Conventional quantitative research in the social sciences today is largely based on an understanding of analysis that is antithetical to configurational thinking. To analyze a phenomenon is to break it into its constituent parts and then to examine how the parts fit together, a two-step process. A common way of accomplishing the first step – breaking things into parts – is to conceptualize variables that can be used to characterize differences across cases.1 In conventional quantitative research the second step – examining how the parts fit together – is accomplished primarily through various forms of cross-case analysis using correlational techniques (e.g., multiple regression). Thus, in conventional quantitative research, assessments of cross-case correlational patterns provide the primary basis for statements about how the parts of cases are connected to each other. Quantitatively oriented researchers studying organizations have produced an abundance of such studies, relating specific aspects of organizations to other aspects based on correlations observed across a set of comparable organizations.
Ragin, C. (2013), "Foreword: The Distinctiveness of Configurational Research", Fiss, P., Cambré, B. and Marx, A. (Ed.) Configurational Theory and Methods in Organizational Research (Research in the Sociology of Organizations, Vol. 38), Emerald Group Publishing Limited, Bingley, pp. xv-xx. https://doi.org/10.1108/S0733-558X(2013)0000038004Download as .RIS
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