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Learning, Experimentation, and the Optimal Output Decisions of a Competitive Firm

Author

Listed:
  • Giora Harpaz

    (Baruch College (CUNY))

  • Wayne Y. Lee

    (Indiana University and University of Texas)

  • Robert L. Winkler

    (Indiana University and INSEAD)

Abstract

This paper considers the effect of learning from experience on the output decisions of a perfectly competitive firm faced with the demand uncertainty. Specifically, a Bayesian framework for expectations formation and demand forecasting by a perfectly competitive firm is presented. Focusing the analysis on the determination of optimal sequential output decisions, it is shown that through output experimentation, the experimenting firm will select a non-myopic sequential policy and will tend to overproduce. The exact magnitude of the overproduction and the economic value of experimentation are contingent upon model parameters and the length of the planning horizon.

Suggested Citation

  • Giora Harpaz & Wayne Y. Lee & Robert L. Winkler, 1982. "Learning, Experimentation, and the Optimal Output Decisions of a Competitive Firm," Management Science, INFORMS, vol. 28(6), pages 589-603, June.
    • Handle: RePEc:inm:ormnsc:v:28:y:1982:i:6:p:589-603
    DOI: 10.1287/mnsc.28.6.589
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    Cited by:

    1. Arnab Bisi & Maqbool Dada, 2007. "Dynamic learning, pricing, and ordering by a censored newsvendor," Naval Research Logistics (NRL), John Wiley & Sons, vol. 54(4), pages 448-461, June.
    2. Horowitz, I. & Thompson, P., 1995. "The sophisticated decision maker: All work and no pay?," Omega, Elsevier, vol. 23(1), pages 1-11, February.
    3. Xiangwen Lu & Jing-Sheng Song & Kaijie Zhu, 2008. "Analysis of Perishable-Inventory Systems with Censored Demand Data," Operations Research, INFORMS, vol. 56(4), pages 1034-1038, August.
    4. Adam J. Mersereau, 2015. "Demand Estimation from Censored Observations with Inventory Record Inaccuracy," Manufacturing & Service Operations Management, INFORMS, vol. 17(3), pages 335-349, July.
    5. Nicholas C. Petruzzi & Maqbool Dada, 2002. "Dynamic pricing and inventory control with learning," Naval Research Logistics (NRL), John Wiley & Sons, vol. 49(3), pages 303-325, April.
    6. Woonghee Tim Huh & Paat Rusmevichientong, 2009. "A Nonparametric Asymptotic Analysis of Inventory Planning with Censored Demand," Mathematics of Operations Research, INFORMS, vol. 34(1), pages 103-123, February.
    7. Katy S. Azoury & Julia Miyaoka, 2014. "Sequential learning versus no learning in Bayesian regression models," Naval Research Logistics (NRL), John Wiley & Sons, vol. 61(7), pages 532-548, October.
    8. Zhang, Jian & Zhang, Juliang & Hua, Guowei, 2016. "Multi-period inventory games with information update," International Journal of Production Economics, Elsevier, vol. 174(C), pages 119-127.
    9. Kohei Kawaguchi, 2021. "When Will Workers Follow an Algorithm? A Field Experiment with a Retail Business," Management Science, INFORMS, vol. 67(3), pages 1670-1695, March.
    10. Nils Rudi & David Drake, 2014. "Observation Bias: The Impact of Demand Censoring on Newsvendor Level and Adjustment Behavior," Management Science, INFORMS, vol. 60(5), pages 1334-1345, May.
    11. Li Chen & Erica L. Plambeck, 2008. "Dynamic Inventory Management with Learning About the Demand Distribution and Substitution Probability," Manufacturing & Service Operations Management, INFORMS, vol. 10(2), pages 236-256, May.
    12. Nicholas C. Petruzzi & Maqbool Dada, 2001. "Information and Inventory Recourse for a Two-Market, Price-Setting Retailer," Manufacturing & Service Operations Management, INFORMS, vol. 3(3), pages 242-263, October.
    13. Steven Nahmias, 1994. "Demand estimation in lost sales inventory systems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 41(6), pages 739-757, October.
    14. Philipp Afèche & Barış Ata, 2013. "Bayesian Dynamic Pricing in Queueing Systems with Unknown Delay Cost Characteristics," Manufacturing & Service Operations Management, INFORMS, vol. 15(2), pages 292-304, May.
    15. Boutselis, Petros & McNaught, Ken, 2014. "Finite-Time Horizon Logistics Decision Making Problems: Consideration of a Wider Set of Factors," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Blecker, Thorsten & Kersten, Wolfgang & Ringle, Christian M. (ed.), Innovative Methods in Logistics and Supply Chain Management: Current Issues and Emerging Practices. Proceedings of the Hamburg International Conferenc, volume 19, pages 249-274, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    16. Xiaomei Ding & Martin L. Puterman & Arnab Bisi, 2002. "The Censored Newsvendor and the Optimal Acquisition of Information," Operations Research, INFORMS, vol. 50(3), pages 517-527, June.
    17. Li Chen, 2010. "Bounds and Heuristics for Optimal Bayesian Inventory Control with Unobserved Lost Sales," Operations Research, INFORMS, vol. 58(2), pages 396-413, April.
    18. Joonkyum Lee & Vishal Gaur & Suresh Muthulingam & Gary F. Swisher, 2016. "Stockout-Based Substitution and Inventory Planning in Textbook Retailing," Manufacturing & Service Operations Management, INFORMS, vol. 18(1), pages 104-121, February.
    19. Katy S. Azoury & Julia Miyaoka, 2009. "Optimal Policies and Approximations for a Bayesian Linear Regression Inventory Model," Management Science, INFORMS, vol. 55(5), pages 813-826, May.
    20. Deligiannis, Michalis & Liberopoulos, George & Pandelis, Dimitrios G., 2023. "Managing supply chain risks with dual sourcing: Bayesian learning of censored supply capacity," International Journal of Production Economics, Elsevier, vol. 265(C).
    21. Martin A. Lariviere & Evan L. Porteus, 1999. "Stalking Information: Bayesian Inventory Management with Unobserved Lost Sales," Management Science, INFORMS, vol. 45(3), pages 346-363, March.
    22. Nils Rudi & David Drake, 2009. "Observation bias: The impact of demand censoring on newsvendor level and adjustment behavior," Harvard Business School Working Papers 12-042, Harvard Business School, revised Dec 2011.
    23. Jiri Chod & Mihalis G. Markakis & Nikolaos Trichakis, 2021. "On the Learning Benefits of Resource Flexibility," Management Science, INFORMS, vol. 67(10), pages 6513-6528, October.
    24. Arnab Bisi & Maqbool Dada & Surya Tokdar, 2011. "A Censored-Data Multiperiod Inventory Problem with Newsvendor Demand Distributions," Manufacturing & Service Operations Management, INFORMS, vol. 13(4), pages 525-533, October.

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