Mapping supply chain collaboration research: a machine learning-based literature review AM Nitsche, CA Schumann, B Franczyk, K Reuther International Journal of Logistics Research and Applications, 1-29, 2021 | 10 | 2021 |
Smarter Relationships? The Present and Future Scope of AI Application in Buyer-Supplier Relationships AM Nitsche, M Burger, J Arlinghaus, CA Schumann, B Franczyk International Conference on Computational Logistics, 237-251, 2021 | 9 | 2021 |
A Systems Theory and Action Design Research Perspective on Supply Chain Collaboration in the Context of SCM 4.0 AM Clauss, CA Schumann 2020 IEEE International Conference on Engineering, Technology and Innovation …, 2020 | 4 | 2020 |
People management challenges for SMEs in five European regions: Spotlighting the (in) visible and the (in) formal and embedding SME HR issues firmly in the business and … K Maršíková, T Rajander, AM Clauss, E Forkel, I Medžiūnienė, D Dulkė, ... University of Huddersfield, 2019 | 4 | 2019 |
Impact of AI Application on Digital Education Focused on STE (A) M CA Schumann, K Reuther, C Tittmann, AM Clauß, J Kauper EDEN Conference Proceedings, 153-161, 2020 | 3 | 2020 |
A Good Practice Guide to Managing Human Resources in Regional SMEs R Komulainen, K Maršíková, J Davies, I Srėbaliūtė, AM Clauss, O Moš, ... | 3 | 2019 |
Challenges and Opportunities of Interoperable and Future-Oriented Technologies for Production Logistics and Supply Chain Management E Forkel, AM Clauss, CA Schumann British Academy of Management Annual Conference, 2019 | 3 | 2019 |
DIGITAL ECOSYSTEM" UNIVERSITY" AS INNOVATION INCUBATOR FOR MERGING HYBRID AND AI-SUPPORTED HIGHER EDUCATION CA Schumann, F Otto, N Kling, C Tittmann, AM Nitsche Shaping the Digital Transformation of the Education Ecosystem in Europe, 5, 2022 | 2 | 2022 |
A Conceptual Reference Framework for Data-driven Supply Chain Collaboration. AM Nitsche, CA Schumann, B Franczyk ICEIS (2), 751-758, 2021 | 2 | 2021 |
HRM challenges and Lifelong Learning in SMEs in Western Saxony. AM Clauss, CA Schumann, E Forkel, K Reuther FormaMente 14 (2), 2019 | 2 | 2019 |
Reference Model for Data-Driven Supply Chain Collaboration AM Nitsche, CA Schumann, B Franczyk International Conference on Computational Logistics, 412-424, 2022 | 1 | 2022 |
Hybridism–Theoretical Learning Response to the Growing Diversity in Higher Education CA Schumann, AM Nitsche, K Reuther, C Tittmann EDEN Conference Proceedings, 97-106, 2021 | 1 | 2021 |
Artificial Intelligence Inspired Supply Chain Collaboration: A Design-Science Research and System Dynamics Approach AM Nitsche, CA Schumann, B Franczyk, K Reuther 2021 IEEE International Conference on Engineering, Technology and Innovation …, 2021 | 1 | 2021 |
Hybridx Higher Education – A Multidimensional Overlay of Hybrid Forms of Learning and Teaching CA Schumann, AM Nitsche, C Tittmann, K Reuther The Learning Ideas Conference, 321-332, 2021 | 1 | 2021 |
Technological and Organisational Readiness in the Age of Data-Driven Decision Making: A Manufacturing Perspective A Nitsche, O Matthias, C Laroque, CA Schumann | 1 | 2020 |
Key role of modularization for new global pathways expanding access to multiple study programs CA Schumann, K Reuther, C Tittmann, H Gerischer, O Schirmer, X Feng, ... https://wcol2019. ie, 833, 2019 | 1 | 2019 |
Artificial Intelligence Support for Smart Logistics Systems in Industrial Environments CA Schumann, R Riedel, S Franke, AM Nitsche, C Runte SAE Technical Paper, 2022 | | 2022 |
Technological Push for Hybridization of Education and Learning Systems CA Schumann, AM Nitsche, K Reuther, C Tittmann Proceedings of the Future Technologies Conference, 674-685, 2021 | | 2021 |
Supply chain management in the course of time-A systematisation of past, present and future objectives AM Nitsche, W Kusturica, D Neumann, CA Schumann, C Laroque Adapting to the Future: Maritime and City Logistics in the Context of …, 2021 | | 2021 |
Multiple Perspektiven bei der Implementierung innovativer technologischer Lösungen im Kontext datengesteuerter Entscheidungsfindung AM Nitsche, CA Schumann, C Laroque, O Matthias Data Science anwenden, 53-68, 2021 | | 2021 |