One of the most significant features of COVID-19 pandemic governance was the involvement of experts in decision-making, which included epidemiologists, medical doctors, economists, and behavioral specialists. In contrast, the knowledge of citizens, business owners, and civil society organizations had less impact on political decisions and interventions. The lack of integration of different types of knowledge may have limited the options for robust governance solutions. This conceptual paper asks how the interactions among different types of knowledge contribute to the robust governance of crisis-induced turbulence. To answer this question, this paper proposes the new concept of societal intelligence. Building on the work on collective wisdom and collective intelligence, societal intelligence aims at filling the gap on the conditions under which knowledge exchanges take place, focusing on the decisions that individual actors such as politicians, experts and citizens must take when facing turbulence. We conceptualize these knowledge exchanges taking place in interfaces, and the conditions for building societal intelligence therein. The paper also discusses practices and mechanisms that built this intelligence during the COVID-19 pandemic, based on data from nine European countries. We argue that building and maintaining societal intelligence can provide more nuanced understanding of a crisis, more responsive and legitimate solutions, and ultimately robust crisis governance.
Research on blame avoidance of public employees primarily focuses on its reactive nature, referring to justifying failures after they happen, while its anticipatory side has received less attention. Using data from 781 Chinese public employees, this study examines how four accountability features, namely, the number of forums, the type of authority, the initiation source, and the evaluative focus, shape their perceptions of anticipatory blame avoidance. Results indicate that political authority and outcome-focused accountability reduce the perceived likelihood of blame avoidance of public employees, whereas the number of forums and the initiation source have little effect. These findings contribute to the governance and policy literature by demonstrating how accountability features shape public employees' anticipation of blame avoidance before misconduct.
Policy reinvention has received substantial scholarly attention. However, little is known about how reinvention at different government levels influences policy implementation outcomes. This study examines the dynamics of multilevel policy reinvention within vertical authority structures. The findings demonstrate that while municipal policy reinvention positively contributes to policy outcomes, excessive policy reinvention at the provincial level can impede municipal policy performance. Contrary to our expectation, faster provincial adoption weakens the positive relationship between municipal reinvention and policy performance. An exploratory typological analysis further shows that conservative reinvention is associated with significantly better outcomes than prudent reinvention. Robustness analyses confirm the stability of these theoretical claims. These findings contribute to a more nuanced understanding of intergovernmental policy processes and offer practical insights into achieving better alignment between policy reinvention efforts across government tiers and policy implementation performance.
Debates over the effectiveness of policy implementation networks and the role of network management have attracted considerable scholarly attention in recent decades. Research has focused on the tasks network managers perform, proposing that network management improves network performance. This study takes a step back by investigating why some network managers intervene in their networks more intensively than others, addressing an important research gap. Using data from 13 Swiss smoking prevention networks, this article bridges the research on policy implementation and public management by analyzing how organizational features and implementation context-related factors jointly influence managerial action within collaborative policy delivery networks. Rather than assuming that managerial activity is driven by single factors, this paper employs Qualitative Comparative Analysis (QCA) alongside in-depth case study evidence to identify combinations of factors that shape the level of managerial activity. The study suggests that high-intensity network management in mandated networks is shaped by the interplay of network managers’ organizational affiliation (public vs. non-state), the presence or absence of goal conflicts, the level of resources available for network management, and the existence of ties within the network. It finds that NGO-affiliated network managers are more likely to apply high-intensity network management – either proactively under favorable conditions or reactively when facing challenges – while public managers typically engage less due to structural constraints or managerial preferences. By conceptualizing network management as a phenomenon situated at the intersection of organizational structure and implementation context, this study offers a more integrated understanding of how public service delivery is coordinated in complex governance settings.
Digital transformation has become a strategic priority for enhancing the competitiveness and sustainability of Micro, Small, and Medium Enterprises (MSMEs). However, the implementation of digital transformation policies across various regions still shows a partial and uneven level of adoption. Previous research has generally examined structural barriers such as infrastructure limitations, regulations, and institutional capacity or cultural barriers such as low digital literacy, motivation, and resistance to change separately. As a result, the resulting policy recommendations have not been able to explain how these two dimensions interact with one another in policy implementation. This study aims to analyze the interaction of structural and cultural factors in the implementation of digital transformation policies for MSMEs and to develop an Adaptive Policy Model to support the digital transformation of MSMEs in Lhokseumawe City. The study employed a qualitative approach using the case study method, involving 47 purposively selected informants, including MSME operators, local government officials, academics, financial institutions, legislators, community members, consumers, and the media. Data were collected through in-depth interviews, observations, and document analysis, and were subsequently analyzed using NVivo 12. The research findings indicate that the implementation of digital transformation policies is influenced by a mutually reinforcing interaction between structural barriers including policy fragmentation, unequal access to digital infrastructure, weak institutional capacity, and poor interagency coordination and cultural barriers, such as low digital literacy, resistance to change, and weak motivation among MSME actors. These interactions have resulted in a digital adoption process that is partial, uneven, and unsustainable Based on these findings, this study developed an Adaptive Policy Model consisting of three mutually integrated stages policy set-up, policy design, and policy implementation, as well as monitoring and evaluation which emphasizes strengthening institutional coordination, long-term planning, interventions tailored to the capacity of MSMEs, inclusive implementation, and data-driven evaluation as a policy learning mechanism. These findings expand the study of public policy implementation through the development of an adaptive policy model that can serve as a reference for local governments in designing a more effective and sustainable digital transformation for MSMEs.
