Abstract
Various industrialized housing technologies were introduced to developing countries in the early 1950–1970s, volumetric (i.e. box), panelized units and tunnel-form are typical examples. These technologies lead to improvements in housing production, such as high turnover, improved productivity of both machines and labour, quick assembly and better quality of industrialized products. However, there are limitations for these technologies such as high production costs, application of heavy and large components, lack of standardization in design, and lack of consideration given to the local environment in choosing materials. Owing to the surging demands for housing, industrialization seems to be an inevitable trend in housing construction particularly for those densely populated cities like Chongqing. Thus, this paper aims to evaluate different innovative systems and determine the most suitable system(s) for the construction of industrialized housing in China, by using Chongqing as a case study. Six innovative housing systems have been considered in this study. These systems have been successfully adopted in major cities in the Chinese Mainland, using prefabrication of standardized components, which provide valuable reference to the undertaking of this study. An analytical hierarchy process (AHP) was adopted as a tool to determine the preferences of Chongqing practitioners in relation to the use of selected innovative housing systems. The finding has highlighted a practical and logical approach to identify the most appropriate industrialized housing system to be adopted in densely populated cities such as Chongqing, as well as promoting the implementation of industrialized housing system in other major cities in China.
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Acknowledgements
This study was founded by the Chongqing Science & Technology Commission (Project No. CSTC, 2008BB0067) and Chongqing Jiaotong University.
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Pan, Y., Wong, F.K.W., Hui, E.C.M. (2011). Application of Industrialized Housing System in China: A Chongqing Study. In: Wu, D. (eds) Modeling Risk Management in Sustainable Construction. Computational Risk Management. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15243-6_19
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DOI: https://doi.org/10.1007/978-3-642-15243-6_19
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