Literature DB >> 17776451

Learning curves in manufacturing.

L Argote, D Epple.   

Abstract

Large increases in productivity are typically realized as organizations gain experience in production. These "learning curves" have been found in many organizations. Organizations vary considerably in the rates at which they learn. Some organizations show remarkable productivity gains, whereas others show little or no learning. Reasons for the variation observed in organizational learning curves include organizational "forgetting," employee turnover, transfer of knowledge from other products and other organizations, and economies of scale.

Entities:  

Year:  1990        PMID: 17776451     DOI: 10.1126/science.247.4945.920

Source DB:  PubMed          Journal:  Science        ISSN: 0036-8075            Impact factor:   47.728


  16 in total

1.  Dematerialization: Variety, caution, and persistence.

Authors:  Jesse H Ausubel; Paul E Waggoner
Journal:  Proc Natl Acad Sci U S A       Date:  2008-08-26       Impact factor: 11.205

2.  [Learning and teaching abilities of a newly inaugurated operation technique. Analysis of learning curves and transferability exemplified by Kypho-IORT].

Authors:  F Bludau; R Schmidt; F Schneider; T Reis; F Wenz; U Obertacke; R Kayser
Journal:  Orthopade       Date:  2013-09       Impact factor: 1.087

3.  The impact of team familiarity and surgical experience on operative efficiency: a retrospective analysis.

Authors:  Mahiben Maruthappu; Antoine Duclos; Charlie D Zhou; Stuart R Lipsitz; John Wright; Dennis Orgill; Matthew J Carty
Journal:  J R Soc Med       Date:  2016-04-06       Impact factor: 5.344

4.  Role of design complexity in technology improvement.

Authors:  James McNerney; J Doyne Farmer; Sidney Redner; Jessika E Trancik
Journal:  Proc Natl Acad Sci U S A       Date:  2011-05-16       Impact factor: 11.205

5.  The spread of technological innovations: effects of psychology, culture and policy interventions.

Authors:  Denis Tverskoi; Sudarsanam Babu; Sergey Gavrilets
Journal:  R Soc Open Sci       Date:  2022-06-22       Impact factor: 3.653

6.  Wind power electricity: the bigger the turbine, the greener the electricity?

Authors:  Marloes Caduff; Mark A J Huijbregts; Hans-Joerg Althaus; Annette Koehler; Stefanie Hellweg
Journal:  Environ Sci Technol       Date:  2012-04-20       Impact factor: 9.028

7.  Patient- and surgeon-adjusted control charts for monitoring performance.

Authors:  Mahiben Maruthappu; Matthew J Carty; Stuart R Lipsitz; John Wright; Dennis Orgill; Antoine Duclos
Journal:  BMJ Open       Date:  2014-01-16       Impact factor: 2.692

8.  Surgical learning curves and operative efficiency: a cross-specialty observational study.

Authors:  Mahiben Maruthappu; Antoine Duclos; Stuart R Lipsitz; Dennis Orgill; Matthew J Carty
Journal:  BMJ Open       Date:  2015-03-13       Impact factor: 2.692

9.  Statistical basis for predicting technological progress.

Authors:  Béla Nagy; J Doyne Farmer; Quan M Bui; Jessika E Trancik
Journal:  PLoS One       Date:  2013-02-28       Impact factor: 3.240

10.  The commercial performance of cellulosic ethanol supply-chains in Europe.

Authors:  Raphael Slade; Ausilio Bauen; Nilay Shah
Journal:  Biotechnol Biofuels       Date:  2009-02-03       Impact factor: 6.040

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