@phdthesis{61916,
  abstract     = {{Diese Dissertation untersucht Optimierungsverfahren für die nachhaltige Gestaltung von Energiesystemen mit Schwerpunkt auf dem Elektrizitätssektor im Kontext der Energiewende. Aufbauend auf Methoden des Operations Research werden Planungs- und Steuerungsprobleme in den Bereichen Stromverteilnetze und energiebewusste Produktionsplanung adressiert. Die Arbeit umfasst fünf Beiträge: (P1) entwickelt ein lineares Multi-Commodity-Flow-Modell für die kostenoptimale Erweiterung großskaliger Verteilnetze unter Berücksichtigung von Resilienzszenarien und analysiert den Zusammenhang zwischen Modellparametern und Rechenzeiten; (P2) und (P3) befassen sich mit der mehrzielorientierten flexible Job Shop Scheduling-Optimierung unter Echtzeit-Strompreisen, wobei (P3) zusätzlich CO2-Emissionen als Zielgröße integriert; (P4) erweitert dieses Szenario um simultane Energiebeschaffungsentscheidungen aus Netz, erneuerbaren Quellen und Speichersystemen unter Unsicherheit mittels Rolling-Horizon-Ansatz; (P5) vergleicht unterschiedliche Klassen von Many-Objective Evolutionary Algorithms (dominanz-, indikatoren- und dekompositionsbasiert) im Hinblick auf Konvergenz, Diversität und Vollständigkeit der Paretofront. Die entwickelten Modelle und Algorithmen – darunter memetische Varianten von NSGA-II, NSGA-III, θ-DEA und HypE – werden durch umfassende Rechenexperimente evaluiert. Die Ergebnisse liefern praxisrelevante Handlungsempfehlungen für Netzbetreiber, produzierende Unternehmen und politische Entscheidungsträger und leisten einen Beitrag zur effizienten, zuverlässigen und emissionsarmen Energieversorgung der Zukunft.}},
  author       = {{Burmeister, Sascha Christian}},
  publisher    = {{LibreCat University}},
  title        = {{{Optimization Techniques for Sustainable Energy System Design}}},
  doi          = {{10.17619/UNIPB/1-2403}},
  year         = {{2025}},
}

@article{59335,
  abstract     = {{Technological advancements and evolving value orientations reshape future value creation and pose new requirements for service innovation. While a variety of disciplines are developing new approaches to drive service innovation, this is primarily done in isolation and generates only fragmented solutions. Sociological theory has proposed “boundary objects” as an effective umbrella for communication and cooperation among communities. Therefore, we introduce continuous value shaping (CVS) as a boundary object describing service innovation approaches along five principles. We reflect on this concept through the different disciplinary lenses of researchers in service marketing, information systems, service engineering, sociology of work, and innovation management. These perspectives highlight how the CVS principles already connect to discourses within the individual disciplines. However, the CVS concept will not only provide an umbrella to embrace existing activities in different academic disciplines. It also assists to identify research themes that will benefit from uniting the power of these disciplines, and it can serve as an integrating framework to conceptualize complex service innovation approaches. Thus, the CVS concept should guide both researchers and practitioners to develop and implement novel innovation and transformation efforts—in and across organizations.}},
  author       = {{Böhmann, Tilo and Roth, Angela and Satzger, Gerhard and Benz, Carina and Beverungen, Daniel and Boes, Andreas and Breidbach, Christoph and Gersch, Martin and Gudergan, Gerhard and Hogreve, Jens and Kurtz, Christian and Langes, Barbara and Leimeister, Jan Marco and Lewandowski, Tom and Meiren, Thomas and Nägele, Rainer and Paluch, Stefanie and Peters, Christoph and Poeppelbuss, Jens and Robra-Bissantz, Susanne and Schultz, Carsten and Schumann, Jan H. and Wirtz, Jochen and Wünderlich, Nancy V.}},
  issn         = {{1019-6781}},
  journal      = {{Electronic Markets}},
  keywords     = {{Continuous value shaping (CVS), Service research, Service innovation, Digitalization, Sustainability, Interdisciplinary research}},
  number       = {{1}},
  publisher    = {{Springer Science and Business Media LLC}},
  title        = {{{Continuous value shaping: A boundary concept for innovating service innovation approaches}}},
  doi          = {{10.1007/s12525-025-00771-1}},
  volume       = {{35}},
  year         = {{2025}},
}

@article{54775,
  author       = {{Trang, Simon Thanh-Nam and Krämer, Tobias  and Trenz, Manuel and Weiger, Welt}},
  journal      = {{Information Systems Research (VHB Jourqual 3 A+, FT50)}},
  number       = {{2}},
  title        = {{{Deeper down the rabbit hole - How technology conspiracy beliefs emerge and foster a conspiracy mindset}}},
  doi          = {{10.1287/isre.2022.0494}},
  volume       = {{36}},
  year         = {{2025}},
}

