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Compete in Price or Service?—A Study of Personalized Pricing and Money Back Guarantees

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  • Chen, Bintong
  • Chen, Jing

Abstract

Retailers use both pricing and service strategies to respond to intensified competition. Here we develop a duopoly model to investigate the impact of the increasingly popular personalized pricing strategy (PPS) and the widely used Money Back Guarantee (MBG) customer returns policy. We consider two retailers who differ in customer satisfaction rates. Each retailer chooses a pricing strategy, PPS or uniform pricing, and a product return strategy, MBG or ‘no returns.’ We show that both PPS and MBG are dominant strategies, but their impact on retailers’ prices and profits are different; while PPS intensifies price competition and may lead to a prisoner’s dilemma in which both retailers may lose profit, MBG mitigates price competition and may result in a Pareto improvement in both retailers’ profits. Both PPS and MBG increase the size of the overall market, but not the total duopoly profit. The total customer surplus and social welfare may increase under either strategy. In addition, we obtain some interesting observations as to how our results may change if the product quality/customer satisfaction rate is endogenously chosen in the duopoly. Some of our findings are in contrast to related results reported in the literature.

Suggested Citation

  • Chen, Bintong & Chen, Jing, 2017. "Compete in Price or Service?—A Study of Personalized Pricing and Money Back Guarantees," Journal of Retailing, Elsevier, vol. 93(2), pages 154-171.
  • Handle: RePEc:eee:jouret:v:93:y:2017:i:2:p:154-171
    DOI: 10.1016/j.jretai.2016.12.005
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    1. Neeraj Arora & Xavier Dreze & Anindya Ghose & James Hess & Raghuram Iyengar & Bing Jing & Yogesh Joshi & V. Kumar & Nicholas Lurie & Scott Neslin & S. Sajeesh & Meng Su & Niladri Syam & Jacquelyn Thom, 2008. "Putting one-to-one marketing to work: Personalization, customization, and choice," Marketing Letters, Springer, vol. 19(3), pages 305-321, December.
    2. Alessandro Acquisti & Hal R. Varian, 2005. "Conditioning Prices on Purchase History," Marketing Science, INFORMS, vol. 24(3), pages 367-381, May.
    3. Mostard, Julien & Teunter, Ruud, 2006. "The newsboy problem with resalable returns: A single period model and case study," European Journal of Operational Research, Elsevier, vol. 169(1), pages 81-96, February.
    4. B. P. S. Murthi & Sumit Sarkar, 2003. "The Role of the Management Sciences in Research on Personalization," Management Science, INFORMS, vol. 49(10), pages 1344-1362, October.
    5. Greg Shaffer & Z. John Zhang, 2002. "Competitive One-to-One Promotions," Management Science, INFORMS, vol. 48(9), pages 1143-1160, September.
    6. Bruce McWilliams, 2012. "Money-Back Guarantees: Helping the Low-Quality Retailer," Management Science, INFORMS, vol. 58(8), pages 1521-1524, August.
    7. Andy A. Tsay & Narendra Agrawal, 2000. "Channel Dynamics Under Price and Service Competition," Manufacturing & Service Operations Management, INFORMS, vol. 2(4), pages 372-391, August.
    8. Suwelack, Thomas & Hogreve, Jens & Hoyer, Wayne D., 2011. "Understanding Money-Back Guarantees: Cognitive, Affective, and Behavioral Outcomes," Journal of Retailing, Elsevier, vol. 87(4), pages 462-478.
    9. Greg Shaffer & Z. John Zhang, 1995. "Competitive Coupon Targeting," Marketing Science, INFORMS, vol. 14(4), pages 395-416.
    10. K. Sridhar Moorthy, 1988. "Product and Price Competition in a Duopoly," Marketing Science, INFORMS, vol. 7(2), pages 141-168.
    11. Vidyanand Choudhary & Anindya Ghose & Tridas Mukhopadhyay & Uday Rajan, 2005. "Personalized Pricing and Quality Differentiation," Management Science, INFORMS, vol. 51(7), pages 1120-1130, July.
    12. Yuxin Chen & Ganesh Iyer, 2002. "Research Note Consumer Addressability and Customized Pricing," Marketing Science, INFORMS, vol. 21(2), pages 197-208, November.
    13. Fernando Bernstein & Awi Federgruen, 2007. "Coordination Mechanisms for Supply Chains Under Price and Service Competition," Manufacturing & Service Operations Management, INFORMS, vol. 9(3), pages 242-262, January.
    14. Goker Aydin & Serhan Ziya, 2009. "Technical Note---Personalized Dynamic Pricing of Limited Inventories," Operations Research, INFORMS, vol. 57(6), pages 1523-1531, December.
    15. Fernando Bernstein & Awi Federgruen, 2004. "A General Equilibrium Model for Industries with Price and Service Competition," Operations Research, INFORMS, vol. 52(6), pages 868-886, December.
    16. Shiou Shieh, 1996. "Price and Money‐Back Guarantees as Signals of Product Quality," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 5(3), pages 361-377, September.
    17. Heiman, Amir & McWilliams, Bruce & Zilberman, David, 2001. "Demonstrations and money-back guarantees: market mechanisms to reduce uncertainty," Journal of Business Research, Elsevier, vol. 54(1), pages 71-84, October.
    18. Sridhar Moorthy & Kannan Srinivasan, 1995. "Signaling Quality with a Money-Back Guarantee: The Role of Transaction Costs," Marketing Science, INFORMS, vol. 14(4), pages 442-466.
    19. Yuxin Chen & Chakravarthi Narasimhan & Z. John Zhang, 2001. "Individual Marketing with Imperfect Targetability," Marketing Science, INFORMS, vol. 20(1), pages 23-41, November.
    20. Lei, Jing & de Ruyter, Ko & Wetzels, Martin, 2008. "Consumer Responses to Vertical Service Line Extensions," Journal of Retailing, Elsevier, vol. 84(3), pages 268-280.
    21. Eric T. Anderson & Karsten Hansen & Duncan Simester, 2009. "The Option Value of Returns: Theory and Empirical Evidence," Marketing Science, INFORMS, vol. 28(3), pages 405-423, 05-06.
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