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The Long-term and Spillover Effects of Price Promotions on Retailing Platforms: Evidence from a Large Randomized Experiment on Alibaba

Author

Listed:
  • Dennis J. Zhang

    (Olin Business School, Washington University in St. Louis, St. Louis, Missouri 63130)

  • Hengchen Dai

    (Anderson School of Management, University of California, Los Angeles, California 90095)

  • Lingxiu Dong

    (Olin Business School, Washington University in St. Louis, St. Louis, Missouri 63130)

  • Fangfang Qi

    (Tmall Business Unit, Alibaba Group, Inc., 310023 Hangzhou, China)

  • Nannan Zhang

    (Tmall Business Unit, Alibaba Group, Inc., 310023 Hangzhou, China)

  • Xiaofei Liu

    (Tmall Business Unit, Alibaba Group, Inc., 310023 Hangzhou, China)

  • Zhongyi Liu

    (Tmall Business Unit, Alibaba Group, Inc., 310023 Hangzhou, China)

  • Jiang Yang

    (Tmall Business Unit, Alibaba Group, Inc., 310023 Hangzhou, China)

Abstract

Dynamic pricing through price promotions has been widely used by online retailers. We study how a promotion strategy, one that offers customers a discount for products in their shopping cart, affects customer behavior in the short and long term on a retailing platform. We conduct a randomized field experiment involving more than 100 million customers and 11,000 retailers with Alibaba Group, one of the world’s largest retailing platform. We randomly assign eligible customers to either receive promotions for products in their shopping cart (treatment group) or not receive promotions (control group). In the short term, our promotion program doubles the sales of promoted products on the day of promotion. In the long term, we causally document unintended consequences of this promotion program during the month after our treatment period. On the positive side, it boosts customer engagement, increasing the daily number of products that customers view and their purchase incidence on the platform. On the negative side, it intensifies strategic customer behavior in the posttreatment period in two ways: (1) by increasing the proportion of products that customers add to their shopping cart conditional on viewing them, possibly because of their intention to get more shopping cart promotions, and (2) by decreasing the price that customers subsequently pay for a product, possibly because of their strategic search for lower prices. Importantly, these long-term effects of price promotions on consumer engagement and strategic behavior spill over to sellers who did not previously offer promotions to customers. Finally, we examine heterogeneous treatment effects across promotion, seller, and consumer characteristics. These findings have important implications for platforms and retailers.

Suggested Citation

  • Dennis J. Zhang & Hengchen Dai & Lingxiu Dong & Fangfang Qi & Nannan Zhang & Xiaofei Liu & Zhongyi Liu & Jiang Yang, 2020. "The Long-term and Spillover Effects of Price Promotions on Retailing Platforms: Evidence from a Large Randomized Experiment on Alibaba," Management Science, INFORMS, vol. 66(6), pages 2589-2609, June.
  • Handle: RePEc:inm:ormnsc:v:66:y:2020:i:6:p:2589-2609
    DOI: 10.1287/mnsc.2019.3316
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    2. Kopalle, Praveen K. & Pauwels, Koen & Akella, Laxminarayana Yashaswy & Gangwar, Manish, 2023. "Dynamic pricing: Definition, implications for managers, and future research directions," Journal of Retailing, Elsevier, vol. 99(4), pages 580-593.
    3. Zikun Ye & Dennis J. Zhang & Heng Zhang & Renyu Zhang & Xin Chen & Zhiwei Xu, 2023. "Cold Start to Improve Market Thickness on Online Advertising Platforms: Data-Driven Algorithms and Field Experiments," Management Science, INFORMS, vol. 69(7), pages 3838-3860, July.
    4. Prakash, David & Spann, Martin, 2022. "Dynamic pricing and reference price effects," Journal of Business Research, Elsevier, vol. 152(C), pages 300-314.
    5. Yong Zha & Quan Li & Tingliang Huang & Yugang Yu, 2023. "Strategic Information Sharing of Online Platforms as Resellers or Marketplaces," Marketing Science, INFORMS, vol. 42(4), pages 659-678, July.
    6. Chen, Pingping & Zhao, Ruiqing & Yan, Yingchen & Zhou, Chi, 2021. "Promoting end-of-season product through online channel in an uncertain market," European Journal of Operational Research, Elsevier, vol. 295(3), pages 935-948.
    7. Ji, Guojun & Fu, Tianyu & Li, Shuhao, 2023. "Optimal selling format considering price discount strategy in live-streaming commerce," European Journal of Operational Research, Elsevier, vol. 309(2), pages 529-544.
    8. Xiaolong Guo & Shengming Zheng & Yugang Yu & Fuqiang Zhang, 2021. "Optimal Bundling Strategy for a Retail Platform Under Agency Selling," Production and Operations Management, Production and Operations Management Society, vol. 30(7), pages 2273-2284, July.
    9. Peng Vincent Zhang & Seoyoung Kim & Anindita Chakravarty, 2023. "Influence of pull marketing actions on marketing action effectiveness of multichannel firms: A meta-analysis," Journal of the Academy of Marketing Science, Springer, vol. 51(2), pages 310-333, March.
    10. Xie, Jiaping & Wei, Lihong & Zhu, Weijun & Zhang, Weisi, 2021. "Platform supply chain pricing and financing: Who benefits from e-commerce consumer credit?," International Journal of Production Economics, Elsevier, vol. 242(C).
    11. Wang, Qian & Chen, Hang, 2022. "Better or Worse? Effects of online promotion habits on customer value: An empirical study," Journal of Retailing and Consumer Services, Elsevier, vol. 68(C).
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    14. Zhang, Yanfen & Xu, Qi & Zhang, Guoqing, 2023. "Optimal contracts with moral hazard and adverse selection in a live streaming commerce market," Journal of Retailing and Consumer Services, Elsevier, vol. 74(C).

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