The project has a dual aim:
to assess longer trends in global governance and their implications for the EU and its future strategy,
and to analyse these against the backdrop of a war in Europe that is destined to have significant (if hard to identify) consequences for the future of global governance and multilateralism.
We must not only consider the potential added value of multilateral public-private partnerships, which is prevalent in fields such as climate change, health and development finance, but also how the war in Ukraine will affect the mobilization of private actors. To this end, we need to assess how different hybrid, ad-hoc, club, or multistakeholder governance arrangements perform on transparency and democratic accountability, but also read these in light of a much more concerted mobilization around democratic values.
Finally, while pre-existing geopolitical rivalry made its mark on all multilateral institutions and mechanisms, the war in Ukraine will surely exacerbate these trends, and likely further push towards minilateral or ad-hoc arrangements between like-minded states that coexist with established but weakened multilateral institutions.
Combining inductive and deductive research strategies
NAVIGATOR thus aims to build on and extend existing research on multilateralism and global governance to develop a comprehensive assessment of the strengths and weaknesses of existing multilaterals, alongside the potential and pitfalls of different non-state governance arrangements. As already outlined, existing research offers a wealth of insights. These can be extended to offer tools for formulating pathways of action that balance an interest in strengthening and reforming existing organizations with geopolitical realities that threaten to undermine the rules-based international order.
We address the abovementioned tasks through a multi-method approach combining inductive and deductive research strategies into an abductive process, using both small-N and large-N methods. The abductive approach stresses how the investigator may commence with some estimations of expected behaviour, and propositions are then refined as evidence is discovered showing that purely deductive assumptions are incorrect. Abduction – the most common but least formally recognized way of doing research – combines deduction and induction, providing a foundation for interdisciplinary research (Mabsout 2015). As a first step, we conduct descriptive statistical analyses to establish a ‘nest’ of data to identify generic patterns from which more specific propositions can be developed, based on analyses of different issue areas (Lieberman 2005).
Combining qualitative-quantitative computational analyses
We use more qualitative and combined qualitative-quantitative computational analyses to identify which factors increase/expand or limit/undermine the EU and its member states’ ability to advance more effective and democratic global governance. This relationship between the ‘nest’ of data and detailed information from the issue-area cases is a recursive process through NAVIGATOR across the work packages. In short, this methodology allows a common conversation among the research team with a focus on identifying pathways of action for the EU. The ultimate outcome of relevance is clear – namely EU ability to shape global governance – but we do not know the variation between issue-areas nor the particular configuration of factors that renders different strategies and resources more or less effective.
We suggest that these objectives are best identified by moving between large-N statistical analyses (LNA) and small-N (SNA) case studies to both build and test propositions about causal relationships (Lieberman 2005). Importantly, nested analyses are well suited not only for comparative issue-area analyses, but also for managing any uncertainty about the future development of global governance following the war in Ukraine. This is because they provide a research strategy that moves between LNA to identify patterns from which propositions can be formulated to SNA that can provide preliminary tests, to identify causal mechanisms in specific cases, and to (re-) formulate key propositions that can, in turn, be subject to tests via LNA. Before spelling out the steps of this methodology, we first discuss our overall research questions and sub-questions.