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Pay Grade Determination Using Cluster Analysis

The Hong Kong University of Science & Technology

This paper applied the cluster analysis technique to group jobs with similar value to the organization into pay grades. The cophenetic correlation was used to select the clustering algorithm that was most similar to the original data matrix. A modification of the total sum of squares within groups was used to determine the statistically optimal number of pay grades based on the selected cluster hierarchy. Applications and limitations of the approaches were dis cussed to guide practitioners.

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