Learning curves in construction

This paper brings forth from the literature a series of learning curve models and evaluates them through the lens of the construction industry. The review suggests that there is still no consensus on which model provides the best fit and predictability for construction data. As such, this paper puts...

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Bibliographic Details
Main Author: Srour, F. Jordan (author)
Other Authors: Kiomjian, Daoud (author), Srour, Issam M. (author)
Format: article
Published: 2016
Online Access:http://hdl.handle.net/10725/4682
http://dx.doi.org/10.1061/(ASCE)CO.1943-7862.0001096
http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php
http://ascelibrary.org/doi/abs/10.1061/(ASCE)CO.1943-7862.0001096
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Summary:This paper brings forth from the literature a series of learning curve models and evaluates them through the lens of the construction industry. The review suggests that there is still no consensus on which model provides the best fit and predictability for construction data. As such, this paper puts forth a new model that is suitable for the modern construction industry as it accommodates for both mechanization and forgetting. The proposed model is similar to the Wright model (an exponential model of learning), but, through recursion, places more emphasis on recent data. The proposed model shows an error of less than 1% when predicting the cumulative average completion times in three out of four cases examined.