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Composition of environmental decision-making networks – a case study in Helsinki, Finland

Composition of environmental decision-making networks – a case study in Helsinki, Finland. M.Soc.Sc. Arho Toikka HERC Seminar Series 22.11.2007. Department of Social Policy, Faculty of Social Sciences. Composition of decision-making networks.

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Composition of environmental decision-making networks – a case study in Helsinki, Finland

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  1. Composition of environmental decision-making networks – a case study in Helsinki, Finland M.Soc.Sc. Arho Toikka HERC Seminar Series 22.11.2007 Department of Social Policy, Faculty of Social Sciences

  2. Composition of decision-making networks • In networks of organizations in charge of making policy decisions and draft policies, some actors are more popular negotiation partners than others. • Why?

  3. The City of Helsinki Environmental Governance Data Set • Based on 70 interviews and archival data • Main interest the Ecological Sustainability Programme of Helsinki • The programme is the environmental strategy of Helsinki • The most important determinator of Helsinki environmental action • Including three types of variables • Network variables • Preference variables • Outcome variables

  4. Modelling the choice of negotiation partners • Exponential Random Graph Modeling ERGM • Possible ties in the network treated as random, dependent variables in the analysis • Network statistics and actor attributes as independent variables • Dependence assumptions

  5. Helsinki Environmental Governance Analysis • The network had considerable impact on the final policies and how different subfields of environmental policy were emphasized • Influence of a single organization over the final policy was generated in the network, through the various partnerships • What made an organization an attractive an sought-after negotiation partner in environmental policy-making?

  6. Helsinki Environmental Governance Analysis • Hypotheses for partner choice • Network characteristics • Well-connected actors are more attractive – you can spread your message • Less popular actors are more attractive – you have more direct influence • Actors in tight subgroups are more attractive – you can build a base of influence • Actor attributes • Official status of the organization • Issue area expertise

  7. Helsinki Environmental Governance Analysis • The model to test these hypotheses includes estimates for the parameters for: • Generalized popularity • alternating-k-stars • Generalized subgroups • alternating-k-triangles • Expertise • Status popularity • Status homophily

  8. Helsinki Environmental Governance Analysis

  9. Conclusion • In the drafting process of environmental policy in Helsinki, the various organizations involved in drafting the policy document were free to choose the collaborators in the process • Contrary to some political science theories, the strongest effects in partner choice were the building of subgroups and status similarity, with small effects for expertise, overall status and popularity

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