This new addition to the Applied Social Research Methods series is unrivalled, it is written by leaders in the growing field of rigorous, comparative techniques.

Some 20 years after the emergence of configurational theory as a key perspective in organization studies in the 1990s, this approach has yet to deliver on its promise. While we know that configurations the relative arrangement of parts and elements - matters, empirical research on configurations is just beginning to deliver on its promise.

This working paper gives an overview of Qualitative Comparative Analysis (QCA), a method that enables systematic cross-case comparison of an intermediate number of case studies. It presents an overview of QCA and detailed descriptions of different versions of the method. Based on the experience applying QCA to CIFOR’s Global Comparative Study on REDD+, the paper shows how QCA can help produce parsimonious and stringent research results from a multitude of in-depth case studies developed by numerous researchers. QCA can be used as a structuring tool that allows researchers to share understanding and produce coherent data, as well as a tool for making inferences usable for policy advice. REDD+ is still a young policy domain, and it is a very dynamic one. Currently, the benefits of QCA result mainly from the fact that it helps researchers to organize the evidence generated. However, with further and more differentiated case knowledge, and more countries achieving desired outcomes, QCA has the potential to deliver robust analysis that allows the provision of information, guidance and recommendations to ensure carbon-effective, cost-efficient and equitable REDD+ policy design and implementation

Cover -- Comparison. A Methodological Introduction for theSocial Sciences -- Table of Content -- Preface -- 1. Introduction: choosing the question? -- 1.1 Starting from the key aspect -- 1.2 Further examples -- 2. Defining Comparison -- 2.1 The key questions -- 2.2 Classic thinkers -- 2.3 Modern theorists -- 3 Why compare? -- 3.1 The goals of comparison -- 3.2 Nomothetic objectives and generalizations -- 3.3 Explanation and understanding -- 3.4 What kind of theory should be adopted in political science? -- 4. What to compare: the basic units -- 4.1 Identifying the issue -- 4.2 Concepts and classes -- 4.3 Properties and variables -- 4.4 Operationalization -- 4.5 The "many variables, small N" dilemma -- 5. What to compare: space and time -- 5.1 Dimensions of comparison -- 5.2 Deciding the space -- 5.2.1 Case study -- 5.2.2 Other strategies -- 5.3 Defining the time -- 5.4 The problem of multicollinearity -- 6. How to compare: the key mechanisms -- 6.1 The available tools -- 6.2 Ogden and Richards' triangle -- 6.3 The rules of conceptualization -- 6.4 The Tree of Porphyry -- 6.5 Classificatory strategies -- 6.6 Mill's canons -- 7. How to compare: recent developments -- 7.1 In search of new rules for conceptualization -- 7.2 Process tracing -- 7.3 The configurational comparative method and qualitative comparative analysis -- 8. Beyond comparison: other research methods -- 8.1 Data collection and relations between variables -- 8.2 More about explanation, generalization and theory -- 8.3 Experimental and non-experimental methods -- 8.4 The statistical method -- 8.4.1 The number of cases -- 8.4.2. Logic -- 8.5 The historical method -- 9. Conclusions. The limits of comparison -- Bibliographical References -- Index

Qualitative Comparative Analysis (QCA) is a configurational comparative method that is still hotly debated among scholars. Nonetheless, the method has made major inroads into the field of International Relations. The present chapter has three main goals. First, it argues that QCA can add significantly to our accumulation of knowledge about cause-effect relations. Second, using an existing study on contributions to military missions of the European Union, it demonstrates the functionality and workings of QCA in order to give applied researchers concrete technical guidance on how to employ the method correctly. Third and last, the chapter briefly introduces Coincidence Analysis (CNA) and Combinational Regularity Analysis (CORA) 'Äì two more recent configurational methods that have solved many of the methodological and technical problems QCA still remains affected by.

Qualitative comparative analysis (QCA) has emerged as a new methodological tool in management studies which is ideally suited to test configurational theories. In this work, the peculiarities of QCA in large-N designs are comprehensively analysed for the first time. Additionally, an illustrative study using the fuzzy set version of QCA is conducted.

When the objectives of public policy programmes have been formulated and decided upon, implementation seems just a matter of following instructions. However, it is underway to the realization of those objectives that public policies get their final substance and form. Crucial is what happens in and around the encounter between public officials and individual citizens at the street level of government bureaucracy. This Research Handbook addresses the state of the art while providing a systematic exploration of the theoretical and methodological issues apparent in the study of street-level bureaucracy and how to deal with them.

In the first volume of its kind, a collection of top policy scholars combine empirical and methodological analysis in the field of comparative policy studies to provide compelling insights into the formulation, implementation and evaluation of policies across regional and national boundaries.

Seminar paper from the year 2006 in the subject Business economics - General, grade: Sehr Gut, Vienna University of Economics and Business (Europainstitut), course: Qualitative Methoden, language: English, abstract: Traditionally most social researchers either employ purely qualitative or quantitative methods, even though a mixed method strategy may promise better results. The present paper introduces Qualitative Comparative Analysis (QCA) as a mixed method alternative for data analysis. It may be of particular value when dealing with small-n case studies, which typically do not permit profound statistical testing. QCA enables researchers to filter those variables or combinations of variables that empirically result in (and possibly explain) a certain outcome. As such, the method can also be used to analyze the impact of social networks on companies' innovation performance and promises valuable new insights in the field.

This innovative book seeks to explain what factors account for the consolidation of young democracies in over thirty countries in Latin America and Europe throughout the last quarter of the twentieth century.