affects consumer decisions in AI-powered retail. NIM Insights, 7, 26-29. ISSN 2944-5981. Available at: https://www.nim.org/forschung/uebersicht-forschungsprojekte/forschungsprojekt/how-sponsored-sontent-affects-consumer-decisions-in-ai-powered-retail

MONDAL, Rahul, Evelina IGNATOVA, Jonas HEINZMANN, Minh Dung DO, Abhivanth MURALI, Daniel WALKE, Patrick CATO, Robert A. BECKER, Thomas BLEISTEIN, Gunter SAAKE, David BRONESKE und Robert HEYER, 2025. SimKit: Similarity Graphs, Eigendecomposition and Spectral Clustering in Neo4j. Proceedings: 2025 IEEE International Conference on High Performance Computing and Communications, HPCC/DSS/SmartCity/DependSys/ICESS 2025. Piscataway: IEEE, Page 985-991. ISBN 979-8-3315-6874-0. Available at: https://doi.org/10.1109/HPCC67675.2025.00145

KAISER, Carolin, René SCHALLNER, Michael JUNGBLUTH, Patrick CATO und Anna ULRICHSHOFER, 2024. AI-powered Digital Sales Assistants: The Future of Shopper Engagement. NIM Insights, 6, 10-13. ISSN 2944-5981. Available at: https://www.nim.org/publikationen/detail/ai-powered-digital-sales-assistants

ULRICHSHOFER, Anna, Michael JUNGBLUTH, Patrick CATO und Carolin KAISER, 2024. Digital Sales Assistants in ‘Bricks & Clicks’ – Deciphering Relative Feature Importance for Shopper Engagement. Proceedings of the European Marketing Academy: EMAC 2024 Annual. Brüssel: EMAC. Available at: https://proceedings.emac-online.org/index.cfm?eventid=48&EMAC%202024%20Annual

CATO, Patrick, 2022. A Simple Approach to Optimize S3 Object Gateways for Massive Numbers of Small File Writes. Proceedings: 2022 IEEE International Conference on Big Data. Piscataway: IEEE, Page 3186-3190. ISBN 978-1-6654-8045-1. Available at: https://doi.org/10.1109/BigData55660.2022.10020881

GÖLZNER, Philipp und Patrick CATO, 2019. Der Weg zu datengetriebenen Geschäftsprozessen: Strategische, technische und organisatorische Herausforderungen für Unternehmen. In: BECKER, Wolfgang, Brigitte EIERLE, Alexander FLIASTER, Björn IVENS, Alexander LEISCHNIG, Alexander PFLAUM und Eric SUCKY, Editors Geschäftsmodelle in der digitalen Welt: Strategien, Prozesse und Praxiserfahrungen. Wiesbaden: Springer Gabler, Page 619-631. ISBN 978-3-658-22129-4. Available at: https://doi.org/10.1007/978-3-658-22129-4_32

CATO, Patrick, Simon BRUMM, Philipp GÖLZER und Walter DEMMELHUBER, 2016. Einflüsse auf den Implementierungserfolg von NoSQL-Systemen: Erkenntnisse einer quantitativ-empirischen Untersuchung. HMD Praxis der Wirtschaftsinformatik, 53(4), 443-452. ISSN 1436-3011. Available at: https://doi.org/10.1365/s40702-016-0238-5

CATO, Patrick, Philipp GÖLZER und Walter DEMMELHUBER, 2015. An investigation into the implementation factors affecting the success of big data systems. In: ISMAIL, Leila, Editors Proceedings of the 2015 11th International Conference on Innovations in Information Technology (IIT): Innovations 2015. Los Alamitos: IEEE, Page 134-139. ISBN 978-1-4673-8511-4. Available at: https://doi.org/10.1109/INNOVATIONS.2015.7381528

GÖLZER, Philipp, Patrick CATO und Michael AMBERG, 2015. Data Processing Requirements of Industry 4.0 - Use Cases for Big Data Applications. ECIS 2015 Research-in-Progress Papers. Atlanta: AIS. ISBN 978-3-00-050284-2. Available at: https://aisel.aisnet.org/ecis2015_rip/61/

GÖLZER, Philipp, Lothar SIMON, Patrick CATO und Michael AMBERG, 2015. Designing Global Manufacturing Networks Using Big Data. Procedia CIRP, 2015(33), 191-196. ISSN 2212-8271. Available at: https://doi.org/10.1016/j.procir.2015.06.035