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Abstract
The case survey method and qualitative comparative analysis (QCA) are two well-established research approaches in a number of research disciplines. They have recently made their way into information systems (IS) research. The case survey method is aimed at comparing previously published case studies, conventionally, using various statistical analysis methods. In turn, QCA relies on set theory, which allows deriving different configurations based on qualitative data corresponding to cases translated into set membership. Several authors have started to combine these two methods. However, so far there is no formalized approach on how to combine them. In this paper, we present a formalized approach to integrate the two methods and demonstrate how this approach can be used to resolve several limitations intrinsic to these methods when being employed on their own. We furthermore discuss the potential of applying our approach for IS research and discuss the proposed approach’s limitations.
Recommended Citation
Soto Setzke, David; Böhm, Markus; and Krcmar, Helmut, "Combining the Case Survey Method and Qualitative Comparative Analysis for Information Systems Research" (2020). AMCIS 2020 Proceedings. 1.
https://aisel.aisnet.org/amcis2020/meta_research_is/meta_research_is/1
Combining the Case Survey Method and Qualitative Comparative Analysis for Information Systems Research
The case survey method and qualitative comparative analysis (QCA) are two well-established research approaches in a number of research disciplines. They have recently made their way into information systems (IS) research. The case survey method is aimed at comparing previously published case studies, conventionally, using various statistical analysis methods. In turn, QCA relies on set theory, which allows deriving different configurations based on qualitative data corresponding to cases translated into set membership. Several authors have started to combine these two methods. However, so far there is no formalized approach on how to combine them. In this paper, we present a formalized approach to integrate the two methods and demonstrate how this approach can be used to resolve several limitations intrinsic to these methods when being employed on their own. We furthermore discuss the potential of applying our approach for IS research and discuss the proposed approach’s limitations.
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