Methods for quantitative risks analysis of cost and deadline overruns in complex projects

Urgilés, Paúl T; Gil, Juan Claver; Sebastián, Miguel Ángel

doi:10.1016/j.promfg.2019.09.055

Cited by 4 publications

(3 citation statements)

References 11 publications

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“…Stochastic Simulation gives useful insights about the main drivers of the outcome of analysis (e.g., profit, costs, Net Present Value etc.). This technique is widely present in the literature as a tool to help create budgets in the field of Project Management applied to construction projects (Urgilés, Claver, and Sebastián 2019) or as a capital budgeting tool (Platon and Constantinescu 2014). Nevertheless, the literature about the application of Monte Carlo Simulation in modelling the primal financial budget of a company is scarce (Hager, Yadavalli, and Webber-Youngman 2015).…”

Section: Budgeting Under Uncertainty and Application Of Monte Carlo S...mentioning

confidence: 99%

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Assessing Budget Risk with Monte Carlo and Time Series Bootstrap

Pereira

Gomes

2023

UPjeng

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Budgets are important management tools recognized for their help in planning, communication, monitoring the expense performance, and even motivating collaborators. However, recently there has been criticism of the traditional Budgeting Process due to its cumbersomeness, long duration, and eventual diversion of the focus from the day-to-day activities. Thus, improving the Budgeting Process by incorporating Expense component uncertainties is of uttermost importance to accelerate its approval. This paper presents a methodology for companies to assess their budget risk based on their historical Expense data by applying Monte Carlo Simulation and Time Series Bootstrapping Techniques. Besides, some state-of-the-art sensitivity Importance Measures are also implemented to help evaluate the relative importance of the Expense components. The methodology proposed, based on a real case study with data from a major Portuguese retailer, has the advantage of being objective and supported by data, thus not being subject to bias from the management.

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Section: Budgeting Under Uncertainty and Application Of Monte Carlo S...mentioning

confidence: 99%

“…Assumes specific distributions. Urgilés, Claver, and Sebastián (2019) Typical Project Management study of assessing Budget Risk of a specific project.…”

Section: Studymentioning

confidence: 99%

Assessing Budget Risk with Monte Carlo and Time Series Bootstrap

Pereira

Gomes

2023

UPjeng

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“…Spanish researchers Urgilés et al (2019) propose a method that make quantitative risks analysis of cost and deadline overruns for hydroelectric project in the Republic of Ecuador by constructing a stochastic simulation model. As result of the case study, they determine rank and probability of risk which can cause overcost and deadline extension [13].…”

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confidence: 99%

A Novel Project Risk Assessment Method Development via AHP-TOPSIS Hybrid Algorithm

Baylan

2020

Emerg Sci J

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In project planning, risk assessment method plays vital role. Poorly assessed project risks cause degeneration at project cost, project completion time, and project output quality and project scope. Each project activity risk influence these project success factors. Implementation performance of a project activity triggers or smooth of its successor’s activity risks. Because of this; employing robust and detailed risk assessment methods is important to reach those project goals. In project risk assessment literature, when it is investigated, it is noticed that risk assessment and evaluation methods are only developed at whole project level. Actually, they are not comprehensive enough to evaluate the project risks at activity level. Besides that traditional risk assessment methods such as risk matrix does not able analyze project risk quantitatively. With this motivation, main aim of this study is developing a multi-criteria based decision method which prioritizing project risks at activity level. AHP and TOPSIS method are combined to developed novel method. In this hybrid method, Constructing AHP model is to prioritize work packages with respect to relative importance of project time, project output quality and project cost. Broken down structure of these work packages are used as input for weighted criteria for TOPSIS method. In second layer of this decision method, TOPSIS model is used for prioritizing predetermined activity risks according weighted project work packages success criteria. In the application of this method, a case study approach is followed. In this sense, “Global Furniture Ltd.” which is established in Istanbul, Turkey is chosen as a case to apply newly developed model. Results showed that application of AHP-Stochastic TOPSIS Hybrid Algorithm provides a platform that project risks could be analyzed as quantitative and also at project activity level.

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