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Over the last years, configurational research has become increasingly popular in the Information Systems (IS) discipline. Researchers value configurational methods like Qualitative Comparative Analysis (QCA) as their application contributes to a better understanding of complex phenomena. QCA helps to uncover interrelations of conditions that lead to an outcome, building on the principles of equifinality, conjunctural causation, and asymmetry. More recently, IS researchers have started to analyze qualitative data, like case study data, with QCA. However, there is a lack of methodological guidance on how to calibrate qualitative data into set membership values for QCA. Therefore, this paper structures methodological steps and the associated options to calibrate qualitative data from an interdisciplinary perspective and critically reviews the observed methodological choices in IS research. This paper also gives recommendations for calibrating qualitative data to support informed methodological choices for future research.



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