University Transfer Architectures for Smart Governance: A Regional Comparison of Scientific Community Building

Abstract

Universities are increasingly expected to contribute not only to teaching and research, but also to public-sector innovation, regional development, and digitally enabled governance. This article examines how higher education institutions organize that contribution by comparing two university-based transfer architectures: Smart-EDU Hub @ SNSPA in Bucharest and the distributed transfer portfolio of RheinMain University of Applied Sciences and Arts (HSRM). Using a qualitative comparative case-study design based on the document analysis of internal strategy and regulatory documents, institutional webpages, and European policy frameworks, the study analyzes the mission framing, organizational form, program architecture, trust infra-structure, and scaling logic. The documentary analysis indicates that Smart-EDU Hub is formally presented and institutionally organized as a centralized, branded, mission-led platform that bundles conferences, courses, projects, visiting scholars, and publication channels under a recognizable public-facing identity. HSRM, by contrast, is documented as a distributed transfer portfolio linking transfer strategy, dialogue formats, digitally supported teaching, administrative digitalization, continuing education, and AI support services. The comparison should therefore be read as an analysis of formal and publicly documented transfer architectures, not as an evaluation of actual institutional performance, stakeholder experience, or societal impact. The article contributes to Administrative Sciences by conceptualizing university transfer for smart governance as a public-management and governance-design problem. It develops an analytical hybrid transfer-architecture framework in which a visible hub is combined with distributed specialist nodes, shared quality assurance, and explicit safeguards for ethics, cybersecurity, and trustworthy AI.

1. Introduction

Universities are now asked to do more than teach and produce research. Across Europe, higher education institutions are also expected to demonstrate societal relevance through knowledge transfer, continuing education, multistakeholder engagement, and contributions to regional innovation ecosystems. This “third mission” has become an important element of university strategy, but its organizational forms remain highly heterogeneous (Benneworth & Cunha, 2015; Compagnucci & Spigarelli, 2020; Kitagawa et al., 2016). The recent work on knowledge exchange further argues that universities should be understood as relational actors whose societal role depends on how they connect academic expertise with public, civic, and professional stakeholders (Dismore et al., 2024; Marzocchi et al., 2023). This broader perspective is also consistent with the research on higher education capability-building, which shows that universities generate societal impact not only through formal curricula, but also through outward-facing ecosystems, partnerships, and role-model-based learning environments (Boldureanu et al., 2020; Vrabie, 2015).

This heterogeneity is especially visible in fields linked to smart cities, digital government, and public-sector innovation. These areas combine technological experimentation with difficult governance questions: public value, democratic legitimacy, cybersecurity, capability-building, accountability, and inclusion. In these domains, digital transformation is not merely a matter of installing new technologies; it is a socio-technical and institutional process shaped by leadership, competences, organizational context, and public value considerations. Vrabie’s notion of e-government 3.0 is especially relevant here because it frames AI-enabled public administration not simply as automation, but as a possible reconfiguration of local democracy and citizen interaction (Vrabie, 2023a). The recent Administrative Sciences research reaches similar conclusions: digital transformation in public administration depends on appropriate competences and leadership (Edelmann et al., 2023), while digital transformation in higher education must be understood as an institution-wide phenomenon spanning teaching, research, administration, and the broader university environment (Gkrimpizi et al., 2024). Contemporary European and international policy frameworks reinforce that complexity. The Digital Decade Policy Programme 2030, the Digital Education Action Plan, the Artificial Intelligence Act, and the NIS2 Directive all point toward a more integrated model of digital transformation that links innovation with trust, rights, and resilience (European Commission, 2025; European Union, 2022a, 2022b, 2024). UNESCO and the OECD make similar arguments in the context of responsible AI and education (OECD, 2024; UNESCO, 2026).

In that policy environment, universities can act as intermediaries between research, administration, professional practice, and civic debate. Yet, the literature still pays limited attention to the governance architectures through which universities organize the transfer on smart governance topics. The existing work has been rich on third-mission rationales, technology transfer, and regional engagement, but less explicit about how university-based initiatives are designed, coordinated, and scaled when the objective is public-value-oriented digital transformation rather than commercialization alone (Benneworth & Cunha, 2015; Bryson et al., 2014; Meijer & Bolívar, 2015). This gap is important because contemporary public-management scholarship increasingly treats digital transformation as a governance challenge involving strategy, legitimacy, collaboration, and organizational reform rather than as a purely technical modernization exercise (Gil-Garcia et al., 2018; Krogh & Triantafillou, 2024; Harb, 2026).

This article addresses that gap through a comparative case study of two European higher education settings: Smart-EDU Hub @ SNSPA in Bucharest and HSRM in Wiesbaden. The cases were selected because they pursue comparable transfer ambitions in digital transformation, yet institutionalize them differently. Smart-EDU Hub is organized as a centralized, named, and mission-led platform. HSRM, by contrast, advances the transfer through a more distributed portfolio composed of strategy, service units, dialogue formats, and digital teaching and administrative infrastructures.

The article asks three architecture-focused research questions. First, how are university-based transfer activities for smart governance and digital transformation formally organized in the two cases? Second, what potential governance advantages and risks can be inferred from the documented features of centralized hub logics compared with distributed portfolio logics? Third, what design principles can be derived, within the limits of a document-based comparative study, for universities seeking to build transfer architectures that are both visible and institutionally robust? The central argument is that the two models are not substitutes in a simple binary sense. Rather, they illuminate complementary organizational strengths and suggest a hybrid design that is better suited to the current public-management agenda around trustworthy digital transformation.

The conceptual contribution is therefore not limited to naming two empirical arrangements. The article develops a contingent transfer-architecture argument: centralized hubs and distributed portfolios can be understood as alternative organizational responses to different combinations of field visibility needs, internal capability distribution, stakeholder complexity, and trust requirements. The proposed hybrid model extends this argument by suggesting that universities operating in smart-governance fields increasingly need both an external agenda-setting capacity and an internally distributed specialist capability.

2. Literature Review

This section reviews the main bodies of literature that inform the comparative analysis. It does not aim to develop a complete theory of university transfer, but to identify the concepts needed to examine how universities organize transfer activities in the field of smart governance. The review is structured around five interconnected literature streams: the smart university, the third mission of higher education, smart governance and public value, digital transformation and trust, and responsible innovation. Together, these literatures provide the basis for the five analytical dimensions used in the case comparison: mission framing, organizational form, program architecture, trust and quality infrastructure, and scaling logic.

The smart university literature helps position the university as an organizational and governance actor rather than only as a provider of teaching and research. Third-mission literature explains why universities are increasingly expected to engage with society, public institutions, professional communities, and regional innovation ecosystems. Smart governance and public value literature clarifies the public-sector context in which this transfer occurs, especially where digital transformation, administrative reform, citizen engagement, and accountability intersect. The literature on digital transformation, trust, and responsible innovation highlights the institutional safeguards required when universities work with artificial intelligence, cybersecurity, data governance, and digitally mediated public services.

