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Study On Urban Residential Construction Project Cost Index

Posted on:2012-04-18Degree:MasterType:Thesis
Country:ChinaCandidate:L H LiaoFull Text:PDF
GTID:2189330335452106Subject:Architecture and Civil Engineering
Abstract/Summary:PDF Full Text Request
This work on urban residential construction project cost index is studied in this paper, which is based on "the notice about carrying out the measurement and issue of urban residential construction project cost information". The notice is made by the Ministry of Construction Standard Quota (No.19 [2008]).Construction cost index is very important for the construction relative units,In the feasibility study stage, project cost index provides the basis for determining the estimated investment, which is the main basis for decision-making owners.In the design stage, it can be used to calculate the estimated cost and provide a reliable reference cost for design-limited and making a reasonable choice of design.In the bidding stage, the tender can use the construction cost index to determine a reasonable bid price and can also avoid the phenomenon that the quoted price less than bid price, but winning bid. In the construction stage, construction cost index provides an important reference for working out budget cost and can give a quick judgment to the accuracy of budget cost.The construction project cost index of residential which occpuies the largest amount the urban construction projects is studied in this paper.Firstly, strating from the choice of index model, eight types of commonly used models are analyzed and compared in this paper. Ultimately Laspeyres and Paasche index model are selected as research tool. Author gives the calculation formula of the construction cost index model. Secondly, author brings forward a combination of qualitative analysis and quantitative analysis method for fixing the weight of the composite index; and then raises a comprehensive proposal for the collecting the information of construction cost. Finally,using prediction model carries on example forecast.The main contents include as follows:①The Selection of Index ModelA comprehensive comparison of the error, advantage and disadvantage among the eight types of index models which are simple index, simple arithmetic average index, Laspeyres index, Paasche index, ideal index, function index, socialist country index and covariation influence index is presented. Ultimately, the Laspeyres index and the Paasche index are selected in this paper.②The Formation of Construction Cost IndexConstruction cost index is divided into single index and the composite index, the formulas of the single index and the comprehensive index are provided in this paper.③The Ensure of Weight in Index ModelThe ensure of weight plays a decisive role in the formation of the composite index. However, the differences among construction projects make the ensure of the weight tend to stay in the subjective experience stage, which also is named qualitative analysis, a qualitative analysis and quantitative analysis method is presented in this paper, which is 1-9 Ratio scale method, also referred to as Ratio scale method, and a simple example is given in this paper.④The Collection Standard of Construction Cost InformationTo strengthen the monitoring and guidance of the construction cost on urban residential building, and standardize and harmonize the construction of urban residential building construction project cost information database, the Ministry of Construction Standard Quota formulates the "urban residential construction project cost information and data standard" (referred to as "data standard") and gives a uniform format and content, the content of the standard is analyzed and introduced in detail in this paper.⑤The Application of Prediction TheoryA comprehensive comparison about eight types of prediction methods is given in this paper. Finally, ARMA model and gray prediction model are selected for the application of practical example.
Keywords/Search Tags:index model, constructioncost index, weight, information collection standard, prediction theory
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