| Author: | Wan, Pui-wah Peggy |
| Title: | The accuracy of quantity surveyor's pre-tender estimates for the HousingAuthority building projects |
| Degree: | M.Sc. |
| Year: | 1998 |
| Subject: | Building -- Estimates -- China -- Hong Kong Construction industry -- China -- Hong Kong -- Costs Hong Kong Polytechnic University -- Dissertations |
| Department: | Department of Building and Real Estate |
| Pages: | xi, 116 leaves : ill. ; 30 cm |
| Language: | English |
| Abstract: | The ability of estimator is perceived to be one of the most important factors that affect estimating accuracy (Skitmore 1990, Ogunlana 1991). This can be considered from both an individual and firm perspective. Flanagan and Norman (1983) and Morrison (1984) analyzed the performance of two Councils and seven quantity surveying offices in U. K. respectively. In developing these studies, the aim of the research is to analyze the accuracy level of the thirteen quantity surveying offices who undertake pre-tender estimate for the Housing Authority's projects through the variables of type of construction, size of work, complexity of work and market conditions. The individual and group performance (according to the Housing Authority banding system) has been considered. The estimating accuracy of the offices is also compared with previous studies from UK, Singapore and Hong Kong. A four-way classification system of quantity surveyors' estimating behaviour is developed according to the accuracy level in terms of mean deviation and coefficient of variation and the order of ranking is sensible estimator (low mean deviation and low coefficient of variation), biased estimator (high mean deviation and low coefficient of variation), inconsistent estimator (low mean deviation and high coefficient of variation) and silly estimator (high mean deviation and high coefficient of variation). In foundation contracts, seven offices are considered as sensible, one office is considered as biased and five offices are considered as silly. Their behaviour is dissimilar in building contracts in which five offices are sensible, another five offices are biased, one is inconsistent and two are silly. Office 2 can be considered as the best estimator among the thirteen quantity surveying offices for both foundation contracts and building contracts because the coefficients of lowest bids are closest to unity. The analysis indicates that the effect of contract size, complexity of projects, market conditions differ among offices in different type of construction works. The analysis according to the Housing Authority classification of quantity surveying offices shows that Band 1 offices are not performing as good as expected. Nevertheless, they are more accurate in estimating large non-standard projects for which they are more familiar with, whilst Band 4 offices are poor in estimating any size / complexity of projects. When the results of analysis are compared with other previous works in the field, it is interesting to find that the highest and lowest mean error / mean deviation are found in the current studies. All quantity surveying offices can achieve a high accuracy level in building contracts but poor accuracy level in foundation contracts. It is suspected that the highest values (i.e. the poorest result) for the foundation contracts is because of the design and build system, whilst the lowest values (i.e. the best result) for the building contracts is because they are highly repetitive in nature and with frequent tenders received which in turn provide sufficient feedback to the quantity surveyors in pre-tender estimating. The comparison also shows that Office 9's performance in Housing Authority's projects is better than the result of a previous similar analysis by Kwan (1996) on a mixed of development. This supports Ashworth and Skitmore's theory that project type and client affect estimating accuracy as well. In Flanagan & Norman's study, it shows that there is a positive correlation between estimate, number of bids and the lowest bid. In the current study, such relations are dissimilar among offices, i.e. some are positively correlated, some are negatively correlated, and some are not significant at all. |
| Rights: | All rights reserved |
| Access: | restricted access |
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| File | Description | Size | Format | |
|---|---|---|---|---|
| b14418782.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 3.66 MB | Adobe PDF | View/Open |
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