@article{RojahnWeberGronau2023,
  author    = {Rojahn, Marcel and Weber, Edzard and Gronau, Norbert},
  title     = {Towards a standardization in scheduling models},
  series = {International journal of industrial and systems engineering},
  volume    = {17},
  journal   = {International journal of industrial and systems engineering},
  number    = {6},
  publisher = {Inderscience Enterprises},
  address   = {Gen{\`e}ve},
  issn      = {1748-5037},
  pages     = {401 -- 408},
  year      = {2023},
  abstract  = {Terminology is a critical instrument for each researcher. Different terminologies for the same research object may arise in different research communities. By this inconsistency, many synergistic effects get lost. Theories and models will be more understandable and reusable if a common terminology is applied. This paper examines the terminological (in)consistence for the research field of job-shop scheduling by a literature review. There is an enormous variety in the choice of terms and mathematical notation for the same concept. The comparability, reusability and combinability of scheduling methods is unnecessarily hampered by the arbitrary use of homonyms and synonyms. The acceptance in the community of used variables and notation forms is shown by means of a compliance quotient. This is proven by the evaluation of 240 scientific publications on planning methods.},
  language  = {en}
}
@inproceedings{GrumBlunkRojahnetal.2020,
  author    = {Grum, Marcus and Blunk, Oliver and Rojahn, Marcel and Fettke, Peter and Gronau, Norbert},
  title     = {Research challenges of knowledge modelling and the outline of a research agenda},
  series = {Knowledge in digital age : IFKAD 2020},
  booktitle = {Knowledge in digital age : IFKAD 2020},
  publisher = {The Arts of Business Institute},
  address   = {Matera, Italy},
  isbn      = {978-88-96687-13-0},
  issn      = {2280-787X},
  year      = {2020},
  language  = {en}
}
@article{Rojahn2023,
  author    = {Rojahn, Marcel},
  title     = {Professionelle Personalzeiterfassung},
  series = {Factory Innovation : agil und smart mit Industrie 4.0},
  volume    = {4},
  journal   = {Factory Innovation : agil und smart mit Industrie 4.0},
  number    = {2},
  publisher = {GITO mbH - Verlag f{\"u}r Industrielle Informationstechnik und Organisation},
  address   = {Berlin},
  issn      = {2749-7593},
  pages     = {74 -- 74},
  year      = {2023},
  abstract  = {Der Einsatz digitaler Personalzeiterfassungssysteme bietet Unternehmen zahlreiche Vorteile, z. B. effizientere Lohn- und Gehaltsabrechnungen, mehr Transparenz und {\"U}bersicht {\"u}ber die Arbeitszeiten der Mitarbeiter sowie flexiblere Erfassungsm{\"o}glichkeiten. In der Testreihe werden neun L{\"o}sungen auf Funktionen, Benutzerfreundlichkeit, Kosten, Zuverl{\"a}ssigkeit, Kompatibilit{\"a}t, Implementierung und Barrierefreiheit getestet. Erfahren Sie, welche L{\"o}sungen am besten abschneiden und ob eine davon f{\"u}r Ihr Unternehmen geeignet ist.},
  language  = {de}
}
@inproceedings{RojahnGronau2024,
  author    = {Rojahn, Marcel and Gronau, Norbert},
  title     = {Openness indicators for the evaluation of digital platforms between the launch and maturity phase},
  series = {Proceedings of the 57th Annual Hawaii International Conference on System Sciences},
  booktitle = {Proceedings of the 57th Annual Hawaii International Conference on System Sciences},
  editor    = {Bui, Tung X.},
  publisher = {Department of IT Management Shidler College of Business University of Hawaii},
  address   = {Honolulu, HI},
  isbn      = {978-0-99813-317-1},
  pages     = {4516 -- 4525},
  year      = {2024},
  abstract  = {In recent years, the evaluation of digital platforms has become an important focus in the field of information systems science. The identification of influential indicators that drive changes in digital platforms, specifically those related to openness, is still an unresolved issue. This paper addresses the challenge of identifying measurable indicators and characterizing the transition from launch to maturity in digital platforms. It proposes a systematic analytical approach to identify relevant openness indicators for evaluation purposes. The main contributions of this study are the following (1) the development of a comprehensive procedure for analyzing indicators, (2) the categorization of indicators as evaluation metrics within a multidimensional grid-box model, (3) the selection and evaluation of relevant indicators, (4) the identification and assessment of digital platform architectures during the launch-to-maturity transition, and (5) the evaluation of the applicability of the conceptualization and design process for digital platform evaluation.},
