Thirty-three international academics and researchers contribute 23 chapters exploring learning curves and their applications in organizational settings. Opening chapters describe the theory and models of learning curves, while subsequent chapters consider their applications. A sampling of topics includes learning and thinking systems, management at the flat end of the learning curve, half-life theory of learning curves, accelerated learning by experimentation, the lot sizing problem and the learning curve, steady-state characteristics under processing-time learning and forgetting, industrial work measurement and improvement through multivariate learning curves, and learning curves in project management, for CAD competence building, and in energy technology policy. The book's readership includes graduate students and researchers in operations research/management science, industrial engineering, management (in fields such as healthcare and energy) and social sciences. Annotation ©2012 Book News, Inc., Portland, OR (booknews.com)
Written by international contributors, Learning Curves: Theory, Models, and Applications first draws a learning map that shows where learning is involved within organizations, then examines how it can be sustained, perfected, and accelerated. The book reviews empirical findings in the literature in terms of different sources for learning and partial assessments of the steps that make up the actual learning process inside the learning curve.
Traditionally, books on learning curves have focused either on cost accounting or production planning and control. In these books, the learning curve has been treated as a forecasting tool. This book synthesizes current research and presents a clear picture of organizational learning curves. It explores how organizations improve other measures of organizational performance including quality, inventory, and productivity, then looks inside the learning curve to determine the actual processes through which organizations learn.
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