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Online Cash-back Shopping: Implications for Consumers and e-Businesses

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  • Yi-Chun (Chad) Ho

    (School of Business, George Washington University, Washington, DC 20052)

  • Yi-Jen (Ian) Ho

    (Smeal School of Business, Pennsylvania State University, University Park, Pennsylvania 16802)

  • Yong Tan

    (Michael G. Foster School of Business, University of Washington, Seattle, Washington 98195; School of Economics and Management, Tsinghua University, 100084 Beijing, China)

Abstract

Through reimbursing a portion of the transactional amount to some consumers in a form of cash back, merchants are able to exercise third-degree price discrimination by offering two asymmetric prices via an online dual channel. To better understand such a novel pricing mechanism, we develop a game theoretical model and start our analyses with a market consisting of one merchant, one affiliate site, and consumers heterogeneous in their product valuation. From a price point of view, cash-back shopping appears to provide site users with a saving opportunity since the effective post-cash-back price they pay is perceived to be lower than the regular price targeted at nonusers. However, we find that under some conditions, this seemingly lower price could be actually higher , compared with the optimal uniform price when the merchant does not price discriminate. An important implication is that all consumers may end up suffering from higher prices in the presence of the cash-back mechanism. This surprising result, referred to as the cash-back paradox , defies a common intuition that a price-discriminating firm must raise the price for one segment of consumers but decrease it for the other. We also develop two extensions to seek explanations behind various industry practices. We find that it is in a merchant’s best interest to affiliate with multiple sites, and the resulting competition improves overall market efficiency. Moreover, merchants who are disadvantageous in brand valuation should target price-sensitive consumers by strategically offering cash-back deals. Our results, consistent with several real-world observations, have useful implications for marketers.

Suggested Citation

  • Yi-Chun (Chad) Ho & Yi-Jen (Ian) Ho & Yong Tan, 2017. "Online Cash-back Shopping: Implications for Consumers and e-Businesses," Information Systems Research, INFORMS, vol. 28(2), pages 250-264, June.
  • Handle: RePEc:inm:orisre:v:28:y:2017:i:2:p:250-264
    DOI: 10.1287/isre.2017.0693
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    References listed on IDEAS

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    Cited by:

    1. Christino, Juliana Maria Magalhães & Silva, Thaís Santos & Cardozo, Erico Aurélio Abreu & de Pádua Carrieri, Alexandre & de Paiva Nunes, Patricia, 2019. "Understanding affiliation to cashback programs: An emerging technique in an emerging country," Journal of Retailing and Consumer Services, Elsevier, vol. 47(C), pages 78-86.
    2. Lifeng Mu & Xin Tang & Vijayan Sugumaran & Wei Xu & Xiangyang Sun, 2023. "Optimal rebate strategy for an online retailer with a cashback platform: commission-driven or marketing-based?," Electronic Commerce Research, Springer, vol. 23(1), pages 475-510, March.
    3. Peter Seele & Claus Dierksmeier & Reto Hofstetter & Mario D. Schultz, 2021. "Mapping the Ethicality of Algorithmic Pricing: A Review of Dynamic and Personalized Pricing," Journal of Business Ethics, Springer, vol. 170(4), pages 697-719, May.
    4. Hu, Li & Zhang, Mengwei & Wen, Xin, 2023. "Optimal distribution strategy of coupons on e-commerce platforms: Sufficient or scarce?," International Journal of Production Economics, Elsevier, vol. 266(C).
    5. Afonso Vieira, Valter & Agnihotri, Raj & de Almeida, Marcos Inácio Severo & Lopes, Evandro Luiz, 2022. "How cashback strategies yield financial benefits for retailers: The mediating role of consumers’ program loyalty," Journal of Business Research, Elsevier, vol. 141(C), pages 200-212.
    6. Guo Li & Hong Zheng & Mengqi Liu, 2020. "Reselling or drop shipping: Strategic analysis of E-commerce dual-channel structures," Electronic Commerce Research, Springer, vol. 20(3), pages 475-508, September.
    7. María Teresa Ballestar & Pilar Grau-Carles & Jorge Sainz, 2019. "Predicting customer quality in e-commerce social networks: a machine learning approach," Review of Managerial Science, Springer, vol. 13(3), pages 589-603, June.
    8. Xu, Lina & Roy, Abhijit, 2022. "Cashback as cash forward: The serial mediating effect of time/effort and money savings," Journal of Business Research, Elsevier, vol. 149(C), pages 30-37.
    9. Ye Qiu & Ram C. Rao, 2020. "Increasing Retailer Loyalty Through the Use of Cash Back Rebate Sites," Marketing Science, INFORMS, vol. 39(4), pages 743-762, July.
    10. Zhen Fang & Yi-Chun (Chad) Ho & Xue (Jane) Tan & Yong Tan, 2021. "Show Me the Money: The Economic Impact of Membership-Based Free Shipping Programs on E-Tailers," Information Systems Research, INFORMS, vol. 32(4), pages 1115-1127, December.

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