For this reason, the purpose of the literature review is selective and analytical. It identifies the concepts that are most relevant for comparing the centralized hub and distributed portfolio models of university transfer. The review therefore functions as the conceptual bridge between the research questions and the empirical comparison, rather than as a stand-alone theoretical framework.

2.1. Smart University as an Integrative Governance Lens

In this article, governance is understood in a public-management sense as the set of institutional arrangements, coordination processes, and accountability mechanisms through which collective action is steered across organizational and sectoral boundaries. It is not used as a synonym for government or formal public authority. From this perspective, universities can be understood as governance actors only in a limited and specific sense. They do not govern by exercising administrative authority. Rather, they contribute to governance by creating arenas, standards, learning environments, and knowledge-transfer channels through which academic expertise is connected to public institutions, professional communities, civic actors, and regional innovation ecosystems. The relevance of the smart university concept therefore lies in showing how universities can organize internal capabilities and external engagement in ways that support knowledge circulation, trust, professional learning, and stakeholder coordination (Schachtner & Baumann, 2023).

Because the article examines transfer architectures rather than isolated digital projects, the smart university concept provides an integrative conceptual lens for the literature review and subsequent analysis. A smart university is understood here not simply as a university that uses digital platforms, artificial intelligence, or data systems, but as a learning, networked, and evidence-informed organization that connects teaching, research, administration, and external engagement.

For the present study, this limited understanding of the university as a governance actor is useful because it explains how universities can organize internal capabilities while creating outward-facing channels through which knowledge supports smart governance in public administration and regional development. This is precisely the problem addressed by the article’s research questions: how universities organize transfer, what advantages and risks emerge from different organizational logics, and what design principles can support visible, trustworthy, and institutionally robust transfer architectures. The comparison between Smart-EDU Hub @ SNSPA and HSRM is therefore not only a comparison of two initiatives, but a comparison of two ways in which the smart university’s third mission can be institutionally configured.

2.2. Third Mission and Heterogeneous Transfer Architectures

Third-mission scholarship emphasizes that universities use multiple pathways to connect teaching and research with society. These pathways include professional education, open knowledge dissemination, partnership-building, applied research, civic engagement, and innovation support. Importantly, the literature cautions against assuming a single best organizational form. Institutional histories, external ecosystems, leadership choices, and disciplinary compositions shape how transfer is configured in practice (Compagnucci & Spigarelli, 2020; Kitagawa et al., 2016). Recent studies on knowledge exchange make the same point from a different angle: universities create societal value through diverse relationships, channels, and stakeholders, not through a single transfer template (Dismore et al., 2024; Marzocchi et al., 2023).

Recent work on higher-education governance and knowledge transfer is useful here less as a catalogue of examples than as a way to identify the organizational problem addressed by the article. Digital transformation in universities is not simply a technical modernization process; it changes the steering capacity, management routines, external relations, and institutional learning (Baumann & Schachtner, 2025). Similarly, studies of knowledge-transfer offices show that organizational structures shape the business model, portfolio logic, and external accessibility of transfer activities (Sengupta & Ray, 2017). Public-value-oriented university engagement also depends on aligning institutional resources, social goals, and collaborative practices rather than merely reproducing technology-transfer-office templates (Benneworth & Cunha, 2015). For the present study, these studies support a specific conceptual implication: university transfer architectures can be analyzed as organizational arrangements that structure visibility, specialization, stakeholder access, quality assurance, and institutional learning. For this article, the relevant insight is therefore not that transfer takes many forms in general, but that centralized hubs and distributed portfolios represent different solutions to the same third-mission design problem.

Applied to the present article, this literature supports the first research question by explaining why Smart-EDU Hub and HSRM should be treated not as competing performance models, but as different institutional responses to the same third-mission challenge: how to organize university knowledge, professional learning, and stakeholder engagement so that they travel beyond the university.

2.3. Smart Governance, Public Value, and Collaborative Governance

The article uses three complementary governance perspectives rather than three separate theories. Smart governance defines the substantive field of analysis: digitally enabled public administration, smart-city and smart-region development, data-informed decision-making, and technology-supported public services. Public value governance provides the normative lens: digital transformation should be assessed not only by efficiency or innovation outputs, but also by legitimacy, accountability, inclusion, democratic responsiveness, and the contribution to collective problem-solving. Collaborative governance explains the coordination mechanism: smart-governance challenges usually require interaction among universities, public authorities, professional communities, businesses, and civic actors rather than action by a single institution.

The smart city literature has moved beyond strongly technocratic definitions toward a governance-oriented view in which digital tools are embedded in social, political, and institutional processes. Angelidou (2015) describes smart cities as shaped by multiple forces rather than a single technological logic, while Meijer and Bolívar (2015) show that smart urban governance requires coordination across actors, sectors, and scales.

For the present argument, the smart-governance literature matters because it defines the external environment in which university transfer takes place. Smart-city and smart-region transitions require more than technical expertise; they require competence development, cross-sector coordination, institutional trust, and the translation of knowledge between public authorities, universities, firms, and civic actors (Ardito et al., 2019; Mora et al., 2023; Schachtner & Baumann, 2025). Universities are therefore relevant not only as producers of research, but also as intermediaries that structure deliberation, professional learning, and knowledge circulation. This helps explain why transfer architecture matters: a hub can create a visible gateway for external stakeholders, while a portfolio can distribute expertise across several organizational nodes.

This intermediary role also resonates with triple-helix thinking, which sees universities as active partners in university–industry–government interaction rather than passive repositories of expertise (Etzkowitz & Zhou, 2018).

A public-management lens strengthens that interpretation. Bryson et al. (2014) argue that public value governance depends on collaboration across public, private, and civic actors and on institutions that can support collective problem solving. Administrative Sciences has recently reinforced this point through work on collaborative governance and accountability, showing that dialogue-based and cross-actor forms of coordination can enhance accountable government when they are supported by appropriate institutional arrangements (Sørensen & Torfing, 2021). From this perspective, a university-based smart governance initiative should be assessed not only by the number of events or outputs it generates, but also by the way it structures dialogue, learning, trust, and accountability.

This strand of literature connects directly to the second research question because the hub and portfolio models must be assessed not only by the number of activities they generate, but by how they structure public-value-oriented dialogue, capability-building, accountability, and multistakeholder coordination.

2.4. Digital Transformation, Trust, and Responsible Innovation

Responsible innovation and governance perspectives further strengthen this point. In fields such as artificial intelligence, cybersecurity, and digital public services, innovation cannot be separated from questions of anticipation, inclusion, reflexivity, and accountability. Universities that organize transfer in these areas therefore need visible safeguards: ethical review, data-protection awareness, cybersecurity routines, human oversight of AI-supported outputs, and procedures for aligning technological experimentation with public values. These safeguards are not external compliance additions; they are part of the transfer architecture itself, because they determine whether knowledge transfer is perceived as legitimate, trustworthy, and socially responsible.

