Of barriers to entry for quantitative multiple streams applications: Methodologic and conceptual considerations

Recent reviews of the multiple streams (MS) literature concluded that although the framework is prolific, there is a lack of contributions applying quantitative research approaches. By addressing which barriers to entry quantitative MS contributions face and by suggesting ways how to handle them, this paper aims at providing researchers with a guideline for quantitative MS-guided research. More precisely, it focuses on four challenges quantitative MS applications must handle: 1) choosing a method that corresponds with the framework’s research questions; 2) defining the causal mechanisms leading to agenda change and/or policy change; 3) translating the framework’s figurative language into falsifiable hypotheses; and 4) defining measurable and quantifiable variables that capture these hypotheses. Regarding the choice of method, we summarize for qualitative comparative analysis, event history analysis, and logistic regression their (dis-)advantages in terms of testing the MS framework and their requirements regarding data structure. Since it is widespread practice today to apply the framework to agenda-setting and decision-making, we draw attention to the need to differentiate two sets of causal mechanisms, namely between those leading to agenda change and those leading to policy change. Irrespective of how the dependent variable is defined, quantitative MS applications require that researchers derive a set of falsifiable hypotheses. Based on a content analysis of peer-reviewed MS articles applying quantitative or mixed methods, we summarize the state-of-the-art regarding hypotheses derived from the framework and their operationalization. Where appropriate, we also discuss alternative ways to operationalize the framework’s key concepts. We conclude that although the barriers of entry are high for quantitative MS applications, they are not insurmountable.