@inproceedings{49362,
  author       = {{Weller, Julian and Migenda, Nico and Wegel, Arthur and Kohlhase, Martin and Schenk, Wolfram and Dumitrescu, Roman}},
  booktitle    = {{IEEE ADACIS 2023}},
  location     = {{Marrakesh, Marokko}},
  title        = {{{Conceptual Framework for Prescriptive Analytics based on decision Theory}}},
  year         = {{2023}},
}

@inproceedings{47836,
  author       = {{Ködding, Patrick and Koldewey, Christian and Dumitrescu, Roman}},
  booktitle    = {{Proceedings of the XXXII ISPIM Innovation Conference}},
  title        = {{{A Reference Process Model for Scenario-based Foresight}}},
  year         = {{2023}},
}

@inbook{49368,
  author       = {{Menzefricke, Jörn Steffen and Koldewey, Christian and Dumitrescu, Roman}},
  booktitle    = {{The Digital Twin of Humans}},
  isbn         = {{9783031261039}},
  publisher    = {{Springer International Publishing}},
  title        = {{{Enhancing Risk Management for Digitalisation Projects in the Context of Socio-Technical Systems}}},
  doi          = {{10.1007/978-3-031-26104-6_3}},
  year         = {{2023}},
}

@inproceedings{48601,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>In global competition, companies are continuously searching for a competitive advantage. A growing number of companies have identified the design of their products as a major success factor. The promises for companies associated with outstanding design are extremely attractive, ranging from better customer experience to higher sales growth. But even though the advantages of design seem to be compelling, companies are still having difficulties in leveraging the benefits of design.</jats:p><jats:p>In this paper, we want to identify the underlying challenges that explain this gap. We are especially interested in the role and challenges of design in interdisciplinary product development. Therefore, we perform a literature review that clarifies terminology, analyses research approaches and identifies challenges. We determine seven key challenges for design in interdisciplinary product development. Furthermore, we observe a limited scope of research approaches in the reviewed literature. Based on these findings, we propose three further research directions to strengthen the role of design in interdisciplinary product development in the future.</jats:p>}},
  author       = {{Stöhr, Bernd and Koldewey, Christian and Dumitrescu, Roman}},
  booktitle    = {{Proceedings of the Design Society}},
  issn         = {{2732-527X}},
  pages        = {{3473--3482}},
  publisher    = {{Cambridge University Press (CUP)}},
  title        = {{{The Role of Design in interdisciplinary Product Development – Challenges, Research Approaches and Further Research needs}}},
  doi          = {{10.1017/pds.2023.348}},
  volume       = {{3}},
  year         = {{2023}},
}

@article{47850,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>The megatrend sustainability will significantly change the future value creation of manufacturing companies. Their current linear value creation models need to change to conform to the requirements of sustainability. To face the challenges the circular economy has emerged as a promising economic model. With the shift from a linear to a circular economy, companies have to adjust their current business models. However, they still lack knowledge and adequate methods to develop circular business models. Hence, the aim of the paper is a circular business model canvas (CBMC) for designing circular businesses. A systematic literature review was conducted to identify significant criteria for circular business models. The criteria were analyzed utilizing a qualitative content analysis to derive the business model elements required for the circular economy. Existing elements from the Business Model Canvas were enriched and five new elements, e.g., reverse logistics, were found. Then, the business model elements were logically arranged resulting in the CBMC. It guides companies to systematically develop business models for the circular economy. The CBMC was evaluated by applying it within a mediumsized company in the electronics sector.</jats:p>}},
  author       = {{Scholtysik, Michel and Rohde, Malte and Koldewey, Christian and Dumitrescu, Roman}},
  issn         = {{2732-527X}},
  journal      = {{Proceedings of the Design Society}},
  pages        = {{1347--1356}},
  publisher    = {{Cambridge University Press (CUP)}},
  title        = {{{Designing Business Models for a Circular Economy}}},
  doi          = {{10.1017/pds.2023.135}},
  volume       = {{3}},
  year         = {{2023}},
}

