An MCDM project portfolio web-based DSS for sustainable strategic decision making in an electricity company
Abstract
Purpose
The purpose of this paper is to analyze the impacts of Portfolio size effect due to scaling issues in the outcome obtained in a project portfolio selection for an electricity company in Brazil, focusing on improving business strategic performance.
Design/methodology/approach
The study uses a web-based decision support system (DSS), in which scaling issues are considered, incorporating results of previous work. The study evaluates 32 projects from the electricity company and compared the possible results when considering different scales. Additionally, a sensitivity analysis was conducted to analyze the robustness of the case, using the web-based DSS.
Findings
The results for an interval scale context showed a portfolio with 21 projects, contrasting with the correct solution of a portfolio containing 23 projects. The latter is related to a ratio scale context, with the proper transformation of weights, which was found to be robust with a sensitivity analysis using Monte Carlo simulation. This demonstrates that only appropriate models for selecting projects can improve the contribution to the company’s permanent strategies of increasing productivity, considering its constraints to achieve optimal results.
Originality/value
Additive value functions approach imposes certain requirements on the measurement scales used for the items in a portfolio that should not be ignored, once they have significant impact on the general portfolio results, which are directly related to the business strategic performance and the facilities of doing that with a web-based DSS.
Keywords
Acknowledgements
This work is part of a research program funded by the Brazilian Research Council (CNPq) and FACEPE (Foundation for support of Research by the State of Pernambuco).
Citation
Martins, C.L., López, H.M.L., de Almeida, A.T., Almeida, J.A. and Bortoluzzi, M.B.d.O. (2017), "An MCDM project portfolio web-based DSS for sustainable strategic decision making in an electricity company", Industrial Management & Data Systems, Vol. 117 No. 7, pp. 1362-1375. https://doi.org/10.1108/IMDS-09-2016-0412
Publisher
:Emerald Publishing Limited
Copyright © 2017, Emerald Publishing Limited