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Title: Study of important factors affecting final account settlement satisfaction of Hong Kong civil engineering projects : contractor's perspective
Other Titles: Cong cheng jian shang de guan dian, yan jiu ying xiang Xianggang tu mu gong cheng de gong cheng jie suan man yi cheng du de zhong yao yin su
從承建商的觀點 , 究影響香港土木工程的工程結算滿意程度的重要因素
Authors: Kwok, Chi Ko (郭志高)
Department: Department of Building and Construction
Degree: Engineering Doctorate
Issue Date: 2009
Publisher: City University of Hong Kong
Subjects: Construction projects -- China -- Hong Kong -- Evaluation.
Notes: CityU Call Number: TH438 .K84 2009
xiv, 253 leaves 30 cm.
Thesis (Eng.D.)--City University of Hong Kong, 2009.
Includes bibliographical references (leaves 189-202)
Type: thesis
Abstract: Construction projects generally comprise four stages, namely, design/planning stage, tender stage, construction stage and final account / defect liability stage. The role and performance of various project participants and contracting parties in a construction project can in each stage influence the project success. Whilst many research studies addressed construction projects performance by examining critical factors to the project success or failure, most of them focused on construction stage with little attention to final account stage. In fact, the backlogs in settlement of Final Account have existed for decades and the important factors significantly affecting settlement of Final Account of construction projects are, among other things, largely founded as Project-related, Contractor-related and Engineer-related. These factors usually attract less attention and priority by project participants and contracting parties in the less pressing final account stage. Undue protracted inaction makes settlement of Final Account more difficult and frequently gives rise to dispute unnecessarily. This research adopts the technique of Multivariate Discriminant Analysis (MDA) to identify the most influential factors affecting the settlement of Final Account. The factors selected for use in the MDA modelling were determined by a pilot study involving face-to-face structured interviews with fellow practitioners who commented the variables identified from rigorous literature review and verified the sustainability of the questionnaire. Independent interviews were also conducted with construction professionals from senior management level of Group C civil engineering contractors, thus bringing into the research independent valuable views. The data were collected through questionnaire survey on civil engineering projects completed by Group C contractors in past ten years, where Final Account was settled or not yet settled. Final account settlement satisfaction is considered as favourable if that final account was achieved on time, i.e. within the prescribed time frame, otherwise it is considered as adverse if it was achieved beyond the prescribed time frame. The main objectives of this research are to identify, through in-depth investigation and exploration, important attributes that can clearly distinguish between on-time settlement and delayed settlement of final account projects, and to develop a quantitative model for prediction of the same. With the use of 108 project data sets and the MDA technique, a discriminant function was derived to classify final account projects into favourable final account settlement satisfaction (on-time settlement) and adverse final account settlement satisfaction (delayed settlement). The research problems as presented corresponded to the classification and prediction ability of MDA and as a result five (5) discriminating variables were identified out of thirteen (13) selected variables. These five discriminating variables are:  Contractor’s organizational approach  Contractor’s employment of consultant  Contractor’s resources allocated to the Final Account project  Engineer’s process of assessment /agreement  Engineer’s resources allocated to the Final Account project A Relative Important Index (RII) study was conducted to further verify and compare the importance of the above critical variables. The classification result of the hold out samples was same as the classification result performed by the discriminant function, which gave an accuracy of 100 % on the hold out samples.
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