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Ration Gaming and the Bullwhip Effect

Author

Listed:
  • Robert L. Bray

    (Department of Operations Management, Kellogg School of Management, Northwestern University, Evanston, Illinois 60208;)

  • Yuliang Yao

    (Department of Management, College of Business and Economics, Lehigh University, Bethlehem, Pennsylvania 18015;)

  • Yongrui Duan

    (Department of Management Science and Engineering, School of Economics and Management, Tongji University, 200092 Shanghai, China)

  • Jiazhen Huo

    (Department of Management Science and Engineering, School of Economics and Management, Tongji University, 200092 Shanghai, China)

Abstract
We model a single-supplier, 73-store supply chain as a dynamic discrete choice problem. We estimate the model with transaction-level data, spanning 3,251 products and 1,370 days. We find two interrelated phenomena: the bullwhip effect and ration gaming. To establish the bullwhip effect, we show that shipments from suppliers are more variable than sales to customers. To establish ration gaming, we show that upstream scarcity triggers inventory runs, with stores simultaneously scrambling to amass private stocks in anticipation of impending shortages. These inventory runs increase our bullwhip measures by between 6% and 19%, which corroborates the long-standing hypothesis that ration gaming causes the bullwhip effect.

Suggested Citation

  • Robert L. Bray & Yuliang Yao & Yongrui Duan & Jiazhen Huo, 2019. "Ration Gaming and the Bullwhip Effect," Operations Research, INFORMS, vol. 67(2), pages 453-467, March.
    • Handle: RePEc:inm:oropre:v:67:y:2019:i:2:p:453-467
    DOI: 10.1287/opre.2018.1774
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    References listed on IDEAS

