IDEAS home Printed from https://ideas.repec.org/a/inm/ormsom/v24y2022i4p2081-2097.html

Offering Free Upgrades Even Before Stocks Run Out: The Value of Proactive Upgrades

Author

Listed:
  • David Chen

    (School of Management and Economics, The Chinese University of Hong Kong, Shenzhen, China)

  • Christopher S. Tang

    (UCLA Anderson School of Management, University of California, Los Angeles, California)

  • Huihui Wang

    (SILC Business School, Shanghai University, Shanghai, China)

  • Rowan Wang

    (Department of Information Systems and Management Engineering, Southern University of Science and Technology, Shenzhen, China)

  • Yimin Yu

    (Department of Management Sciences, City University of Hong Kong, Hong Kong, China)

Abstract

Problem definition : When selling multiple products with different feature combinations over a short selling season, a seller often adopts a “reactive” upgrade policy by offering a free upgrade to the next-price-level product only after a customer’s preferred product is out of stock. However, when customers’ preferences are heterogeneous for different feature combinations, some unyielding customers may reject free upgrades. In this paper, we consider a new “proactive” upgrade policy under which the seller may offer free upgrades even before a product is out of stock. Academic/practical relevance : The proactive upgrade policy enables the seller to strategically keep some units of a product in reserve to secure future sales of this product for those unyielding customers. However, the value of the proactive upgrade policy over the traditional reactive upgrade policy remains unclear. Methodology : Given the product choice probability the “upgrade acceptance probability” of each arriving customer, we formulate the problem of how to offer proactive upgrades as a finite horizon dynamic program with an embedded Markov decision process, and we determine the optimal proactive upgrade policy. Results : By exploiting the underlying mathematical structure, we prove that the optimal value function possesses the “anti-multimodularity” property such that the optimal upgrade strategy under the proactive upgrade policy is governed by two state-dependent thresholds: one threshold dictates when to offer proactive upgrades, and the other threshold dictates when to offer reactive upgrades. We also show that the proactive upgrade policy can create significant value over the reactive upgrade policy when the next-price-level product has similar consumer utility or when the price sensitivity is intermediate. Managerial implications : We identify the conditions under which the proactive upgrade policy provides significant value over the traditional reactive upgrade policy. These results can be useful for sellers who sell variants of similar products with different feature combinations to customers with heterogeneous feature preferences.

Suggested Citation

  • David Chen & Christopher S. Tang & Huihui Wang & Rowan Wang & Yimin Yu, 2022. "Offering Free Upgrades Even Before Stocks Run Out: The Value of Proactive Upgrades," Manufacturing & Service Operations Management, INFORMS, vol. 24(4), pages 2081-2097, July.
  • Handle: RePEc:inm:ormsom:v:24:y:2022:i:4:p:2081-2097
    DOI: 10.1287/msom.2022.1084
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/msom.2022.1084
    Download Restriction: no

