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Please use this identifier to cite or link to this item: http://hdl.handle.net/2031/4588

Title: Bidding strategy using multivariate distribution and EM algorithm
Other Titles: Li yong duo yuan fen bu ji EM fang fa de jing biao ce l{uml}ue
利用多元分佈及 EM 方法的競標策略
Authors: Lam, Ma Li (林瑪莉)
Department: Dept. of Management Sciences
Degree: Master of Philosophy
Issue Date: 2004
Publisher: City University of Hong Kong
Subjects: Construction contracts -- China -- Hong Kong
Expectation-maximization algorithms
Letting of contracts -- China -- Hong Kong
Multivariate analysis
Notes: 100 leaves : ill. ; 30 cm.
CityU Call Number: TH435.L36 2004
Includes bibliographical references (leaves 72-75)
Thesis (M.Phil.)--City University of Hong Kong, 2004
Type: Thesis
Abstract: In many industries, a sizeable proportion of business is obtained through competitive sealed bidding. Construction contracts are a typical example of this. In Hong Kong, construction industry is a major business and there are more than ten thousand registered construction companies. The best way to allocate construction projects to construction companies is by using competitive sealed bidding. Each bidding contractor determines a bidding price based on a cost-plus method. Once the contractor’s cost is estimated, a mark-up as a percentage of the cost is added, and the sum is the tender price. The difficulty facing a competing contractor is in setting the tender price at an appropriate level. A contractor may lose to the competition if his tender is overstated. On the other hand, the project will not be profitable if the tender price is too low. Therefore, the development of a successful bidding strategy is a key factor in the survival of construction companies. Two major criticisms of most bidding strategies are that they use a single distribution with fixed parameters to model the bidding patterns and assume independence of bids among competitors. In this study, a generalized bidding model is proposed to answer these two criticisms by developing realistic multivariate distributions. Instead of assuming a fixed bidding pattern for all contractors, the study estimates bidding patterns and applies them to the bidding model. The EM algorithm will also be used to estimate the covariances of bids by pairs of contractors. Multivariate distribution can be formed once the covariances are determined. Using multivariate distributions, the probabilities of winning and the corresponding mark-ups for projects can be determined by numerical integrations.
Online Catalog Link: http://lib.cityu.edu.hk/record=b1929050
Appears in Collections:MS - Master of Philosophy

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