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Cited by 5Construction Project Management and PerformanceCapital Investment and Risk AnalysisExperimental Learning in Engineering

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Análisis cuantitativo de riesgos utilizando "MCSimulRisk" como herramienta didáctica

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Acebes Senovilla, Fernando, Curto Lorenzo, David, De Antón Heredero, Juan, Villafáñez Cardeñoso, Félix·2024·Dirección y Organización
DOI 10.37610/dyo.v0i82.662
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Abstract

Practical classes are an ideal and essential complement to theoretical classes. Risk Management, taught in the Master's Degree in Project Management at the University of Valladolid, mainly focuses on project uncertainty and quantitative risk analysis. To transmit the knowledge tangibly to the students, the theoretical classes are complemented with practical classes, where the students carry out exercises related to the subject taught, reinforcing the knowledge acquired. Quantitative risk analysis involves Monte Carlo simulation as the most appropriate method for dealing with project uncertainty. Our experience as teachers, teaching Monte Carlo simulation applied to quantitative risk analysis in projects for several years, helped us detect students' difficulties when using specific commercial software tools during the project modelling process. This fact motivated us to look for a solution to facilitate the student's work in class and help increase their learning. This led us to create the teaching software application called ‘MCSimulRisk’. In this article, we present the didactic tool 'MCSimulRisk' that we will use as a teaching tool to carry out Monte Carlo simulation and project control. ‘MCSimulRisk' was developed to solve the problems encountered by the students during the laboratory exercises after the experience acquired when using other commercial tools. The use of this tool is intended to (1) allow students to efficiently carry out Monte Carlo simulation for any project network, regardless of its complexity; (2) easily integrate into the model different types of uncertainty (aleatoric, stochastic, and epistemic one) that may affect the project objectives. In addition to the above, this tool should help research efforts by extending lines of research yet to be addressed in the literature to integrate different types of uncertainty.

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  • With the MCSimulRisk software, the impact of each risk on project duration objectives (quantified in time units) and cost objectives (quantified in monetary units) is determined.

    “With the help of the 'MCSimulRisk' simulation software (Acebes et al. 2024;Acebes et al. 2023), this paper determines the impact of each risk on project duration objectives (quantified in time units) and cost objectives (quantified in monetary units).”

    From Beyond probability-impact matrices in project risk management: A quantitative methodology for risk prioritisation (2024) · cites this paper as Acebes et al. 2024

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Research works printed but not linked: 27

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Metadata

Authors
Acebes Senovilla, F., Curto Lorenzo, D., De Antón Heredero, J., & Villafáñez Cardeñoso, F.
ORCID
Venue
Dirección y Organización
Publisher
Asociación para el Desarrollo de la Ingeniería de Organización
Published
2024-04-01
Pages
87-99
ISSN
  • 1132-175X (ISSN-L)
  • 2171-6323
DOI
10.37610/dyo.v0i82.662
OpenAlex
W4396836581
Cited by
5
References
0
Citations by year
2026: 4 · 2024: 1
FWCI
1.13
Type
journal article
Language
es
Open access
Licence
Locations
  • Dirección y Organización (publishedVersion, cc-by-nc-sa)
  • RePEc: Research Papers in Economics (submittedVersion)
  • arXiv (Cornell University) (submittedVersion, cc-by-nc-nd)
  • UVaDOC UVaDOC University of Valladolid Documentary Repository (University of Valladolid) (submittedVersion, cc-by-nc-nd)
  • arXiv (Cornell University)
Topics
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Construction Project Management and Performance
  • Social Sciences › Economics, Econometrics and Finance › Finance › Capital Investment and Risk Analysis
  • Social Sciences › Education › Experimental Learning in Engineering
Keywords
quantitative risk analysis, Monte Carlo simulation, educational software, project uncertainty, project risk management, project control, aleatoric uncertainty, epistemic uncertainty, project management education

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