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contributor authorPaul M. Goodrum
contributor authorCarl T. Haas
contributor authorCarlos Caldas
contributor authorDong Zhai
contributor authorJordan Yeiser
contributor authorDaniel Homm
date accessioned2017-05-08T21:39:22Z
date available2017-05-08T21:39:22Z
date copyrightSeptember 2011
date issued2011
identifier other%28asce%29co%2E1943-7862%2E0000334.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/58485
description abstractAlthough some new technologies promise to improve construction productivity, their ability to deliver is not always realized. Building on a great deal of prior research, a four-stage predictive model was developed and validated to estimate the potential for a technology to have a positive impact on construction productivity. The four stages examine the costs, feasibility, usage history, and technical impact of a technology. The predictive model combines results from historical analyses to formalize how selected technologies with improved construction productivity can be used as a predictor of how future technologies might do the same. Each of the stages of a predictive model was subdivided into a series of categories and questions, which were weighted by importance by using the analytic hierarchy process and historical analysis to generate a performance score for the analyzed technology. The predictive model was then validated by using 74 previous and existing construction technologies. Statistical analysis confirmed that average performance scores produced by the model were significantly different across the categories of successful, inconclusive, and unsuccessful in the actual implementation experience of technologies.
publisherAmerican Society of Civil Engineers
titleModel to Predict the Impact of a Technology on Construction Productivity
typeJournal Paper
journal volume137
journal issue9
journal titleJournal of Construction Engineering and Management
identifier doi10.1061/(ASCE)CO.1943-7862.0000328
treeJournal of Construction Engineering and Management:;2011:;Volume ( 137 ):;issue: 009
contenttypeFulltext


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