In the face of disruptions, increasing complexity and intensifying competitive pressure, organizations must adapt their structures and operations. In this context, Enterprise Architecture Management (EAM) is considered a promising approach to address these challenges by enabling holistic organizational overview, breaking down silos, and reducing complexity. However, the organizational implementation of EAM remains challenging, with little established methodological guidance available for context-specific realization. The research presented in this paper aims to support the organizational introduction of EAM. To this end, we present a practical evaluation approach to guide the selection of appropriate EAM implementation strategies. Through a single-case study conducted in collaboration with ETAS GmbH, this research explores a potential implementation of EAM. By conducting expert workshops and semi-structured interviews, an assessment approach and a decision-supporting “fitting matrix” were developed. The matrix evaluates twelve EAM implementation variants using seven collaboratively defined success criteria. The results indicate that a federated EAM model led by the CIO is considered the most suitable for this case.
Software release management coordinates planning, gating, deployment and monitoring in CI/CD-intensive environments where rapid iteration compresses decision windows and increases risk. This paper examines how Analytical AI and Generative AI support those decisions. Based on qualitative interviews with industry experts, we identify key benefits of AI integration, such as increased automation of repetitive tasks, more efficient resource allocation, enhanced risk forecasting, and improved over-all decision-making. These advances support faster, more reliable software deployments by streamlining processes and enabling data-driven insights. However, the study also highlights significant hurdles to effective AI/ML adoption, including integration complexity, the opacity of AI models, and organizational resistance. Addressing these challenges proves essential for realizing the full potential of AI in software release management. By examining both the practical advantages and limitations, this research offers actionable guidance for industry practitioners and contributes to broader discussions on the responsible application of AI in contemporary software product management.
As societies undergo digital transformation, organizations face the challenge of actively shaping it. Ethical concerns need to be embedded in the process of digital strategy development itself to be effective. This paper explores not only ethics through strategy but also strategy through ethics. How is ethics perceived within a digital strategy process? In what ways can ethics contribute to the development of a more effective strategy? To address these questions, we conducted a qualitative case study at a German public university. Sixteen employees involved in IT strategy, implementation, and administration across all hierarchical levels were interviewed. While “ethics” was rarely mentioned explicitly – mostly as an individual concern – the analysis revealed that “balancing power and participation” constitutes a central tension. We argue that typical decision-making challenges, such as IT project prioritization and resource allocation, are inherently ethical. A discourse-ethical approach, with agile methods, can support such decisions in a structured, value-sensitive way. Our transdisciplinary study draws on three fields: (1) emergent strategy and Open Strategy in digitalization contexts; (2) integration of ethics into IT governance; and (3) political-philosophical theories on power and participation. The study offers practical guidance for decision-makers, developers, and staff engaged in complex implementation processes during digital transformation.
Software-intensive businesses play a dual role in environmental sustainability by enabling efficiency and resource optimization while contributing to environmental impact through energy use, software evolution, and hardware dependence. This study examines how environmental sustainability is manifested in software-intensive organizations and what factors hinder or motivate sustainable practices. Based on 22 semi-structured interviews with 38 individual participants from two Finnish Green ICT projects (2022–2025), thematic analysis identified practices across organizational, process, product, and external aspects. Key barriers include low prioritization, unclear roles, limited client influence, and lack of expertise, while benefits relate to competitiveness, reputation, and efficiency. The study emphasizes the need for shared understanding, integrated competencies, and measurable metrics to enhance sustainability in the software industry.
Service-oriented value creation requires coordinated decisions across partners, resources, activities, and value appropriation. To support these decisions, we develop a model-driven, software-supported approach for configuring service value networks. At its core is a metamodel derived from analytic metatheory based on literature and expert workshops. The metamodel is implemented in a modeling software tool that integrates relevant service-oriented, value creation elements and their relationships into one single data model. The approach supports comparison of partner constellations, alignment of supply and demand, and evaluation of implications across the network. It enables firms to represent their value network, assess properties, simulate value distribution and optimize feasible configurations. The metamodel and the software tool have been evaluated in mobility, construction and additive manufacturing domain. Early results indicate that it is particularly effective in the systematic identification and analysis of interdependent action areas, the design of feasible business models, and the development of implementation strategies and funding opportunities in collaboration with relevant stakeholders.
