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Capacity Allocation over a Long Horizon: The Return on Turn-and-Earn

Author

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  • Lauren Xiaoyuan Lu

    (Kenan-Flagler Business School, University of North Carolina, Chapel Hill, North Carolina 27599)

  • Martin A. Lariviere

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

Abstract

We consider a supply chain in which a supplier sells products to multiple retailers. When orders from the retailers exceed the supplier's capacity, she must employ an allocation mechanism to balance supply and demand. In particular, we consider a commonly used allocation scheme in the automobile industry: turn-and-earn, which uses past sales to allocate capacity. In essence, retailers "earn" an allotment of a vehicle after they sell one. In contrast to turn-and-earn, fixed allocation ignores past sales and gives each retailer an equal share of the capacity. Earlier work has demonstrated that turn-and-earn induces more sales in a two-period setting compared to fixed allocation. The question remains unanswered whether turn-and-earn induces similar behaviors over a long horizon when retailers possess private demand information. We construct a dynamic stochastic game of order competition over an infinite horizon to track the order dynamics of the supply chain. We obtain a richer set of equilibrium behaviors than existing models predict. Instead of a symmetric allocation outcome, we observe that sales leadership may arise in equilibrium and that retailers with different past sales adopt distinct ordering strategies to respond to demand uncertainty. Transient sales dynamics suggest that sales leadership may not be persistent and can be eliminated by the occurrence of extremely low demand. This provides a theoretical explanation for several behavioral observations of some U.S. automobile dealers. In addition to the sales-inducing effect, interestingly, turn-and-earn also causes the retailers to absorb local demand variability.

Suggested Citation

  • Lauren Xiaoyuan Lu & Martin A. Lariviere, 2012. "Capacity Allocation over a Long Horizon: The Return on Turn-and-Earn," Manufacturing & Service Operations Management, INFORMS, vol. 14(1), pages 24-41, January.
  • Handle: RePEc:inm:ormsom:v:14:y:2012:i:1:p:24-41
    DOI: 10.1287/msom.1110.0346
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    References listed on IDEAS

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    1. Richard Ericson & Ariel Pakes, 1995. "Markov-Perfect Industry Dynamics: A Framework for Empirical Work," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 62(1), pages 53-82.
    2. Gérard P. Cachon & Martin A. Lariviere, 1999. "Capacity Allocation Using Past Sales: When to Turn-and-Earn," Management Science, INFORMS, vol. 45(5), pages 685-703, May.
    3. Ariel Pakes & Paul McGuire, 1994. "Computing Markov-Perfect Nash Equilibria: Numerical Implications of a Dynamic Differentiated Product Model," RAND Journal of Economics, The RAND Corporation, vol. 25(4), pages 555-589, Winter.
    4. Stephen M. Gilbert & Z. Kevin Weng, 1998. "Incentive Effects Favor Nonconsolidating Queues in a Service System: The Principal--Agent Perspective," Management Science, INFORMS, vol. 44(12-Part-1), pages 1662-1669, December.
    5. David Besanko & Ulrich Doraszelski & Lauren Xiaoyuan Lu & Mark Satterthwaite, 2010. "Lumpy Capacity Investment and Disinvestment Dynamics," Operations Research, INFORMS, vol. 58(4-part-2), pages 1178-1193, August.
    6. Gabriel Y. Weintraub & C. Lanier Benkard & Benjamin Van Roy, 2008. "Markov Perfect Industry Dynamics With Many Firms," Econometrica, Econometric Society, vol. 76(6), pages 1375-1411, November.
    7. Ulrich Doraszelski & Mark Satterthwaite, 2010. "Computable Markov‐perfect industry dynamics," RAND Journal of Economics, RAND Corporation, vol. 41(2), pages 215-243, June.
    8. Jiri Chod & Nils Rudi, 2005. "Resource Flexibility with Responsive Pricing," Operations Research, INFORMS, vol. 53(3), pages 532-548, June.
    9. Pakes, Ariel & McGuire, Paul, 2001. "Stochastic Algorithms, Symmetric Markov Perfect Equilibrium, and the 'Curse' of Dimensionality," Econometrica, Econometric Society, vol. 69(5), pages 1261-1281, September.
    10. 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.
    11. Maskin, Eric & Tirole, Jean, 2001. "Markov Perfect Equilibrium: I. Observable Actions," Journal of Economic Theory, Elsevier, vol. 100(2), pages 191-219, October.
    12. 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.
    13. Gabriel Y. Weintraub & C. Lanier Benkard & Benjamin Van Roy, 2010. "Computational Methods for Oblivious Equilibrium," Operations Research, INFORMS, vol. 58(4-part-2), pages 1247-1265, August.
    14. Gérard P. Cachon & Fuqiang Zhang, 2007. "Obtaining Fast Service in a Queueing System via Performance-Based Allocation of Demand," Management Science, INFORMS, vol. 53(3), pages 408-420, March.
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    Cited by:

