Title: Multi-criteria model for selecting project managers in the public sector

Authors: Fernando Escobar; João Varajão; Nilton Takagi; Ulysses Almeida Neto

Addresses: University of Brasília (UnB), Departamento de Ciência da Computação, CIC, Campus Darcy Ribeiro, Asa Norte, 70910-900, Brasília, DF, Brazil ' Department of Information Systems and ALGORITMI Research Centre, School of Engineering, University of Minho, Campus de Azurém, 4804-533 Guimarães, Portugal ' Federal University of Mato Grosso – UFMT, Av. Fernando Corrêa da Costa, nº 2367, Boa Esperança, 78060-900 – Cuiabá, MT, Brazil; Department of Information Systems and ALGORITMI Research Centre, School of Engineering, University of Minho, Campus de Azurém, 4804-533 Guimarães, Portugal ' Kemmy Business School, University of Limerick, Limerick V94 T9PX, Ireland

Abstract: To assure effectiveness in the management of projects, it is required that project managers have the right competencies, according to the context and characteristics of each project they are involved. Based on several competencies frameworks (including PMI's PMCDF, IPMA's ICB, APM's CF, and AIPM's PCSPM), this paper proposes a unified multi-criteria model to be used as a decision-making tool for selecting the most suitable managers and defining competencies pathways for public sector projects. A hierarchical structure comprising weighted elements related to behavioural, management, and contextual/organisational competencies is proposed. For researchers, the presented model of competencies enables a better understanding of the phenomenon and can be used to structure further research in other contexts than the public sector. It is also a valuable tool for practitioners and project management offices since it allows comparing the candidates for managing a project using an organised and rigorous process anchored on empirically well-grounded criteria.

Keywords: project manager; project management; selection; decision; analytic hierarchical process; AHP; competencies; frameworks; public sector; Brazil.

DOI: 10.1504/IJIDS.2022.125168

International Journal of Information and Decision Sciences, 2022 Vol.14 No.3, pp.205 - 242

Received: 06 May 2020
Accepted: 23 Sep 2020
Published online: 01 Sep 2022 *

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