Wissenschaftliche Publikationen

@conference{J.2024,
title = {A systematic literature review of after-crisis learning processes in PSM enhancing supply chain resilience},
author = {Brinkmeyer J. and Henke, M.},
year = {2024},
date = {2024-03-27},
booktitle = {Proceedings of the International Purchasing and Supply Education and Research Association (IPSERA). Rio de Janeiro, Brasil, 24–27th March 2024},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}

@article{Paffrath2024,
title = {Supply chain resilience of open source integration strategies – a literature analysis},
author = {Paffrath, F. N. and Brinkmeyer J.},
year = {2024},
date = {2024-03-24},
journal = {Proceedings of the International Purchasing and Supply Education and Research Association (IPSERA). Rio de Janeiro, Brasil, 24–27th March 2024},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{Paffrath2024b,
title = {A theoretical framework for managing open source integration strategies – a PSM perspective},
author = {Paffrath, F. N. and Henke, M.},
year = {2024},
date = {2024-03-24},
journal = {Proceedings of the International Purchasing and Supply Education and Research Association (IPSERA). Rio de Janeiro, Brasil, 24–27th March 2024},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{Tkáč2024,
title = {MachineLearnAthon: An Action-Oriented Machine Learning Didactic Concept},
author = {Tkáč, M. and Sieber, J. and Kuhlmann, L. and Brüggenolte, M. and Rinciog, A. and Henke, M. and Schweidtmann, A. M. and Gao, Q. and Theisen, M. F. and El Shawi, R.},
editor = {arXiv},
url = {https://arxiv.org/pdf/2401.16291.pdf},
doi = {arXiv:2401.16291},
year = {2024},
date = {2024-01-29},
urldate = {2024-01-29},
journal = {Arxiv},
abstract = {Machine Learning (ML) techniques are encountered nowadays across disciplines, from social sciences, through natural sciences to engineering. The broad
application of ML and the accelerated pace of its evolution lead to an increasing
need for dedicated teaching concepts aimed at making the application of this
technology more reliable and responsible. However, teaching ML is a daunting
task. Aside from the methodological complexity of ML algorithms, both with
respect to theory and implementation, the interdisciplinary and empirical nature
of the field need to be taken into consideration. This paper introduces the MachineLearnAthon format, an innovative didactic concept designed to be inclusive for students of different disciplines with heterogeneous levels of mathematics, programming and domain expertise. At the heart of the concept lie ML challenges, which make use of industrial data sets to solve real-world problems. These cover the entire ML pipeline, promoting data literacy and practical skills, from data preparation, through deployment, to evaluation.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{Große2024,
title = {Designing trust-enabling blockchain systems for the inter-organizational exchange of capacity},
author = {Große, N. and Möller, F. and Schoormann, T. and Henke, M.},
doi = {https://doi.org/10.1016/j.dss.2024.114182},
year = {2024},
date = {2024-01-23},
journal = {Decision Support Systems},
volume = {114182},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@inproceedings{Eichholz2024,
title = {Approaching value co-creation in different contexts through a bibliometric analysis},
author = {Eichholz, J. and Heimburg, V. and Große, N. and Hefft, D. and Henke, M. and Wiesche, M.},
editor = {Elsevier B.V.},
doi = {10.1016/j.procir.2023.09.142},
year = {2024},
date = {2024-01-12},
booktitle = {56th CIRP Conference on Manufacturing Systems, CIRP CMS ‘23, South Africa},
abstract = {Value co-creation has become a widely used concept in various domains due to its broad applicability. However, the lack of a consensus among researchers regarding the underlying concepts and related processes has resulted in disparate definitions, leading to misunderstandings both within and across disciplines. Moreover, the abundance of literature on value co-creation makes it challenging to identify relevant papers and derive future research directions. Therefore, it is difficult to find the most relevant papers and to derive future research directions in each case. To address these challenges, this paper elaborates a bibliometric analysis of value co-creation, which offers the possibility to analyse the multitude of contributions on the topic. Through the use of different techniques of performance analysis and science mapping, we outline the different domains in which value co-creation is studied, identify connections between different streams, highlight overarching concepts and find emerging trends. This provides a foundation for future researchers in disciplines such as management, business, social sciences, information systems as well as engineering, who are interested in contributing to the value co-creation research.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}

@inproceedings{derFalk2024b,
title = {Introduction to the Minitrack on Federated Industrial Platform Ecosystems: Technologies, Business Models, and Data-Driven Artifacts},
author = {Van der Falk, H. and Duparc, E. and Große, N. and Gürpinar, T.},
url = {https://hdl.handle.net/10125/106924},
doi = {https://hdl.handle.net/10125/106924},
year = {2024},
date = {2024-01-06},
booktitle = {Proceedings of the 57th Hawaii International Conference on System Sciences},
issuetitle = {Proceedings of the 57th Hawaii International Conference on System Sciences (HICSS)},
journal = {Proceedings of the 57th Hawaii International Conference on System Sciences (HICSS)},
pages = {4493-4495},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}

@inproceedings{Stuckmann-Blumenstein2024bb,
title = {Problems and Potentials of Shared Manufacturing in the Context of Industrial Ecosystems: A Bibliometric Analysis},
author = {Patrick Stuckmann-Blumenstein; Dominik Bons ; Nick Große ; Lana Benkhoff},
url = {https://www.researchgate.net/publication/377207051_Problems_and_Potentials_of_Shared_Manufacturing_in_the_Context_of_Industrial_Ecosystems_A_Bibliometric_Analysis},
doi = {https://hdl.handle.net/10125/106413},
year = {2024},
date = {2024-01-03},
booktitle = {57th Hawaii International Conference on System Sciences},
journal = {57th Hawaii International Conference on System Sciences},
abstract = {Shared Manufacturing has emerged as a transformative paradigm in the manufacturing industry that can potentially disrupt the sector. In particular, the formation of ecosystems could serve as an incubator for sharing approaches. New business models linked to demand-based resource allocation could increase the manufacturer’s competitiveness and can even help to achieve sustainability goals. While sharing approaches have already emerged in some sectors, the impact on manufacturing has been inhibited so far. This bibliometric analysis aims to provide a high-level overview of the research landscape on hurdles and potentials related to Shared Manufacturing in ecosystems. The findings provide researchers with entry points for a problem-centered approach to the topic, serving as an initial starting point for a more in-depth work and examination. In this way, further research can address the challenges and liberate the full potential of Shared Manufacturing.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}