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Governance of learning processes in transdisciplinary research teams

22 March 2012. Governance of learning processes in transdisciplinary research teams. Wouter Boon | 1. Knowledge co-production…. 22 March 2012. ‘Mode 2’ science Organisational heterogeneity, transdisciplinary, contextualised knowledge production Suitable for ‘wicked problems’

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Governance of learning processes in transdisciplinary research teams

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  1. 22 March 2012 Governance of learning processes in transdisciplinary research teams Wouter Boon | 1

  2. Knowledge co-production… 22 March 2012 • ‘Mode 2’ science • Organisational heterogeneity, transdisciplinary, contextualised knowledge production • Suitable for ‘wicked problems’ • Co-production of knowledge by producers and users Wouter Boon | 2

  3. … in teams 22 March 2012 • Initiatives that encompass a large range of scientists, disciplines and locations (Stokols et al., 2008) • There is work on science collaboration and team work • Research question: individual, interactional and institutional factors  effectiveness of teams? Wouter Boon | 3

  4. Research question 22 March 2012 • Initiatives that encompass a large range of scientists, disciplines and locations (Stokols et al., 2008) • There is work on science collaboration and team work • Research question: individual, interactional and institutional factors  effectiveness of teams? Wouter Boon | 4

  5. Perspective: linear  team science 22 March 2012 • Linear view of science production • With endpoints in technology and policy • Science for ‘wicked problems’: • Extended peer community • Integration of concepts and methods • Contextualisation • Co-production of knowledge in teams Wouter Boon | 5

  6. Science in teams: characteristics 22 March 2012 • Knowledge users and producers coming from different organisations, disciplines and normative backgrounds. • Teams positioned outside existing organisations (“decoupling”) • Design from scratch • Two principles • Research objective as a starting point, but problem definition and methodology need to be articulated Wouter Boon | 6

  7. Conceptual model Individual factors Competences (collaborative experience and readiness) Motivations 22 March 2012 Performance 1st order and 2nd order learning Interactional factors Diversity of members and disciplines History of collaboration Interaction patterns Institutional factors Incentive system Nature of support Wouter Boon | 2

  8. Case selection 22 March 2012 • Knowledge for Climate • Hotspot Mainport Rotterdam (local, rich, networked) • Projects (first tranche; heterogeneity of participants) Wouter Boon | 8

  9. Case introduction 22 March 2012 Flood risks in unembanked areas Urban heat Heusinkveld et al. (2011) Veerbeek et al. (2010) Wouter Boon | 9

  10. Methodology 22 March 2012 • In-depth interviews • Document analysis Wouter Boon | 10

  11. Results: urban heat (1) 22 March 2012 • 1st order learning: • On outcomes • Chain of research questions • No integration • 2nd order learning: • Acknowledgement • No shared vision Wouter Boon | 11

  12. Results: urban heat (2) 22 March 2012 • Individual factors • No previous collaborations; science push and policy pull • ‘Hobby horses’, self-interests • Motivations: content-driven • Interactional factors • Team diversity: high • Formal, business-like interactions; distributed governance • Network with scientists as hub • Institutional factors • Individual-oriented; divergent evaluation at home org. • Administrative support ánd burden Wouter Boon | 12

  13. Results: flood risks (1) 22 March 2012 • 1st order learning: • Part of continuous learning process • 2nd order learning: • Commercial chances • Awareness of blind spots Wouter Boon | 13

  14. Results: flood risks (2) 22 March 2012 • Individual factors • Previous collaborations; policy pull • Methodologies further developed • Motivations: content-driven • Interactional factors • Team diversity: mostly the same disciplinary background • Informal, also bilateral interactions; lead organisation governance • Institutional factors • Individual-oriented; evaluation: new knowledge and network • Administrative support ánd burden Wouter Boon | 14

  15. Conclusions 22 March 2012 • Urban heat • New field and lots of opportunities; fragmented and distributed patterns; no shared vision and integration • Flood risks • Previous and continuous collaborations; co-production of data; continuous learning • Individual, interactional and institutional factors (partly) explained the level of learning in the urban heat and flood risk teams Wouter Boon | 15

  16. Discussion 22 March 2012 • Expansion to other cases/teams: • Monodisciplinary teams • Other hotspots • Other programmes (less ‘safe harbour’) • Other sectors • Expansion of methods • Bibliometrics, CV analysis Wouter Boon | 16

  17. Wrap up 22 March 2012 • The individual, interactional and institutional factors partly explained the level of learning in the urban heat and flood risk teams. • The analyses contribute to formulating recommendations on the governance of user-producer knowledge production. Wouter Boon | 17

  18. w.boon@rathenau.nl 22 March 2012 • Thankyouforyour attention! Wouter Boon | 18

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