Title: Soft skills fuzzy TOPSIS ranked multi-criteria to select project manager
Authors: Luciano Ferreira da Silva; Paulo Sergio Gonçalves de Oliveira; Gustavo Grander; Renato Penha; Flavio Santino Bizarrias
Addresses: Nove de Julho University – UNINOVE, Deputado Salvador Julianelli Street, s/n – First Floor, Barra Funda, São Paulo/SP, 01156-080, Brazil ' Anhembi Morumbi University, Casa do Ator Street, 275 – Vila Olímpia, São Paulo/SP, 04546-001, Brazil ' Nove de Julho University – UNINOVE, Deputado Salvador Julianelli Street, s/n – First Floor, Barra Funda, São Paulo/SP, 01156-080, Brazil ' Nove de Julho University – UNINOVE, Deputado Salvador Julianelli Street, s/n – First Floor, Barra Funda, São Paulo/SP, 01156-080, Brazil ' Nove de Julho University – UNINOVE, Deputado Salvador Julianelli Street, s/n – First Floor, Barra Funda, São Paulo/SP, 01156-080, Brazil
Abstract: This study aims to use fuzzy logic to select a project manager based on soft skills. In the first phase, a focus group interview was applied to establish the weights according to the soft skills list selected. In the second phase, the fuzzy TOPSIS logic was applied. According to the concept of the fuzzy TOPSIS, a closeness coefficient is defined to determine the ranking order of all alternatives. The results allowed the construction of the framework here called fuzzy TOPSIS ranked multi-criteria for selecting the best candidate according to the profile and criteria adopted. The contribution of this study is to allow the attribution of values to soft skills that, in essence, are subjectivity. This framework is friendly, the investment required is low, and it is adaptable to different contexts.
Keywords: fuzzy TOPSIS; multi-criteria decision; project manager selection; soft skill; human resources; competencies; competence; people management; project manager.
DOI: 10.1504/IJIDS.2024.136280
International Journal of Information and Decision Sciences, 2024 Vol.16 No.1, pp.19 - 45
Received: 15 Mar 2021
Accepted: 04 Jul 2021
Published online: 26 Jan 2024 *