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.
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Bibliographic InfoArticle provided by INFORMS in its journal Manufacturing & Service Operations Management.
Volume (Year): 10 (2008)
Issue (Month): 4 (July)
newsvendor problem; dynamic learning;
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- 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.
- Jason Shachat & J. Todd Swarthout, 2003.
"Learning about Learning in Games through Experimental Control of Strategic Interdependence,"
- 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, 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.
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