The paper introduces rules that help identify and depict in a model enterprise elements that are aimed at acquiring stakeholders, e.g., customers, employees, and partners. Without these activities, a business service cannot be provided. The modeling is done using a specific enterprise modeling technique called Fractal Enterprise Model (FEM). However, the result can be of interest to researchers and practitioners using other modeling techniques. Though the processes of acquiring stakeholders are discussed in the literature, not all important elements of these processes are depicted. The type of rules presented in this paper follows our suggestion to consider the so-called discovery power of  enterprise modeling languages alongside their expressive power.

Sweden’s decentralised municipal structure creates a complex setting for digital transformation. Despite national strategies promoting artificial intelligence (AI), adoption remains uneven across municipalities due to regulatory uncertainty, budget limitations, and ethical concerns. This study investigates how technological, organisational, and contextual factors influence AI adoption and how municipalities manage trust and transparency. Drawing on the Technology–Organisation–Environment (TOE) framework and Public Value Management (PVM) theory, data were collected through a survey of municipal officials and analysed using descriptive statistics, regression modelling, and thematic analysis. Findings show leadership support as the strongest enabler, while inadequate infrastructure, unclear legal frameworks, and low public trust hinder progress. Limited budgets further restrict implementation, though collaboration and shared learning present underused opportunities. The study highlights the importance of strategic leadership, transparent governance, and inter-municipal cooperation to promote trustworthy and sustainable AI adoption in local government.

Data sovereignty has become a central concern in public-sector digital transformation, particularly with the rise of data-intensive technologies such as Generative Artificial Intelligence (GenAI). However, existing research has primarily focused on conceptual and regulatory dimensions, with limited empirical insight into how sovereignty shapes technology adoption in practice. This study examines how data sovereignty influences the adoption and use of GenAI in the public sector. Drawing on a qualitative case study based on 19 interviews across national governance and service delivery contexts, the findings show that data sovereignty operates as a socio-technical condition shaping organisational decision-making. It constrains implementation pathways and generates tensions related to control, compliance, infrastructure, and strategic autonomy. These findings shift the understanding of data sovereignty from a policy concern to an organisationally enacted condition that structures digital innovation. The study contributes to research on AI governance by demonstrating how sovereignty is operationalised in practice and how it shapes public-sector GenAI adoption in resource-constrained contexts.

Enterprise Architecture (EA) plays a critical role in delivering information products such as process models, governance frameworks, and reference architectures. For these information products to be effective, they must help stakeholders within an organization to perform their work more effectively—for example, when analyzing organizational structures, introducing new tools, or aligning business and IT operations. Therefore, these information products must be designed with the stakeholders’ needs and practices in mind. This paper presents a systematic literature review focusing on research that evaluates EA and considers stakeholders, their relationships, and their practices. As the foundation for this review, we apply the Work-Oriented Approach (WOA), which structures descriptions of stakeholders, their relationships, practices, use and co-use of information products, and examines how information products are integrated into these practices. The literature review reveals several challenges. A key issue is uneven stakeholder participation in evaluations, with EA experts and IT personnel dominating, while other stakeholders are often underrepresented. Furthermore, stakeholders’ relationships and work practices are frequently poorly defined, making assessing how EA provides tangible organizational benefits difficult. To address these issues, we propose using WOA to improve and shift the focus of EA evaluations towards the work practices most affected by EA. This will ensure that the evaluations are more comprehensive and grounded in the real-world practices of the stakeholders.

This study investigates the role of Enterprise Architecture (EA) in enhancing business-IT alignment during a large-scale re-engineering project at a European agency. Using a qualitative case study approach, the research analyzes insights from business and IT stakeholders involved in the Surveillance Systems Re-engineering (SSR) project. Focus group sessions were conducted to identify the strengths, weaknesses, and practical recommendations for EA implementation. The findings are organized across four dimensions of alignment: Communication, Governance, Partnership, and IT Scope & Architecture—adapted from Luftman’s maturity model. Results show that EA contributes significantly to mutual understanding, learning acceleration, and strategic alignment but is challenged by complex methodologies, rigid modeling languages, and organizational readiness issues.

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.

The scientific literature related to business ecosystems is growing. However, the majority of this literature is devoted to so-called Digital Business Ecosystems (DBE), which are largely related to the networking aspect of business ecosystems, i.e., the 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 excluded. In this work, we take a different approach, namely, to model an ecosystem that exists around a specific enterprise. The work is based on concepts transferred from biological cybernetics to business, such as structural coupling and autopoiesis. In this work, the Fractal Enterprise Model (FEM) is used for modeling business ecosystems. The research follows the Design Science methodology. 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. The patterns can help identify activities that are missing in the enterprise itself, thereby providing a basis for improving its functioning.

Digital transformation (DT) has significantly reshaped many organizations’ business models, processes, and strategies, focusing on creating value propositions for stakeholders. Despite its potential, DT often encounters challenges rooted in organizational culture. However, research on these cultural barriers remains fragmented, leaving a knowledge gap in understanding how they hinder transformation. This study systematically reviews existing research literature to identify and analyze the organizational culture barriers that impede DT. The systematic review reveals 10 key and 44 specific organizational cultural barriers to successful DT. To address them, the study proposes targeted solutions framed within elements of adaptive culture, recognizing that these cultural barriers can hinder the development of adaptive culture that supports successful DT. This proposed approach contributes a structured framework that synthesizes existing findings and offers insights to guide organizational practice, academic research, and policymaking related to DT.

Digital transformation (DT) is a fundamental change process enabled by digital technologies and strategic resource alignment that aims to improve organizational performance and stakeholder value radically. Although often viewed through a technological lens, DT also requires cultural readiness to ensure sustainable outcomes. There is a need to identify and validate the organizational culture values critical for DT success. This study addresses the gap by examining these values in a developing-country context. Drawing on 22 organizational cultural values synthesized from previous studies, a two-round Fuzzy Delphi Method was conducted with an expert panel of academic researchers, digital strategy consultants, and practitioners in Indonesia. The results identified nine critical organizational cultural values for DT success: Commitment, Innovation, Continuous Improvement, Cooperation and Collaboration, Customer Centricity, Empowerment, Adaptability, Forward-Thinking, and Technology Acceptance. The study provides insights into how these values manifest across contexts and offers theoretical understanding and practical guidance for policymakers and leaders.

Digital health in Africa is gaining momentum, yet remains fragmented due to gaps in strategic coherence, capacity, and system interoperability. To address these challenges, this study proposes a Reference Goal Model that captures and structures the key goals and means underpinning digitalization and interoperability initiatives across multiple governance levels-national, regional, and continental. We applied the Business Motivation Model (BMM) to systematically analyze strategic content from three key strategic documents: Rwanda's National Digital Health Strategic Plan, the East African Community's (EAC) Digital REACH Initiative Strategic Plan, and the African Union's (AU) Digital Transformation Strategy. Statements from the three documents were decomposed into atomic goals and means, illustrating how digital health and interoperability are conceived. The resulting Reference Goal Model for Digital Health in Africa (RGMDHA) identifies a set of goals and means for both digitalization and interoperability. By making these goals and means explicit and structured, the RGMDHA facilitates the strategic evaluation of national, regional, and continental plans, enables communication and stakeholder alignment in the digital health domain, and can be used as a tool for guiding the design and analysis of digital health and interoperability projects.