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Ruud Bråten, V. (2019) Risk Management in the Infrastructure Industry How Can Monte Carlo Simulations Reduce Uncertainty in Infrastructure Projects?. Göteborg : Chalmers University of Technology (Master thesis. E - Department of Technology Management and Economics, Chalmers University of Technology, Göteborg, Sweden, nr: E2019:001).
BibTeX
@mastersthesis{
Ruud Bråten2019,
author={Ruud Bråten, Vetle},
title={Risk Management in the Infrastructure Industry How Can Monte Carlo Simulations Reduce Uncertainty in Infrastructure Projects?},
abstract={The infrastructure industry is known for underestimating project risks. Monte Carlo simulation is a probabilistic risk analysis method that can quantify consequences of risks but is not frequently used in the infrastructure industry even though the method has been available for decades. The aim of this thesis was to investigate to what extent Monte Carlo simulations are used and how these simulations can be implemented into the risk management process in the Swedish infrastructure industry. The thesis is based on a literature study and an interview study with five consultants and three experts from the Swedish Transport Administration.
The main findings are that Monte Carlo simulations seldom are used in the Swedish infrastructure industry today and that there is a difference between consultants and clients in perception of the benefits of Monte Carlo simulations. Consultants mostly appreciate the Monte Carlo method while the government client experts do not believe the benefits outweigh the added costs. Furthermore, the study indicates that Monte Carlo simulations can improve the risk management process by clearly visualizing and communicating risks to project participants, and that it should be possible to implement Monte Carlo simulations in many projects even without extensive knowledge of the method.},
publisher={Institutionen för teknikens ekonomi och organisation, Service Management and Logistics, Chalmers tekniska högskola},
place={Göteborg},
year={2019},
series={Master thesis. E - Department of Technology Management and Economics, Chalmers University of Technology, Göteborg, Sweden, no: E2019:001},
keywords={risk, risk management, risk analysis, Monte Carlo simulation, Monte Carlo method},
note={47},
}
RefWorks
RT Generic
SR Electronic
ID 256468
A1 Ruud Bråten, Vetle
T1 Risk Management in the Infrastructure Industry How Can Monte Carlo Simulations Reduce Uncertainty in Infrastructure Projects?
YR 2019
AB The infrastructure industry is known for underestimating project risks. Monte Carlo simulation is a probabilistic risk analysis method that can quantify consequences of risks but is not frequently used in the infrastructure industry even though the method has been available for decades. The aim of this thesis was to investigate to what extent Monte Carlo simulations are used and how these simulations can be implemented into the risk management process in the Swedish infrastructure industry. The thesis is based on a literature study and an interview study with five consultants and three experts from the Swedish Transport Administration.
The main findings are that Monte Carlo simulations seldom are used in the Swedish infrastructure industry today and that there is a difference between consultants and clients in perception of the benefits of Monte Carlo simulations. Consultants mostly appreciate the Monte Carlo method while the government client experts do not believe the benefits outweigh the added costs. Furthermore, the study indicates that Monte Carlo simulations can improve the risk management process by clearly visualizing and communicating risks to project participants, and that it should be possible to implement Monte Carlo simulations in many projects even without extensive knowledge of the method.
PB Institutionen för teknikens ekonomi och organisation, Service Management and Logistics, Chalmers tekniska högskola,
T3 Master thesis. E - Department of Technology Management and Economics, Chalmers University of Technology, Göteborg, Sweden, no: E2019:001
LA eng
LK http://publications.lib.chalmers.se/records/fulltext/256468/256468.pdf
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