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Estimation of optimal productivity i...
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Kisi, Krishna Prasad.
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Estimation of optimal productivity in labor-intensive construction operations.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Estimation of optimal productivity in labor-intensive construction operations./
作者:
Kisi, Krishna Prasad.
面頁冊數:
264 p.
附註:
Source: Dissertation Abstracts International, Volume: 76-11(E), Section: B.
Contained By:
Dissertation Abstracts International76-11B(E).
標題:
Engineering. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3712536
ISBN:
9781321894349
Estimation of optimal productivity in labor-intensive construction operations.
Kisi, Krishna Prasad.
Estimation of optimal productivity in labor-intensive construction operations.
- 264 p.
Source: Dissertation Abstracts International, Volume: 76-11(E), Section: B.
Thesis (Ph.D.)--The University of Nebraska - Lincoln, 2015.
In an attempt to evaluate the efficiency of labor-intensive construction operations, project managers typically compare actual with historical productivity for equivalent operations. However, this approach toward examining productivity only provides a relative benchmark for efficiency and may lead to the characterization of operations as objectively efficient when in reality such operations might simply be comparably efficient. Just because actual productivity equals average historical productivity does not necessarily mean that an operation is efficient; the case may be that the operation's efficiency is only in line with historical averages, which may be well below optimal productivity.
ISBN: 9781321894349Subjects--Topical Terms:
586835
Engineering.
Estimation of optimal productivity in labor-intensive construction operations.
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Source: Dissertation Abstracts International, Volume: 76-11(E), Section: B.
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Advisers: Terence Foster; Eddy M. Rojas.
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Thesis (Ph.D.)--The University of Nebraska - Lincoln, 2015.
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In an attempt to evaluate the efficiency of labor-intensive construction operations, project managers typically compare actual with historical productivity for equivalent operations. However, this approach toward examining productivity only provides a relative benchmark for efficiency and may lead to the characterization of operations as objectively efficient when in reality such operations might simply be comparably efficient. Just because actual productivity equals average historical productivity does not necessarily mean that an operation is efficient; the case may be that the operation's efficiency is only in line with historical averages, which may be well below optimal productivity.
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Optimal productivity is the highest sustainable productivity achievable under good management and typical field conditions. Optimal productivity is useful in the determination of the absolute efficiency of construction operations because an accurate estimate of optimal labor productivity allows for the comparison of actual vs. optimal (unbiased) rather than actual vs. historical (biased) productivity.
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This research contributes to the body of knowledge by introducing a two-prong strategy for estimating optimal labor productivity in labor-intensive construction operations and applying it in an activity with a single worker and sequential tasks as well as in an activity with multiple workers and sequential and parallel tasks. The first prong, or a top-down approach, estimates the upper limit of optimal productivity by introducing system inefficiencies into the productivity frontier -- productivity achieved under perfect conditions. A qualitative factor model is used to achieve this objective. The second prong, or a bottom-up approach, estimates the lower limit of optimal productivity by taking away operational inefficiency from actual productivity -- productivity recorded in the field. A discrete event simulation model is used to estimate this value. An average of the upper and lower limits is taken as the best estimate of optimal productivity.
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In conjunction with a relevant literature review and a discussion of the two-prong approach's methodology, this research ultimately analyzes data from a pilot study with a single worker and sequential actions and an advanced study containing multiple workers and sequential and parallel tasks and actions, and evaluates the feasibility of this two-prong strategy for estimating optimal productivity in construction operations.
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