E-government has evolved from simple electronic service delivery (e-government 1.0) to Web-2.0 based interaction (e-government 2.0), and now to e-government 3.0, where emerging technologies such as AI are used to transform service delivery, enhance citizen participation, and increase the responsiveness of administrative systems (Vrabie, 2023a; Schachtner, 2022). Digital transformation in higher education is not only a technological modernization project; it is also an institutional redesign challenge. The recent work on the platformization and digitalization of higher education shows that data infrastructures, digital services, and AI tools can reconfigure value creation, organizational coordination, and power relations (Komljenovic, 2022; Schachtner, 2021). Administrative Sciences adds an important clarification here: digital transformation in higher education should be defined broadly enough to include strategy, governance, organizational culture, academic work, and administrative systems rather than being reduced to isolated digital projects (Gkrimpizi et al., 2024). Vrabie similarly argues that Education 3.0 requires institutions to integrate AI-supported and interactive learning designs into broader capability-building processes, not just into classroom experimentation (Vrabie, 2023b). The European University Association (2025) likewise stresses that effective higher-education digital transformation requires holistic institutional frameworks rather than isolated digital projects.

This broader debate is highly relevant to smart governance transfer. Universities that address digital government, AI, cybersecurity, or smart-city capacity building must embed these topics in governance mechanisms that safeguard academic quality, data protection, ethical reflection, and organizational learning. The AI Act, NIS2, the Digital Decade, and UNESCO’s guidance on generative AI collectively reinforce the importance of trustworthy, rights-respecting, and resilience-oriented institutional design (European Commission, 2025; European Union, 2022a, 2022b, 2024; OECD, 2024; UNESCO, 2026). The recent evidence from Administrative Sciences also shows that the success of public-sector digital transformation depends heavily on institutional context and crisis-management capacity, not only on technological readiness (Harb, 2026).

This strand of literature supports the third research question by showing that any proposed model for university-based transfer must include safeguards for ethics, cybersecurity, data governance, and responsible AI, rather than treating them as external compliance issues.

2.5. Synthesis of the Literature and Analytical Dimensions

The preceding literature review provides the conceptual basis for the comparative analysis. Rather than treating the reviewed literatures as separate and self-contained debates, the article uses them to derive a set of analytical dimensions suitable for comparing university transfer architectures in the field of smart governance. These dimensions are mission framing, organizational form, program architecture, trust and quality infrastructure, and scaling logic. Mission framing follows from the smart university and third-mission literatures, which show that universities increasingly define their societal role through engagement with public institutions, professional communities, civic actors, and regional innovation ecosystems. In this study, mission framing captures whether the transfer is presented primarily as a visible field-building activity, as a broad institutional responsibility, or as a combination of both.

The organizational form and program architecture follow from the literature on heterogeneous third-mission pathways and knowledge-transfer arrangements. This literature indicates that universities may concentrate transfer activities in visible hubs or distribute them across several institutional units, service structures, and dialogue formats. These two dimensions therefore help distinguish between centralized hub logics and distributed portfolio logics.

The trust and quality infrastructure is derived from the literature on digital transformation, responsible innovation, and public-value governance. In smart-governance fields, university transfer often involves artificial intelligence, digital public services, cybersecurity, data governance, and digitally supported learning. For this reason, transfer architectures must be examined not only in terms of activities and outputs, but also in terms of ethical safeguards, academic quality assurance, data-protection awareness, human oversight, and institutional responsibility.

Scaling logic follows from the smart-governance and public-value literature, which emphasizes that digital transformation requires durable capabilities, stakeholder coordination, and institutional learning rather than isolated events or one-off projects. This dimension captures whether transfer scales mainly through public visibility, repeated dissemination, and community-building, or through internal institutionalization, professional routines, and distributed capability-building.

Taken together, these five dimensions translate the literature review into an analytical structure for the case comparison. They do not constitute a fully developed causal theory of university transfer. Instead, they provide a focused conceptual lens for examining how different universities formally organize, communicate, and govern transfer activities in smart-governance fields.

The literature review is therefore intentionally selective. It does not attempt to cover the full bodies of work on the third mission, smart cities, digital transformation, public value governance, responsible innovation, or AI governance. Instead, it identifies the concepts most relevant for the article’s comparative purpose: why transfer architectures differ, how centralized hub and distributed portfolio models can be distinguished, and why trust, quality assurance, and scaling capacity are central to university-based transfer in smart-governance fields.

3. Materials and Methods

3.1. Research Design and Case Selection

The study follows a qualitative comparative case-study design suited to context-rich institutional phenomena for which experimental control is neither possible nor desirable (Bartlett & Vavrus, 2017; Yin, 2017; Brosser & Vrabie, 2015). The goal is analytical generalization rather than statistical representativeness.

The selection of Romania and Germany follows a purposive, contrastive logic rather than a representative sampling logic. Both countries are located within the same European policy environment shaped by the Digital Decade, the Digital Education Action Plan, the AI Act, and cybersecurity-related regulation, but they also offer different institutional and administrative settings for university transfer. This makes the comparison analytically useful: it allows the study to examine how similar European-level pressures around digital transformation, smart governance, and trustworthy technology are translated into different university-based transfer architectures.

The two universities were selected as information-rich cases rather than as statistically representative examples of Romanian and German higher education. Smart-EDU Hub @ SNSPA and HSRM were chosen because they combine three characteristics that are central to the article’s research questions. First, both institutions engage with digital transformation, knowledge transfer, and public-facing university missions. Second, they institutionalize these ambitions through clearly contrasting governance logics: Smart-EDU Hub @ SNSPA represents a centralized, branded, and mission-led hub, whereas HSRM represents a distributed portfolio embedded across transfer strategy, teaching support, administrative digitalization, continuing education, and AI-related services. Third, both cases were accessible to the authors through direct institutional involvement, which made it possible to reconstruct not only the formal documents and public webpages, but also the organizational chronology, internal logic, and ecosystem relationships behind the documented transfer activities.

This insider access is not treated as a substitute for methodological control. On the contrary, it is treated as a source of case knowledge that required explicit positionality safeguards. Because the authors are affiliated with the institutional environments under study, the analysis followed a document-first protocol, relied on official and publicly verifiable sources wherever possible, and used theoretically derived comparison categories rather than retrospective personal judgement. The purpose of the comparison is therefore not to claim that SNSPA and HSRM are the most representative European cases, nor to generalize about Romania and Germany as national systems as a whole. Rather, the purpose is to use two information-rich and institutionally contrasting cases to examine how different university transfer architectures can emerge under a broadly shared European policy agenda.