  language  = {en}
}
@inproceedings{RojahnGronau2023,
  author    = {Rojahn, Marcel and Gronau, Norbert},
  title     = {Digital platform concepts for manufacturing companies},
  series = {10th International Conference on Future Internet of Things and Cloud (FiCloud)},
  booktitle = {10th International Conference on Future Internet of Things and Cloud (FiCloud)},
  publisher = {IEEE},
  address   = {[Erscheinungsort nicht ermittelbar]},
  isbn      = {979-8-3503-1635-3},
  doi       = {10.1109/FiCloud58648.2023.00030},
  pages     = {149 -- 158},
  year      = {2023},
  abstract  = {Digital Platforms (DPs) has established themself in recent years as a central concept of the Information Technology Science. Due to the great diversity of digital platform concepts, clear definitions are still required. Furthermore, DPs are subject to dynamic changes from internal and external factors, which pose challenges for digital platform operators, developers and customers. Which current digital platform research directions should be taken to address these challenges remains open so far. The following paper aims to contribute to this by outlining a systematic literature review (SLR) on digital platform concepts in the context of the Industrial Internet of Things (IIoT) for manufacturing companies and provides a basis for (1) a selection of definitions of current digital platform and ecosystem concepts and (2) a selection of current digital platform research directions. These directions are diverted into (a) occurrence of digital platforms, (b) emergence of digital platforms, (c) evaluation of digital platforms, (d) development of digital platforms, and (e) selection of digital platforms.},
  language  = {en}
}
@incollection{GronauRojahn2021,
  author    = {Gronau, Norbert and Rojahn, Marcel},
  title     = {Das Industrial Internet of Things (IIOT)},
  series = {IT-Recht : Recht, Wirtschaft und Technik der digitalen Transformation},
  booktitle = {IT-Recht : Recht, Wirtschaft und Technik der digitalen Transformation},
  editor    = {Leupold, Andreas and Wiebe, Andreas and Glossner, Silke},
  edition   = {4., {\"u}berarbeitet und erweitert},
  publisher = {C.H. Beck},
  address   = {M{\"u}nchen},
  isbn      = {978-3-406-74458-7},
  pages     = {1115 -- 1124},
  year      = {2021},
  language  = {de}
}
@incollection{RojahnAmbrosBiruetal.2023,
  author    = {Rojahn, Marcel and Ambros, Maximilian and Biru, Tibebu and Krallmann, Hermann and Gronau, Norbert and Grum, Marcus},
  title     = {Adequate basis for the data-driven and machine-learning-based identification},
  series = {Artificial intelligence and soft computing},
  booktitle = {Artificial intelligence and soft computing},
  editor    = {Rutkowski, Leszek and Scherer, Rafał and Korytkowski, Marcin and Pedrycz, Witold and Tadeusiewicz, Ryszard and Zurada, Jacek M.},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-031-42504-2},
  doi       = {10.1007/978-3-031-42505-9_48},
  pages     = {570 -- 588},
  year      = {2023},
  abstract  = {Process mining (PM) has established itself in recent years as a main method for visualizing and analyzing processes. However, the identification of knowledge has not been addressed adequately because PM aims solely at data-driven discovering, monitoring, and improving real-world processes from event logs available in various information systems. The following paper, therefore, outlines a novel systematic analysis view on tools for data-driven and machine learning (ML)-based identification of knowledge-intensive target processes. To support the effectiveness of the identification process, the main contributions of this study are (1) to design a procedure for a systematic review and analysis for the selection of relevant dimensions, (2) to identify different categories of dimensions as evaluation metrics to select source systems, algorithms, and tools for PM and ML as well as include them in a multi-dimensional grid box model, (3) to select and assess the most relevant dimensions of the model, (4) to identify and assess source systems, algorithms, and tools in order to find evidence for the selected dimensions, and (5) to assess the relevance and applicability of the conceptualization and design procedure for tool selection in data-driven and ML-based process mining research.},
  language  = {en}
}