
doi: 10.1111/psj.12582
AbstractPolicy process literature offers several frameworks and theories to understand the adoption or modification of policies across different jurisdictions. Extant studies focus on the emergence of coalitions, actors, strategies, etc. as they relate to individual policies. Policy actions, however, are typically deployed as packages—combinations of different instruments or measures. Policy mixes—also used interchangeably with terms such as policy packaging, policy bundling, etc.—are an important aspect of policy design. However, the role and emergence of policy mixes in the context of the policy process have not been studied in great depth. This study examines the role of different policy pathways that yield desired policy outcomes in the electric vehicle (EV) policy subsystem. We use the case of sub‐national EV policies across the US to analyze how different combinations of policy actions operate in combination and/or competition with each other to achieve the desired policy objectives. The study contributes to the policy design scholarship in two ways. First, by analyzing the emergence of policy mixes as policy outputs during the policy design process using a theoretical lens applying the multiple streams framework. Second, by deploying fuzzy set Qualitative Comparative Analysis as a methodological tool to uncover causal pathways to desired policy outcomes.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 5 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
