IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v19y1985i2p191-200.html
   My bibliography  Save this article

On the statistical origins of the learning curve

Author

Listed:
  • Venezia, Itzhak

Abstract

No abstract is available for this item.

Suggested Citation

  • Venezia, Itzhak, 1985. "On the statistical origins of the learning curve," European Journal of Operational Research, Elsevier, vol. 19(2), pages 191-200, February.
    • Handle: RePEc:eee:ejores:v:19:y:1985:i:2:p:191-200
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/0377-2217(85)90172-9
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Bentefouet, Frank & Nembhard, David A., 2013. "Optimal flow-line conditions with worker variability," International Journal of Production Economics, Elsevier, vol. 141(2), pages 675-684.
    2. Boyan Jovanovic, 2019. "The entrepreneurship premium," Small Business Economics, Springer, vol. 53(3), pages 555-568, October.
    3. Chen, Xi & Hewitt, Mike & Thomas, Barrett W., 2018. "An approximate dynamic programming method for the multi-period technician scheduling problem with experience-based service times and stochastic customers," International Journal of Production Economics, Elsevier, vol. 196(C), pages 122-134.
    4. 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.
    5. 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.
    6. 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.
    7. Boyan Jovanovic & Yaw Nyarko, 1995. "A Bayesian Learning Model Fitted to a Variety of Empirical Learning Curves," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 26(1995 Micr), pages 247-305.
    8. 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.
    9. 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.

    More about this item

    Statistics

    Access and download statistics

    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:eee:ejores:v:19:y:1985:i:2:p:191-200. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.