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It has been noted in the literature that firms rarely follow a single theoretical model when designing their compensation policy. This study illustrates how a fuzzy cluster analysis can be helpful in understanding the way employees are rewarded according to firms' specificity and market conditions. For this purpose, we convert linked employer-employee data (LEED) into firm level data prior to fuzzy...
We use an information-theoretic criterion to assess the goodness-of-fit of the output of archetypal analysis (AA), also intended as a fuzzy clustering tool. It is an adaptation of an existing AIC-like measure to the specifics of AA. We test its effectiveness using artificial data and some data sets arising from real life problems. In most cases, the results achieved are similar to those provided by...
This empirical study extends the results of Hüllermeier, Rifqi, Henzgen, and Senge (2012). It examines the ability of a generalization of the Rand index and four related measures of similarity to recover the cluster structure of the data in the framework of fuzzy $c$-means clustering. The index range is also used as a criterion statistic. A Monte Carlo simulation is conducted for both the null case...
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