The “qualitative” in qualitative comparative analysis (QCA): research moves, case-intimacy and face-to-face interviews

Sofia Pagliarin (), Salvatore Mendola () and Barbara Vis ()
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Sofia Pagliarin: Otto-Friedrich-Universität Bamberg
Salvatore Mendola: Padua University
Barbara Vis: Utrecht University

Quality & Quantity: International Journal of Methodology, 2023, vol. 57, issue 1, No 23, 489-507

Abstract: Abstract Qualitative Comparative Analysis (QCA) includes two main components: QCA “as a research approach” and QCA “as a method”. In this study, we focus on the former and, by means of the “interpretive spiral”, we critically look at the research process of QCA. We show how QCA as a research approach is composed of (1) an “analytical move”, where cases, conditions and outcome(s) are conceptualised in terms of sets, and (2) a “membership move”, where set membership values are qualitatively assigned by the researcher (i.e. calibration). Moreover, we show that QCA scholars have not sufficiently acknowledged the data generation process as a constituent research phase (or “move”) for the performance of QCA. This is particularly relevant when qualitative data–e.g. interviews, focus groups, documents–are used for subsequent analysis and calibration (i.e. analytical and membership moves). We call the qualitative data collection process “relational move” because, for data gathering, researchers establish the social relation “interview” with the study participants. By using examples from our own research, we show how a dialogical interviewing style can help researchers gain the in-depth knowledge necessary to meaningfully represent qualitative data into set membership values for QCA, hence improving our ability to account for the “qualitative” in QCA.

Keywords: Calibration; Data generation; Interviewing; In-depth knowledge; Qualitative data (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11135-022-01358-0

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