IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v44y1998i7p910-920.html
   My bibliography  Save this article

Toward a Theory of Continuous Improvement and the Learning Curve

Author

Listed:
  • 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)

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.

Suggested Citation

  • Willard I. Zangwill & Paul B. Kantor, 1998. "Toward a Theory of Continuous Improvement and the Learning Curve," Management Science, INFORMS, vol. 44(7), pages 910-920, July.
    • Handle: RePEc:inm:ormnsc:v:44:y:1998:i:7:p:910-920
    DOI: 10.1287/mnsc.44.7.910
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.44.7.910
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mnsc.44.7.910?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Paul S. Adler & Kim B. Clark, 1991. "Behind the Learning Curve: A Sketch of the Learning Process," Management Science, INFORMS, vol. 37(3), pages 267-281, March.
    2. Charles H. Fine & Evan L. Porteus, 1989. "Dynamic Process Improvement," Operations Research, INFORMS, vol. 37(4), pages 580-591, August.
    3. Willard I. Zangwill, 1992. "The Limits of Japanese Production Theory," Interfaces, INFORMS, vol. 22(5), pages 14-25, October.
    4. Ferdinand K. Levy, 1965. "Adaptation in the Production Process," Management Science, INFORMS, vol. 11(6), pages 136-154, April.
    5. John F. Muth, 1986. "Search Theory and the Manufacturing Progress Function," Management Science, INFORMS, vol. 32(8), pages 948-962, August.
    6. Linda Argote & Sara L. Beckman & Dennis Epple, 1990. "The Persistence and Transfer of Learning in Industrial Settings," Management Science, INFORMS, vol. 36(2), pages 140-154, February.
    7. Dutton, John M. & Thomas, Annie & Butler, John E., 1984. "The History of Progress Functions as a Managerial Technology," Business History Review, Cambridge University Press, vol. 58(2), pages 204-233, July.
    8. Venezia, Itzhak, 1985. "On the statistical origins of the learning curve," European Journal of Operational Research, Elsevier, vol. 19(2), pages 191-200, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wang, Weijia & Plante, Robert D. & Tang, Jen, 2013. "Minimum cost allocation of quality improvement targets under supplier process disruption," European Journal of Operational Research, Elsevier, vol. 228(2), pages 388-396.
    2. Witjes, Sjors & Vermeulen, Walter J.V. & Cramer, Jacqueline M., 2017. "Assessing Corporate Sustainability integration for corporate self-reflection," Resources, Conservation & Recycling, Elsevier, vol. 127(C), pages 132-147.
    3. Silbermayr, Lena & Minner, Stefan, 2016. "Dual sourcing under disruption risk and cost improvement through learning," European Journal of Operational Research, Elsevier, vol. 250(1), pages 226-238.
    4. Demeester, Lieven L. & Qi, Mei, 2005. "Managing learning resources for consecutive product generations," International Journal of Production Economics, Elsevier, vol. 95(2), pages 265-283, February.
    5. Kobos, Peter H. & Erickson, Jon D. & Drennen, Thomas E., 2006. "Technological learning and renewable energy costs: implications for US renewable energy policy," Energy Policy, Elsevier, vol. 34(13), pages 1645-1658, September.
    6. Bossink, Bart, 2020. "Learning strategies in sustainable energy demonstration projects: What organizations learn from sustainable energy demonstrations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    7. Biskup, Dirk, 2008. "A state-of-the-art review on scheduling with learning effects," European Journal of Operational Research, Elsevier, vol. 188(2), pages 315-329, July.
    8. Heese, H. Sebastian, 2015. "Single versus multiple sourcing and the evolution of bargaining positions," Omega, Elsevier, vol. 54(C), pages 125-133.
    9. Terwiesch, Christian & E. Bohn, Roger, 2001. "Learning and process improvement during production ramp-up," International Journal of Production Economics, Elsevier, vol. 70(1), pages 1-19, March.
    10. Biskup, Dirk & Simons, Dirk, 2004. "Common due date scheduling with autonomous and induced learning," European Journal of Operational Research, Elsevier, vol. 159(3), pages 606-616, December.
    11. Sáenz-Royo, Carlos & Lozano-Rojo, Álvaro, 2023. "Authoritarianism versus participation in innovation decisions," Technovation, Elsevier, vol. 124(C).
    12. Morrison, J. Bradley, 2008. "Putting the learning curve in context," Journal of Business Research, Elsevier, vol. 61(11), pages 1182-1190, November.
    13. Sáenz-Royo, Carlos & Salas-Fumás, Vicente, 2013. "Learning to learn and productivity growth: Evidence from a new car-assembly plant," Omega, Elsevier, vol. 41(2), pages 336-344.
