Addressing the ‘Qualitative’ in fuzzy set Qualitative Comparative Analysis: The Generic Membership Evaluation Template

Zsófia Tóth, Stephan C. Henneberg, Peter Naudé

Research output: Contribution to journalArticlepeer-review


Fuzzy set Qualitative Comparative Analysis (fsQCA) can help researchers to address causal complexity, especially in relation to the interactions between different conditions leading to the outcome in question. FsQCA helps investigate how alternative solutions (different configurations of conditions) make up the outcome, and considers the asymmetrical nature of social phenomena. An important challenge that researchers often face when they apply fsQCA to qualitative data is the lack of distinct and operationalizable anchor points for fuzzy set calibration. This study offers the Generic Membership Evaluation Template (GMET) to support the decision making about assigning fuzzy set values to conditions, and therefore improves the transparency of the qualitative calibration process. This paper aims to highlight why and how fsQCA can be carried out to obtain a more in-depth understanding of complex problems using qualitative data, to identify some core method issues involved in this analytical process, and to develop a conceptual and empirical framework that helps in managing some methodological issues, with special regard to the calibration process. For illustration of the method we scrutinize ways in which the customer firm can achieve attractiveness in the eyes of the supplier. Our study explores configurations leading to the Relational Attractiveness of the Customer (RAC) based on 28 in-depth interviews with senior managers on the supplier side. In the interest of methodological reflections and parsimony, it is assumed that the reader is familiar with the principles of fsQCA.

Original languageEnglish
Pages (from-to)192-204
Number of pages13
JournalIndustrial Marketing Management
Publication statusPublished - 1 May 2017


  • Calibration
  • FsQCA
  • Generic Membership Evaluation Template
  • Qualitative data analysis


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