IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this article or follow this journal

Newsvendor "Pull-to-Center" Effect: Adaptive Learning in a Laboratory Experiment

  • AJ A. Bostian

    ()

    (Australian School of Business, University of New South Wales, UNSW Sydney, NSW 2052, Australia)

  • Charles A. Holt

    ()

    (Department of Economics, University of Virginia, Charlottesville, Virginia 22904)

  • Angela M. Smith

    ()

    (Department of Economics, James Madison University, Harrisonburg, Virginia 22807)

In the newsvendor game, the expected-profit-maximizing order quantity is higher in the demand interval when the per-unit profit margin is high and lower in the demand interval when the per-unit profit margin is low. However, laboratory experiments show a "pull-to-center" effect: average order quantities are too low when they should be high and vice versa. We replicate this pull-to-center effect in laboratory experiments and construct an adaptive learning model that incorporates memory, reinforcement, and probabilistic choice to explain individual decisions. The intuition underlying the model's prediction is that the most recent demand observation is more likely to have been greater than the optimal order quantity if the optimal order quantity is low, in which case a recency bias tends to pull the order quantity upward. A countervailing downward pull exists if the optimal order quantity is high. The recency effect may be augmented by a reinforcement bias, which causes subjects to focus more on the profitability of decisions they actually make and less on counterfactual payoffs that would have resulted from other order quantities. The predictions of this model track the observed data patterns across treatments. A pull-to-center pattern is also observed in designs involving doubled payoffs and reduced order frequency.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://dx.doi.org/10.1287/msom.1080.0228
Download Restriction: no

Article provided by INFORMS in its journal Manufacturing & Service Operations Management.

Volume (Year): 10 (2008)
Issue (Month): 4 (July)
Pages: 590-608

as
in new window

Handle: RePEc:inm:ormsom:v:10:y:2008:i:4:p:590-608
Contact details of provider: Postal: 7240 Parkway Drive, Suite 300, Hanover, MD 21076 USA
Phone: +1-443-757-3500
Fax: 443-757-3515
Web page: http://www.informs.org/
Email:


More information through EDIRC

No references listed on IDEAS
You can help add them by filling out this form.

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:inm:ormsom:v:10:y:2008:i:4:p:590-608. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Mirko Janc)

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

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

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.