    File URL: https://libkey.io/10.1287/msom.2022.1084?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Tang, Christopher S., 2006. "Perspectives in supply chain risk management," International Journal of Production Economics, Elsevier, vol. 103(2), pages 451-488, October.
    2. Garrett van Ryzin & Siddharth Mahajan, 1999. "On the Relationship Between Inventory Costs and Variety Benefits in Retail Assortments," Management Science, INFORMS, vol. 45(11), pages 1496-1509, November.
    3. Dorothée Honhon & Vishal Gaur & Sridhar Seshadri, 2010. "Assortment Planning and Inventory Decisions Under Stockout-Based Substitution," Operations Research, INFORMS, vol. 58(5), pages 1364-1379, October.
    4. Eitan Altman & Bruno Gaujal & Arie Hordijk, 2000. "Multimodularity, Convexity, and Optimization Properties," Mathematics of Operations Research, INFORMS, vol. 25(2), pages 324-347, May.
    5. Dorothee Honhon & Sreelata Jonnalagedda & Xiajun Amy Pan, 2012. "Optimal Algorithms for Assortment Selection Under Ranking-Based Consumer Choice Models," Manufacturing & Service Operations Management, INFORMS, vol. 14(2), pages 279-289, April.
    6. A. Gürhan Kök & Marshall L. Fisher, 2007. "Demand Estimation and Assortment Optimization Under Substitution: Methodology and Application," Operations Research, INFORMS, vol. 55(6), pages 1001-1021, December.
    7. Christopher S. Tang & Kumar Rajaram & Ayd{i}n Alptekinou{g}lu & Jihong Ou, 2004. "The Benefits of Advance Booking Discount Programs: Model and Analysis," Management Science, INFORMS, vol. 50(4), pages 465-478, April.
    8. Kelly L. Haws & William O. Bearden, 2006. "Dynamic Pricing and Consumer Fairness Perceptions," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 33(3), pages 304-311, October.
    9. Serguei Netessine & Gregory Dobson & Robert A. Shumsky, 2002. "Flexible Service Capacity: Optimal Investment and the Impact of Demand Correlation," Operations Research, INFORMS, vol. 50(2), pages 375-388, April.
    10. Robert A. Shumsky & Fuqiang Zhang, 2009. "Dynamic Capacity Management with Substitution," Operations Research, INFORMS, vol. 57(3), pages 671-684, June.
    11. Qing Li & Peiwen Yu, 2014. "Multimodularity and Its Applications in Three Stochastic Dynamic Inventory Problems," Manufacturing & Service Operations Management, INFORMS, vol. 16(3), pages 455-463, July.
    12. Bruce Hajek, 1985. "Extremal Splittings of Point Processes," Mathematics of Operations Research, INFORMS, vol. 10(4), pages 543-556, November.
    13. Yueshan Yu & Xin Chen & Fuqiang Zhang, 2015. "Dynamic Capacity Management with General Upgrading," Operations Research, INFORMS, vol. 63(6), pages 1372-1389, December.
    14. Yehuda Bassok & Ravi Anupindi & Ram Akella, 1999. "Single-Period Multiproduct Inventory Models with Substitution," Operations Research, INFORMS, vol. 47(4), pages 632-642, August.
    15. Lingxiu Dong & Panos Kouvelis & Zhongjun Tian, 2009. "Dynamic Pricing and Inventory Control of Substitute Products," Manufacturing & Service Operations Management, INFORMS, vol. 11(2), pages 317-339, December.
    16. Wei Chen & Milind Dawande & Ganesh Janakiraman, 2014. "Fixed-Dimensional Stochastic Dynamic Programs: An Approximation Scheme and an Inventory Application," Operations Research, INFORMS, vol. 62(1), pages 81-103, February.
    17. Gérard P. Cachon & Christian Terwiesch & Yi Xu, 2005. "Retail Assortment Planning in the Presence of Consumer Search," Manufacturing & Service Operations Management, INFORMS, vol. 7(4), pages 330-346, August.
    18. William L. Cooper & Tito Homem-de-Mello, 2007. "Some Decomposition Methods for Revenue Management," Transportation Science, INFORMS, vol. 41(3), pages 332-353, August.
    19. Dorothée Honhon & Sridhar Seshadri, 2013. "Fixed vs. Random Proportions Demand Models for the Assortment Planning Problem Under Stockout-Based Substitution," Manufacturing & Service Operations Management, INFORMS, vol. 15(3), pages 378-386, July.
    20. Hossein Abouee‐Mehrizi & Opher Baron & Oded Berman & David Chen, 2019. "Managing Perishable Inventory Systems with Multiple Priority Classes," Production and Operations Management, Production and Operations Management Society, vol. 28(9), pages 2305-2322, September.
    21. Sobel, Joel, 1991. "Durable Goods Monopoly with Entry of New Consumers," Econometrica, Econometric Society, vol. 59(5), pages 1455-1485, September.
    22. Wedad Elmaghraby & P{i}nar Keskinocak, 2003. "Dynamic Pricing in the Presence of Inventory Considerations: Research Overview, Current Practices, and Future Directions," Management Science, INFORMS, vol. 49(10), pages 1287-1309, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yu, Yimin & Shou, Biying & Ni, Yaodong & Chen, Li, 2017. "Optimal production, pricing, and substitution policies in continuous review production-inventory systems," European Journal of Operational Research, Elsevier, vol. 260(2), pages 631-649.
