Understanding firms compensation policy using fuzzy sets

Abstract

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 clustering. Then, we explore the particular distribution of firms on the emerged fuzzy partition to sort them by compensation policy and, eventually, to examine the potential factors behind a specific option.