Qualitative comparative analysis (QCA) – especially its fuzzy set version – has emerged as a new methodological tool in management studies which is ideally suited to test configurational theories. For the first time, the peculiarities of QCA in large-N designs are comprehensively analysed. Based on a systematic compilation of 145 empirical QCA studies valuable insights for the use of QCA as a quantitative technique are presented. For example, an innovative formula is developed which can substantially improve future model specifications. In a next step, the potential of QCA in management research is outlined by tracing configurational theories in a range of disciplines including strategy, HRM, marketing, and international business. This tour d’horizon through management studies highlights the wide application area of the methodology. Finally, an illustrative study is conducted using the fuzzy set version of QCA.
CCMs add to the methodological landscape insofar as a wider range of research questions can be addressed and hypotheses can be tested with the appropriate method in future research. CCMs can extract the configurational information contained in management scientists’ data. While traditional statistical methods are in line with linear co-variational hypotheses and statements based on univer- salistic and contingency theory, CCMs are inherently connected to configura- tional approaches. The key assumptions underpinning both configurational theo- ry and QCA coincide, and find their expression in the notion of multiple con- junctural causation. Since configurational theories and methods are younger than their linear counterparts, there is much room for their utilisation. They help to shed light on the equivocal and questionable findings of previous research, which stem from a misfit between method and theory. In order for QCA to deliver meaningful and understandable results, more standards of good practice must be established. The comprehensive review, in this thesis, of QCA studies from diverse disciplines reveals that generally more transparency and clarity is needed in the usage of CCMs. Although journal arti- cles commonly face space restrictions, they need to provide more documentation of the steps of a QCA. First and foremost, there is a need for greater clarity in the wording in published articles, since some scholars revert to notations of linearity and probability when describing results. Not only the initial hypotheses, but also the final assertions about the results should ideally be formulated ex- plicitly in terms of necessity and sufficiency...
You are not authenticated to view the full text of this chapter or article.
This site requires a subscription or purchase to access the full text of books or journals.
Do you have any questions? Contact us.Or login to access all content.