Estimating the Optimal Time for a Road Concession Contract in Brazil

Pivatto, Douglas; Fernandez, Rodrigo Nobre; Saulo, Helton; Carraro, André

doi:10.5539/ijef.v9n12p44

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…So, the analysis and modeling of risk leads to informed decisions for procurement the public works and services. Major risk variables of determination the optimal concession period are construction period (Tc), project development cost (NPV), market demand, sale price, project operation and maintenance costs, and discount rate (interest rate of retune and inflation rate) [21].…”

Section: Risks Affecting the Concession Periodmentioning

confidence: 99%

Determination a Reasonable Concession Period for (PPP) Projects

Hadi

Erzaij

2019

Civ Eng J

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Public Private Partnership (PPP) are agreements where public bodies enter into long term contractual with private entities for construction or management the public sector facilities, or provision services to the community. Internal rate of return (IRR), pay back regime or tariff, and the concession period (CP) are essential items to success (PPP) projects. This research presents a systematic approach for a win-win partnership contract determined on a quantitative basis, by informing the partnership parties how long contract period should be made. Essence of the proposed methodology is that project completion time should allow a competent contractor to complete the project on schedule and operation period should be long enough to enable the concessionaire to achieve a reasonable return, but not too long such that concessionaire’s return is excessive and public sector’s interests are sacrificed. A case study of a PPP project in Mayoralty of Baghdad was conducted to evaluate performance of the developed mathematical models. The determined concession period (CP) has found to be approximately equal to actual concession period (CP) granted to the private sector. Evaluation shows the possibility to adopt the proposed approach to determine the concession period (CP) more effectively. Instead of opportunism policy, the proposed methodology enables local government of Baghdad province to enhance its policies of awarding the partnership projects to increase private sector participation in infrastructure development. Finally, the proposed method can be used by investment practitioners as a decision support tool for contract concession period (CP), and is worth popularizing to design the contracted concession period (CCP) for partnership projects in Iraq, and also can use as a methodology to assess the critical aspects which related to partnership projects in general.

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Section: Risks Affecting the Concession Periodmentioning

confidence: 99%

Determination a Reasonable Concession Period for (PPP) Projects

Hadi

Erzaij

2019

Civ Eng J

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“…Road concessions have great autonomy and resources available to make the necessary investments. These scenarios, quite opposite to those of public authorities which face severe budgetary constraints, must comply with the legal criteria for hiring specialized companies to perform the services of road maintenance and conservation (Gaussmann et al, 2020;Pivatto et al, 2017). In order to regulate the legal criteria for public procurement in Brazil, Law 8,666 was sanctioned in 1993, which establishes that the procurement and acquisition of goods and services in the public sector must be carried out through the elaboration of a detailed budget of the desired object, and based on the reference price table adopted by the agency, the overall value of the acquisition or contracting is obtained (Pivatto et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Estimated Maintenance Costs of Brazilian Highways Using Machine Learning Algorithms

Gaussmann

Coelho

Fernandes

et al. 2020

J INFORM SYSTEMS ENG

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The road infrastructure is considered to be a key prerequisite of social and economic development of any country and therefore solutions that assist in the management and maintenance of this key infrastructure are important. This paper presents the application of Machine Learning algorithms, such as Multilayer Perceptron Neural Network and K-means for estimating the level of services required for highway conservation in Brazil. The data used is from the Federal District highways, recorded in the form of Service Orders in the Road Administration System, as well as the road solutions catalog elaborated from the price table of the Federal District Roads Department. A database was created containing data for routine maintenance history, road solutions catalog and price lists. The machine learning algorithms were applied and evaluated, and it was concluded that the K-means algorithm had the best performance for estimating the maintenance costs of Brazilian highways.

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