Prioritizing Management Action of Stricto Sensu Course: Data Analysis Supported by the k-means Algorithm

The challenge of balancing the benefits and pitfalls of adopting general or customized management strategies is always present. However, the planning effort must be sufficiently flexible because making judgments before complete and in-depth evaluation could mean making a decision too late. The management of a stricto sensu specialization course relies heavily on academic publication rates and citation counts, as is well known. In this study, we present and test a novel idea for cluster analysis using the k-means method and the creation of generic responses for the groups found. The SCOPUS platform of the 17 researchers who make up the faculty of a production engineering course in Brazil was examined for indicators over the previous ten years.