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ISSN (print) 1136-0593 · ISSN (online) 2445-4192

A fuzzy decision support system to identify establishments with low paid employees in the british economy

Malcolm J. Beynon, Keith Whitfield. Cardiff University


Enforcing compliance with the National Minimum Wage (NMW) in the British economy requires the identification of those establishments that are likely to pay a substantial proportion of their employees less than the NMW. In this paper, a fuzzy decision support system is constructed to aid in the elucidation of such an establishment and their proportion of employees paid less than the NMW. Moreover, through an inductive fuzzy decision tree approach, a set of fuzzy rules enables the prediction of this proportion value. These fuzzy rules allow a more human linguistic approach to the problem, which can be interpreted by non-technical individuals whose role it is to target certain establishments for further inspection. Through a semi-automated procedure for the construction of the fuzzy set theory related membership functions, the whole process mitigates the need for the influence of subjective expert opinion. With rule description and a comparison to multivariate discriminant analysis models, these fuzzy rules are shown to be an appropriate tool for the elicitation of establishments not in compliance with the NMW.



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