@article{47813,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>The development of modern vehicles is complex, especially regarding compliance with security and safety. ISO/SAE 21434 considers security and safety along the entire product life cycle. According to the standard, a system architecture, a risk analysis, and the application of countermeasures are carried out in the early system design. Design patterns are solutions to known design problems. Security Design Patterns (SDP) describe countermeasures and are used to reduce risk. After our literature review, we did not find a suitable approach that presents SDPs that would be applicable in early system design. In this paper, we present 10 SDPs for early system design, which we evaluated during an 11-week student project with 28 teams. We present the results of the quantitative analysis and the evaluation of the feedback.</jats:p>}},
  author       = {{Japs, Sergej and Faheem, Faizan and Anacker, Harald and Husung, Stephan and Dumitrescu, Roman}},
  issn         = {{2732-527X}},
  journal      = {{Proceedings of the Design Society}},
  pages        = {{2675--2684}},
  publisher    = {{Cambridge University Press (CUP)}},
  title        = {{{Model-based Systems Engineering using Security Design Patterns in the Context of ISO/SAE 21434}}},
  doi          = {{10.1017/pds.2023.268}},
  volume       = {{3}},
  year         = {{2023}},
}

@inproceedings{49361,
  author       = {{Seidenberg, Tobias and Disselkamp, Jan-Philipp and Jürgenhake, Christoph and Wicker, Ansgar and Dumitrescu, Roman and Tolo, Edmund}},
  location     = {{Edingburgh}},
  title        = {{{TCO analysis of a modular and integral product architecture in shipbuilding}}},
  doi          = {{ 10.1109/ICE/ITMC58018.2023.10332277}},
  year         = {{2023}},
}

@inproceedings{49360,
  author       = {{Disselkamp, Jan-Philipp and Seidenberg, Tobias and Jürgenhake, Christoph and Anacker, Harald and Dumitrescu, Roman}},
  location     = {{Edingburgh}},
  title        = {{{Future production of ships – case study for modular high-speed ferries}}},
  doi          = {{ 10.1109/ICE/ITMC58018.2023.10332382}},
  year         = {{2023}},
}

@inproceedings{52369,
  abstract     = {{Megatrends, such as digitization or sustainability, are confronting the product management of manufacturing companies with a variety of challenges regarding the design of future products, but also the management of the actual products. To successfully position their products in the market, product managers need to gather and analyze comprehensive information about customers, developments in the products’ environment, product usage, and more. The digitization of all aspects of life is making data on these topics increasingly available – via social media, documents, or the internet of things from the products themselves. The systematic collection and analysis of these data enable the exploitation of new potentials for the adaption of existing products and the creation of the products of tomorrow. However, there are still no insights into the main concepts and cause-effect relationships in exploiting data-driven approaches for product management. Therefore, this paper aims to identify the main concepts and advantages of data-driven product management. To answer the corresponding research questions a comprehensive systematic literature review is conducted. From its results, a detailed description of the main concepts of data-driven product management is derived. Furthermore, a taxonomy for the advantages of data-driven product management is presented. The main concepts and the taxonomy allow for a deeper understanding of the topic while highlighting necessary future actions and research needs.}},
  author       = {{Fichtler, Timm and Grigoryan, Khoren and Koldewey, Christian and Dumitrescu, Roman}},
  booktitle    = {{2023 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD)}},
  keywords     = {{Product Lifecyle Management (PLM), Data Analytics, Data-driven Design, Engineering Management, Lifecycle Data}},
  location     = {{Rabat, Morocco}},
  publisher    = {{IEEE}},
  title        = {{{Towards a Data-Driven Product Management – Concepts, Advantages, and Future Research}}},
  doi          = {{10.1109/ictmod59086.2023.10438135}},
  year         = {{2023}},
}

