R\&D evaluation methodology based on group-AHP with uncertainty
Abstract
In this paper, we present an approach to evaluate Research \& Development (R\&D) performance based on the Analytic Hierarchy Process (AHP) method. Through a set of questionnaires submitted to a team of experts, we single out a set of indicators needed for R\&D performance evaluation. The indicators, together with the corresponding criteria, form the basic hierarchical structure of the AHP method. The numerical values associated with all the indicators are then used to assign a score to a given R\&D project. In order to aggregate consistently the values taken on by the different indicators, we operate on them so that they are mapped to dimensionless quantities lying in a unit interval. This is achieved by employing the empirical Cumulative Density Function (CDF) for each of the indicators. We give a thorough discussion on how to assign a score to an R\&D project along with the corresponding uncertainty due to possible inconsistencies of the decision process. A particular example of R\&D performance is finally considered.
Keywords
Cite
@article{arxiv.2108.02595,
title = {R\&D evaluation methodology based on group-AHP with uncertainty},
author = {Alberto Garinei and Emanuele Piccioni and Massimiliano Proietti and Andrea Marini and Stefano Speziali and Marcello Marconi and Raffaella Di Sante and Sara Casaccia and Paolo Castellini and Milena Martarelli and Nicola Paone and Gian Marco Revel and Lorenzo Scalise and Marco Arnesano and Paolo Chiariotti and Roberto Montanini and Antonino Quattrocchi and Sergio Silvestri and Giorgio Ficco and Emanuele Rizzuto and Andrea Scorza and Matteo Lancini and Gianluca Rossi and Roberto Marsili and Emanuele Zappa and Salvatore Sciuto and Gaetano Vacca and Laura Fabbiano},
journal= {arXiv preprint arXiv:2108.02595},
year = {2021}
}
Comments
13 pages, 2 figures