This contrast makes it possible to examine the trade-offs between coherence and specialization, visibility and diffusion, and hub-centered and networked forms of coordination. It also allows the article to draw design-oriented lessons about the strengths and risks of centralized hubs and distributed portfolios without presenting the two cases as exhaustive of European university transfer models.

3.2. Documentary Corpus

The empirical corpus combines internal project documents supplied by the authors with public institutional and policy sources (

Table 1. Documentary corpus and analytical use.

Source Block	Examples	Main Analytical Use	Status
Internal Smart-EDU Hub documents	Strategy 2030; organizational regulation; founding note	Chronology, mission, formal governance, values, future orientation	Author-supplied; used as core case material; interpreted as formal documentation, not impact evidence
Smart-EDU Hub public webpages	About; conferences; courses; projects; contests; visiting scholars; digital library	Verification of current activity portfolio and public-facing positioning	Public; accessed April 2026
HSRM public webpages	Transfer strategy; transfer formats; HessenHub; digital transformation; DTO; LLZ; AI pages	Reconstruction of distributed portfolio and institutional digitalization logic	Public; accessed March 2026
Policy documents	Digital Decade; Digital Education Action Plan; AI Act; NIS2; UNESCO; OECD	Contextual framing for trustworthy and resilient digital transformation	Public; accessed March and April 2026
Scholarly literature	Third mission, smart governance, public value, comparative case study	Derivation of analytical dimensions and interpretation	Peer-reviewed and academic sources

). For Smart-EDU Hub, the internal corpus includes the Strategy 2030 document, the organizational regulation, and a founding note clarifying that the Smart-EDU Hub was created within the earlier CFSEA structure in 2021 through project CNFIS-FDI-2021-0327 and later formalized through organizational renaming and regulation (Faculty of Public Administration, SNSPA, 2021; Smart-EDU Hub @ SNSPA, 2026a, 2026b). Public Smart-EDU Hub webpages were used to verify current activities, including conferences, courses, projects, scientific contests, visiting scholars, publications, digital-library resources, and online dissemination channels. Additional public-facing digital learning and dissemination sources, including APCAMPUS, LIVRESQ, and the Smart-EDU Hub YouTube channel, were consulted to clarify the hub’s asynchronous course-delivery infrastructure and broader outreach capacity (Faculty of Public Administration, SNSPA, 2026; Smart-EDU Hub, 2021).

For HSRM, the corpus was intentionally anchored in publicly accessible official materials: the transfer strategy, transfer-format pages, HessenHub, the digital transformation profile, the Digital Transformation Office, the TeachingLearningCenter, and AI-related support pages (RheinMain University of Applied Sciences and Arts, 2026f, 2026g). European and international policy documents were used to contextualize the cases, while scholarly literature informed the analytical dimensions. All public webpages were accessed in March and April of 2026.

The reliance on institutional documents, webpages, and internal strategy materials follows from the object of analysis. The article does not seek to measure implementation outcomes or stakeholder experience, but to reconstruct formal transfer architectures: stated missions, organizational responsibilities, program portfolios, public-facing interfaces, trust-related safeguards, and scaling assumptions (

Table 2. Alignment between research questions, literature and conceptual support, analytical dimensions, and documentary evidence.

Research Question	Literature and Conceptual Support	Main Analytical Dimensions	Documentary Evidence Used	Type of Claim Supported
RQ1. How are university-based transfer activities for smart governance and digital transformation formally organized in the two cases?	Smart university; third mission; knowledge exchange; higher education governance	Mission framing; organizational form; program architecture	Smart-EDU Hub Strategy 2030, organizational regulation, founding note, public webpages; HSRM transfer strategy, transfer webpages, Digital Transformation Office, HessenHub, TeachingLearningCenter, and AI-support pages	Descriptive and interpretive claim about formal organizational architecture
RQ2. What potential governance advantages and risks can be inferred from centralized hub logics compared with distributed portfolio logics?	Governance literature understood through three complementary lenses: smart governance as the substantive field of digitally enabled public-sector transformation; public value governance as the normative lens of legitimacy, accountability, and public purpose; collaborative governance as the coordination lens for multi-actor interaction; organizational models of knowledge transfer.	Organizational form; stakeholder interface; trust and quality infrastructure; scaling logic	Case-specific documents coded against the five dimensions; comparison of governance bodies, program portfolios, stakeholder interfaces, digital-learning infrastructures, and AI/digitalization support structures	Comparative analytical claim about plausible strengths and vulnerabilities, not measured impact
RQ3. What design principles can be derived for visible and institutionally robust transfer architectures?	Smart university; digital transformation; responsible AI; cybersecurity and trust frameworks; third-mission dynamic capabilities	Trust and quality infrastructure; scaling logic; program architecture	Cross-case synthesis of the two documented models, interpreted in relation to European policy frameworks and scholarly literature	Conceptual design claim, limited to analytical generalization

). For this purpose, official documents and institutional webpages are analytically relevant because they show how universities formally define, authorize, and communicate transfer arrangements. At the same time, these sources are treated critically rather than as neutral descriptions of practice. Claims based on institutional materials are therefore limited to documented architecture and institutional self-presentation, and are not interpreted as evidence of actual effectiveness, everyday operation, or societal impact.

3.3. Analytical Procedure: Directed Qualitative Content Analysis and Cross-Case Synthesis

The documentary corpus was analyzed through directed qualitative content analysis, followed by cross-case synthesis. Directed qualitative content analysis (Hsieh & Shannon, 2005; Schreier, 2012) was appropriate because the study did not aim to generate an entirely new coding structure inductively, but to examine the two cases through theoretically derived categories established in Section 2: mission framing, organizational form, program architecture, trust and quality infrastructure, and scaling logic. These categories functioned as an initial coding framework for reading the institutional documents, webpages, and policy sources. Within each category, the authors identified textual evidence concerning how each university defines transfer, organizes responsibility, structures activities, embeds trust-related safeguards, and envisages scaling.

The analysis proceeded in three stages. First, each case was reconstructed intra-case through focused document reading and coding. Special attention was paid to mission statements, governance arrangements, recurring activity formats, stakeholder interfaces and the treatment of trust-related issues such as ethics, cybersecurity, and AI governance. Second, the coded material was organized in a comparative matrix structured around the five analytical dimensions. This allowed similarities and differences between Smart-EDU Hub @ SNSPA and HSRM to be assessed systematically rather than impressionistically. Third, cross-case synthesis was used to identify the distinctive strengths, vulnerabilities, and design implications of centralized hub and distributed portfolio models. The purpose of this procedure was not to quantify document frequencies, but to interpret how institutional arrangements express different transfer logics and how these logics can inform a hybrid model for university-based smart governance transfer.