@article{56603,
  author       = {{Trang, Simon Thanh-Nam and Trenz, Manuel and Welf, Weiger}},
  journal      = {{Journal of Information Technology}},
  number       = {{3}},
  title        = {{{Don’t count your chickens before they hatch: Conceptualizing and exploring deviations from polls during public health app releases}}},
  doi          = {{10.1177/02683962241295781}},
  volume       = {{40}},
  year         = {{2025}},
}

@article{54576,
  author       = {{Nastjuk, Ilja and Rampold, Florian and Trang, Simon Thanh-Nam and Benitez, Jose}},
  issn         = {{0960-085X}},
  journal      = {{European Journal of Information Systems (VHB Jourqual 3 A)}},
  number       = {{4}},
  pages        = {{1--24}},
  publisher    = {{Informa UK Limited}},
  title        = {{{A field experiment on ISP training designs for enhancing employee information security compliance}}},
  doi          = {{10.1080/0960085x.2024.2359460}},
  volume       = {{34}},
  year         = {{2025}},
}

@article{62151,
  author       = {{Keller, Thomas and Warwas, Julia and Klein, Julia and Henkenjohann, Richard and Trenz, Manuel and Trang, Simon Thanh-Nam}},
  journal      = {{JMIR Medical Education}},
  number       = {{e73245}},
  title        = {{{ Motivational Framing Strategies in Health Care Information Security Training: Randomized Controlled Trial}}},
  doi          = {{10.2196/73245}},
  volume       = {{11}},
  year         = {{2025}},
}

@article{62152,
  author       = {{Schütz, Florian and Ortiz de Guinea Lopez, Ana and Wolf, Tobias and Trang, Simon Thanh-Nam}},
  journal      = {{Communications of the Association for Information Systems}},
  title        = {{{Better (Cyber) Insured than Sorry? Unraveling Cognitive Factors in the (Non-)Adoption of Personal Cyber Insurance using fsQCA}}},
  volume       = {{accepted}},
  year         = {{2025}},
}

@techreport{62282,
  author       = {{Althaus, Maike}},
  pages        = {{24 -- 25}},
  title        = {{{Datenraum Kultur - Neue Forschung aus dem Projekt}}},
  volume       = {{3}},
  year         = {{2025}},
}

@techreport{62281,
  author       = {{Kundisch, Dennis}},
  pages        = {{20 -- 21}},
  title        = {{{Startschuss für die digitale Zukunft - Das Digital Talents Program geht in die nächste Runde}}},
  volume       = {{3}},
  year         = {{2025}},
}

@techreport{63024,
  author       = {{Vorbohle, Christian and Althaus, Maike and Kundisch, Dennis}},
  title        = {{{Identifizierung und Entwicklung von tragfähigen Geschäftsmodellen für Kulturplattformen im Datenraum Kultur}}},
  year         = {{2025}},
}

@techreport{63025,
  author       = {{Vorbohle, Christian and Althaus, Maike and Kundisch, Dennis}},
  title        = {{{Sponsoring als Geschäftsmodell für Kulturplattformen im Datenraum Kultur: Vorstellung und Validierung}}},
  year         = {{2025}},
}

@techreport{63022,
  author       = {{Althaus, Maike and Vorbohle, Christian and Kundisch, Dennis}},
  title        = {{{Kulturplattformen im Datenraum Kultur: Eine Analyse bestehender Geschäftsmodelle von Kulturplattformen}}},
  year         = {{2025}},
}

@inproceedings{63199,
  author       = {{Hövel, Gilbert Georg and Brinkmeier, Tim and Trang, Simon Thanh-Nam}},
  booktitle    = {{Proceedings of the International Conference on Information Systems 2025}},
  title        = {{{Trust Me If You Can! Examining the Role of Ransomware Darknet Platforms in Building Trust Between Hackers and Victims}}},
  year         = {{2025}},
}

@inproceedings{63524,
  abstract     = {{Recommendation systems are essential for delivering personalized content across e-commerce and streaming services. However, traditional methods often fail in cold-start scenarios where new items lack prior interactions. Recent advances in large language models (LLMs) offer a promising alternative. In this paper, we adopt the retrieve-and-recommend framework and propose to fine-tune the LLM jointly on warm-and cold-start next-item recommendation tasks, thus, mitigating the need for separate models for both item types. We computationally compare zero-shot prompting, in-context learning, and fine-tuning using the same LLM backbone, and benchmark them against strong PLM-based baselines. Our findings provide practical insights into the trade-offs between accuracy and computational cost of these methods for next-item recommendation. To enhance reproducibility, we release the source code under https://github. com/HayaHalimeh/LLMs-For-Next-Item-Recommendation.git.}},
  author       = {{Halimeh, Haya and Freese, Florian and Müller, Oliver}},
  booktitle    = {{International Conference on Information Systems Development}},
  issn         = {{2938-5202}},
  publisher    = {{University of Gdansk, Department of Business Informatics & University of Belgrade, Faculty of Organizational Sciences}},
  title        = {{{LLMs For Warm and Cold Next-Item Recommendation: A Comparative Study across Zero-Shot Prompting, In-Context Learning and Fine-Tuning}}},
  doi          = {{10.62036/isd.2025.68}},
  year         = {{2025}},
}

