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Fuzzy set ideal type analysis
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DOI：10.1016/j.jbusres.2007.01.005.png)
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Abstract
En 中文
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. (c) 2007 Elsevier Inc. All rights reserved.
Keywords:
case study research
measurement
fuzzy sets
concepts
ideal types
Journal
IF:
9.8
Papers:
1.0W
Citations:
8.7W
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