@misc{52671,
  author       = {{Dumitrescu, Roman and Hölzle, K.}},
  isbn         = {{978-3-947647-32-3}},
  title        = {{{Vorausschau und Technologieplanung. 17. Symposium für Vorausschau und Technologieplanung }}},
  volume       = {{Band 413}},
  year         = {{2023}},
}

@inbook{53553,
  author       = {{Özcan, Leon and Drewel, Marvin and Koldewey, Christian and Dumitrescu, Roman}},
  booktitle    = {{Digitalisierung: Fallstudien, Tools und Erkenntnisse für das digitale Zeitalter}},
  editor       = {{Schallmo, Daniel and Lang, Klaus and Werani, Thomas and Krumay, Barbara}},
  isbn         = {{9783658366339}},
  issn         = {{2569-2348}},
  publisher    = {{Springer Fachmedien Wiesbaden}},
  title        = {{{Strategische Planung des Einstiegs in die Plattformökonomie}}},
  doi          = {{10.1007/978-3-658-36634-6_7}},
  year         = {{2023}},
}

@techreport{53554,
  author       = {{Dumitrescu, Roman and Riemensperger, Frank and Schuh, Günther and Biehler, Jan and Frey, Anna and Hocken, Christian and Koldewey, Christian and Kühn, Arno and Rabe, Martin and Schacht, Maximilian and Comans, Sebastian and Fichtler, Timm and Govioni, Alina and Harland, Tobias and Kaufmann, Jonas and Optehostert, Felix and Rieger, Marcel and Scholtysik, Michel and Schreiner, Nick and Sedlmeir, Joachim and Sommer, Franziska}},
  title        = {{{acatech Maturity Index Smart Services}}},
  year         = {{2023}},
}

@inproceedings{49363,
  author       = {{Scholtysik, Michel and Rohde, Malte and Koldewey, Christian and Dumitrescu, Roman}},
  title        = {{{Circular Product-Service-System Ideation Canvas – A Framework for the Design of circular Product-Service-System Ideas}}},
  volume       = {{120}},
  year         = {{2023}},
}

@inbook{47834,
  author       = {{Ködding, Patrick and Koldewey, Christian and Dumitrescu, Roman}},
  booktitle    = {{New Digital Work}},
  editor       = {{Shajek, Alexandra and Hartmann, Ernst A.}},
  pages        = {{51--67}},
  title        = {{{Scenario-Based Foresight in the Age of Digital Technologies and AI}}},
  year         = {{2023}},
}

@article{47835,
  author       = {{Ködding, Patrick and Ellermann, Kai and Koldewey, Christian and Dumitrescu, Roman}},
  issn         = {{2212-8271}},
  journal      = {{Procedia CIRP}},
  keywords     = {{General Medicine}},
  pages        = {{740--745}},
  publisher    = {{Elsevier BV}},
  title        = {{{Scenario-based Foresight in the Age of Digitalization and Artificial Intelligence – Identification and Analysis of Existing Use Cases}}},
  doi          = {{10.1016/j.procir.2023.01.015}},
  volume       = {{119}},
  year         = {{2023}},
}

