R&D project portfolio selection using the Iterative Trichotomic Approach in order to study how subjectivity of the weights is reflected in the selected projects of the final portfolio

Abstract

Project portfolio selection is a common problem in modern organizations. The allocation of resources to projects taking into account (a) the multi-criteria evaluation of projects and (b) the policy requirements for the final portfolio, is often addressed with a combination of multi-criteria analysis for the evaluation part and integer programming for the optimization part. However, the final portfolio is sensitive to changes in the importance of criteria, due to the multi-criteria evaluation of the projects which is the driver of the optimization. In the proposed approach, we take into account the inherent subjectivity expressed in the weights of criteria using a variation of the Iterative Trichotomic Approach method (Mavrotas and Pechak in Int J Mult Criteria Decis Mak 3:79–97, 2013). Specifically, we use an iterative process that starts considering portfolios that emerge from optimizing separately each criterion and gradually converging to the original set of criteria weights. The additional information provided to the decision maker by the proposed method, is that she/he can realize if the selection or exclusion of a specific project in the final portfolio is objective or it depends on the subjective weights and to what extent, while the conventional MCDA-IP approach does not differentiate the selected projects according to the imposed degree of subjectivity. The method is illustrated with a real data application from a project portfolio selection problem in Greece with 540 R&D projects that have to follow sectoral and geographical constraints.