QCA, the Truth Table Analysis and Large-N Survey Data : The Benefits of Calibration and the Importance of Robustness Tests

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Designing Research With Qualitative Comparative Analysis (QCA): Approaches, Challenges, and Tools (2020, methodology): “Different approaches offer several tools for addressing measurement error (Cooper and Glaesser 2016b; Emmenegger, Schraff, and Walter 2014; Greckhamer et al. 2013; Maggetti and Levi-Faur 2013; Ragin 2008a; Rohlfing and Schneider 2014; Skaaning 2011; Thiem 2014a; Thiem, Spöhel, et al. 2016).”
When do Dynamic Capabilities Lead to Competitive Advantage? The Importance of Strategic Fit (2018, unknown): “…responses a given scale invokes, set calibration of survey data with Likert-type scales does not always follow an adherence to the ‘natural’ anchors such scales intuitively provide (e.g., Emmenegger et al., 2014; Fiss, 2011; Ho et al., 2016; Meijerink and Bondarouk, 2018; Mikalef and Pateli, 2017).”
An overview of qualitative comparative analysis: A bibliometric analysis (2017, methodology): “Although historically QCA has been used for small- or edium-N, Emmenegger, Schraff, and Walter (2014) maintain hat the method is applicable to research using survey data. o avoid the disadvantages of such samples, the authors recmmend analyzing the strength of the results and propose technique to…”