Title: A systematic comparison of multi-criteria decision making methods for the improvement of project portfolio management in complex organisations

Authors: Darius Danesh; Michael J. Ryan; Alireza Abbasi

Addresses: School of Engineering and Information Technology, University of New South Wales (UNSW), Sydney NSW 2052, Australia ' School of Engineering and Information Technology, University of New South Wales (UNSW), Sydney NSW 2052, Australia ' School of Engineering and Information Technology, University of New South Wales (UNSW), Sydney NSW 2052, Australia

Abstract: The successful delivery of organisational objectives is significantly linked to the effective collection of project portfolios. There are many different multi-criteria decision making (MCDM) methods available which can be used to calculate examine and select project portfolio management (PPM) decision options. However, finding the most suitable one is a challenging task which requires a constructive review and comparison of existing PPM MCDM approaches. This study identifies the strengths and weaknesses of MCDM methods for assisting in PPM decision making. Of more than 100 methods identified in more than 1,400 publications, eight [analytic hierarchy process (AHP), analytic network process (ANP), data envelopment analysis (DEA), dominance-based rough set approach (DRSA), elimination and choice expressing the reality (ELECTRE), preference-ranking organisation method for enrichment evaluations (PROMETHEE), technique for order preference by similarity to ideal solution (TOPSIS), and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR)] that best suit PPM are down-selected and compared. Although none is ideally suited for the application to portfolio management, two standard ones (AHP and DEA) are shown to be the most suitable and are recommended for the further investigation and validation.

Keywords: project portfolio management; PPM; multi-criteria decision making; MCDM; MCDM comparison; decision making.

DOI: 10.1504/IJMDM.2017.085638

International Journal of Management and Decision Making, 2017 Vol.16 No.3, pp.280 - 320

Received: 27 Jan 2017
Accepted: 21 Mar 2017

Published online: 03 Aug 2017 *

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