The evidentiary logic of the study is therefore one of analytical generalization rather than empirical impact measurement. The literature provides the conceptual categories through which transfer architectures can be compared, while the documentary corpus provides evidence of how those architectures are formally described, organized, and publicly communicated. The study does not claim that documents alone can demonstrate stakeholder satisfaction, learning outcomes, policy influence, or regional impact. Instead, it uses documents to analyze the institutional design of transfer: what missions are declared, what structures are established, what programs are bundled or distributed, what trust-related mechanisms are visible, and what scaling assumptions are embedded in each model. This distinction is important because the article’s contribution is located at the level of governance architecture and design principles, not at the level of causal evaluation of outcomes.

The authors’ institutional proximity to the two cases created both an analytical advantage and a risk of positionality bias. It provided access to contextual knowledge about chronology, organizational development, and ecosystem relationships that would be difficult to reconstruct from public webpages alone. At the same time, it increased the need to guard against selective emphasis, overly positive framing, or asymmetrical case treatment. To reduce this risk, the analysis followed a document-first protocol, privileged official and publicly verifiable sources over anecdotal knowledge, and used the same five comparison categories for both cases: mission framing, organizational form, program architecture, trust and quality infrastructure, and scaling logic. During revision, the case descriptions were also reviewed for symmetry so that both Smart-EDU Hub @ SNSPA and HSRM were discussed in terms of formal mission, organizational structure, program portfolio, stakeholder interface, trust infrastructure, strengths, and vulnerabilities. Even so, the article remains a document-based study and therefore cannot substitute for stakeholder interviews, participant observation, or output-impact measurement.

A further limitation of documentary analysis is that official documents and institutional webpages tend to present formal intentions, public narratives, and authorized descriptions of organizational structures. They are less able to capture informal practices, internal disagreements, implementation difficulties, stakeholder perceptions, or the actual use of transfer activities by external partners. For this reason, the analysis treats documents as evidence of formal governance architecture and institutional self-presentation, not as direct proof of practical effectiveness. This limitation was mitigated by triangulating different types of documents within each case and by comparing internal documents, public webpages, policy sources, and scholarly literature, but it cannot be eliminated without additional empirical methods such as interviews, surveys, observation, or longitudinal impact indicators.

This limitation has direct implications for the validity of the findings. The study can validly compare how the two institutions formally define missions, allocate responsibilities, describe programs, present stakeholder interfaces, and articulate trust-related safeguards. It cannot, on the basis of documents alone, verify whether these arrangements are implemented consistently in everyday practice, how stakeholders experience them, whether internal actors interpret them differently, or whether they produce measurable policy, educational, or regional-development outcomes. For this reason, the terms “hub model”, “portfolio model”, and “hybrid model” are used as analytical reconstructions of documented governance architectures, not as validated descriptions of actual organizational performance. Throughout the interpretation, documentary evidence is therefore treated as evidence of formal architecture and institutional self-presentation, while claims about effectiveness, impact, and lived practice are deliberately avoided.

3.4. Ethical and GenAI Disclosure

No human participants, personal data collection, or intervention procedures were involved. The study is based on documentary sources and publicly available webpages; therefore, ethical review and informed consent were not required.

During manuscript preparation, AI-assisted tools were used only for language editing and clarity checks. They were not used for data collection, source selection, coding, analysis, reference generation, or the production of empirical findings. All substantive claims, case interpretations, comparisons, and references were reviewed and validated by the authors, who take full responsibility for the final manuscript.

4. Results

The results are presented as an analysis of documented governance architectures. They do not evaluate the overall effectiveness of either institution, but examine how each case formally organizes transfer, stakeholder engagement, digital transformation support, and trust-related responsibilities. Accordingly, expressions such as “centralized hub” and “distributed portfolio” refer to documented and publicly visible organizational arrangements, not to independently observed patterns of daily operation.

4.1. Smart-EDU Hub @ SNSPA as a Centralized Integrative Hub

Smart-EDU Hub can best be understood as a centralized integrative hub built around a clear thematic identity. Its public self-description presents it as a platform that convenes academia, the public sector, business and professional communities around smart cities, and related topics. Internal documents deepen that profile by expanding the mission toward digital education, AI, smart governance, and public-interest-oriented innovation (Smart-EDU Hub @ SNSPA, 2026a, 2026b).

A crucial chronological clarification emerges from the project corpus. The Smart Cities conference lineage goes back to 28 November 2013, which provides continuity, legitimacy, and community memory. However, the Smart-EDU Hub as an organizational center was created in 2021 within CFSEA through project CNFIS-FDI-2021-0327 and later formalized through the renaming and regulation of the center (Faculty of Public Administration, SNSPA, 2021; Smart-EDU Hub @ SNSPA, 2026b). Distinguishing historical event continuity from formal organizational creation is analytically important because it shows how a long-running conference ecosystem was converted into a more durable institutional platform.

The governance architecture is unusually explicit for a university transfer initiative of this size. According to the regulation, the center operates within the Faculty of Public Administration under a director, technical secretariat, scientific council, advisory council, ethics and academic integrity commission, and research teams. The mission emphasizes transforming knowledge into action through interdisciplinary research, training, and smart solutions for education, administration, and society, while the values stress open science, inclusion, ethics, and public impact (Smart-EDU Hub @ SNSPA, 2026b).

The program portfolio reinforces that centralized identity. Smart-EDU Hub bundles recurring international conferences, post-university and executive training, research and outreach projects, scientific contests and hackathons, visiting-scholar activities, and publication channels, including a visible digital-library layer. The conference stream is especially important because it functions both as a field-building mechanism and as a gateway into publications, community formation, and partner relationships. The digital dissemination layer further strengthens this centralized transfer logic. Beyond conferences, publications, and project-based activities, Smart-EDU Hub also maintains an active YouTube channel as part of its wider digital-library and communication ecosystem (Smart-EDU Hub, 2025). With more than 13,000 subscribers (at the time of writing the present article), the channel extends the reach of the hub beyond the immediate academic and professional audiences physically present at events. It therefore functions not only as a promotional instrument, but also as a low-threshold public knowledge-transfer channel through which conference materials, expert discussions, podcasts, and educational content can reach a larger and more heterogeneous audience. In governance terms, this reinforces the hub’s capacity for agenda setting, community maintenance, and public-facing continuity between formal events. The 2026 TRUST theme, “Building Cyber-Resilient Intelligent Cities”, and the 2025 SCIC theme, “Leading for the People, Accelerating with the Digital”, illustrate the hub’s current framing of smart governance as simultaneously technological, managerial, and normative (Smart-EDU Hub @ SNSPA, 2026b; Smart-EDU Hub, 2013).

