System complexity as key determinant in achieving efficacious policy transposition and implementation

Policy implementation and transposition do not take place in a “vacuum†, but are influenced by a variety of surrounding factors, stakeholder agendas and by socioeconomic or institutional boundaries. All factors together are shaping the policy performance. Consequently, understanding a policy’s surrounding context is crucial for efficacious policy transposition and implementation. In this chapter we analyse how policies unfold their performance within a pre-existing system using the example of low carbon technology adoption for mobility and heating demand in Austrian households. By using fuzzy cognitive mapping, for both areas, we find a mainly subsidy-based policy framework often lacking innovative solutions and being strongly influenced by surrounding contextual factors and stakeholder constellations. In particular both cases show that barriers for target achievement in the case of low carbon technology adoption are mainly characterized by uncertainties and individual concerns about future benefits, technology effects or financial burdens. Our findings in combination with lessons learned from Europe-wide best practice examples highlight the importance and benefit of smart policy mixes in future policy design. In particular our analysis reveals that smart policy mixes are more robust and more easily adaptable concerning influences of complex system correlations, thus not only in the case of low carbon technology adoption in Austrian households but also for policy design in general.