Fuzzy set ideal type analysis

• Published in: Journal of business research Vol. 60; no. 5; pp. 474 - 481
• Main Author: Kvist, Jon
• Format: Journal Article
• Language: English
• Published: New York Elsevier Inc 01.05.2007; Elsevier; Elsevier Sequoia S.A
• Series: Journal of Business Research
• Subjects: Case studies; Case study research; Concepts; Conceptualization; Empirical research; Fuzzy sets; Ideal types; Measurement; Research methods; Set theory; Statistical methods; Studies; Measurement; Fuzzy sets; Concepts; Case study research; Ideal types
• ISSN: 0148-2963; 1873-7978
• DOI: 10.1016/j.jbusres.2007.01.005

This article advances a new method for studying cases, fuzzy set ideal type analysis, which is a framework that allows a precise operationalization of theoretical concepts, the configuration of concepts into ideal types, and the categorisation of cases. In a Weberian sense, ideal types are analytical constructs for use as yardsticks for measuring the similarity and difference between concrete phenomena. Ideal type analysis involves differentiation of both categories and degrees of membership in such categories. In social science jargon, this analysis involves the evaluation of qualitative and quantitative differences or, in brief, of diversity. Fuzzy set theory provides a calculus of compatibility. Fuzzy set theory can measure and compute theoretical concepts and analytical constructs in a manner that remains true to their formulation and meaning. This article sets out elements and principles of fuzzy set theory relevant for ideal type analysis and demonstrates their usefulness in an example drawn from comparative welfare state research on the conformity of changing unemployment policies to predefined ideal typical models.