Toward a Theory of Continuous Improvement and the Learning Curve

Willard I. Zangwill and Paul B. Kantor
Additional contact information
Willard I. Zangwill: Graduate School of Business, 1101 East 58th Street, University of Chicago, Chicago, Illinois 60637
Paul B. Kantor: Tantalus, Inc. and RUTCOR, Rutgers University, New Brunswick, New Jersey 08903

Management Science, 1998, vol. 44, issue 7, 910-920

Abstract: Continuous improvement (CI) unceasingly strives to improve the performance of production and service firms. The learning curve (LC) provides1988 Department of Industrial Engineering and a means to observe and track that improvement. At present, however, the concepts of CI are abstract and imprecise and the rationale underpinning the LC is obscure. For managers to improve processes effectively, they need a more scientific theory of CI and the LC. This paper begins to develop such a theory. Our approach is based on learning cycles, that is, in each period management takes an action to improve the process, observes the results, and thereby learns how to improve the process further over time. This analysis suggests a differential equation that not only characterizes continuous improvement but also reveals how learning might occur in the learning curve. This differential equation might help management to evaluate the effectiveness of various procedures and to improve and enhance industrial processes more quickly.

Keywords: Continuous Improvement; Improvement; Learning; Learning Cycle; Learning Curve; Learning Theory; Management Effectiveness; Quality; Total Quality Management; Value Added; Deming; Lotka; Volterra (search for similar items in EconPapers)
Date: 1998
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)

Downloads: (external link)
http://dx.doi.org/10.1287/mnsc.44.7.910 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:44:y:1998:i:7:p:910-920

Access Statistics for this article

More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().