The scientific literature related to business ecosystems is growing. However, the major part of this literature is devoted to so-called Digital Business Ecosystems (DBE) that are largely related to only the networking part of the business ecosystems, i.e., exchange of values among their participants. Other parts related to the work of a participating enterprise, as well as its suppliers and regulators, are often left outside. In this work, we take a different approach, namely, to model an ecosystem that exists around a specific enterprise. The work is based on the concepts transferred to business from biological cybernetics, such as structural coupling and autopoiesis. In this work, the Fractal Enterprise Model (FEM) is used for modeling business ecosystems. The goal is to suggest some patterns expressed in the modeling language that can help an enterprise build a model of the ecosystem of which the enterprise is in focus.
Artificial Intelligence (AI) has attracted significant attention among researchers and practitioners as it emerges as a strategic asset for organizations across sectors and industries. Within the public sector, the deployment of AI is anticipated to enhance the responsiveness of public organizations in delivering appropriate services and addressing complex societal challenges. This study examines the readiness of public organizations for AI adoption within Kenya’s public sector and explores its implications for public value creation. Anchored in the Technology-Organization-Environment framework and informed by Dynamic Capabilities theory, the article analyzes how structural conditions within organizations interact with adaptive capabilities to shape trajectories of AI readiness. Drawing on qualitative interviews with seventeen public sector experts, the study identifies a set and dynamic interdependence of critical readiness factors, including technological infrastructure, data quality, leadership commitment, staff competencies, organizational culture, regulatory frameworks, public trust, and external partnerships. By offering an empirically grounded and comparative perspective, the study aims to enhance our understanding of the relationship between AI readiness and public value creation, drawing on Kenya’s example. The results may also provide valuable inputs for policymakers in formulating actionable plans concerning differentiated implementation pathways, capacity development, and the ethical governance of AI in the public sector.
Complex Systems Informatics and Modeling Quarterly (CSIMQ) continues to serve as a forum for high-quality research at the intersection of informatics, modeling, and the study of complex socio-technical systems. This issue brings together seven contributions that reflect the breadth and depth of current research in these fields. The issue opens with two articles that explore advanced modeling and data-driven analysis within complex economic and organizational environments. The next two articles shift the focus toward the digital transformation of public services and the organizational capabilities needed to manage such change. The rest three articles address organizational transformation, IS integration challenges, and regulatory compliance in increasingly complex digital ecosystems. Together, the articles in this issue reflect the journal’s commitment to advancing knowledge on the modelling, governance, and transformation of complex systems. They showcase how researchers combine conceptual rigor, empirical investigation, and methodological innovation to address contemporary challenges in digital transformation, public-sector innovation, organizational alignment, and cybersecurity governance.
The revised Network and Information Security Directive (NIS2) aims to achieve a high level of common cybersecurity across the European Union. Several stakeholders, including member states, supervisory authorities, and critical infrastructure service providers, are expected to support this effort by ensuring a high level of information security. Part of increasing security levels involves implementing risk management measures by service providers, but also an evaluation of the security situation and its changes is necessary from the perspective of each stakeholder. Previous research has described NIS2-related activities through user stories that encompass six types of stakeholders with their respective goals in relation to the security level evaluation of organizations. In this article, we examine the real-life implementation of these security evaluation user stories and demonstrate how the framework for security level evaluation (F4SLE) can be utilized to achieve NIS2 compliance within this narrowed scope of security level evaluation. The advantage of F4SLE is that the data can be collected once and then reused to satisfy different stakeholders without imposing an additional reporting burden on entities that must be NIS2-compliant.
Post-merger integration (PMI) presents unique challenges for professionals responsible for information systems’ (IS) integration when aligning and combining diverse system architectures of merging organizations. Although the theoretical and practical guidance exists for PMI on the business level, there is a significant gap in training for IS integration in this context. In prior research, specific methods AMILI (Support method for informed decision identification) and AMILP (Support method for informed decision-making) were introduced for the support of IS integration decisions in PMI. But during the practical application, a high learning curve and low learner motivation were reported. This study examines how game-based learning can transform the training of these methods into a more engaging and motivating experience, tailored to the context of the specific PMI case. Building on instructional design theory, game design theory, cognitive load principles, motivation models, and specifics of the IS integration in the scope of the PMI, the article derives a structured catalogue of requirements for a game-based learning design framework tailored to PMI-specific conditions. Additionally, a metamodel is defined to show how these requirements are systematically transformed into design activities and artefacts, resulting in a consistent learning design process and a corresponding data model aimed at designing a learning experience for IS integration within the scope of a specific PMI. The metamodel’s applicability is demonstrated through instantiations of representative requirements.