The training and outreach layers broaden the transfer chain from convening to capability-building. The post-university course on public innovation and smart-city strategies translates the agenda into professional learning. Projects such as #IN NOVA connect smart-city and digital topics to inclusion-oriented youth engagement. Scientific contests and hackathons mobilize applied experimentation, including the use of generative AI tools in educational design, while visiting-scholar events bring external expertise on AI, biometrics, and democracy into the local ecosystem (Smart-EDU Hub, 2026a, 2026c, 2026d, 2026f). The course architecture further demonstrates that Smart-EDU Hub’s transfer model is not restricted to synchronous formats. University courses associated with the hub are hosted on dedicated digital learning environments, including APCAMPUS (Faculty of Public Administration, SNSPA, 2026) and LIVRESQ (Smart-EDU Hub, 2021), and are designed so that learning materials can be accessed in a fully asynchronous manner. At the same time, this asynchronous infrastructure does not replace the professor’s face-to-face role; rather, it complements it by transforming teaching materials into reusable digital learning resources. This dual arrangement strengthens the hub’s scaling logic: knowledge transfer can occur through direct academic interaction, but also through structured self-paced access, delayed participation, and repeated engagement with digital course content.

Finally, the Smart-EDU Hub Strategy for 2030 shows a move from an event-centered platform toward a more mature governance model. It articulates a Vision 2030, theory-of-change logic, flagship programs, KPIs, funding diversification, and risk management, and it explicitly embeds trust, academic integrity, ethics, AI governance, and cyber-resilience in future development. In governance terms, the centralized hub model gives Smart-EDU Hub strong visibility, coherent external signaling, and a high convening capacity, but it also increases the dependence on core leadership, brand coherence, and a sustained coordination capacity (Smart-EDU Hub @ SNSPA, 2026a; Smart-EDU Hub, 2026b, 2026e).

4.2. HSRM as a Distributed Transfer Portfolio

HSRM organizes transfer through a different logic. Rather than concentrating smart-governance-related activities in one branded center, it treats transfer as an institution-wide performance dimension alongside teaching and research. The official transfer strategy defines transfer broadly as the exchange of scientific knowledge with society, culture, business, and politics, and presents it as a dialogical process in which impulses also return from practice to the university (RheinMain University of Applied Sciences and Arts, 2026f, 2026g). In this sense, HSRM does not lack a transfer architecture; rather, its architecture is less centralized and less dependent on a single public-facing label.

The organizational form is therefore portfolio-based. Transfer is articulated through several interconnected structures and formats rather than through one flagship hub. Outward-facing dialogue formats, such as HSRM Dialog, Azare Lunchtalk, and the RheinMain ProjectHub, provide interfaces with society, practice, and regional actors. These formats perform a convening role, but they do so through multiple access points instead of one dominant gateway. This differs from the Smart-EDU Hub model, where conferences, publications, courses, projects, and dissemination channels are more visibly bundled under a common identity.

A second layer of the HSRM portfolio concerns digitally supported teaching and learning. HessenHub supports the planning and realization of digitally supported teaching and learning, while the TeachingLearningCenter provides future-skills, continuing-education, and professional-development offers (RheinMain University of Applied Sciences and Arts, 2026a, 2026e). These structures show that transfer is not understood only as external communication, but also as a matter of internal capability-building. In analytical terms, HSRM’s transfer logic relies on diffusion: the knowledge-transfer capacity is strengthened by embedding digital and pedagogical support across the institution rather than concentrating it in a separate center.

A third layer concerns administrative digitalization and responsible AI. The Digital Transformation Office coordinates strategically relevant administrative digitalization projects, while AI-related pages and tools provide structured support for the responsible use of generative AI across the institution (RheinMain University of Applied Sciences and Arts, 2026a, 2026b, 2026c, 2026d, 2026e, 2026f). This gives HSRM a different trust infrastructure from Smart-EDU Hub. Instead of locating ethics, AI governance, and cyber-resilience primarily within the strategy of a named hub, HSRM embeds these concerns in university-wide service and support structures. The result is a model in which trust-related responsibilities are distributed across organizational units.

The distributed structure has several advantages. First, it enables specialization: different units can focus on administrative processes, teaching and learning, dialogue formats, AI support, or continuing education without forcing all activities into a single umbrella program. Second, it supports institutional diffusion: digital transformation is not delegated to a symbolic center but becomes part of the teaching, administration, and professional-development structures. Third, it increases organizational resilience because transfer capacity is spread across several structures rather than concentrated in one core team.

At the same time, the HSRM model also has vulnerabilities. It is less visible as a single external identity, and its public-facing narrative must be assembled from several pages, units, and formats. This makes external communication more difficult and may reduce the agenda-setting power that a centralized hub can generate. It may also complicate evaluation because outcomes are distributed across different units rather than attached to one recognizable platform. In comparative terms, HSRM illustrates how a university can sustain substantial smart-governance-relevant transfer without building one flagship center, but it also shows the coordination, communication, and evaluation challenges of a portfolio model.

4.3. Cross-Case Comparison

Table 3. Comparative governance architecture of the two cases.

Analytical Dimension	Smart-EDU Hub @ SNSPA	HSRM	Governance Mechanism	Expected Architecture-Level Effect	Potential Risk	Theoretical Implication
Mission framing	Named platform for smart governance, smart education and public-facing field building	Transfer as broad institutional performance dimension	Strategic framing and mission articulation	Clarifies institutional purpose and stakeholder expectations	Mission inflation or symbolic branding	Transfer architectures differ according to whether visibility or institutional embedding is prioritized
Organizational form	Centralized hub with director, councils, ethics structure, and program identity	Distributed portfolio of strategy, service units, and dialogue formats	Centralized coordination versus distributed responsibility	Hub coherence versus portfolio specialization	Leadership dependence in hubs; fragmentation in portfolios	Organizational form shapes how universities balance coherence, specialization and resilience
Program architecture	Conferences, training, projects, contests, visiting scholars, publications, digital-learning platforms, and online dissemination channels under one umbrella	Teaching support, administrative digitalization, dialogue formats, continuing education, and AI support across several nodes	Bundling versus modular diffusion	Concentrated field-building in the hub; institution-wide capability-building in the portfolio	Over-centralization in hubs; weak external legibility in portfolios	Program architecture determines whether transfer is experienced as a single gateway or as multiple institutional access points
Stakeholder interface	Strong external convening role across academia, public sector, business, and experts	Multiple interfaces linked to teaching, administration, society, and practice	Boundary-spanning through one gateway versus many gateways	Easier external access in the hub; broader internal reach in the portfolio	Narrow dependence on hub events; dispersed communication in the portfolio	Stakeholder access is mediated by the architecture’s gateway logic
Trust and quality infrastructure	Explicit strategy focus on integrity, ethics, cyber-resilience and trustworthy technology	Responsible AI, digitalization governance, and support structures embedded in institutional units	Advisory structures, AI guidance, cybersecurity awareness, quality assurance, and human validation	Strengthens legitimacy and responsible digital transformation	Trust safeguards may remain formal unless embedded in routines	Trust infrastructure is a core component of transfer architecture, not an external compliance add-on
Scaling logic	Visibility, public dissemination, conference continuity, digital-library resources, and asynchronous learning platforms	Institutional diffusion through service units, teaching support, administrative digitalization, and continuing education	Public-facing scaling versus internal organizational diffusion	Hub model scales through reach and recognition; portfolio model scales through embedding and repetition	Audience reach may be mistaken for impact; internal diffusion may be hard to communicate externally	Scaling depends on whether transfer is designed primarily for external visibility or internal institutionalization
Overall contribution	Strong agenda-setting and community-building capacity	Strong specialization, resilience, and institutional embedding	Complementary governance mechanisms	Supports a design proposition for combining visibility with distributed competence	Hybridization may create coordination complexity	Hub, portfolio, and hybrid models should be understood as contingent governance arrangements rather than as universally superior models

summarizes the most important differences. Smart-EDU Hub is mission-led, externally legible, and capable of concentrating multistakeholder attention around a recognizable platform. HSRM is more strongly embedded in institution-wide governance and offers specialized nodes that support transfer, digitalization, and learning at different points of the organization. The first model is especially effective for field formation, signaling, and boundary-spanning convening. The second is especially effective for mainstreaming digital transformation inside the university and aligning diverse functions without requiring a single organizational brand.

