IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v57y2019i11p3435-3465.html
   My bibliography  Save this article

An empirical analysis of the main drivers affecting the buyer surplus in E-auctions

Author

Listed:
  • Oktay Karabağ
  • Barış Tan

Abstract

We empirically examine the impacts of the product category, the auction format, the 2008 global financial crisis, the group purchasing, the contract type, the platform ownership, and the number of participating suppliers on the buyer surplus obtained from e-auctions. To this end, we collect a unique dataset from a purchasing organisation that offers e-auction solutions to its corporate customers. By using a standard Tobit model, we show that the product categories, the auction type, and the number of participating suppliers have significant effects on the decrease in the procurement prices with respect to the minimum of the initial submitted bids. It is observed that the 2008 global financial crisis led to an increase in the buyer surplus. We classify the product categories into three groups based on their impacts on the average of the decrease in the procurement prices. We show that the average decrease in procurement prices is higher for the group purchasing option than for the individual buying option. It is concluded that the types of contract between buyers and auctioneer and the platform ownership have no statistically significant effects on the average decrease in procurement prices.

Suggested Citation

  • Oktay Karabağ & Barış Tan, 2019. "An empirical analysis of the main drivers affecting the buyer surplus in E-auctions," International Journal of Production Research, Taylor & Francis Journals, vol. 57(11), pages 3435-3465, June.
  • Handle: RePEc:taf:tprsxx:v:57:y:2019:i:11:p:3435-3465
    DOI: 10.1080/00207543.2018.1536835
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2018.1536835
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/00207543.2018.1536835?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.

    Citations

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


    Cited by:

    1. Radovan Dráb & Tomáš Štofa & Radoslav Delina, 2022. "Analysis of the efficiency of electronic reverse auction settings: big data evidence," Electronic Commerce Research, Springer, vol. 22(2), pages 427-450, June.
    2. Aijun Liu & Yaxuan Xiao & Zengxian Li & Ruiyao Wang, 2022. "An agent‐based multiattribute reverse auction approach for online secondhand commodities," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(1), pages 129-145, January.

    More about this item

    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:taf:tprsxx:v:57:y:2019:i:11:p:3435-3465. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TPRS20 .

    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.