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    1. Miron, Jeffrey A & Zeldes, Stephen P, 1988. "Seasonality, Cost Shocks, and the Production Smoothing Models of Inventories," Econometrica, Econometric Society, vol. 56(4), pages 877-908, July.
    2. Igal Hendel & Aviv Nevo, 2006. "Sales and consumer inventory," RAND Journal of Economics, RAND Corporation, vol. 37(3), pages 543-561, September.
    3. Victor Aguirregabiria & Pedro Mira, 2002. "Swapping the Nested Fixed Point Algorithm: A Class of Estimators for Discrete Markov Decision Models," Econometrica, Econometric Society, vol. 70(4), pages 1519-1543, July.
    4. Victor Aguirregabiria, 1999. "The Dynamics of Markups and Inventories in Retailing Firms," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 66(2), pages 275-308.
    5. Aguirregabiria, Victor & Mira, Pedro, 2010. "Dynamic discrete choice structural models: A survey," Journal of Econometrics, Elsevier, vol. 156(1), pages 38-67, May.
    6. Alan S. Blinder & Louis J. Maccini, 1991. "Taking Stock: A Critical Assessment of Recent Research on Inventories," Journal of Economic Perspectives, American Economic Association, vol. 5(1), pages 73-96, Winter.
    7. Fangruo Chen & Jing-Sheng Song, 2001. "Optimal Policies for Multiechelon Inventory Problems with Markov-Modulated Demand," Operations Research, INFORMS, vol. 49(2), pages 226-234, April.
    8. Lode Li, 1992. "The Role of Inventory in Delivery-Time Competition," Management Science, INFORMS, vol. 38(2), pages 182-197, February.
    9. Eichenbaum, Martin, 1989. "Some Empirical Evidence on the Production Level and Production Cost Smoothing Models of Inventory Investment," American Economic Review, American Economic Association, vol. 79(4), pages 853-864, September.
    10. Tülin Erdem & Susumu Imai & Michael Keane, 2003. "Brand and Quantity Choice Dynamics Under Price Uncertainty," Quantitative Marketing and Economics (QME), Springer, vol. 1(1), pages 5-64, March.
    11. Maccini, Louis J & Rossana, Robert J, 1984. "Joint Production, Quasi-Fixed Factors of Production, and Investement in Finished Goods Inventories," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 16(2), pages 218-236, May.
    12. Yang, Yi & Yuan, Quan & Xue, Weili & Zhou, Yun, 2014. "Analysis of batch ordering inventory models with setup cost and capacity constraint," International Journal of Production Economics, Elsevier, vol. 155(C), pages 340-350.
    13. Gérard P. Cachon & Taylor Randall & Glen M. Schmidt, 2007. "In Search of the Bullwhip Effect," Manufacturing & Service Operations Management, INFORMS, vol. 9(4), pages 457-479, April.
    14. Hau L. Lee & V. Padmanabhan & Seungjin Whang, 1997. "Information Distortion in a Supply Chain: The Bullwhip Effect," Management Science, INFORMS, vol. 43(4), pages 546-558, April.
    15. Robert L. Bray & Haim Mendelson, 2015. "Production Smoothing and the Bullwhip Effect," Manufacturing & Service Operations Management, INFORMS, vol. 17(2), pages 208-220, May.
    16. Alan S. Blinder, 1981. "Retail Inventory Behavior and Business Fluctuations," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 12(2), pages 443-520.
    17. Peter Arcidiacono & Paul B. Ellickson, 2011. "Practical Methods for Estimation of Dynamic Discrete Choice Models," Annual Review of Economics, Annual Reviews, vol. 3(1), pages 363-394, September.
    18. Igal Hendel & Aviv Nevo, 2006. "Measuring the Implications of Sales and Consumer Inventory Behavior," Econometrica, Econometric Society, vol. 74(6), pages 1637-1673, November.
    19. Hall, George & Rust, John, 2000. "An empirical model of inventory investment by durable commodity intermediaries," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 52(1), pages 171-214, June.
    20. Peter Arcidiacono & John Bailey Jones, 2003. "Finite Mixture Distributions, Sequential Likelihood and the EM Algorithm," Econometrica, Econometric Society, vol. 71(3), pages 933-946, May.
    21. Li Chen & Hau L. Lee, 2012. "Bullwhip Effect Measurement and Its Implications," Operations Research, INFORMS, vol. 60(4), pages 771-784, August.
    22. Robert L. Bray & Haim Mendelson, 2012. "Information Transmission and the Bullwhip Effect: An Empirical Investigation," Management Science, INFORMS, vol. 58(5), pages 860-875, May.
    23. Robert L. Bray, 2019. "Strong convergence and dynamic economic models," Quantitative Economics, Econometric Society, vol. 10(1), pages 43-65, January.
    24. Peter Arcidiacono & Robert A. Miller, 2011. "Conditional Choice Probability Estimation of Dynamic Discrete Choice Models With Unobserved Heterogeneity," Econometrica, Econometric Society, vol. 79(6), pages 1823-1867, November.
    25. Igal Hendel & Aviv Nevo, 2006. "Sales and Consumer Inventory," RAND Journal of Economics, The RAND Corporation, vol. 37(3), pages 543-561, Autumn.
    26. Gérard P. Cachon & Martin A. Lariviere, 1999. "Capacity Choice and Allocation: Strategic Behavior and Supply Chain Performance," Management Science, INFORMS, vol. 45(8), pages 1091-1108, August.
    27. Kahn, James A, 1987. "Inventories and the Volatility of Production," American Economic Review, American Economic Association, vol. 77(4), pages 667-679, September.
    28. Arthur F. Veinott, 1965. "The Optimal Inventory Policy for Batch Ordering," Operations Research, INFORMS, vol. 13(3), pages 424-432, June.
    29. Lai, Richard, 2005. "Bullwhip in a Spanish Shop," MPRA Paper 4758, University Library of Munich, Germany.
    30. Fangruo Chen & Yu-Sheng Zheng, 1994. "Evaluating Echelon Stock (R, nQ) Policies in Serial Production/Inventory Systems with Stochastic Demand," Management Science, INFORMS, vol. 40(10), pages 1262-1275, October.
    31. Mor Armony & Erica L. Plambeck, 2005. "The Impact of Duplicate Orders on Demand Estimation and Capacity Investment," Management Science, INFORMS, vol. 51(10), pages 1505-1518, October.
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    4. Marshall Fisher & Marcelo Olivares & Bradley R. Staats, 2020. "Why Empirical Research Is Good for Operations Management, and What Is Good Empirical Operations Management?," Manufacturing & Service Operations Management, INFORMS, vol. 22(1), pages 170-178, January.
    5. Villa, Sebastián, 2022. "Competing for supply and demand: Understanding retailers' ordering decisions," International Journal of Production Economics, Elsevier, vol. 244(C).
    6. Erkan Bayraktar & Kazim Sari & Ekrem Tatoglu & Selim Zaim & Dursun Delen, 2020. "Assessing the supply chain performance: a causal analysis," Annals of Operations Research, Springer, vol. 287(1), pages 37-60, April.
    7. QU, Zhan & RAFF, Horst, 2023. "Two-part tariffs, inventory stockpiling, and the bullwhip effect," European Journal of Operational Research, Elsevier, vol. 308(1), pages 201-214.
    8. Brett A. Hathaway & Seyed M. Emadi & Vinayak Deshpande, 2021. "Don’t Call Us, We’ll Call You: An Empirical Study of Caller Behavior Under a Callback Option," Management Science, INFORMS, vol. 67(3), pages 1508-1526, March.

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