IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v291y2020i1d10.1007_s10479-019-03193-3.html
   My bibliography  Save this article

Business analytics: online promotion with gift rewards

Author

Listed:
  • Huan Yu

    (University of Science and Technology of China)

  • Ye Shi

    (University of Science and Technology of China)

  • Yugang Yu

    (University of Science and Technology of China)

  • Jie Liu

    (University of Science and Technology of China)

  • Feng Yang

    (University of Science and Technology of China)

  • Jie Wu

    (University of Science and Technology of China)

Abstract

This study analytically examines online promotions with gift rewards based on data from a Chinese tea retailer, Huiliu. Gift rewards benefit Huiliu by improving promotional performance. However, they generate operational problems, especially by increasing the costs of holding gift inventory. To address Huiliu’s concerns about gift rewards, we first conduct an empirical study based on Huiliu’s promotional data to examine the effect of gift rewards on customer purchase behavior. The empirical result suggests that gift rewards induce more repeat customer purchases; however, they do not induce customers to spend more money. This empirical result reveals that the effect of gift rewards on customer purchase behavior leads to Huiliu’s intensifying gift inventory pressure. Based on this empirical finding, we develop a theoretical model that addresses gift inventory management. Because of the difficulty of precisely estimating the distributions of some key random variables (e.g., customer demands), we employ a robust approach to solve this model and provide near-optimal robust solutions. We finally present a case study to illustrate how to improve Huiliu’s gift allocation based on the robust inventory solutions. The numerical results show that the improved gift allocation significantly increases Huiliu’s profits (the average profit increment is 3.58%).

