Peer Fiss

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University of St.Gallen
University of Southern California

Course location

University of St.Gallen

Home university

University of Southern California
Peer-Fiss
Peer Fiss is the Jill and Frank Fertitta Chair of Business Administration and a Professor of Management & Organization, and Sociology (by courtesy) at the University of Southern California. His research interests include organization theory, framing, and social categorization. He has also been working for almost two decades on the use of set-analytic methods in the social sciences, and specifically on the use of fuzzy set qualitative comparative analysis (QCA). His work has been published in the Academy of Management Journal, Academy of Management Review, Administrative Science Quarterly, American Sociological Review, MIS Quarterly, Organization Science, and the Strategic Management Journal, among others. His recent book with Charles Ragin on applying set-analytic methods to policy analysis is entitled Intersectional Inequality: Race, Class, Test Scores, and Poverty (University of Chicago Press, 2017).

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Qualitative Comparative Analysis

Qualitative comparative analysis (QCA) is a research approach consisting of both an analytical technique and a conceptual perspective for researchers interested in studying configurational phenomena. QCA is particularly appropriate for the analysis of causally complex phenomena marked by multiple, conjunctural causation where multiple causes combine to bring about outcomes in complex ways.

QCA was developed in the 1980s by Charles Ragin, a sociologist and political scientist, as an alternative comparative approach that lies midway between the primarily qualitative, case-oriented approach and the primarily quantitative, variable-oriented approach, with the goal of bridging both by combining their advantages and tackling situations where causality is complex and conjunctural. QCA uses Boolean algebra for the analysis of set relations and allows researchers to formally analyze patterns of necessity and sufficiency regarding outcomes of interest. Since its inception, QCA has developed into a broad set of techniques that share their set-analytic nature and include both descriptive and inferential techniques.

Many researchers have drawn on QCA because it offers a means to systematically analyze data sets with relatively few observations. In fact, QCA was originally developed for small- to medium-N situations with between 10 and 50 cases. In such situations there are frequently too many cases to pursue a classical qualitative approach but too few cases for conventional statistical analysis. However, more recently, researchers have also applied QCA to medium- and large-N situations marked by hundreds of thousands of cases. While these applications require some changes to how QCA is applied, they retain many advantages for analyzing situations that are configurational in nature and marked by causal complexity.

The goal of this workshop is to provide a ground-up introduction to Qualitative Comparative Analysis (QCA) and fuzzy sets. Participants will get intensive instruction in the method as well as hands-on experience with the fsQCA software package. On completion of the course, participants should be prepared to design and execute research projects using the set-analytic approach.

Specifically, after successful completion of you should be able to:
1. understand the goals, assumptions, and key concepts of QCA
2. conduct data analysis using the fsQCA software package
3. design and execute research projects using a set-analytic approach
4. apply advanced forms of set-analytic investigation


I would like this workshop to be as useful to you as possible. To get the most out of this workshop, you would ideally already be working on an empirical project that might be aided by taking a configurational approach, but that is not essential. Over the course of this workshop, I hope you will be thinking about how you can apply these methods to your research, and I will do my best to be of assistance.
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M

2024

Qualitative Comparative Analysis

Qualitative comparative analysis (QCA) is a research approach consisting of both an analytical technique and a conceptual perspective for researchers interested in studying configurational phenomena. QCA is particularly appropriate for the analysis of causally complex phenomena marked by multiple, conjunctural causation where multiple causes combine to bring about outcomes in complex ways.

QCA was developed in the 1980s by Charles Ragin, a sociologist and political scientist, as an alternative comparative approach that lies midway between the primarily qualitative, case-oriented approach and the primarily quantitative, variable-oriented approach, with the goal of bridging both by combining their advantages and tackling situations where causality is complex and conjunctural. QCA uses Boolean algebra for the analysis of set relations and allows researchers to formally analyze patterns of necessity and sufficiency regarding outcomes of interest. Since its inception, QCA has developed into a broad set of techniques that share their set-analytic nature and include both descriptive and inferential techniques.

Many researchers have drawn on QCA because it offers a means to systematically analyze data sets with relatively few observations. In fact, QCA was originally developed for small- to medium-N situations with between 10 and 50 cases. In such situations there are frequently too many cases to pursue a classical qualitative approach but too few cases for conventional statistical analysis. However, more recently, researchers have also applied QCA to medium- and large-N situations marked by hundreds of thousands of cases. While these applications require some changes to how QCA is applied, they retain many advantages for analyzing situations that are configurational in nature and marked by causal complexity.

The goal of this workshop is to provide a ground-up introduction to Qualitative Comparative Analysis (QCA) and fuzzy sets. Participants will get intensive instruction in the method as well as hands-on experience with the fsQCA software package. On completion of the course, participants should be prepared to design and execute research projects using the set-analytic approach.

Specifically, after successful completion of you should be able to:
1. understand the goals, assumptions, and key concepts of QCA
2. conduct data analysis using the fsQCA software package
3. design and execute research projects using a set-analytic approach
4. apply advanced forms of set-analytic investigation


I would like this workshop to be as useful to you as possible. To get the most out of this workshop, you would ideally already be working on an empirical project that might be aided by taking a configurational approach, but that is not essential. Over the course of this workshop, I hope you will be thinking about how you can apply these methods to your research, and I will do my best to be of assistance.
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