    14. Taylor, W.A. & Wright, G.H., 2006. "The contribution of measurement and information infrastructure to TQM success," Omega, Elsevier, vol. 34(4), pages 372-384, August.
    15. Shittu, Ekundayo & Kamdem, Bruno G. & Weigelt, Carmen, 2019. "Heterogeneities in energy technological learning: Evidence from the U.S. electricity industry," Energy Policy, Elsevier, vol. 132(C), pages 1034-1049.
    16. Vits, Jeroen & Gelders, Ludo, 2002. "Performance improvement theory," International Journal of Production Economics, Elsevier, vol. 77(3), pages 285-298, June.
    17. Kim, Youngsoo, 2022. "Taxi driver’s learning curves: An empirical analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 166(C), pages 1-13.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Guido Fioretti, 2007. "A connectionist model of the organizational learning curve," Computational and Mathematical Organization Theory, Springer, vol. 13(1), pages 1-16, March.
    2. Eelke Wiersma, 2007. "Conditions That Shape the Learning Curve: Factors That Increase the Ability and Opportunity to Learn," Management Science, INFORMS, vol. 53(12), pages 1903-1915, December.
    3. Fioretti, Guido, 2009. "From men and machines to the organizational learning curve," MPRA Paper 19392, University Library of Munich, Germany.
    4. Manda, A.B. & Uzsoy, Reha, 2021. "Managing product transitions with learning and congestion effects," International Journal of Production Economics, Elsevier, vol. 239(C).
    5. Michael A. Lapré & Amit Shankar Mukherjee & Luk N. Van Wassenhove, 2000. "Behind the Learning Curve: Linking Learning Activities to Waste Reduction," Management Science, INFORMS, vol. 46(5), pages 597-611, May.
    6. Vits, Jeroen & Gelders, Ludo, 2002. "Performance improvement theory," International Journal of Production Economics, Elsevier, vol. 77(3), pages 285-298, June.
    7. Anupam Agrawal & Suresh Muthulingam, 2015. "Does Organizational Forgetting Affect Vendor Quality Performance? An Empirical Investigation," Manufacturing & Service Operations Management, INFORMS, vol. 17(3), pages 350-367, July.
    8. Christina Fang, 2012. "Organizational Learning as Credit Assignment: A Model and Two Experiments," Organization Science, INFORMS, vol. 23(6), pages 1717-1732, December.
    9. Ngwenyama, Ojelanki & Guergachi, Aziz & McLaren, Tim, 2007. "Using the learning curve to maximize IT productivity: A decision analysis model for timing software upgrades," International Journal of Production Economics, Elsevier, vol. 105(2), pages 524-535, February.
    10. Kannan Srikanth & Jaideep Anand & Mihaela Stan, 2021. "The origins of time compression diseconomies," Strategic Management Journal, Wiley Blackwell, vol. 42(9), pages 1573-1599, September.
    11. Thompson, Peter, 2010. "Learning by Doing," Handbook of the Economics of Innovation, in: Bronwyn H. Hall & Nathan Rosenberg (ed.), Handbook of the Economics of Innovation, edition 1, volume 1, chapter 0, pages 429-476, Elsevier.
    12. Michael A. Lapré & Luk N. Van Wassenhove, 2001. "Creating and Transferring Knowledge for Productivity Improvement in Factories," Management Science, INFORMS, vol. 47(10), pages 1311-1325, October.
    13. Carlos Ocaña Pérez de Tudela, 1993. "Modelos dinámicos de competencia estratégica y cambio técnico: una panorámica," Investigaciones Economicas, Fundación SEPI, vol. 17(1), pages 43-63, January.
    14. Tammy L. Madsen & Michael J. Leiblein, 2015. "What Factors Affect the Persistence of an Innovation Advantage?," Journal of Management Studies, Wiley Blackwell, vol. 52(8), pages 1097-1127, December.
    15. Anelí Bongers, 2017. "Learning and forgetting in the jet fighter aircraft industry," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-19, September.
    16. Tat Y. Chan & Jia Li & Lamar Pierce, 2014. "Learning from Peers: Knowledge Transfer and Sales Force Productivity Growth," Marketing Science, INFORMS, vol. 33(4), pages 463-484, July.
    17. Peter Thompson, 2001. "How Much Did the Liberty Shipbuilders Learn? New Evidence for an Old Case Study," Journal of Political Economy, University of Chicago Press, vol. 109(1), pages 103-137, February.
    18. Biskup, Dirk, 2008. "A state-of-the-art review on scheduling with learning effects," European Journal of Operational Research, Elsevier, vol. 188(2), pages 315-329, July.
    19. Robert S. Huckman & Gary P. Pisano, 2006. "The Firm Specificity of Individual Performance: Evidence from Cardiac Surgery," Management Science, INFORMS, vol. 52(4), pages 473-488, April.
    20. Fioretti, Guido, 2007. "The organizational learning curve," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1375-1384, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormnsc:v:44:y:1998:i:7:p:910-920. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.