    1. Qing, Qiankai & Deng, Tianhu & Wang, Hongwei, 2017. "Capacity allocation under downstream competition and bargaining," European Journal of Operational Research, Elsevier, vol. 261(1), pages 97-107.
    2. Zhibin (Ben) Yang & Xinxin Hu & Haresh Gurnani & Huiqi Guan, 2018. "Multichannel Distribution Strategy: Selling to a Competing Buyer with Limited Supplier Capacity," Management Science, INFORMS, vol. 64(5), pages 2199-2218, May.
    3. Can Zhang & Atalay Atasu & Turgay Ayer & L. Beril Toktay, 2020. "Truthful Mechanisms for Medical Surplus Product Allocation," Manufacturing & Service Operations Management, INFORMS, vol. 22(4), pages 735-753, July.
    4. Soo-Haeng Cho & Christopher S. Tang, 2014. "Technical Note---Capacity Allocation Under Retail Competition: Uniform and Competitive Allocations," Operations Research, INFORMS, vol. 62(1), pages 72-80, February.
    5. Eirini Spiliotopoulou & Karen Donohue & Mustafa Çagri Gürbüz, 2022. "Ordering Behavior and the Impact of Allocation Mechanisms in an Integrated Distribution System," Production and Operations Management, Production and Operations Management Society, vol. 31(2), pages 422-441, February.
    6. Ghamat, Salar & Pun, Hubert, 2023. "The impact of capacity information on lexicographical capacity allocation," European Journal of Operational Research, Elsevier, vol. 308(2), pages 636-649.
    7. Hongmin Li & Hao Zhang & Charles H. Fine, 2013. "Dynamic Business Share Allocation in a Supply Chain with Competing Suppliers," Operations Research, INFORMS, vol. 61(2), pages 280-297, April.
    8. Dinah A. Cohen-Vernik & Devavrat Purohit, 2014. "Turn-and-Earn Incentives with a Product Line," Management Science, INFORMS, vol. 60(2), pages 400-414, February.
    9. Hofstra, Nienke & Spiliotopoulou, Eirini, 2022. "Behavior in rationing inventory across retail channels," European Journal of Operational Research, Elsevier, vol. 299(1), pages 208-222.
    10. Tony Haitao Cui & Yinghao Zhang, 2018. "Cognitive Hierarchy in Capacity Allocation Games," Management Science, INFORMS, vol. 64(3), pages 1250-1270, March.
    11. Lee, Chungseung & Park, Kun Soo, 2016. "Inventory and transshipment decisions in the rationing game under capacity uncertainty," Omega, Elsevier, vol. 65(C), pages 82-97.
    12. Deligiannis, Michalis & Liberopoulos, George, 2023. "Dynamic ordering and buyer selection policies when service affects future demand," Omega, Elsevier, vol. 118(C).
    13. Cai, Xueyuan & Li, Jianbin & Lian, Zhaotong & Liu, Zhixin, 2022. "Fixed allocation of capacity for multiple retailers under demand competition," Omega, Elsevier, vol. 110(C).
    14. Tava Lennon Olsen & Rodney P. Parker, 2014. "On Markov Equilibria in Dynamic Inventory Competition," Operations Research, INFORMS, vol. 62(2), pages 332-344, April.

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