IDEAS home Printed from https://ideas.repec.org/a/pal/jorapm/v18y2019i2d10.1057_s41272-019-00187-5.html
   My bibliography  Save this article

Price differentiation model: its challenges and solutions

Author

Listed:
  • Amoy X. Yang

    (Analytics Consulting)

Abstract

Conventional price models resolved one optimal price that aims at maximizing an overall profit in universe. If the point-optimization can be further refined into multiple price-tiers, it is the price differentiation model that caters to different price perceptions in terms of customers’ engagements, preferences, affordability, and so forth. Modeling for differentiation virtually strives for an additional lift over the benchmark that is pre-established on ‘test’ versus ‘control’. Pricing model in conjunction with such an algorithm exhibits how to leverage marketing strategy by making right offers to right audiences. However, no pricing model is simple—not to mention differential complexity, from which true difference(s) to be discovered in many cases could be tricky, subtle or ambiguous. Analysts in price industry have long encountered difficulties when navigating a strong yet robust model, particularly in lack of literatures detailed with its procedures. This is where we come from to probe into its challenge and relevant solutions.

Suggested Citation

  • Amoy X. Yang, 2019. "Price differentiation model: its challenges and solutions," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 18(2), pages 123-132, April.
  • Handle: RePEc:pal:jorapm:v:18:y:2019:i:2:d:10.1057_s41272-019-00187-5
    DOI: 10.1057/s41272-019-00187-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41272-019-00187-5
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1057/s41272-019-00187-5?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. Praveen K. Kopalle & Carl F. Mela & Lawrence Marsh, 1999. "The Dynamic Effect of Discounting on Sales: Empirical Analysis and Normative Pricing Implications," Marketing Science, INFORMS, vol. 18(3), pages 317-332.
    2. Peter J. Danaher, 2002. "Optimal Pricing of New Subscription Services: Analysis of a Market Experiment," Marketing Science, INFORMS, vol. 21(2), pages 119-138, February.
    3. Ronald B. Larson, 1997. "Using price discrimination theory to plan promotions," Agribusiness, John Wiley & Sons, Ltd., vol. 13(4), pages 401-408.
    4. Eitan Gerstner & Duncan Holthausen, 1986. "Profitable Pricing When Market Segments Overlap," Marketing Science, INFORMS, vol. 5(1), pages 55-69.
    5. Ganesh Iyer & P.B. Seetharaman, 2003. "To Price Discriminate or Not: Product Choice and the Selection Bias Problem," Quantitative Marketing and Economics (QME), Springer, vol. 1(2), pages 155-178, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jeong, Misun & Yang, Kiseol & Kim, HaeJung Maria & Min, Jihye, 2024. "Curation subscription box services: Implications for the pet industry," Journal of Retailing and Consumer Services, Elsevier, vol. 76(C).

    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. Ozgun Caliskan Demirag & Ozgul Baysar & Pinar Keskinocak & Julie L. Swann, 2010. "The effects of customer rebates and retailer incentives on a manufacturer's profits and sales," Naval Research Logistics (NRL), John Wiley & Sons, vol. 57(1), pages 88-108, February.
    2. Michis Antonis A, 2009. "Regression Analysis of Marketing Time Series: A Wavelet Approach with Some Frequency Domain Insights," Review of Marketing Science, De Gruyter, vol. 7(1), pages 1-43, July.
    3. Kummer, Michael & Schulte, Patrick, 2014. "Money and privacy: Android market evidence," ZEW Discussion Papers 14-131, ZEW - Leibniz Centre for European Economic Research.
    4. Marshall Freimer & Dan Horsky, 2008. "Try It, You Will Like It—Does Consumer Learning Lead to Competitive Price Promotions?," Marketing Science, INFORMS, vol. 27(5), pages 796-810, 09-10.
    5. Kopalle, Praveen & Biswas, Dipayan & Chintagunta, Pradeep K. & Fan, Jia & Pauwels, Koen & Ratchford, Brian T. & Sills, James A., 2009. "Retailer Pricing and Competitive Effects," Journal of Retailing, Elsevier, vol. 85(1), pages 56-70.
    6. Andrés Elberg & Pedro M. Gardete & Rosario Macera & Carlos Noton, 2019. "Dynamic effects of price promotions: field evidence, consumer search, and supply-side implications," Quantitative Marketing and Economics (QME), Springer, vol. 17(1), pages 1-58, March.
    7. Craig J. Chapman & Thomas J. Steenburgh, 2011. "An Investigation of Earnings Management Through Marketing Actions," Management Science, INFORMS, vol. 57(1), pages 72-92, January.
    8. 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.
    9. Tülin Erdem & Susumu Imai & Michael Keane, 2003. "Brand and Quantity Choice Dynamics Under Price Uncertainty," Quantitative Marketing and Economics (QME), Springer, vol. 1(1), pages 5-64, March.
    10. Nicholas Economides & Katja Seim & V. Brian Viard, 2008. "Quantifying the benefits of entry into local phone service," RAND Journal of Economics, RAND Corporation, vol. 39(3), pages 699-730, September.
    11. Reza Ahmadi & B. Rachel Yang, 2000. "Parallel Imports: Challenges from Unauthorized Distribution Channels," Marketing Science, INFORMS, vol. 19(3), pages 279-294, March.
    12. Kusum L. Ailawadi & Praveen K. Kopalle & Scott A. Neslin, 2005. "Predicting Competitive Response to a Major Policy Change: Combining Game-Theoretic and Empirical Analyses," Marketing Science, INFORMS, vol. 24(1), pages 12-24, September.
    13. Guhl, Daniel, 2019. "Addressing endogeneity in aggregate logit models with time-varying parameters for optimal retail-pricing," European Journal of Operational Research, Elsevier, vol. 277(2), pages 684-698.
    14. Schlereth, Christian & Stepanchuk, Tanja & Skiera, Bernd, 2010. "Optimization and analysis of the profitability of tariff structures with two-part tariffs," European Journal of Operational Research, Elsevier, vol. 206(3), pages 691-701, November.
    15. Bernhard Baumgartner & Daniel Guhl & Thomas Kneib & Winfried J. Steiner, 2018. "Flexible estimation of time-varying effects for frequently purchased retail goods: a modeling approach based on household panel data," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(4), pages 837-873, October.
    16. Csilla Horváth & Dennis Fok, 2013. "Moderating Factors of Immediate, Gross, and Net Cross-Brand Effects of Price Promotions," Marketing Science, INFORMS, vol. 32(1), pages 127-152, July.
    17. Philipp Aschersleben & Winfried J. Steiner, 2024. "Dynamic pricing using flexible heterogeneous sales response models," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 46(1), pages 29-72, March.
    18. Heiman, Amir & Ofir, Chezy, 2010. "The effects of imbalanced competition on demonstration strategies," International Journal of Research in Marketing, Elsevier, vol. 27(2), pages 175-187.
    19. Fruchter, Gila E. & Sigué, Simon P., 2013. "Dynamic pricing for subscription services," Journal of Economic Dynamics and Control, Elsevier, vol. 37(11), pages 2180-2194.
    20. Eva Ascarza & Bruce G. S. Hardie, 2013. "A Joint Model of Usage and Churn in Contractual Settings," Marketing Science, INFORMS, vol. 32(4), pages 570-590, July.

    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:pal:jorapm:v:18:y:2019:i:2:d:10.1057_s41272-019-00187-5. 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.palgrave.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.