    2. Shin, Hojung & Park, Soohoon & Lee, Euncheol & Benton, W.C., 2015. "A classification of the literature on the planning of substitutable products," European Journal of Operational Research, Elsevier, vol. 246(3), pages 686-699.
    3. Yalçın Akçay & Yunke Li & Harihara Prasad Natarajan, 2020. "Category Inventory Planning With Service Level Requirements and Dynamic Substitutions," Production and Operations Management, Production and Operations Management Society, vol. 29(11), pages 2553-2578, November.
    4. Mou, Shandong & Robb, David J. & DeHoratius, Nicole, 2018. "Retail store operations: Literature review and research directions," European Journal of Operational Research, Elsevier, vol. 265(2), pages 399-422.
    5. Lingxiu Dong & Panos Kouvelis & Zhongjun Tian, 2009. "Dynamic Pricing and Inventory Control of Substitute Products," Manufacturing & Service Operations Management, INFORMS, vol. 11(2), pages 317-339, December.
    6. Vasilyev, Andrey & Maier, Sebastian & Seifert, Ralf W., 2025. "Optimizing omnichannel assortments and inventory provisions under the multichannel attraction model," European Journal of Operational Research, Elsevier, vol. 324(3), pages 799-813.
    7. Transchel, Sandra, 2017. "Inventory management under price-based and stockout-based substitution," European Journal of Operational Research, Elsevier, vol. 262(3), pages 996-1008.
    8. Fernando Bernstein & A. Gürhan Kök & Lei Xie, 2015. "Dynamic Assortment Customization with Limited Inventories," Manufacturing & Service Operations Management, INFORMS, vol. 17(4), pages 538-553, October.
    9. Menezes, Mozart B.C. & Pinto, Roberto, 2022. "Product proliferation, cannibalisation, and substitution: A first look into entailed risk and complexity," International Journal of Production Economics, Elsevier, vol. 243(C).
    10. Tang, Christopher S., 2010. "A review of marketing-operations interface models: From co-existence to coordination and collaboration," International Journal of Production Economics, Elsevier, vol. 125(1), pages 22-40, May.
    11. Vashkar Ghosh & Anand Paul & Lingjiong Zhu, 2022. "Stocking Under Random Demand and Product Variety: Exact Models and Heuristics," Production and Operations Management, Production and Operations Management Society, vol. 31(3), pages 1006-1032, March.
    12. Lu, Fen & Xu, He & Chen, Pengyu & Zhu, Stuart X., 2018. "Joint pricing and production decisions with yield uncertainty and downconversion," International Journal of Production Economics, Elsevier, vol. 197(C), pages 52-62.
    13. Transchel, Sandra & Buisman, Marjolein E. & Haijema, Rene, 2022. "Joint assortment and inventory optimization for vertically differentiated products under consumer-driven substitution," European Journal of Operational Research, Elsevier, vol. 301(1), pages 163-179.
    14. Victor Martínez-de-Albéniz & Sumit Kunnumkal, 2022. "A Model for Integrated Inventory and Assortment Planning," Management Science, INFORMS, vol. 68(7), pages 5049-5067, July.
    15. Jie Zhang & Weijun Xie & Subhash C. Sarin, 2021. "Multiproduct Newsvendor Problem with Customer-Driven Demand Substitution: A Stochastic Integer Program Perspective," INFORMS Journal on Computing, INFORMS, vol. 33(3), pages 1229-1244, July.
    16. Zhang, Jie & Xie, Weijun & Sarin, Subhash C., 2021. "Robust multi-product newsvendor model with uncertain demand and substitution," European Journal of Operational Research, Elsevier, vol. 293(1), pages 190-202.
    17. David Chen & Ruoran Chen & Rowan Wang & Xuan Wang, 2025. "Optimal Control of Service Systems with Heterogeneous Servers and Priority Customers," Management Science, INFORMS, vol. 71(8), pages 6559-6579, August.
    18. Pol Boada-Collado & Victor Martínez-de-Albéniz, 2020. "Estimating and Optimizing the Impact of Inventory on Consumer Choices in a Fashion Retail Setting," Manufacturing & Service Operations Management, INFORMS, vol. 22(3), pages 582-597, May.
    19. Yi-Chun Akchen & Felipe Caro, 2026. "On Size Substitution and Its Role in Assortment and Inventory Planning," Manufacturing & Service Operations Management, INFORMS, vol. 28(2), pages 624-642, March.
    20. Ioannis Stamatopoulos & Christos Tzamos, 2019. "Design and Dynamic Pricing of Vertically Differentiated Inventories," Management Science, INFORMS, vol. 65(9), pages 4222-4241, September.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormsom:v:24:y:2022:i:4:p:2081-2097. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.