Positive Research On The Price And Cost Of Residential Construction In China

The decision-making and design of the(housing) products prior toimplementationdetermine not only the sales price and cost, but also the success of the project.Due to the difference betweendomestic and international projects in the management pattern and the environment, the price /cost composition and their influencing factors of residential projects is varied. In the practical operation of cost management in Chinese residential projects, cost managementis often limited to the main contractor during the construction phase while cost management in the design and decision-making stage is neglected. In addition, because of the uncertainty in the administration authority of the project owners as well as the singular characteristics of construction engineering, the cost composition of construction project is complicated.What’s more, the lack of communication and contact between the cost management and investment management caused that in the in the late phase of construction, cost reduction can only be realized by reducing the material quality and standards. Therefore, management should take full account of the quantitative relationship between the management of the construction project cost management and investment prior to the implementation stage. Obviously, in order to achieve the above goal, it is necessary to establish forecast model of price and cost based on product features. However, due to the scarcity of basic data on cost composition prediction, collection and processing of project cost data is the focus of the present study.In this paper, based on the cost management theory, statistical theory, and statistical analysis theory, taking theprice and construction cost of 57 commercial housing projects in Zhengzhou as the subject of research, the relationship between residential project features and cost/price was investigated;focused on the residential character, cost management and corresponding control process and valuation methods in the design stage were proposed; and by establishing relationships between housing characteristics and cost/price, a method ofcontrolling residential project cost was discussed. Most importantly, in the practical study on the price and cost of residential projects, the collected data was analyzed systematically with statistical theory, which not only provides powerful ground for the valuation method and theory of engineering cost, but also fills the gaps in the empirical data of domestic engineering research theory and method for cost prediction.The main content of the present research work includes the following aspects: 1.Apart from the introduction of TCM and LCC into the entire process cost management theory, taking the retailing price of housing projects into consideration in the housing characteristics index system, the concept of cost management based on the housing characteristics in the design and decision-making stage was proposed. In that way, the feature design of housing products is able to be controlled by the retailing price, thus ensuring the implementation of cost management on the premise of success of project investment. 2. With the help of fuzzy mathematics comprehensive evaluation method, the residential housing index system that influencesthe housing price and engineering cost was established, and through the sample data and the characteristic index system to collect to predict reasonable housing price. Through collected housing price data and based on the index system, reasonable housing price was predicted. The establishment of residential housing price prediction model based on the housing features is the key to the cost management in the decision-making and design stage. Therefore, the design and implementation of residential projects are solely dependent upon the retail price of the housing, to avoid the imbalance of cost distribution. 3. The author collected, processedand analyzedthe engineering cost data in a systematical way, and established the standard of collecting and processing residential project cost, which improved the situation in which there was lacking of verified data of engineering cost. 4.The data were collected and analyzed statistically, and singular points were removed in order to make prediction and establish the relationship between cost and features of housing projects.Through the comparative analysis, partial least squares can well explain the fitted model between the cost and the characteristic, the prediction ability and weight of features on the cost, and it was proved a good method tomake quick prediction of the project cost in the design evaluation.