Thijssen, Jacco orcid.org/0000-0001-6207-5647 (2022) Optimal Investment and Abandonment Decisions for Projects with Construction Uncertainty. European Journal of Operational Research. pp. 368-379. ISSN 0377-2217
Abstract
A model of investment in projects with uncertain construction time is presented in which both the cashflows upon completion and construction progress are modeled as diffusions. The decision maker has three sequential options: (i) to start construction, (ii) to abandon the project during construction, and (ii) to start operations or abandon after completion. Existence of a solution and some of its qualitative properties are proved. A Markov-chain approximation is used to numerically approximate the solution is introduced. The model is applied to a real-world railway project for which it is found that it does not represent value for money (VfM) and is unlikely to do so in the next decade. A comparative statics analysis reveals that the presence of an abandonment option can increase project value substantially and can speed up investment. Finally, it is argued that the commonly-used benefit-to-cost ratio (BCR) is not an appropriate measure to summarize a project’s VfM. Instead, the value ratio (VR) is suggested as an alternative.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 Elsevier B.V. All rights reserved. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Mathematics (York) The University of York > Faculty of Social Sciences (York) > The York Management School |
Depositing User: | Pure (York) |
Date Deposited: | 02 Jul 2021 09:20 |
Last Modified: | 02 Apr 2025 23:22 |
Published Version: | https://doi.org/10.1016/j.ejor.2021.07.003 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1016/j.ejor.2021.07.003 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:175837 |