@article{34402, author = {{Yigitbas, Enes and Klauke, Jonas and Gottschalk, Sebastian and Engels, Gregor}}, journal = {{Journal on Computer Languages (COLA) }}, publisher = {{Elsevier}}, title = {{{End-User Development of Interactive Web-Based Virtual Reality Scenes}}}, year = {{2023}}, } @inproceedings{33511, author = {{Yigitbas, Enes and Engels, Gregor}}, booktitle = {{56th Hawaii International Conference on System Science (HICSS 2023) }}, publisher = {{ScholarSpace}}, title = {{{Enhancing Robot Programming through Digital Twin and Augmented Reality }}}, year = {{2023}}, } @inproceedings{34401, author = {{Yigitbas, Enes and Krois, Sebastian and Gottschalk, Sebastian and Engels, Gregor}}, booktitle = {{Proceedings of the 7th International Conference on Human Computer Interaction Theory and Applications (HUCAPP'23) }}, title = {{{Towards Enhanced Guiding Mechanisms in VR Training through Process Mining}}}, year = {{2023}}, } @inproceedings{43424, author = {{Yigitbas, Enes and Nowosad, Alexander and Engels, Gregor}}, booktitle = {{Proceedings of the 19th IFIP TC13 International Conference on Human-Computer Interaction (INTERACT 2023)}}, publisher = {{Springer}}, title = {{{Supporting Construction and Architectural Visualization through BIM and AR/VR: A Systematic Literature Review}}}, year = {{2023}}, } @inproceedings{34294, author = {{Wolters, Dennis and Engels, Gregor}}, booktitle = {{MODELSWARD'23}}, isbn = {{978-989-758-633-0}}, issn = {{2184-4348}}, pages = {{133--142}}, publisher = {{SCITEPRESS}}, title = {{{Model-driven Collaborative Design of Professional Education Programmes With Extended Online Whiteboards}}}, doi = {{10.5220/0011675700003402}}, year = {{2023}}, } @inbook{45897, author = {{Gottschalk, Sebastian and Vorbohle, Christian and Kundisch, Dennis and Engels, Gregor and Wünderlich, Nacy V.}}, booktitle = {{On-The-Fly Computing -- Individualized IT-services in dynamic markets}}, editor = {{Haake, Claus-Jochen and Meyer auf der Heide, Friedhelm and Platzner, Marco and Wachsmuth, Henning and Wehrheim, Heike}}, pages = {{203--224}}, publisher = {{Heinz Nixdorf Institut, Universität Paderborn}}, title = {{{Architectural Management of OTF Computing Markets}}}, doi = {{10.5281/zenodo.8068691}}, volume = {{412}}, year = {{2023}}, } @article{47051, author = {{Yigitbas, Enes and Schmidt, Maximilian and Bucchiarone, Antonio and Gottschalk, Sebastian and Engels, Gregor}}, journal = {{Science of Computer Programming}}, publisher = {{Elsevier}}, title = {{{GaMoVR: Gamification-Based UML Learning Environment in Virtual Reality}}}, year = {{2023}}, } @inproceedings{47150, author = {{Yigitbas, Enes and Witalinski, Iwo and Gottschalk, Sebastian and Engels, Gregor}}, booktitle = {{Proceedings of the 24th International Conference on Product-Focused Software Process Improvement (PROFES 2023)}}, publisher = {{Springer}}, title = {{{Virtual Reality Collaboration Platform for Agile Software Development}}}, year = {{2023}}, } @inbook{28338, author = {{Kehrbusch, Burkhard and Engels, Gregor}}, booktitle = {{Digital Transformation: Core Technologies and Emerging Topics from a Computer Science Perspective}}, editor = {{Vogel-Heuser, Birgit and Wimmer, Manuel}}, publisher = {{Springer-Vieweg}}, title = {{{Digital Transformation - Towards flexible human-centric enterprises}}}, year = {{2022}}, } @inproceedings{29839, abstract = {{The development of business models is a challenging task that can be supported with software tools. Here, existing approaches and tools do not focus on the company’s situation in which the development takes place (e.g., financial resources, product type). To tackle this challenge, we used design science research to develop a situation-specific business model development approach that contains three stages: First, existing knowledge in terms of tasks to do (e.g., analyze competitive advantage), and decisions to be made (e.g., social media marketing) are stored in repositories. Second, the knowledge is used to compose a development method based on the company’s situation. Third, the development method is enacted to develop a business model. This demonstration paper presents a tool-support called Situational Business Model Developer that supports all stages of our approach. We release the tool under open-source and evaluate it with a case study on developing business models for mobile apps.}}, author = {{Gottschalk, Sebastian and Yigitbas, Enes and Nowosad, Alexander and Engels, Gregor}}, booktitle = {{Proceedings of the 17th International Conference on Wirtschaftsinformatik}}, keywords = {{Business Model Development, Situational Method Engineering, Tool Support}}, location = {{Nuremberg}}, publisher = {{AIS}}, title = {{{Situational Business Model Developer: A Tool-support for Situation-specific Business Model Development}}}, year = {{2022}}, } @inproceedings{29840, abstract = {{Due to the proliferation of Virtual Reality (VR) technology, VR is finding new applications in various domains, such as stock trading. Here, traders invest in stocks intending to increase their profit. For this purpose, in conventional stock trading, traders usually make use of 2D applications on desktop or laptop devices. This leads to many drawbacks such as poor visibility due to limited 2D representation, complex interaction due to indirect interaction via mouse and keyboard, or restricted support for collaboration between traders. To overcome these issues, we have developed a novel collaborative, virtual environment for stock trading, which enables stock traders to view financial information and trade stocks with other collaborators. The main results of a usability study indicate that the VR environment, compared to conventional stock trading, shows no significant advantages concerning efficiency and effectiveness, however, we could observe an increased user satisfaction and better collaboration.