3 June 2014

Analysing multi-level dynamics with multi-source data

Date:Tuesday June 3, 2014

15.00 – 17.00h.

Location: RA1247

Speakers: Carla Alvial, Haico te Kulve and Bart Walhout


The NanoNextNL research projects of Carla Alvial, Haico te Kulve and Bart Walhout all concern the study of phenomena with ‘multi-level dynamics’. That is, the projects acknowledge that innovation processes are distributed among heterogeneous actors and that relevant interactions take place in inter-related spaces with various problems framings and perspectives. The projects aim to take these complexities into account in a meaningful and productive way.


Carla studies dynamics of expectations and questions whether and how to characterise these dynamics as discursive ‘regimes’ or ‘arrangements’, made up by and impacting individual/local practices.


Haico studies demand articulation at the level of organisations while accounting for ‘sector level’ dynamics (food and water) as a relevant backdrop for actor strategies and uses this knowledge in strategic articulation sessions.


Bart studies ‘governance practices’ of responsible research and innovation (RRI), situated in the governance of research and innovation (R&I) and is tracing how de facto governance of RRI is conditioned by various factors.

In all three projects, multi-level dynamics play a role. Rather than fully describing and analysing dynamics at different levels and their relationships, it may be sufficient for the purposes of the individual projects to point out different kind of dynamics at different levels, without systematically and empirically tracing how these different dynamics are related to each other. However, this still leaves the question what counts as sufficiently solid, valid, and convincing in the argumentation and provision of evidence regarding the dynamics studied in each project. Since all three projects draw on multiple sources (observations, interviews, blogs, reports, papers), this question becomes even more challenging.

The aim of this data session is to generate feedback for improving the quality of these projects specifically rather than generic methodological discussions and reflections. Therefore we would like to discuss each project in terms of:


What should a single paper/chapter/thesis aim to explain in relation to multiple levels?


How to present multi-level data?


How to account for heterogeneous sources?


How to account (or mention, or address) what is NOT explained in our data/work


What kind of methodological considerations are worth mentioning to the reader in order to make sense, and legitimize what we present as evidence?

ross-cutting questions and discussions.