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This paper proposes selecting a construction project portfolio in the context of a public institution, which makes it possible to assess quantitative and qualitative criteria, thereby meeting the needs of the institution and the existing constraints.

The research design follows a framework using technique for order preference by similarity to ideal solution (TOPSIS) associated with integer linear programming.

The method involves a flow of assessments allowing criteria and weights to be elicited where outcomes are based on the experts' intra-criteria assessment of alternatives and decision-makers' inter-criteria assessment. This is of utmost interest to public organizations, where selections must result in benefits and lower costs, integrating the experts' technical and management perspectives.

Public institutions are characterized by having limited financial and personnel resources for project development despite having a high demand for requests not associated with profits, making it essential to have a framework that enables using multiple criteria to better evaluate the benefits related to these decisions.

The main contributions of this article are: (1) the proposition of a framework for selecting construction project portfolios considering the organization's strategic needs; (2) identifying quantitative and qualitative assessment criteria for project selection; (3) integrating TOPSIS with an optimization process for selecting the construction project portfolios and (4) providing a structured decision process for selecting the portfolio that best represents the interests of the institution within its limited resources and personnel.

The purpose of this paper is to propose a supply chain risk management (SCRM) maturity model combined with a fuzzy TOPSIS classification method to evaluate and sort an organization into a pre-defined maturity level.

An axiomatic and prescriptive research method guided this study. Therefore, it proposes a prescriptive approach of maturity classification based on a theoretical SCRM maturity model combined with a multi-criteria decision technique.

The results of a pilot application indicated a consistent classification and the value of the model for diagnosing flaws and pointing directions for improving operational and disruption risk management. Its comprehensiveness allows applying it to supply chains of several industry sectors.

The proposed model does not include all possible risks and could be revised in further developments. Also, adjustment of the maturity profiles of the multi-criteria decision-making (MCDM) model requires a learning process from practical applications.

The adoption of the risk management maturity grid by practitioners may bring the benefit of a more objective and comprehensive evaluation of risk management processes in the supply chain context.

An immediate social implication derives from the improvement actions that may result from the diagnosis of risk management vulnerabilities identified in the pilot application. In general, the proposed model has the potential to reduce risks, improve results and contribute to economic sustainability.

The maturity grid and decision model integrate overall aspects of risk management, bringing together managerial concepts to deal with a variety of supply chain operational risks. The combined multi-criteria classification procedure to sort the maturity level of an organization is also a novelty.

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.

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.

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.

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.