
Multilevel governance (MLG) is not only a highly debated notion in the academic literature on public policy, but also a normative idea underlying discussions in various – local, regional, EU – policymaking circles and fora. From this perspective, MLG offers an alternative paradigm to hierarchical policymaking, by substituting command and control with collaboration and coordination across different levels of government and among all concerned public and non-public actors. It is however still unclear to what extent and under which circumstances MLG emerges in times of crisis. Furthermore, it is also an open question whether and to what extent MLG can contribute to achieve robust crisis governance, implying the capacity to alleviate turbulence (through innovative and/or adaptive responses) without compromising core democratic values and norms. This report aims to fill these gaps, elaborating on data collected through interviews and an extensive analysis of policy documents conducted by the partners of the ROBUST project. More specifically, the report builds on the mainly theoretical results of other project deliverables (D3.1), aiming to transition to more concrete applications in empirical data and crisis evaluation.
Interactivity, Robust Governance, Robustness, Multi-Level Governance
Interactivity, Robust Governance, Robustness, Multi-Level Governance
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
