Structure Matters – A Social Network Analysis on Swiss Stakeholders’ Information Exchange About SDG 6

In 2015, the member states of the United Nations (UN) developed and passed the Agenda 2030 for sustainable development. The Agenda 2030 is an action plan for the next 15 years designated to lead to a sustainable future. It includes 17 Sustainable Development Goals (SDGs) which cover the social, environmental and economic dimension of sustainability and are a guideline for all the UN member states. According to the United Nations resolution covering the Agenda 2030, countries should not only implement the Sustainable Development Goals nationally, but also support other countries in their implementation. Our presentation investigates how Switzerland deals with the challenge of implementing the Sustainable Development Goal 6 (Water) in developing countries. Although Switzerland itself performs well regarding this goal, it has a high virtual water footprint, which has a high impact on the water situation in developing countries where quantity and quality of water are problematic. One way of taking responsibility of its high impact in developing countries is to mobilize Swiss expertise to solve water problems in these countries. To ensure evidence-based decision-making in this process, information exchange between stakeholders is key. We use social network analysis and evidence from qualitative interviews to investigate what influences information exchange between Swiss stakeholders involved in the implementation of the Sustainable Development Goal 6 (Water) in developing countries. The networks are composed of 80 stakeholders from research, public administration, NGOs and others, and of ties of political and technical information exchange. We analyse these networks through Exponential Random Graph Models (ERGMs) that allow to investigate the importance of different factors behind the ties among stakeholders. These factors are on the level of the network itself (endogenous network factors), on the level of stakeholders (node-level factors) or on the level of stakeholder pairs (dyad-level factors). Preliminary results show that stakeholders tend to exchange information with stakeholders that are similar to themselves. Stakeholders can be similar to each other according to many different dimensions. We consider different types of similarities such as the size and resources of the organization, their background (academia, public administration, civil society and private sector) and related role in the social system, their issue specialization and related involvement in other SDGs, or their attendance of the same events and policy forums.