@inproceedings{54286,
  abstract     = {{<jats:p>The integration of Artificial Intelligence (AI) techniques into various domains has revolutionized numerous industries, and Supply Chain Management (SCM) is no exception. This paper addresses the challenges encountered in SCM and the development of AI solutions within this context. Specifically, we focus on the application of AI in optimizing supply chain planning tasks. This includes forecasting demand, availability and feasibility checks for customer orders, supply chain network design and information flow inside the supply chain planning processes.  However, the successful implementation of AI in SCM requires a deep understanding of both the domain-specific challenges and the capabilities and limitations of AI technologies. Thus, this paper proposes an overarching approach that facilitates collaboration between domain experts in SCM and AI experts, enabling them to jointly develop effective solutions.The paper begins by outlining the key challenges faced by SCM professionals, including demand volatility, complexities in inventory management, and dynamic market conditions. Subsequently, it delves into the challenges associated with developing AI solutions for SCM, including data quality, interpretability, and model transparency. To address these challenges, the proposed approach promotes close collaboration and knowledge exchange between SCM and AI experts. By leveraging the domain knowledge and experience of SCM experts, AI experts  can better understand the special issues of SCM processes and tailor AI techniques to suit specific needs. In turn, SCM experts can gain insights into the capabilities and limitations of AI, allowing them to make informed decisions regarding the adoption and integration of AI in their supply chain planning operations. Furthermore, the paper discusses the importance of establishing a multidisciplinary team comprising experts from the fields of SCM, AI, and IT.   This team-based approach fosters a holistic understanding of SCM challenges and ensures the development of AI solutions that align with business goals and practical constraints.In conclusion, this paper highlights the challenges in combining SCM and AI and proposes a collaborative approach to address these challenges effectively. By leveraging the expertise of both domain and AI experts, organizations can develop tailored AI solutions that enhance supply chain planning, improve decision-making processes, and drive competitive advantage. The proposed approach contributes to the successful integration of AI in SCM, ultimately leading to more efficient and resilient supply chains in the era of artificial intelligence.</jats:p>}},
  author       = {{Lick, Jonas and Wohlers, Benedict and Sahrhage, Philipp and Schreckenberg, Felix and Klöckner, Susanne and Von Enzberg, Sebastian and Kühn, Arno and Dumitrescu, Roman}},
  booktitle    = {{Artificial Intelligence, Social Computing and Wearable Technologies}},
  issn         = {{2771-0718}},
  publisher    = {{AHFE International}},
  title        = {{{Integrating Domain Expertise and Artificial Intelligence for Effective Supply Chain Management Planning Tasks: A Collaborative Approach}}},
  doi          = {{10.54941/ahfe1004185}},
  year         = {{2023}},
}

@inproceedings{54506,
  author       = {{Lick, Jonas and Schreckenberg, Felix and Sahrhage, Philipp  and Wohlers, Benedict and Klöcker, Susanne and von Enzberg,  Sebastian  and Kühn,  Arno and Dumitrescu, Roman}},
  booktitle    = {{Artificial Intelligence, Social Computing and Wearable Technologies, Vol. 113}},
  editor       = {{Karwowsk, Waldemar  and Ahram, Tareq }},
  location     = {{Hawaii}},
  title        = {{{Integrating Domain Expertise and Artificial Intelligence for Effective Supply Chain Management Planning Tasks: A Collaborative Approach}}},
  year         = {{2023}},
}

@inproceedings{54503,
  author       = {{Günther, Matthias and Göllner, Denis and Heihoff-Schwede, Jörg and Anacker, Harald  and Dumitrescu, Roman}},
  booktitle    = {{Tag des Systems Engineering 2023}},
  editor       = {{Wilke, Daria and Koch, Walter and Kaffenberger, Rüdiger and Dreiseitel, Stefan}},
  location     = {{Würzburg}},
  title        = {{{Engineering und Management von System of Systems–Gestaltungskonzepte im SoS-Engineering}}},
  year         = {{2023}},
}

@inproceedings{54505,
  author       = {{Wilke, Daria and Heitmann, Rebecca and Tekaat, Julian  and Anacker, Harald and Dumitrescu, Roman}},
  booktitle    = {{Tag des Systems Engineering 2023}},
  editor       = {{Wilke, Daria and Koch, Walter and Kaffenberger, Rüdiger and Dreiseitel, Stefan}},
  location     = {{Würzburg}},
  title        = {{{Reifegradmodell zur Einführung von Systems Engineering–Systemdenken als Handlungsfeld}}},
  year         = {{2023}},
}

@inproceedings{54507,
  author       = {{Mager, Thomas and Dumitrescu, Roman}},
  location     = {{Amberg}},
  title        = {{{Hybrid design approach for the design of high-frequency components in MID technology}}},
  year         = {{2023}},
}