IDEAS home Printed from https://ideas.repec.org/h/pal/palchp/978-0-230-29477-6_10.html
   My bibliography  Save this book chapter

B2B Price Optimization Analytics

In: Revenue Management

Author

Listed:
  • Jon A. Higbie

Abstract

Business to business (B2B) pricing differs from business to consumer (B2C) pricing. In both paradigms modeling demand as a function of price is central, but the nature of demand in the two cases is different, necessitating different analytic models. B2C is characterized by large demand volumes, each transaction representing a very small proportion of total revenue. On the other hand, B2B is characterized by relatively smaller transaction volumes, with each transaction representing a much larger proportion of total revenue. The fundamental differences in transaction volumes and revenue per transaction require different analytic processes. In the B2C setting demand can be modeled in aggregate and individual price recommendations applied to multiple transactions. In the B2B setting, each transaction is analysed and priced individually, characteristics enabled by the relatively smaller volume of transactions, and necessitated by the much larger revenue impact of each transaction.

Suggested Citation

  • Jon A. Higbie, 2011. "B2B Price Optimization Analytics," Palgrave Macmillan Books, in: Ian Yeoman & Una McMahon-Beattie (ed.), Revenue Management, chapter 9, pages 120-135, Palgrave Macmillan.
    • Handle: RePEc:pal:palchp:978-0-230-29477-6_10
    DOI: 10.1057/9780230294776_10
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

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


    Cited by:

    1. Claudia Olimpia MOISÄ‚ & Lucian STANCIU-GORUN, 2019. "The Opportunity For The Introduction Of Prediction Models In Hotel Management Case Study Hotel Deva ***, Deva, Romania," Annales Universitatis Apulensis Series Oeconomica, Faculty of Sciences, "1 Decembrie 1918" University, Alba Iulia, vol. 1(21), pages 1-10.

    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:palchp:978-0-230-29477-6_10. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.