}}, author = {{Yigitbas, Enes and Gottschalk, Sebastian and Nowosad, Alexander and Engels, Gregor}}, booktitle = {{Proceedings of the 17th International Conference on Wirtschaftsinformatik}}, keywords = {{virtual reality, stock trading, collaboration, usability}}, location = {{Nuremberg}}, publisher = {{AIS}}, title = {{{Development and Evaluation of a Collaborative Stock Trading Environment in Virtual Reality}}}, year = {{2022}}, } @inproceedings{29927, author = {{Yigitbas, Enes and Karakaya, Kadiray and Jovanovikj, Ivan and Engels, Gregor}}, booktitle = {{Software Engineering 2022, Fachtagung des GI-Fachbereichs Softwaretechnik, 21.-25. Februar 2022, Virtuell}}, editor = {{Grunske, Lars and Siegmund, Janet and Vogelsang, Andreas}}, pages = {{95–96}}, publisher = {{Gesellschaft für Informatik e.V.}}, title = {{{Enhancing Human-in-the-Loop Adaptive Systems through Digital Twins and VR Interfaces}}}, doi = {{10.18420/se2022-ws-033}}, volume = {{{P-320}}}, year = {{2022}}, } @inproceedings{29926, author = {{Yigitbas, Enes and Gorissen, Simon and Weidmann, Nils and Engels, Gregor}}, booktitle = {{Software Engineering 2022, Fachtagung des GI-Fachbereichs Softwaretechnik, 21.-25. Februar 2022, Virtuell}}, editor = {{Grunske, Lars and Siegmund, Janet and Vogelsang, Andreas}}, pages = {{93–94}}, publisher = {{Gesellschaft für Informatik e.V.}}, title = {{{Collaborative Software Modeling in Virtual Reality}}}, doi = {{10.18420/se2022-ws-032}}, volume = {{{P-320}}}, year = {{2022}}, } @inbook{29928, author = {{Yigitbas, Enes and Sauer, Stefan and Engels, Gregor}}, booktitle = {{Digital Transformation: Core Technologies and Emerging Topics from a Computer Science Perspective}}, editor = {{Vogel-Heuser, Birgit and Wimmer, Manuel}}, publisher = {{Springer-Vieweg}}, title = {{{Self-Adaptive Digital Assistance Systems for Work 4.0}}}, year = {{2022}}, } @inproceedings{29842, abstract = {{To build successful software products, developers continuously have to discover what features the users really need. This discovery can be achieved with continuous experimentation, testing different software variants with distinct user groups, and deploying the superior variant for all users. However, existing approaches do not focus on explicit modeling of variants and experiments, which offers advantages such as traceability of decisions and combinability of experiments. Therefore, our vision is the provision of model-driven continuous experimentation, which provides the developer with a framework for structuring the experimentation process. For that, we introduce the overall concept, apply it to the experimentation on component-based software architectures and point out future research questions. In particular, we show the applicability by combining feature models for modeling the software variants, users, and experiments (i.e., model-driven) with MAPE-K for the adaptation (i.e., continuous experimentation) and implementing the concept based on the component-based Angular framework.}}, author = {{Gottschalk, Sebastian and Yigitbas, Enes and Engels, Gregor}}, booktitle = {{Proceedings of the 18th International Conference on Software Architecture Companion }}, keywords = {{continuous experimentation, model-driven, component-based software architectures, self-adaptation}}, location = {{Hawaii}}, publisher = {{IEEE}}, title = {{{Model-driven Continuous Experimentation on Component-based Software Architectures }}}, doi = {{10.1109/ICSA-C54293.2022.00011}}, year = {{2022}}, } @inbook{34023, abstract = {{Decision makers increasingly rely on decision support systems for optimal decision making. Recently, special attention has been paid to process-driven decision support systems (PD-DSS) in which a process model prescribes the invocation sequence of software-based decision support services and the data exchange between them. Thus, it is possible to quickly combine available decision support services as needed for optimally supporting the decision making process of an individual decision maker. However, process modelers may accidentally create a process model which is technically well-formed and executable, but contains functional and behavioral flaws such as redundant or missing services. These flaws may result in inefficient computations or invalid decision recommendations when the corresponding PD-DSS is utilized by a decision maker. In this paper, we therefore propose an approach to validate functionality and behavior of a process model representing a PD-DSS. Our approach is based on expressing flaws as anti-patterns for which the process model can be automatically checked via graph matching. We prototypically implemented our approach and demonstrate its applicability in the context of decision making for energy network planning.