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Decision making in life cycle costing

Feddon, H; (2006) Decision making in life cycle costing. Doctoral thesis , UCL (University College London). Green open access

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There has been increasing demand by clients the construction industry to understand the Life Cycle Costs (LCC) of their projects. This report establishes that the formation of LCC forecasts requires decision-making by the LCC consultants where not all information is available, or all of the variables known. The LCC consultant is required to make rational decisions based on professional judgement The appliance of various theories is discussed and it is established that Behavioural Theory, rather than Preference Theory, can be better used to understand the decisions make by the LCC consultant Inherent to decision-making is the perception of risk. The application of Behavioural Theory requires risk to be assessed in a non-quantitative manner. There are difficulties both for the LCC consultant in methodically analysing the risk and to the client in understanding where that risk exists in the LCC forecast In order to provide a greater understanding of where the risk exists in the LCC forecast this report analysis each of those variables which requires decision-making by the LCC Consultant. The sensitivity of the forecast to changes in the LCC forecast is undertaken in the context of total 'real' cost and net present value. The study found the LCC forecast was sensitive to the following variables in descending order Component Life, Sub-Component Life, Quantity of Replacement, Uplift Cost This proves the reports hypothesis, which was that the Component Life and Sub-Component Life were most sensitive, correct. Recommendations are that this analysis is applied to a wider range of building types, that LCC consultants gain awareness of the risks associated with decision making, and that there be a case study using emerging decision-making techniques in LCC.

Type: Thesis (Doctoral)
Title: Decision making in life cycle costing
Open access status: An open access version is available from UCL Discovery
Language: English
Additional information: Thesis digitised by ProQuest.
UCL classification:
URI: https://discovery.ucl.ac.uk/id/eprint/1568116
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