In addressing various policy problems, deciding which policy measure to start with given the range of measures available is challenging and essentially involves a process of ranking the alternatives, commonly done using multicriteria decision analysis (MCDA) techniques. In this paper a new methodology for analysis and ranking of policy measures is introduced which combines network analysis and MCDA tools. This methodology not only considers the internal properties of the measures but also their interactions with other potential measures. Consideration of such interactions provides additional insights into the process of policy formulation and can help domain experts and policy makers to better assess the policy measures and to understand the complexities involved. This new methodology is applied in this paper to the formulation of a policy to increase walking and cycling.
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