}}, author = {{Kirchhoff, Jonas and Engels, Gregor}}, booktitle = {{Software Business}}, isbn = {{9783031207051}}, issn = {{1865-1348}}, pages = {{227----243}}, publisher = {{Springer International Publishing}}, title = {{{Anti-pattern Detection in Process-Driven Decision Support Systems}}}, doi = {{10.1007/978-3-031-20706-8_16}}, volume = {{463}}, year = {{2022}}, } @article{33251, author = {{Robra-Bissantz, Susanne and Lattemann, Christoph and Laue, Ralf and Leonhard-Pfleger, Raphaela and Wagner, Luisa and Gerundt, Oliver and Schlimbach, Ricarda and Baumann, Sabine and Vorbohle, Christian and Gottschalk, Sebastian and Kundisch, Dennis and Engels, Gregor and Wünderlich, Nancy and Nissen, Volker and Lohrenz, Lisa and Michalke, Simon}}, journal = {{HMD Praxis der Wirtschaftsinformatik}}, number = {{5}}, pages = {{1227 -- 1257}}, title = {{{Methoden zum Design digitaler Plattformen, Geschäftsmodelle und Service-Ökosysteme}}}, volume = {{59}}, year = {{2022}}, } @inbook{34292, author = {{Wolters, Dennis and Engels, Gregor}}, booktitle = {{Product-Focused Software Process Improvement}}, editor = {{Taibi, Davide and Kuhrmann, Marco and Mikkonen, Tommi and Klünder, Jil and Abrahamsson, Pekka}}, isbn = {{9783031213878}}, issn = {{0302-9743}}, pages = {{235--242}}, publisher = {{Springer International Publishing}}, title = {{{Towards Situational Process Management for Professional Education Programmes}}}, doi = {{10.1007/978-3-031-21388-5_16}}, volume = {{13709}}, year = {{2022}}, } @inbook{32792, abstract = {{Decision makers in complex business environments have different goals and constraints and therefore require tailored decision support systems (DSS). Following a low-code approach, a tailored DSS can be created by a decision maker as a process-based composition of existing, interoperable decision support services. Data incompatibilities may be introduced during the design or execution of such a process-driven DSS, e.g., when a service always generates or a decision maker selects data which violates a data constraint of a subsequent service. These incompatibilities cause interrupted or erroneous decision processes. In this paper, we contribute an approach which enables the detection of data incompatibilities in process-driven DSS during process design and execution. Our approach utilizes the JSON Schema specification to define service interfaces and associated type constraints which data produced by services or decision makers can be validated against. We demonstrate our approach in the context of decision support for energy network planning using a prototypical open-source implementation.}}, author = {{Kirchhoff, Jonas and Gottschalk, Sebastian and Engels, Gregor}}, booktitle = {{Lecture Notes in Business Information Processing}}, isbn = {{9783031115097}}, issn = {{1865-1348}}, publisher = {{Springer International Publishing}}, title = {{{Detecting Data Incompatibilities in Process-Driven Decision Support Systems}}}, doi = {{10.1007/978-3-031-11510-3_6}}, year = {{2022}}, } @inbook{30941, abstract = {{Decision support systems are crucial in helping decision makers to quickly identify optimal business decisions in increasingly volatile and complex business environments. However, the ideal DSS for one decision maker may not optimally address the requirements for decision support of another decision maker. This is due to differences between decision makers in business goals, regulatory restrictions or availability of resources such as data. By using a suboptimal DSS, decision makers risk implementing suboptimal decision recommendations which endanger the success of their business. This presents DSS developers with the challenge to implement a customizable DSS which can be tailored to the individual requirements for decision support of a single decision maker. In order to address this challenge, we suggest a decision support ecosystem in which DSS developers, decision makers and other domain experts collaborate using a shared platform to provide and combine reusable decision support services into a tailored DSS. The contribution of our paper is twofold: First, we define the concept of a decision support ecosystem with respect to existing digital business ecosystems and discuss expected benefits and challenges. Second, we present a reference architecture for a shared platform supporting the realization of a decision support ecosystem. We demonstrate our contributions in the example application domain of regional energy distribution network planning.}}, author = {{Kirchhoff, Jonas and Weskamp, Christoph and Engels, Gregor}}, booktitle = {{Decision Support Systems XII: Decision Support Addressing Modern Industry, Business, and Societal Needs}}, publisher = {{Springer}}, title = {{{Decision Support Ecosystems: Definition and Platform Architecture}}}, doi = {{10.1007/978-3-031-06530-9_8}}, volume = {{447}}, year = {{2022}}, }