@inproceedings{63523,
  abstract     = {{Data spaces have become a strategic pillar of Europe's digital agenda, enabling sovereign, legally compliant data sharing within decentralized ecosystems. As data space initiatives evolve, personalized recommendations are increasingly recognized as key use cases. However, traditional recommendation approaches typically rely on centralized aggregation of user behavior data-directly conflicting with the core ethos of data spaces: sovereignty, privacy, and trust. Federated recommendation systems offer a promising alternative by training models locally and exchanging only intermediate parameters to build a global model. Despite this potential, the integration of federated recommendation techniques and data space architectures remains largely underexplored in research and practice. This paper addresses this gap by designing and evaluating a prototype of a federated recommendation system specifically tailored for data spaces and compliant with their underlying infrastructure. Our findings highlight the viability of developing privacy-preserving, collaborative recommendation systems within data spaces, and contribute to the broader adoption of AI across these emerging ecosystems.}},
  author       = {{Halimeh, Haya and zur Heiden, Philipp}},
  booktitle    = {{2025 27th International Conference on Business Informatics (CBI)}},
  publisher    = {{IEEE}},
  title        = {{{Preserving Sovereignty and Privacy for Personalization: Designing a Federated Recommendation System for Data Spaces}}},
  doi          = {{10.1109/cbi68102.2025.00019}},
  year         = {{2025}},
}

@inproceedings{63525,
  abstract     = {{Recommender systems (RS) can support sustainable development by steering users toward more sustainable choices. Sustainability-aware explanations represent one avenue for contributing to this goal by foregrounding the environmental and social aspects of the recommended products or services. This paper advances the line of research on sustainability-aware explanations by integrating nudging mechanisms into their design and by evaluating their effectiveness through a randomized between-subjects online vignette experiment across two item domains (). Our findings offer actionable design guidelines for building RS that foster sustainability-aware decision making and enrich the empirical foundation for impact-oriented research on explanation in RS.
}},
  author       = {{Halimeh, Haya and Müller, Oliver}},
  location     = {{Prague, Czech Republic}},
  title        = {{{Towards Greener Choices: Decision Information Nudging for Sustainability-Aware Recommender Explanations}}},
  doi          = {{10.1007/978-3-032-13342-7}},
  year         = {{2025}},
}

@techreport{63026,
  author       = {{Althaus, Maike and Beverungen, Daniel and Flath, Beate and Halimeh, Haya and Hansmeier, Philipp and zur Heiden, Philipp and Kundisch, Dennis and Müller, Michelle and Müller, Oliver and Oberthür, Simon and Vorbohle, Christian and Momen Pour Tafreshi, Maryam and Mauß, Sebastian and Mücke, Alina and Müller, Jörg and Peter, Malte and Schmitt-Chandon, Ariane and Sellerberg, Kerstin and Steinhäuser, Moritz}},
  title        = {{{Positionspapier Use Case 1: Vernetzte Kulturplattformen}}},
  year         = {{2025}},
}

@book{59182,
  editor       = {{Beverungen, Daniel and Lehrer, Christiane and Trier, Matthias}},
  isbn         = {{9783031801242}},
  issn         = {{2195-4968}},
  publisher    = {{Springer Nature Switzerland}},
  title        = {{{Transforming the Digitally Sustainable Enterprise}}},
  doi          = {{10.1007/978-3-031-80125-9}},
  year         = {{2025}},
}

@book{59287,
  editor       = {{Beverungen, Daniel and Lehrer, Christiane and Trier, Matthias}},
  isbn         = {{9783031801211}},
  issn         = {{2195-4968}},
  publisher    = {{Springer Nature Switzerland}},
  title        = {{{Solutions and Technologies for Responsible Digitalization}}},
  doi          = {{10.1007/978-3-031-80122-8}},
  year         = {{2025}},
}

@inproceedings{60534,
  author       = {{Vorbohle, Christian}},
  booktitle    = {{Proceedings of the Business Model Conference 2025}},
  location     = {{Oulu, Finland}},
  title        = {{{Toward Design Principles to Enhance Visual Inquiry Tools for Ecosystem Design}}},
  year         = {{2025}},
}