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

Author

Listed:
  • 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)

Abstract

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.

Suggested Citation

  • AJ A. Bostian & Charles A. Holt & Angela M. Smith, 2008. "Newsvendor "Pull-to-Center" Effect: Adaptive Learning in a Laboratory Experiment," Manufacturing & Service Operations Management, INFORMS, vol. 10(4), pages 590-608, July.
  • Handle: RePEc:inm:ormsom:v:10:y:2008:i:4:p:590-608
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    File URL: http://dx.doi.org/10.1287/msom.1080.0228
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    References listed on IDEAS

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    Cited by:

    1. repec:eee:ejores:v:264:y:2018:i:1:p:181-199 is not listed on IDEAS
    2. 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.
    3. 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.
    4. repec:eee:jeborg:v:141:y:2017:i:c:p:301-315 is not listed on IDEAS
    5. Zhao, Yingshuai & Zhao, Xiaobo, 2015. "On human decision behavior in multi-echelon inventory management," International Journal of Production Economics, Elsevier, vol. 161(C), pages 116-128.
    6. 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.
    7. Arshavskiy V. & Okulov V. & Smirnova A., 2014. "Newsvendor Problem Experiments: Riskiness of the Decisions and Learning by Experience," International Journal of Business and Social Research, MIR Center for Socio-Economic Research, vol. 4(5), pages 137-150, May.
    8. Becker-Peth, Michael & Thonemann, Ulrich W., 2016. "Reference points in revenue sharing contracts—How to design optimal supply chain contracts," European Journal of Operational Research, Elsevier, vol. 249(3), pages 1033-1049.
    9. Khanra, Avijit & Soman, Chetan & Bandyopadhyay, Tathagata, 2014. "Sensitivity analysis of the newsvendor model," European Journal of Operational Research, Elsevier, vol. 239(2), pages 403-412.
    10. 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.
    11. Mohammad Reza Nikbakht & Mehrdad Sadr Ara, 2016. "A new experimental model for profit maximization," Journal of Economic and Financial Studies (JEFS), LAR Center Press, vol. 4(3), pages 45-52, June.
    12. Feng, Tianjun & Keller, L. Robin & Zheng, Xiaona, 2011. "Decision making in the newsvendor problem: A cross-national laboratory study," Omega, Elsevier, vol. 39(1), pages 41-50, January.
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    15. repec:wyi:journl:002151 is not listed on IDEAS
    16. repec:gam:jsusta:v:10:y:2018:i:4:p:1119-:d:140162 is not listed on IDEAS
    17. Ockenfels, Axel & Selten, Reinhard, 2014. "Impulse balance in the newsvendor game," Games and Economic Behavior, Elsevier, vol. 86(C), pages 237-247.
    18. Hwang, Joon Ho & Kim, Min-Su, 2015. "Misunderstanding of the binomial distribution, market inefficiency, and learning behavior: Evidence from an exotic sports betting market," European Journal of Operational Research, Elsevier, vol. 243(1), pages 333-344.
    19. Ubøe, Jan & Andersson, Jonas & Jörnsten, Kurt & Lillestøl, Jostein & Sandal, Leif K., 2014. "Probabilistic cost efficiency and bounded rationality in the newsvendor model," Discussion Papers 2014/41, Norwegian School of Economics, Department of Business and Management Science.
    20. Ubøe, Jan & Andersson, Jonas & Jörnsten, Kurt & Lillestøl, Jostein & Sandal, Leif, 2017. "Statistical testing of bounded rationality with applications to the newsvendor model," European Journal of Operational Research, Elsevier, vol. 259(1), pages 251-261.
    21. repec:pal:jorsoc:v:68:y:2017:i:5:d:10.1057_s41274-016-0103-5 is not listed on IDEAS
    22. Christian Köster & Heike Y. Schenk-Mathes, 2016. "Explanatory and predictive power of the adaptive learning model: average and heterogeneous behavior in a newsvendor context," Journal of Business Economics, Springer, vol. 86(4), pages 361-387, May.

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    Keywords

    newsvendor problem; dynamic learning;

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