The comparison also reveals model-specific risks. Centralized hubs can become over-dependent on leadership continuity, vulnerable to resource bottlenecks, and tempted by branding without sufficient institutional deepening. Distributed portfolios can become fragmented, harder to communicate externally, and more difficult to evaluate as a coherent strategic whole. In other words, the central trade-off is not between effectiveness and ineffectiveness, but between two distinct ways of organizing coherence.

The comparison should therefore not be read as a positive evaluation of one case and a deficient evaluation of the other. Smart-EDU Hub and HSRM are treated as analytically different architectures, each combining strengths and vulnerabilities: the hub model concentrates visibility and agenda-setting capacity but risks leadership dependence and over-centralization, while the portfolio model supports specialization and institutional diffusion but risks fragmentation and weaker external legibility.

To make the comparison more explicit, Table 3 summarizes not only the documented features of the two cases, but also the governance mechanisms, expected architecture-level effects, potential risks, and theoretical implications associated with each analytical dimension.

4.4. Toward a Hybrid Model as a Design Proposition

The cross-case synthesis points toward a hybrid transfer-architecture framework for universities operating in smart-governance fields. Such a framework combines the external visibility and convening capacity of a named hub with the internal robustness and specialization of distributed competence nodes. In practical terms, this means pairing a public-facing platform for conferences, partnerships, professional learning, and strategic communication with formally linked substructures for teaching innovation, administrative digitalization, AI support, ethics oversight, cybersecurity awareness, and continuing education.

The value of the hybrid model lies in its capacity to address the main trade-off identified in the comparison. A centralized hub can generate identity, visibility, and field-building capacity, but it may become dependent on a limited coordination core. A distributed portfolio can support specialization, internal diffusion, and resilience, but it may be less visible to external stakeholders. A hybrid architecture seeks to combine these strengths by creating one recognizable gateway for external engagement while preserving the distributed expertise inside the university. The hub gives the transfer agenda public legibility; the specialist nodes provide depth, continuity, and implementation capacity.

A hybrid model also requires a shared quality infrastructure. In practical terms, safeguards for trustworthy artificial intelligence should be implemented through a combination of governance bodies, procedural checks, and pedagogical routines. First, the visible hub should be supported by an ethics, data protection, and AI-governance advisory function responsible for reviewing AI-related courses, events, projects, and public-sector collaborations. Second, every AI-related transfer activity should include a basic risk-screening procedure aligned with principles of human oversight, transparency, privacy, non-discrimination, cybersecurity, and accountability. Third, AI-supported teaching or public-sector training materials should include clear authorship, the disclosure of AI use where relevant, a periodic content review, and the human validation of AI-generated outputs. Fourth, projects involving public-sector partners should include data-protection and cybersecurity checks before implementation, especially when administrative data, citizen-facing tools, or automated decision-support systems are discussed. Finally, these safeguards should be embedded in annual planning, risk registers, evaluation routines, and staff-development activities rather than treated as ad hoc compliance requirements.

The hybrid framework translates the cross-case comparison into a design agenda for universities operating in smart-governance fields. It highlights how external visibility, distributed expertise, shared quality assurance, and trust-related safeguards can be combined within one transfer architecture. Future research can extend this framework by examining institutions that have implemented hybrid structures or by following universities longitudinally as they combine visible hub functions with distributed specialist nodes.

5. Discussion

The article does not claim to produce a fully tested causal theory. It proposes a middle-range explanatory framework that can be tested in future research. The comparison advances a middle-range analytical framework for understanding university transfer architectures in smart-governance fields (Compagnucci & Spigarelli, 2020; Kitagawa et al., 2016). It shows that centralized hubs and distributed portfolios are not merely administrative variants, but distinct governance arrangements through which universities organize visibility, stakeholder access, specialization, trust infrastructure, and scaling capacity. The framework helps explain why different universities may adopt different transfer architectures and how these architectures shape their capacity to contribute to public-sector digital transformation, professional learning, and regional innovation ecosystems (Dismore et al., 2024; Marzocchi et al., 2023).

Conceptual Contribution: A Contingent Transfer-Architecture Framework

The comparison allows the article to move beyond a descriptive distinction between a hub and a portfolio. It suggests a contingent transfer-architecture framework in which universities select, develop, or inherit different organizational forms depending on the strategic problem they need to solve. A centralized hub is theoretically more likely when a university seeks to create visibility around an emerging policy field, convene heterogeneous external actors, build a recognizable identity, and concentrate the agenda-setting capacity. A distributed portfolio is theoretically more likely when transfer activities are already embedded across several institutional domains, when specialized support units exist, and when the main challenge is not external visibility but internal diffusion, professionalization, and resilience.

The two architectures also rely on different mechanisms. The hub model operates through bundling, symbolic visibility, boundary-spanning, and centralized coordination. By placing conferences, training, projects, publications, and dissemination channels under one recognizable identity, it can reduce external search costs for stakeholders and create a visible gateway into the university. Its main theoretical risk is the dependence on leadership continuity, brand coherence, and a sustained coordination capacity. The portfolio model operates through specialization, modular diffusion, redundancy, and institutional embedding. By distributing transfer, teaching innovation, administrative digitalization, continuing education, and AI support across several units, it can make transfer less dependent on a single centre and more resilient inside the organization. Its main theoretical risk is fragmentation, weaker external legibility, and more complex evaluation.

From this perspective, the question is not which architecture is universally superior, but under what conditions each architecture is more appropriate. Hub architectures appear more suitable where the field is still forming, where external stakeholders need a clear point of access, where public visibility is strategically important, and where the university seeks to position itself as an agenda setter in smart governance. Portfolio architectures appear more suitable where digital transformation is already institution-wide, where expertise is distributed across several professional units, where the university needs to support multiple internal communities and where resilience matters more than a single public brand. Hybrid architectures become theoretically attractive when universities face both conditions simultaneously: they need a public-facing platform for external engagement and distributed specialist nodes for internal capability-building, trust governance, and implementation support.

