IDEAS home Printed from https://ideas.repec.org/a/ebl/ecbull/eb-14-00104.html
   My bibliography  Save this article

An HLM-model of online price premia

Author

Listed:
  • Evgeny A. Antipov

    (National Research University Higher School of Economics)

Abstract

Some Internet stores manage to charge prices that are significantly higher than market averages, therefore, obtaining some sort of price premium. This paper is dedicated to building a model that can be used to explain and predict a typical price premium that an Internet store charges for a specific product based on the information about the characteristics of the store and the features of the market for this product. Such models can provide support for pricing and assortment decisions: in particular, they allow detecting products that a store is likely to sell with the highest or the lowest markup based on price premia that are charged by stores with similar characteristics on similar markets.

Suggested Citation

  • Evgeny A. Antipov, 2014. "An HLM-model of online price premia," Economics Bulletin, AccessEcon, vol. 34(2), pages 892-900.
    • Handle: RePEc:ebl:ecbull:eb-14-00104
    as

    Download full text from publisher

    File URL: http://www.accessecon.com/Pubs/EB/2014/Volume34/EB-14-V34-I2-P84.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Glenn Ellison & Sara Fisher Ellison, 2009. "Search, Obfuscation, and Price Elasticities on the Internet," Econometrica, Econometric Society, vol. 77(2), pages 427-452, March.
    2. Varian, Hal R, 1980. "A Model of Sales," American Economic Review, American Economic Association, vol. 70(4), pages 651-659, September.
    3. Eric K. Clemons & Il-Horn Hann & Lorin M. Hitt, 2002. "Price Dispersion and Differentiation in Online Travel: An Empirical Investigation," Management Science, INFORMS, vol. 48(4), pages 534-549, April.
    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. Michael R. Baye & John Morgan, 2009. "Brand and Price Advertising in Online Markets," Management Science, INFORMS, vol. 55(7), pages 1139-1151, July.
    2. Evgeny A. Antipov, 2014. "The Determinants Of Online Merchant’s Price Premium: Evidence From Russia," HSE Working papers WP BRP 19/MAN/2014, National Research University Higher School of Economics.
    3. Nelson Granados & Alok Gupta & Robert J. Kauffman, 2010. "Research Commentary---Information Transparency in Business-to-Consumer Markets: Concepts, Framework, and Research Agenda," Information Systems Research, INFORMS, vol. 21(2), pages 207-226, June.
    4. Thomas A. Weber & Zhiqiang (Eric) Zheng, 2007. "A Model of Search Intermediaries and Paid Referrals," Information Systems Research, INFORMS, vol. 18(4), pages 414-436, December.
    5. Morgan, John & Ong, David & Zhong, Zemin (Zachary), 2018. "Location still matters: Evidence from an online shopping field experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 146(C), pages 43-54.
    6. Bachis, Enrico & Piga, Claudio A., 2011. "Low-cost airlines and online price dispersion," International Journal of Industrial Organization, Elsevier, vol. 29(6), pages 655-667.
    7. Edgardo Arturo Ayala Gaytán, 2009. "Social network externalities and price dispersion in online markets," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(2), pages 1-28, November.
    8. Michael R. Baye & John Morgan & Patrick Scholten, 2004. "Price Dispersion In The Small And In The Large: Evidence From An Internet Price Comparison Site," Journal of Industrial Economics, Wiley Blackwell, vol. 52(4), pages 463-496, December.
    9. Øystein Foros & Mai Nguyen-Ones & Frode Steen, 2021. "The Effects of a Day off from Retail Price Competition: Evidence on Consumer Behavior and Firm Performance in Gasoline Retailing," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 28(1), pages 49-87, January.
    10. Hämäläinen, Saara, 2018. "Competitive search obfuscation," Journal of Economic Dynamics and Control, Elsevier, vol. 97(C), pages 38-63.
    11. Dirk Bergemann & Benjamin Brooks & Stephen Morris, 2021. "Search, Information, and Prices," Journal of Political Economy, University of Chicago Press, vol. 129(8), pages 2275-2319.
    12. Wilson, Chris M., 2010. "Ordered search and equilibrium obfuscation," International Journal of Industrial Organization, Elsevier, vol. 28(5), pages 496-506, September.
    13. Glenn Ellison & Sara Fisher Ellison, 2005. "Lessons About Markets from the Internet," Journal of Economic Perspectives, American Economic Association, vol. 19(2), pages 139-158, Spring.
    14. Karine Lamiraud & Pierre Stadelmann, 2020. "Switching costs in competitive health insurance markets: The role of insurers' pricing strategies," Health Economics, John Wiley & Sons, Ltd., vol. 29(9), pages 992-1012, September.
    15. Fiona Scott Morton, 2006. "Consumer Benefit from Use of the Internet," NBER Chapters, in: Innovation Policy and the Economy, Volume 6, pages 67-90, National Bureau of Economic Research, Inc.
    16. Kenneth Gillingham, Hao Deng, Ryan Wiser, Naim Darghouth, Gregory Nemet, Galen Barbose, Varun Rai, and Changgui Dong, 2016. "Deconstructing Solar Photovoltaic Pricing," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    17. Monica Giulietti & Michael Waterson & Matthijs Wildenbeest, 2014. "Estimation of Search Frictions in the British Electricity Market," Journal of Industrial Economics, Wiley Blackwell, vol. 62(4), pages 555-590, December.
    18. Ioana Chioveanu & Jidong Zhou, 2013. "Price Competition with Consumer Confusion," Management Science, INFORMS, vol. 59(11), pages 2450-2469, November.
    19. Janssen, Aljoscha & Kasinger, Johannes, 2021. "Obfuscation and rational inattention in digitalized markets," SAFE Working Paper Series 306, Leibniz Institute for Financial Research SAFE.
    20. Franz Hackl & Michael Hölzl‐Leitner & Rudolf Winter‐Ebmer & Christine Zulehner, 2021. "Successful retailer strategies in price comparison platforms," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(5), pages 1284-1305, July.

    More about this item

    Keywords

    hierarchical linear modeling; e-Commerce; price dispersion;
    All these keywords.

    JEL classification:

    • M0 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - General
    • M3 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising

    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:ebl:ecbull:eb-14-00104. 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: John P. Conley (email available below). General contact details of provider: .

    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.