IDEAS home Printed from https://ideas.repec.org/a/kap/qmktec/v6y2008i2p109-137.html
   My bibliography  Save this article

Do frequency reward programs create switching costs? A dynamic structural analysis of demand in a reward program

Author

Listed:
  • Wesley Hartmann
  • V. Viard

Abstract

This paper examines a common assertion that customers in reward programs become "locked in" as they accumulate credits toward earning a reward. We define a measure of switching costs and use a dynamic structural model of demand in a reward program to illustrate that frequent customers' incentives to purchase are practically invariant to the number of credits. In our empirical example, these customers comprise over eighty percent of all rewards and over two-thirds of all purchases. Less frequent customers may face substantial switching costs when close to a reward, but rarely reach this state.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Wesley Hartmann & V. Viard, 2008. "Do frequency reward programs create switching costs? A dynamic structural analysis of demand in a reward program," Quantitative Marketing and Economics (QME), Springer, vol. 6(2), pages 109-137, June.
    • Handle: RePEc:kap:qmktec:v:6:y:2008:i:2:p:109-137
    DOI: 10.1007/s11129-007-9035-3
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11129-007-9035-3
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11129-007-9035-3?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 look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Rust, John, 1987. "Optimal Replacement of GMC Bus Engines: An Empirical Model of Harold Zurcher," Econometrica, Econometric Society, vol. 55(5), pages 999-1033, September.
    2. Paul Klemperer, 1987. "Markets with Consumer Switching Costs," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 102(2), pages 375-394.
    3. Daniel Ackerberg, 2009. "A new use of importance sampling to reduce computational burden in simulation estimation," Quantitative Marketing and Economics (QME), Springer, vol. 7(4), pages 343-376, December.
    4. Borenstein, S., 1993. "Repeat Buyer Programs in Network industries," Papers 93-10, California Davis - Institute of Governmental Affairs.
    5. Robert D. Cairns & John W. Galbraith, 1990. "Artificial Compatibility, Barriers to Entry, and Frequent-Flyer Programs," Canadian Journal of Economics, Canadian Economics Association, vol. 23(4), pages 807-816, November.
    6. Jean-Pierre Dube & Guenter J. Hitsch & Peter Rossi, 2006. "Do Switching Costs Make Markets Less Competitive?," 2006 Meeting Papers 514, Society for Economic Dynamics.
    7. Wesley Hartmann, 2006. "Intertemporal effects of consumption and their implications for demand elasticity estimates," Quantitative Marketing and Economics (QME), Springer, vol. 4(4), pages 325-349, December.
    8. Caminal, Ramon & Matutes, Carmen, 1990. "Endogenous switching costs in a duopoly model," International Journal of Industrial Organization, Elsevier, vol. 8(3), pages 353-373, September.
    9. Matthew Shum, 2004. "Does Advertising Overcome Brand Loyalty? Evidence from the Breakfast‐Cereals Market," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 13(2), pages 241-272, June.
    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. Jeremy T. Fox, 2010. "Estimating the Employer Switching Costs and Wage Responses of Forward-Looking Engineers," Journal of Labor Economics, University of Chicago Press, vol. 28(2), pages 357-412, April.
    2. Andrew Ching & Susumu Imai & Masakazu Ishihara & Neelam Jain, 2012. "A practitioner’s guide to Bayesian estimation of discrete choice dynamic programming models," Quantitative Marketing and Economics (QME), Springer, vol. 10(2), pages 151-196, June.
    3. Koray Cosguner & Tat Y. Chan & P. B. (Seethu) Seetharaman, 2018. "Dynamic Pricing in a Distribution Channel in the Presence of Switching Costs," Management Science, INFORMS, vol. 64(3), pages 1212-1229, March.
    4. Javier D. Donna, 2021. "Measuring long‐run gasoline price elasticities in urban travel demand," RAND Journal of Economics, RAND Corporation, vol. 52(4), pages 945-994, December.
    5. Donna, Javier D., 2018. "Measuring Long-Run Price Elasticities in Urban Travel Demand," MPRA Paper 90059, University Library of Munich, Germany.
    6. Daniel Ackerberg, 2009. "A new use of importance sampling to reduce computational burden in simulation estimation," Quantitative Marketing and Economics (QME), Springer, vol. 7(4), pages 343-376, December.
    7. Matthew Osborne, 2011. "Consumer learning, switching costs, and heterogeneity: A structural examination," Quantitative Marketing and Economics (QME), Springer, vol. 9(1), pages 25-70, March.
    8. Bryan Bollinger, 2015. "Green technology adoption: An empirical study of the Southern California garment cleaning industry," Quantitative Marketing and Economics (QME), Springer, vol. 13(4), pages 319-358, December.
    9. Ribeiro, Ricardo, 2010. "Consumer demand for variety: intertemporal effects of consumption, product switching and pricing policies," MPRA Paper 25812, University Library of Munich, Germany.
    10. Bryan Bollinger, 2015. "Green technology adoption: An empirical study of the Southern California garment cleaning industry," Quantitative Marketing and Economics (QME), Springer, vol. 13(4), pages 319-358, December.
    11. Ryan Monarch, 2014. ""It's Not You, It's Me": Breakup In U.S.-China Trade Relationships," Working Papers 14-08, Center for Economic Studies, U.S. Census Bureau.
    12. Federico Rossi & Pradeep K. Chintagunta, 2023. "Consumer Loyalty Programs and Retail Prices: Evidence from Gasoline Markets," Marketing Science, INFORMS, vol. 42(4), pages 794-818, July.
    13. Claudio Agostini, 2005. "El Mercado de Transporte Aéreo: Lecciones para Chile de una Revisión de la Literatura," ILADES-UAH Working Papers inv163, Universidad Alberto Hurtado/School of Economics and Business.
    14. Aviv Nevo & John L. Turner & Jonathan W. Williams, 2016. "Usage‐Based Pricing and Demand for Residential Broadband," Econometrica, Econometric Society, vol. 84, pages 411-443, March.
    15. Javier D. Donna & Pedro Pereira, 2024. "Structural Presumptions for Non-horizontal Mergers in the 2023 Merger Guidelines: A Primer and a Path Forward," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 65(1), pages 303-345, August.
    16. Yufeng Huang, 2022. "Tied Goods and Consumer Switching Costs," Marketing Science, INFORMS, vol. 41(1), pages 93-114, January.
    17. Huric Larsen, Jesper Fredborg, 2012. "Pricing behaviour at capacity constrained facilities," MPRA Paper 39362, University Library of Munich, Germany.
    18. Aguirregabiria, Victor & Mira, Pedro, 2010. "Dynamic discrete choice structural models: A survey," Journal of Econometrics, Elsevier, vol. 156(1), pages 38-67, May.
    19. Miettinen, Topi & Stenbacka, Rune, 2015. "Personalized pricing versus history-based pricing: implications for privacy policy," Information Economics and Policy, Elsevier, vol. 33(C), pages 56-68.
    20. Bakhtiari, Ali & Murthi, B.P.S. & Steffes, Erin, 2013. "Evaluating the Effect of Affinity Card Programs on Customer Profitability Using Propensity Score Matching," Journal of Interactive Marketing, Elsevier, vol. 27(2), pages 83-97.

    More about this item

    Keywords

    Switching costs; Reward programs; Dynamic programming; Discrete-choice; D40; L10; M31;
    All these keywords.

    JEL classification:

    • D40 - Microeconomics - - Market Structure, Pricing, and Design - - - General
    • L10 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - General
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

    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:kap:qmktec:v:6:y:2008:i:2:p:109-137. 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.