The framework generates analytical propositions that can guide future comparative and longitudinal research on university transfer architectures. Because the present study is based on documents, it can identify formal architectures and plausible mechanisms (

Table 4. Contingent transfer-architecture framework.

Architecture	Conditions Under Which It Is Theoretically Preferable	Main Mechanisms	Expected Architecture-Level Advantages	Main Theoretical Risks
Centralized hub	Emerging or weakly structured policy field; need for visibility; need for a single stakeholder gateway; strong leadership coalition; strategic interest in agenda setting	Bundling; symbolic visibility; boundary-spanning; centralized coordination; identity-building	External legibility; stakeholder convening; field-building; coherent public communication	Leadership dependence; resource bottlenecks; over-centralization; risk of branding without institutional depth
Distributed portfolio	Mature or institution-wide digital-transformation agenda; multiple specialized units; need for internal diffusion; diverse stakeholder and service demands; emphasis on resilience	Specialization; modular diffusion; redundancy; institutional embedding; professional support routines	Internal capability-building; resilience; specialization; integration with teaching, administration and continuing education	Fragmentation; weaker external identity; coordination costs; difficulty of evaluating the whole architecture
Hybrid architecture	Simultaneous need for external visibility and internal diffusion; high trust, AI and cybersecurity requirements; complex smart-governance ecosystem; need to connect public engagement with implementation capacity	Visible integrative node combined with distributed specialist nodes; shared quality assurance; AI-governance procedures; risk screening; feedback loops	Combination of agenda-setting and institutional resilience; stronger trust infrastructure; clearer stakeholder entry point with deeper implementation capacity	Governance complexity; need for sustained coordination; risk of duplicating responsibilities between hub and nodes

), but it cannot demonstrate actual causal effects on stakeholder engagement, learning outcomes, or policy change. Future research can test the proposed framework by examining whether hub models actually produce stronger agenda-setting and stakeholder convening, whether portfolio models actually produce greater institutional resilience and internal diffusion, and whether hybrid models are better able to combine visibility with trustworthy implementation.

The findings also enrich smart governance debates. Much of the smart-city literature has focused on technology, policy instruments, and urban experimentation. The two cases demonstrate that universities matter not just as knowledge suppliers, but as institutional designers of transfer environments. Smart-EDU Hub shows how a university can create a recognizable public arena for smart-governance discourse and learning. HSRM shows how similar goals can be pursued through mainstreamed digital and transfer infrastructures distributed across the organization. This reinforces the public-value perspective: the design question is not simply how to introduce digital tools, but how to embed them in trustworthy institutional arrangements (Bryson et al., 2014; Meijer & Bolívar, 2015). In public-management terms, the comparison also resonates with arguments that contemporary governance reform increasingly combines internal organizational coordination with collaborative, cross-boundary problem solving (Krogh & Triantafillou, 2024; Sørensen & Torfing, 2021).

A further implication concerns trust and regulation. The policy context represented by the Digital Decade, the AI Act, NIS2, UNESCO guidance, and OECD principles suggests that future university transfer initiatives will be judged not only by innovation outputs but also by their ability to handle ethics, explainability, security, privacy, and inclusion. Smart-EDU Hub’s explicit Strategy 2030 emphasis on trustworthy technology and cyber-resilience, together with HSRM’s administrative digitalization and AI support structures, indicate that the governance of transfer now increasingly overlaps with the governance of institutional digital transformation itself (European Commission, 2025; European Union, 2022a, 2022b, 2024; UNESCO, 2026). This conclusion is also compatible with Bercu’s work on strategic decision making and public-sector performance, which underlines that public institutions must balance efficiency goals with broader responsibilities toward citizens and public value (Bercu, 2013; Bercu et al., 2020).

For university managers, the paper offers three practical lessons. First, visibility matters: initiatives that aspire to shape a policy field need a recognizable external interface. Second, diffusion matters: transfer capacity becomes more sustainable when it is connected to teaching, administration, and continuing education rather than isolated in one project unit. Third, trust infrastructure matters: advisory boards, ethical review, AI guidance, and cybersecurity awareness should be built into the program architecture from the beginning. A fourth lesson follows from the comparison itself: university initiatives that operate in smart-governance and regional-development ecosystems should pay closer attention to multilevel coordination, because transfer architectures must connect university capabilities with local administrations, professional communities, and wider policy environments.

The Smart-EDU Hub case also suggests that digital dissemination and asynchronous learning infrastructures should be treated as part of the transfer architecture, not merely as communication or teaching support. An active online video channel and structured course delivery through digital platforms extend the temporal and spatial reach of university transfer. They allow the hub to remain visible between conferences, to reuse and recombine educational content, and to support learners who cannot participate synchronously. However, this scaling capacity also raises quality-assurance questions: asynchronous materials require periodic updating, clear authorship, accessibility standards, and alignment with the face-to-face teaching component. For this reason, digital reach should be interpreted not only as audience growth, but also as a governance responsibility.

The study has limitations that define the scope of its claims. Because the analysis is document-based, it reconstructs formal missions, governance arrangements, program architectures, stakeholder interfaces, and stated trust mechanisms. It does not directly measure stakeholder experience, learning outcomes, policy influence, or regional impact. Future research can extend the framework through interviews, surveys, participation data, bibliometric indicators, learning analytics, partnership mapping, and longitudinal observation of transfer activities.

6. Conclusions

This article compared two organizational pathways through which universities contribute to smart governance and digital transformation. Smart-EDU Hub @ SNSPA represents a centralized hub model that bundles conferences, training, projects, and publications under a coherent public-facing identity. HSRM represents a distributed portfolio model in which transfer, digital teaching, administrative digitalization, and AI-related support are organized across multiple strategically aligned structures.

The comparison shows that centralized hub and distributed portfolio models address different governance problems. The hub model is especially suited to visibility, agenda setting, and multistakeholder convening, while the portfolio model is especially suited to specialization, internal diffusion, and organizational resilience. Their complementarity supports the article’s hybrid transfer-architecture framework: universities working in smart-governance fields can benefit from combining a visible public-facing hub with distributed specialist nodes, shared trust mechanisms, and explicit links to continuing education and institutional digital transformation.

The broader theoretical implication is that university transfer architectures should be understood contingently. They are not merely administrative containers for activities, but governance arrangements that respond to different combinations of visibility needs, capability distribution, stakeholder complexity, and trust requirements. The hub, portfolio, and hybrid models therefore provide a conceptual vocabulary for analyzing how universities organize their third mission in fields where digital transformation, public value, and trustworthy technology intersect.

Seen from the perspective of public management, the central message is clear: university-based smart governance transfer is a governance design problem. Its success depends less on whether institutions use fashionable digital tools than on whether they build credible, collaborative and ethically grounded structures through which knowledge can travel into public action.