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.
Considering the increasing scenario of natural gas consumption, it is necessary that all agents in the chain use methods that structure decision-making and problem-solving processes. This paper proposes a multicriteria decision model to solve a site selection problem for a pressure reducing station. A natural gas distribution company was selected to test the model and the preference modeling was conducted through the flexible interactive tradeoff (FITradeoff) approach, according to the preferences of the decision maker (DM). FITradeoff's decision support system was used to assess the alternatives of the model, through the inference of the criteria scale constants. The results proved the robustness of the model and the DM evidenced consistency in its preferences. Also, the FITradeoff method demonstrated to be intuitive to apply, since a smaller effort is required from the DM and this is because the procedure does not require complete information in the scale constants elicitation process.
Organizational climate impacts on the employee’s well-being, commitment and positive behavior. Most studies to assess climate in healthcare organizations use qualitative and/or statistical methods. Here, we propose a general framework, based on a multiple criteria decision making/aid (MCDM / A) method, which considers different objectives in a single problem. Such framework includes internal and external factors to assess organizational climate and presented adequate results when tested in a particular case. To assess the organizational climate, we use the ELECTRE TRI method, an outranking method that combine the decision-maker (DM) preferences and his value judgments. We conclude that MCDM methods can improve agility, provide a systemic vision on organizational climate assessment and contribute to the decision-making process
This study aims to demonstrate how the design of a decision support system (DSS) can improve the process of internal resource allocation in Brazil public universities. Currently, there are not any kind of general DSS for such a problem. To do so, the analysis is carried out by identifying the general model from the Brazilian Ministry of Education and the models from every federal university, finding similarities between each model, and dividing the models into categories, according to their similarities. Thus, a DSS resource allocation model prototype was proposed. The perspectives are to contribute to the decision problem of how to allocate resources properly faced by Brazilians public universities, take safer and reliable decisions, seeking to reduce uncertainties and to maximize their results.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.