R\&D evaluation methodology based on group-AHP with uncertainty

TL;DR

This paper introduces a novel R&D evaluation methodology using group-AHP combined with uncertainty analysis, employing expert questionnaires and empirical CDFs to score projects and account for decision inconsistencies.

Contribution

It presents a new R&D performance evaluation approach integrating group-AHP with uncertainty quantification through empirical CDFs, enhancing decision accuracy.

Findings

Effective scoring of R&D projects using AHP and empirical CDFs.

Inclusion of uncertainty analysis improves evaluation robustness.

Application example demonstrates practical utility.

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.