dc.contributor.author |
Russell, AD |
|
dc.contributor.author |
Ranasinghe, M |
|
dc.date.accessioned |
2023-02-03T06:59:52Z |
|
dc.date.available |
2023-02-03T06:59:52Z |
|
dc.date.issued |
1992 |
|
dc.identifier.citation |
Russell, A. D., & Ranasinghe ∗, M. (1992). Analytical approach for economic risk quantification of large engineering projects. Construction Management and Economics, 10(4), 277–301. https://doi.org/10.1080/01446199200000027 |
en_US |
dc.identifier.uri |
http://dl.lib.uom.lk/handle/123/20364 |
|
dc.description.abstract |
A consistent,four moment based approach for quantifying time and economic risks is presented. The goal is to produce a computationally efficient tool that can be used to explore economic feasibility and tradeoffs between cost and time performance versus risk as a function of various strategies for executing and sequencing major work packages. A three level hierarchy of parameters is used, starting with time, cost and revenue performance at the work package/revenue stream level to rate of return at the overall project level. Use of a four moment approach and Pearson distributions at all levels of the hierarchy permit the formulation of a consistent and readily automated approach to risk measurement. Treatment of correlations is included. A modified form of PNET is presented for quantifying time uncertainty. Use of limiting values (0, 1) of the PNET transitional correlation provide bounds for decision parameters. |
en_US |
dc.language.iso |
en_US |
en_US |
dc.publisher |
Taylor and Francis |
en_US |
dc.subject |
Economic risk quantification |
en_US |
dc.subject |
large engineering projects |
en_US |
dc.subject |
probability analysis |
en_US |
dc.subject |
moment analysis |
en_US |
dc.subject |
Pearson distributions |
en_US |
dc.title |
Analytical approach for economic risk quantification of large engineering projects |
en_US |
dc.type |
Article-Full-text |
en_US |
dc.identifier.year |
1992 |
en_US |
dc.identifier.journal |
Construction Management and Economics |
en_US |
dc.identifier.issue |
04 |
en_US |
dc.identifier.volume |
10 |
en_US |
dc.identifier.database |
Taylor & Francis Online |
en_US |
dc.identifier.pgnos |
277-301 |
en_US |
dc.identifier.doi |
https://doi.org/10.1080/01446199200000027 |
en_US |