Newsvendor "Pull-to-Center" Effect: Adaptive Learning in a Laboratory Experiment
AbstractIn 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.
Download InfoIf 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.
Bibliographic InfoArticle provided by INFORMS in its journal Manufacturing & Service Operations Management.
Volume (Year): 10 (2008)
Issue (Month): 4 (July)
newsvendor problem; dynamic learning;
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Shachat, Jason & Swarthout, J. Todd, 2012.
"Learning about learning in games through experimental control of strategic interdependence,"
Journal of Economic Dynamics and Control,
Elsevier, vol. 36(3), pages 383-402.
- Jason Shachat & J. Todd Swarthout, 2003. "Learning about Learning in Games through Experimental Control of Strategic Interdependence," Experimental 0310003, EconWPA.
- Jason Shachat & J. Todd Swarthout, 2002. "Learning about Learning in Games through Experimental Control of Strategic Interdependence," Experimental Economics Center Working Paper Series 2006-17, Experimental Economics Center, Andrew Young School of Policy Studies, Georgia State University, revised Aug 2008.
- Ancarani, A. & Di Mauro, C. & D'Urso, D., 2013. "A human experiment on inventory decisions under supply uncertainty," International Journal of Production Economics, Elsevier, vol. 142(1), pages 61-73.
- Elahi, Ehsan & Lamba, Narasimha & Ramaswamy, Chinthana, 2013. "How can we improve the performance of supply chain contracts? An experimental study," International Journal of Production Economics, Elsevier, vol. 142(1), pages 146-157.
- repec:wyi:journl:002151 is not listed on IDEAS
- Wu, Diana Yan, 2013. "The impact of repeated interactions on supply chain contracts: A laboratory study," International Journal of Production Economics, Elsevier, vol. 142(1), pages 3-15.
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.