2000
DOI: 10.1287/mnsc.46.5.597.12049
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Behind the Learning Curve: Linking Learning Activities to Waste Reduction

Abstract: This exploratory research on a decade of Total Quality Management in one factory opens up the black box of the learning curve. Based on the organizational learning literature, we derive a quality learning curve that links different types of learning in quality improvement projects to the evolution of the factory's waste rate. Only 25% of the quality improvement projects---which acquired both know-why and know-how---accelerated waste reduction. The other 75% of the projects either impeded or did not affect wast… Show more

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Cited by 303 publications
(222 citation statements)
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“…We note that the above specification follows a long line of research in cardiac risk stratification that link patient risk variables to outcomes using a logistic regression (see also, Parsonnet, Dean and Bernstein 1989;Higgins et al 1992; Nashef et al 3 We use counts of our experience variables, rather than their logs for two reasons. First, the log-linear learning curve model is derived from theory, and supported empirically while the log-log learning curve model is just from empirical results (Levy 1965;Lapré, Mukherjee and Wassenhove 2000). Second, if experience has been gained prior to the start of the dataset then the log-log learning curve model will yield biased coefficients (Lapré and Tsikriktsis 2006).…”
Section: Empirical Strategymentioning
confidence: 99%
“…We note that the above specification follows a long line of research in cardiac risk stratification that link patient risk variables to outcomes using a logistic regression (see also, Parsonnet, Dean and Bernstein 1989;Higgins et al 1992; Nashef et al 3 We use counts of our experience variables, rather than their logs for two reasons. First, the log-linear learning curve model is derived from theory, and supported empirically while the log-log learning curve model is just from empirical results (Levy 1965;Lapré, Mukherjee and Wassenhove 2000). Second, if experience has been gained prior to the start of the dataset then the log-log learning curve model will yield biased coefficients (Lapré and Tsikriktsis 2006).…”
Section: Empirical Strategymentioning
confidence: 99%
“…One of these issues is based on the fact that "Six Sigma is an organizational learning process and one that results in greater knowledge" (Schroeder et al, 2008, p.549). As a consequence, "viewing Six Sigma through the lens of knowledge management and organizational learning can lead to insights about how to create, retain, and diffuse knowledge using a structured method" Lapré et al, 2000). Other recent studies have indicated the importance of pursuing this issue in the study of Six Sigma.…”
Section: Introductionmentioning
confidence: 99%
“… Analytical papers that simply summarize all wastes under one measure (Li & O'Brien, 1999;Lapré et al, 2000). But it is more than questionable how far one specific measure can accurately represent the whole complexity of the waste concept.…”
Section: Other Definitions Of Wastementioning
confidence: 99%
“…This definition appears interesting at first sight, including elements of the theory of swift and even flow (Schmenner & Swink, 1998 Lim et al (1999) The term waste is described in the Webster's English dictionary as produced in excess. However, Shingo (1989), tackling the issue from a practitioner's point of view, defines waste in terms of seven categories:.. (p304) Lapré et al (2000) …waste rate (measured by the ratio of wasted material to total material released to the process). (p598) de Treville & Antonakis (2006) ...; any slack in the system is referred to as ''waste'' (e.g., Womack et al 1990).…”
Section: Other Definitions Of Wastementioning
confidence: 99%