Suggested Citation

  • Huan Yu & Ye Shi & Yugang Yu & Jie Liu & Feng Yang & Jie Wu, 2020. "Business analytics: online promotion with gift rewards," Annals of Operations Research, Springer, vol. 291(1), pages 1061-1076, August.
    • Handle: RePEc:spr:annopr:v:291:y:2020:i:1:d:10.1007_s10479-019-03193-3
    DOI: 10.1007/s10479-019-03193-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-019-03193-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10479-019-03193-3?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. V. Kumar & Rajkumar Venkatesan & Tim Bohling & Denise Beckmann, 2008. "—The Power of CLV: Managing Customer Lifetime Value at IBM," Marketing Science, INFORMS, vol. 27(4), pages 585-599, 07-08.
    2. Berger, Paul D. & Bechwati, Nada Nasr, 2001. "The allocation of promotion budget to maximize customer equity," Omega, Elsevier, vol. 29(1), pages 49-61, February.
    3. Roland T. Rust & Tuck Siong Chung, 2006. "Marketing Models of Service and Relationships," Marketing Science, INFORMS, vol. 25(6), pages 560-580, 11-12.
    4. A. Ben-Tal & A. Nemirovski, 1998. "Robust Convex Optimization," Mathematics of Operations Research, INFORMS, vol. 23(4), pages 769-805, November.
    5. Tat Y. Chan & Chunhua Wu & Ying Xie, 2011. "Measuring the Lifetime Value of Customers Acquired from Google Search Advertising," Marketing Science, INFORMS, vol. 30(5), pages 837-850, September.
    6. Dimitris Bertsimas & Melvyn Sim, 2004. "The Price of Robustness," Operations Research, INFORMS, vol. 52(1), pages 35-53, February.
    7. S Delanote & R Leus & F Talla Nobibon, 2013. "Optimization of the annual planning of targeted offers in direct marketing," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 64(12), pages 1770-1779, December.
    8. Mauricio M. Palmeira & Joydeep Srivastava, 2013. "Free Offer ≠ Cheap Product: A Selective Accessibility Account on the Valuation of Free Offers," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 40(4), pages 644-656.
    9. Jinfeng Yue & Bintong Chen & Min-Chiang Wang, 2006. "Expected Value of Distribution Information for the Newsvendor Problem," Operations Research, INFORMS, vol. 54(6), pages 1128-1136, December.
    10. Sharad Borle & Siddharth S. Singh & Dipak C. Jain, 2008. "Customer Lifetime Value Measurement," Management Science, INFORMS, vol. 54(1), pages 100-112, January.
    11. Praveen K. Kopalle & Yacheng Sun & Scott A. Neslin & Baohong Sun & Vanitha Swaminathan, 2012. "The Joint Sales Impact of Frequency Reward and Customer Tier Components of Loyalty Programs," Marketing Science, INFORMS, vol. 31(2), pages 216-235, March.
    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. Kohsuke Matsuoka, 2020. "Exploring the interface between management accounting and marketing: a literature review of customer accounting," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 31(3), pages 157-208, September.
    2. Shipra Agrawal & Yichuan Ding & Amin Saberi & Yinyu Ye, 2012. "Price of Correlations in Stochastic Optimization," Operations Research, INFORMS, vol. 60(1), pages 150-162, February.
    3. Steffen Rebennack, 2022. "Data-driven stochastic optimization for distributional ambiguity with integrated confidence region," Journal of Global Optimization, Springer, vol. 84(2), pages 255-293, October.
    4. Xie, Chen & Wang, Liangquan & Yang, Chaolin, 2021. "Robust inventory management with multiple supply sources," European Journal of Operational Research, Elsevier, vol. 295(2), pages 463-474.
    5. Wenqing Chen & Melvyn Sim & Jie Sun & Chung-Piaw Teo, 2010. "From CVaR to Uncertainty Set: Implications in Joint Chance-Constrained Optimization," Operations Research, INFORMS, vol. 58(2), pages 470-485, April.
    6. Stefan Mišković, 2017. "A VNS-LP algorithm for the robust dynamic maximal covering location problem," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(4), pages 1011-1033, October.
    7. Chassein, André & Dokka, Trivikram & Goerigk, Marc, 2019. "Algorithms and uncertainty sets for data-driven robust shortest path problems," European Journal of Operational Research, Elsevier, vol. 274(2), pages 671-686.
    8. Beck, Yasmine & Ljubić, Ivana & Schmidt, Martin, 2023. "A survey on bilevel optimization under uncertainty," European Journal of Operational Research, Elsevier, vol. 311(2), pages 401-426.
    9. Antonio G. Martín & Manuel Díaz-Madroñero & Josefa Mula, 2020. "Master production schedule using robust optimization approaches in an automobile second-tier supplier," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(1), pages 143-166, March.
    10. Hamed Mamani & Shima Nassiri & Michael R. Wagner, 2017. "Closed-Form Solutions for Robust Inventory Management," Management Science, INFORMS, vol. 63(5), pages 1625-1643, May.
    11. Steve Zymler & Daniel Kuhn & Berç Rustem, 2013. "Worst-Case Value at Risk of Nonlinear Portfolios," Management Science, INFORMS, vol. 59(1), pages 172-188, July.
    12. Shunichi Ohmori, 2021. "A Predictive Prescription Using Minimum Volume k -Nearest Neighbor Enclosing Ellipsoid and Robust Optimization," Mathematics, MDPI, vol. 9(2), pages 1-16, January.
    13. Roberto Gomes de Mattos & Fabricio Oliveira & Adriana Leiras & Abdon Baptista de Paula Filho & Paulo Gonçalves, 2019. "Robust optimization of the insecticide-treated bed nets procurement and distribution planning under uncertainty for malaria prevention and control," Annals of Operations Research, Springer, vol. 283(1), pages 1045-1078, December.
    14. Wang, Xiaohan & Chen, Xiqun (Michael) & Xie, Chi & Cheong, Taesu, 2024. "Coordinative dispatching of shared and public transportation under passenger flow outburst," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 189(C).
    15. L. Jeff Hong & Zhiyuan Huang & Henry Lam, 2021. "Learning-Based Robust Optimization: Procedures and Statistical Guarantees," Management Science, INFORMS, vol. 67(6), pages 3447-3467, June.
    16. Soyster, A.L. & Murphy, F.H., 2013. "A unifying framework for duality and modeling in robust linear programs," Omega, Elsevier, vol. 41(6), pages 984-997.
    17. F. Davarian & J. Behnamian, 2022. "Robust finite-horizon scheduling/rescheduling of operating rooms with elective and emergency surgeries under resource constraints," Journal of Scheduling, Springer, vol. 25(6), pages 625-641, December.
    18. Corina Birghila & Tim J. Boonen & Mario Ghossoub, 2023. "Optimal insurance under maxmin expected utility," Finance and Stochastics, Springer, vol. 27(2), pages 467-501, April.
    19. Fanwen Meng & Jin Qi & Meilin Zhang & James Ang & Singfat Chu & Melvyn Sim, 2015. "A Robust Optimization Model for Managing Elective Admission in a Public Hospital," Operations Research, INFORMS, vol. 63(6), pages 1452-1467, December.
    20. Viktoryia Buhayenko & Dick den Hertog, 2017. "Adjustable Robust Optimisation approach to optimise discounts for multi-period supply chain coordination under demand uncertainty," International Journal of Production Research, Taylor & Francis Journals, vol. 55(22), pages 6801-6823, November.

    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:spr:annopr:v:291:y:2020:i:1:d:10.1007_s10479-019-03193-3. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.