Abstract European research framework programs have long governed knowledge through architecture rather than through funding instruments alone. The proposed post-2027 reconfiguration of Horizon Europe is therefore interpreted as a recalibration of an established knowledge-governance architecture. The article conceptualizes program architecture as the formal-organizational configuration of a public program: the arrangement of pillars, domains, budgetary couplings, coordination mechanisms, eligibility rules, steering devices, valorization pathways, and accountability routines through which authority, participation, and access to resources are structured. This definition positions program architecture as a meso-level mechanism of policy steering between individual instruments and broader governance regimes. Drawing on qualitative document analysis and cross-temporal comparison of Horizon Europe 2021–2027 and the proposed 2028–2034 framework, the article identifies five interrelated shifts. First, the proposed Pillar II “Competitiveness and Society” more closely links societal relevance to strategic, industrial, and technological priorities. Second, ERA and widening move from horizontal and partly compensatory support toward infrastructural integration. Third, dispersed innovation support is consolidated into a strategically governed valorization pipeline connecting co-creation, industry-academia alignment, standardization, scale-up, strategic technologies, and sovereignty. Fourth, budgetary coupling with competitiveness-oriented investment structures anchors strategic selectivity. Fifth, performance steering is strengthened through high-visibility initiatives, milestones, and accountability routines that make program results more traceable to political priorities. The article shows how program architecture filters societal relevance, inclusion, and valorization without formally abolishing scientific autonomy. It thereby explains how public programs steer knowledge by structuring the routes through which research becomes fundable, visible, valorizable, and politically relevant.
Understanding whether compliance tendencies generalize across legal domains is central to behavioral public policy. This study examines whether psychological mechanisms that shape compliance in one context also predict decisions in others. Using a multi-vignette survey conducted in the United Kingdom (N = 498) across 7 regulatory scenarios, we assess how perceptions of injunctive norms, reputational risk, attitudes toward legal objectives, legal legitimacy beliefs, perceived cost, perceived complexity, and self-efficacy influence stated compliance intentions. Several mechanisms show cross-domain consistency, although they are measured within each vignette. Legitimacy and injunctive norms are robust predictors, while moral costs and perceived risk exhibit moderate but patterned effects. Other influences, such as perceived burden or alignment with specific rules, vary more sharply across contexts, indicating that compliance reflects both situational features and cross-domain variation in interpretive tendencies. These findings have implications for trust-based and risk-based regulation. Cross-domain tendencies offer some support for differentiating oversight based on past behavior, yet the observed contextual variation cautions against mechanistic profiling. Effective regulatory design should combine broader psychological levers with context-specific strategies, recognizing both stability and flexibility in how people interpret legal demands. The study contributes to debates on the generalizability of compliance mechanisms and offers behavioral insights for more calibrated and responsive enforcement.
Complex societal problems (CSPs) such as climate change, pandemics, and polarization are persistent, interdependent, and difficult to define, yet they are often reduced to binary labels like "wicked" or "tame" or high-level typologies that oversimplify their underlying complexity. This paper revisits these typologies and proposes a conceptual framework that treats complexity as a layered structure of interacting dimensions rather than discrete categories. Based on an integrative review of 25 typologies from policy science, systems science, and management, the framework organizes problem complexity into two families: system complexity (structure, dynamics, and scope) and stakeholder divergence (values, knowledge, and power). These dimensions can be visualized through multi-level representations such as radar diagrams that reveal a problem's complexity profile. The paper outlines three modes of application: problem diagnosis to support sensemaking; frame comparison to monitor (temporal) problem perception differences; and method and governance alignment to connect salient complexity dimensions to appropriate governance instruments and systems methods. This approach reduces risks of misclassification, improves analytical precision, and provides a shared language that supports interdisciplinary collaboration. The framework offers a more nuanced characterization of CSPs and introduces concrete tools for governance and design.
Abstract Collaborative arrangements have become popular in contemporary public policy and administration, particularly in the domain of social policy. Drawing on five articles spanning four countries, our symposium examines the design and performance of collaborative governance when we move from ideal conditions into specific, often demanding, real-world contexts. This preface introduces three tensions that confront collaborative governance arrangement in social policy. First, when enabling conditions are weak or actively hostile, collaborative governance does not simply fail and instead, persists through other means like ‘street-level partnerships’. Second, when politics enter the picture, it can both undermine and sustain collaboration, depending on the nature of contestations. Third, theories of collaborative governance that are built disproportionately on cases from stable advanced democracies are translatable to Global South and post-socialist environments if they are attendant to the bottom-up processes that permits collaboration to emerge. This symposium sheds light on the relationship between formal institutional design and the everyday relational work through which practitioners in various contexts keep collaborative arrangements alive. It hopes to inspire future research on the costs of failed collaborative governance and the role of civil society beyond the service delivery partner they are traditionally thought to perform.
When citizens evaluate proposed policy packages, do their judgments of acceptability, perceived effectiveness, and willingness to contribute to implementation move together, or do they capture distinct dimensions of public feasibility? Using a pre-registered conjoint survey experiment in the United States (N = 1,506), we examine how citizens evaluate policy packages combining taxes, regulations, subsidies, and information measures across 3 high-difficulty domains: electric-vehicle transition, AI regulation, and population aging. We distinguish push instruments, which impose costs or constraints, from pull instruments, which provide incentives or guidance, and we separate package-level composition from instrument-level marginal evaluations. 3 findings stand out. First, packages weighted toward pull instruments are more likely to be chosen and rated acceptable. Second, this package-level pattern does not produce a clean instrument-level hierarchy: baseline-referenced marginal effects favor subsidies and information, but marginal means show that absolute acceptability differs only modestly across instruments, and reactions to taxes and regulations depend on whether costs fall on individuals or on firms and employers. Third, perceived effectiveness and willingness to co-produce diverge from acceptability and vary systematically by domain and by whether contributions involve time or money. These results highlight that public feasibility is multidimensional and context-dependent: it cannot be inferred from acceptability alone but must be understood as a joint evaluation of whether packages are perceived as acceptable, effective, and implementable. The paper contributes to policy design theory by reframing public feasibility as multidimensional and clarifying how conjoint experiments can distinguish package-level composition from instrument-level evaluations.
