Human Capital in Public Research Laboratory: Towards an Alternative Evaluation and Prediction Method Based on Hybridization

The alternative proposed method aims to combine management accounting, precisely the activity-based system, and statistical tools to develop a method of assessing and predicting human capital within research laboratory. Statistical tools are Standardized Mean Difference, Hierarchical Cluster Analysis and Discriminant Analysis. The first normalizes the activities of the laboratory; the second classifies the results obtained, while the third standardizes these results by expressing them in terms of probability. The standardized scores are used for the computation and the prediction of human capital in research laboratories via activity regrouping center. The originality of this work is to fill a research gap in the field of hybridization in calculation and prediction of human capital by integrating the two disciplines mentioned above. Likewise, the originality of this work lies in the use of an activity-based accounting architecture to process outputs (and not costs) related to intangible aspects. The proposed method has research and social implications since it allows making appropriate research policy, adequate management control and improves organizational relations within the laboratory concerned. The findings show, through an illustration, the applicability of the proposed method and the usefulness of the tools used to do this.