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- ZeitschriftenartikelHybrid Adaptive Systems(Business & Information Systems Engineering: Vol. 66, No. 2, 2024) Benke, Ivo; Knierim, Michael; Adam, Marc; Beigl, Michael; Dorner, Verena; Ebner-Priemer, Ulrich; Herrmann, Manfred; Klarmann, Martin; Maedche, Alexander; Nafziger, Julia; Nieken, Petra; Pfeiffer, Jella; Puppe, Clemens; Putze, Felix; Scheibehenne, Benjamin; Schultz, Tanja; Weinhardt, Christof
- ZeitschriftenartikelThe Power of Ethics: Uncovering Technology Risks and Positive Value Potentials in IT Innovation Planning(Business & Information Systems Engineering: Vol. 66, No. 2, 2024) Bednar, Kathrin; Spiekermann, SarahThe digital transformation of the economy is accelerating companies’ engagement in information technology (IT) innovation. To anticipate which technologies will become relevant over time and integrate them in their innovation plans, companies often rely on product roadmaps as strategic tools. However, ethical issues resulting from ubiquitous IT use have shown the need to accommodate hyped technical advancements in information systems (IS) design and acknowledge human values with moral relevance. Scholars have argued that this moral relevance can only come from an ethical framework. The empirical study presented here investigates whether the three ethical theories of utilitarianism, virtue ethics, and deontology can complement traditional innovation planning approaches. The mixed-method study covers three IT products – a digital toy, a food-delivery app and a telemedicine system. The results reveal that the three ethical theories boost creativity around values and enrich IT innovation planning by supporting the acknowledgment of more and higher value principles (e.g., freedom or personal growth), more diverse value classes (e.g., individual and social values) as well as more original values (e.g., human contact) in system design. What is more, participants identify and mitigate potential social and ethical issues associated with the IT product. Against this background, the findings in this paper suggest that a “value-based roadmapping” approach could be a vital stimulus for future IT innovation planning.
- ZeitschriftenartikelMatthias Jarke (1952–2024), A Pioneer in Information Systems and Data Management(Business & Information Systems Engineering: Vol. 66, No. 2, 2024) Aalst, Wil M. P.
- ZeitschriftenartikelA Taxonomy Development Method to Define the Vocabulary for Rule-Based Guidance in Complex Emerging Technologies(Business & Information Systems Engineering: Vol. 66, No. 2, 2024) Sangupamba Mwilu, Odette; Prat, Nicolas; Comyn-Wattiau, IsabelleEmerging technologies are characterized by their uncertainty and potential impact. Decisions about these technologies are therefore crucial and difficult. The problem is particularly acute for complex emerging technologies, which combine several technologies. Guidance on emerging technologies is often lacking, even more for complex ones. In this research, methods and models to guide practitioners (members of the IT personnel) in the adoption of complex emerging technologies are defined. Guidance is provided by means of productions rules, requiring a controlled vocabulary organized as a taxonomy. The rules, and the vocabulary for the rules, are defined by researchers for a specific complex emerging technology (e.g., business intelligence and analytics in the cloud). They may then be applied by practitioners to decide on the adoption of the emerging technology in a specific organizational context. The approach is based on systematic literature review, thereby contributing to evidence-based practice. This paper focuses on the method to define the controlled vocabulary for the production rules. This taxonomy development method is built by combining systematic literature review with a method for taxonomy development, considering the specificities of rule-based guidance and complex emerging technologies. It is demonstrated on business intelligence and analytics in the cloud and evaluated in a government agency.
- ZeitschriftenartikelSWEL: A Domain-Specific Language for Modeling Data-Intensive Workflows(Business & Information Systems Engineering: Vol. 66, No. 2, 2024) Salado-Cid, Rubén; Vallecillo, Antonio; Munir, Kamram; Romero, José RaúlData-intensive applications aim at discovering valuable knowledge from large amounts of data coming from real-world sources. Typically, workflow languages are used to specify these applications, and their associated engines enable the execution of the specifications. However, as these applications become commonplace, new challenges arise. Existing workflow languages are normally platform-specific, which severely hinders their interoperability with other languages and execution engines. This also limits their reusability outside the platforms for which they were originally defined. Following the Design Science Research methodology, the paper presents SWEL (Scientific Workflow Execution Language). SWEL is a domain-specific modeling language for the specification of data-intensive workflows that follow the model-driven engineering principles, covering the high-level definition of tasks, information sources, platform requirements, and mappings to the target technologies. SWEL is platform-independent, enables collaboration among data scientists across multiple domains and facilitates interoperability. The evaluation results show that SWEL is suitable enough to represent the concepts and mechanisms of commonly used data-intensive workflows. Moreover, SWEL facilitates the development of related technologies such as editors, tools for exchanging knowledge assets between workflow management systems, and tools for collaborative workflow development.
- ZeitschriftenartikelDigital Democracy: A Wake-Up Call(Business & Information Systems Engineering: Vol. 66, No. 2, 2024) Weinhardt, Christof; Fegert, Jonas; Hinz, Oliver; Aalst, Wil M. P.
- ZeitschriftenartikelThe Impact of Resource Allocation on the Machine Learning Lifecycle(Business & Information Systems Engineering: Vol. 66, No. 2, 2024) Duda, Sebastian; Hofmann, Peter; Urbach, Nils; Völter, Fabiane; Zwickel, AmelieAn organization’s ability to develop Machine Learning (ML) applications depends on its available resource base. Without awareness and understanding of all relevant resources as well as their impact on the ML lifecycle, we risk inefficient allocations as well as missing monopolization tendencies. To counteract these risks, the study develops a framework that interweaves the relevant resources with the procedural and technical dependencies within the ML lifecycle. To rigorously develop and evaluate this framework the paper follows the Design Science Research paradigm and builds on a literature review and an interview study. In doing so, it bridges the gap between the software engineering and management perspective to advance the ML management discourse. The results extend the literature by introducing not yet discussed but relevant resources, describing six direct and indirect effects of resources on the ML lifecycle, and revealing the resources’ contextual properties. Furthermore, the framework is useful in practice to support organizational decision-making and contextualize monopolization tendencies.
- ZeitschriftenartikelFoundation Models(Business & Information Systems Engineering: Vol. 66, No. 2, 2024) Schneider, Johannes; Meske, Christian; Kuss, Pauline