IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Log in (now much improved!) to save this article

The Little Engines That Could: Modeling the Performance of World Wide Web Search Engines

Listed author(s):
  • Eric T. Bradlow

    ()

    (The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104-6371)

  • David C. Schmittlein

    ()

    (The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104-6371)

Registered author(s):

    This research examines the ability of six popular Web search engines, individually and collectively, to locate Web pages containing common marketing/management phrases. We propose and validate a model for search engine performance that is able to represent key patterns of coverage and overlap among the engines. The model enables us to estimate the typical additional benefit of using multiple search engines, depending on the particular set of engines being considered. It also provides an estimate of the number of relevant Web pages found by any of the engines. For a typical marketing/management phrase we estimate that the “best” search engine locates about 50% of the pages, and all six engines together find about 90% of the total. The model is also used to examine how properties of a Web page and characteristics of a phrase affect the probability that a given search engine will find a given page. For example, we find that the number of Web page links increases the prospect that each of the six search engines will find it. Finally, we summarize the relationship between major structural characteristics of a search engine and its performance in locating relevant Web pages.

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

    File URL: http://dx.doi.org/10.1287/mksc.19.1.43.15180
    Download Restriction: no

    Article provided by INFORMS in its journal Marketing Science.

    Volume (Year): 19 (2000)
    Issue (Month): 1 (June)
    Pages: 43-62

    as
    in new window

    Handle: RePEc:inm:ormksc:v:19:y:2000:i:1:p:43-62
    Contact details of provider: Postal:
    7240 Parkway Drive, Suite 300, Hanover, MD 21076 USA

    Phone: +1-443-757-3500
    Fax: 443-757-3515
    Web page: http://www.informs.org/
    Email:


    More information through EDIRC

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

    as
    in new window


    1. Terry Elrod, 1988. "Choice Map: Inferring a Product-Market Map from Panel Data," Marketing Science, INFORMS, vol. 7(1), pages 21-40.
    2. Peter E. Rossi & Robert E. McCulloch & Greg M. Allenby, 1996. "The Value of Purchase History Data in Target Marketing," Marketing Science, INFORMS, vol. 15(4), pages 321-340.
    3. Roland T. Rust & David C. Schmittlein, 1985. "A Bayesian Cross-Validated Likelihood Method for Comparing Alternative Specifications of Quantitative Models," Marketing Science, INFORMS, vol. 4(1), pages 20-40.
    4. J. Yannis Bakos, 1997. "Reducing Buyer Search Costs: Implications for Electronic Marketplaces," Management Science, INFORMS, vol. 43(12), pages 1676-1692, December.
    Full references (including those not matched with items on IDEAS)

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    When requesting a correction, please mention this item's handle: RePEc:inm:ormksc:v:19:y:2000:i:1:p:43-62. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Mirko Janc)

    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 references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.