Universitat Internacional de Catalunya

Introduction to Qualitative Comparative Analysis (QCA) Using of FsQCA Software

Introduction to Qualitative Comparative Analysis (QCA) Using of FsQCA Software
Second semester
Main language of instruction: English

Other languages of instruction: Catalan, Spanish


Comparative research methods such as qualitative comparative analysis (QCA) offer an innovative approach especially in situations with multilevel explanations and influences. Although multiple regression analysis is effective at identifying symmetric relationships, there are not always symmetric relationships among the observations. Management fields are causally complex, requiring alternative analytical methods. QCA effectively deals with this complexity and studies cases as configurations of causes and conditions rather than treating each independent variable. Furthermore, QCA has the advantage of performing particularly well with small-to-intermediate-N research designs. This method is increasingly gaining researchers’ attention, being used in a variety of disciplines (e.g. psychology, marketing, political sciences, sociology, public administration, business and management research).

Pre-course requirements

There is no prerequisite, although basic knowledge on descriptive statistics and the use of excel (pivot tables) is highly advisable.


This 5-hours workshop will give participants a basic understanding of the theoretical and methodological underpinnings of QCA.

The course also includes a step by step guide that will enable participants to independently perform a basic QCA study.

Learning outcomes

At the end of the course, participants will:

  • Have a basic understanding of the theoretical underpinnings of QCA
  • Know the different steps that are required to conduct a QCA study and the potential difficulties/issues that require special attention
  • Be able to independently carry out a QCA study
  • Be able to understand and interpret the results of QCA


Topics that will be covered include:       

  • What is QCA? Epistemological assumptions and terminology
  • Relevance of QCA in the academic literature
  • Calibration
  • Model fit: Coverage and consistency
  • Analysis of necessity and sufficiency
  • Truth table and minimisation
  • Evaluation and interpretation of the results
  • XY plots
  • Robustness checks

Teaching and learning activities

In person

Theoretical explanations will be combined with practical exercises.

fsQCA software will be used, which can be freely download from this website:


The new version (3.0) does not require any installation package. Just download it and unzip the files. To execute the program, open the file named “fsQCA”. It is highly recommended bringing your own laptop.

The supporting material will be uploaded to the platform of the course a couple of days before the date of the workshop. There is no need to prepare anything in advance.

Evaluation systems and criteria

In person

A certificate of completion will be issued to participants that successfully complete the program (attended and actively participated during the 5-hours workshop).

Bibliography and resources

Berg-Schlosser, D., De Meur, G., Rihoux, B., Ragin, C.C. (2009). Qualitative comparative analysis (QCA) as an approach. Configurational comparative methods, 1-18.

Legewie, N. (2013). An Introduction to Applied Data Analysis with Qualitative Comparative Analysis (QCA). Forum: Qualitative Social Research (FSQ), 14(3), article 15.

Medina, I., Castillo Ortiz, P. J., Álamos-Concha, P. & Rihoux, B. (2017). Análisis Cualitativo Comparado (QCA) (Vol. 56). CIS-Centro de Investigaciones Sociológicas.

Ragin, C.C., Drass, K.A., Davey, S. (2006). Fuzzy-set/qualitative comparative analysis 2.0. Tucson, Arizona: Department of Sociology, University of Arizona.

Ragin, C.C., Rihoux, B. (Eds.). (2009). Configurational Comparative Methods: Qualitative Comparative Analysis (QCA) and Related Techniques (pp. 87-122). Sage.

Schneider, C.Q., Wagemann, C. (2010). Standards of good practice in qualitative comparative analysis (QCA) and fuzzy-sets. Comparative Sociology, 9(3), 397-418.

Woodside, A. G. (2013). Moving beyond multiple regression analysis to algorithms: Calling for adoption of a paradigm shift from symmetric to asymmetric thinking in data analysis and crafting theory. Journal of Business Research, 66(4), 463-472.