Rethinking policy-related research: charting a path using qualitative comparative analysis and complexity theory

摘要

This article argues that conventional quantitative and qualitative research methods have largely failed to provide policy practitioners with the knowledge they need for decision making. These methods often have difficulty handling real-world complexity, especially complex causality. This is when the mechanism of change is a combination of conditions that occur in a system such as an organisation or locality. A better approach is to use qualitative comparative analysis (QCA), a hybrid qualitative/quantitative method that enables logical reasoning about actual cases, their conditions and how outcomes emerge from combinations of these conditions. Taken together, these comprise a system, and the method works well with a whole-system view, avoiding reductionism to individual behaviours by accounting for determinants that operate at levels beyond individuals. Using logical reduction, QCA identifies causal mechanisms in sub-types of cases differentiated by what matters to whether the outcome happens or not. In contrast to common variable-based methods such as multiple regression, which are divorced from actual case realities, QCA is case-based and rooted in these realities. The use of qualitative descriptors of conditions such as ways of working engages practitioners, while their standardisation enables systematic comparison and a degree of generalisation about 'why' questions that qualitative techniques typically do not achieve. The type of QCA described in the article requires conditions and outcomes to be dichotomised as present or absent, which is helpful to practitioners facing binary decisions about whether to do (a) or (b), or whether or not an outcome has been achieved.