The purpose of this paper is to address and test two assumptions on which csQCA is based, namely that csQCA will generate contradictions and low consistency scores if models are ill-specified. The first part of the paper introduces csQCA in general and as a stepwise approach. In a second part a real-life example is introduced with the purpose of illustrating how csQCA operates and as an input for a simulation in the subsequent part. The third part introduces contradictions, consistency, their interrelatedness and the assumptions which are made with regard to contradictions and consistency. Subsequently the assumptions are tested via a simulation on the basis of a csQCA analysis of over 5 million random datasets. The paper argues that researchers cannot always assume that csQCA will generate contradictions or low consistency scores when models are ill-specified. Such an assumption is only justified when csQCA applications take limitations with regard to model specification (the number of conditions and the number of cases) into account. Benchmark tables for model specification purposes are developed. Since these tables are based on a probability value of 0.5 the paper also tests the results for contradictions and consistency for the probabilities which were present in a real-life example. This test shows that the 0.5 probability generates an appropriate measure for the occurrence of contradictions and consistency indicating that the benchmark tables can be used for different applications with different distributions of 0's and 1's in the conditions and outcomes. The paper ends with a conclusion.

A quarter century ago, in 1987, Charles C. Ragin published The Comparative Method, introducing a new method to the social sciences called Qualitative Comparative Analysis (QCA). QCA is a comparative case-oriented research approach and collection of techniques based on set theory and Boolean algebra, which aims to combine some of the strengths of qualitative and quantitative research methods. Since its launch in 1987, QCA has been applied extensively in the social sciences. This review essay first sketches the origins of the ideas behind QCA. Next, the main features of the method, as presented in The Comparative Method, are introduced. A third part focuses on the early applications. A fourth part presents early criticisms and subsequent innovations. A fifth part then focuses on an era of further expansion in political science and presents some of the main applications in the discipline. In doing so, this paper seeks to provide insights and references into the origin and development of QCA, a non-technical introduction to its main features, the path travelled so far, and the diversification of applications.

The notion of configuration – that the whole is best understood from a systemic perspective and should be viewed as a constellation of interconnected elements – is arguably one of the central ideas of organization studies. Yet, this idea also remains one of the field’s least understood aspects. In this volume and its introduction, we outline a new perspective for understanding configuration. Our starting point is the emergence of set theoretic configurational methods, and especially Qualitative Comparative Analysis (QCA), which provides novel ways for analyzing configurations. Our volume goes beyond introducing a new method to the fields of management and organization, as these methods furthermore offer an opportunity to rethink our understanding of the field and to develop different ways of theorizing the rich complexity of relationships that characterize organizational life. In this introduction, we introduce some of the key themes that differentiate the approach taken here from previous work on organizational configurations and provide evidence for the emerging renaissance of the configurational approach in organizational theory and research.

Public-private partnerships for sustainable development have been in operation for several decades from the local to the international level