اتخاذ مسکن پیش ساخته ؛ نقش زمینه ای کشور
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|69177||2016||10 صفحه PDF||سفارش دهید||6510 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Sustainable Cities and Society, Volume 22, April 2016, Pages 126–135
This exploratory paper examines secondary sources to develop hypotheses for future testing in quantitative research, around the question ‘How do housing industry contexts in different countries influence the adoption of prefabricated housing construction?’ This is a management study of innovation adoption. Prefabricated housing has been routinely promoted as a means to improve the efficiency, quality and environmental performance of house construction, use and demolition. The uptake of prefabrication internationally has not however been consistent, with a clear division between leading and laggard countries. The role of the national housing industry in developing and maintaining a jurisdiction's prefabrication industry has not been previously explored comprehensively. This gap in knowledge is addressed in the current paper. A focus is given to collecting verifiable data to expose the differences between jurisdictions with both high and low levels of prefabrication adoption. Adoption is measured using data on prefabrication use. Based on content analysis, the main determinants of adoption are revealed to be (1) annual number of housing completions, (2) rates of new building versus renovation, (3) new housing ownership models, and (4) types of housing constructed. Analyses revealed the complexity of interacting factors and their potential influences on the uptake of prefabricated housing. The academic contribution of the paper is in providing a robust basis for more refined investigations of this emerging topic. The practical value of the paper is in providing guidance for policy makers to help them improve adoption of prefabrication, through demonstration projects for example. A limitation of this paper is that the data available is insufficient to facilitate more comprehensive analysis. Future quantitative, theory-driven research is needed to formalise the hypothesised relationships and conduct thorough statistical testing.