IDEAS home Printed from https://ideas.repec.org/a/inm/ormksc/v1y1982i1p1-29.html
   My bibliography  Save this article

News: A Decision-Oriented Model for New Product Analysis and Forecasting

Author

Listed:
  • Lewis G. Pringle

    (BBDO, Inc., 383 Madison Avenue, New York, New York 10017)

  • R. Dale Wilson

    (BBDO, Inc., 383 Madison Avenue, New York, New York 10017)

  • Edward I. Brody

    (BBDO, Inc., 383 Madison Avenue, New York, New York 10017)

Abstract

Modeling efforts in the area of new product introductions have had a significant impact on marketing planning and strategy. One result of these efforts, BBDO's New Product Early Warning System (NEWS), has been used since the late 1960s to provide marketing managers with forecasts and diagnostic information regarding their new product strategies. This article presents the specification of the NEWS model, its parameter estimation methods, and its validation. A brief case history is also included which illustrates how the model is applied in a typical new product situation. NEWS is designed to use a variety of readily obtainable input data to generate forecasts of consumer awareness, trial, repeat purchase, usage, sales, and market share for a new brand. These outputs, combined with diagnostics from the model, can then be incorporated into the marketing plan in a way that will improve the new entry's chances of success in the marketplace. The model can be used to project early test market data (NEWS/Market); or it can be used to analyze pre-test market data (NEWS/Planner).

Suggested Citation

  • Lewis G. Pringle & R. Dale Wilson & Edward I. Brody, 1982. "News: A Decision-Oriented Model for New Product Analysis and Forecasting," Marketing Science, INFORMS, vol. 1(1), pages 1-29.
    • Handle: RePEc:inm:ormksc:v:1:y:1982:i:1:p:1-29
    DOI: 10.1287/mksc.1.1.1
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mksc.1.1.1
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mksc.1.1.1?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
    ---><---

    Citations

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


    Cited by:

    1. Meade, Nigel & Islam, Towhidul, 2010. "Using copulas to model repeat purchase behaviour - An exploratory analysis via a case study," European Journal of Operational Research, Elsevier, vol. 200(3), pages 908-917, February.
    2. Morwitz, Vicki G. & Steckel, Joel H. & Gupta, Alok, 2007. "When do purchase intentions predict sales?," International Journal of Forecasting, Elsevier, vol. 23(3), pages 347-364.
    3. Preyas S. Desai & David Bell & Gary Lilien & David Soberman, 2012. "Editorial --The Science-to-Practice Initiative: Getting New Marketing Science Thinking into the Real World," Marketing Science, INFORMS, vol. 31(1), pages 1-3, January.
    4. Edward I. Brody, 2001. "Marketing Engineering at BBDO," Interfaces, INFORMS, vol. 31(3_supplem), pages 74-81, June.
    5. Li, Hao & Elbakidze, Levan, 2016. "Application of Regression Discontinuity Approach in Experimental Auctions: A Case Study of Gaining Participants’ Trust and Their Willingness to Pay," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236149, Agricultural and Applied Economics Association.
    6. Peter S. Fader & Bruce G. S. Hardie & Chun-Yao Huang, 2004. "A Dynamic Changepoint Model for New Product Sales Forecasting," Marketing Science, INFORMS, vol. 23(1), pages 50-65, October.
    7. Urban, Glen L. & Weinberg, Bruce D. & Hauser, John R., 1994. "Premarket forecasting of really new products," Working papers 3689-94., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    8. Urban, Glen L. & Roberts, John H. & Hauser, John R., 1986. "Prelaunch forecasting of new automobiles : models and implementation," Working papers 1820-86., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    9. Richard C. Hanna & Scott D. Swain & Paul D. Berger, 2016. "Optimizing time-limited price promotions," Journal of Marketing Analytics, Palgrave Macmillan, vol. 4(2), pages 77-92, July.
    10. Jehoshua Eliashberg & Jedid-Jah Jonker & Mohanbir S. Sawhney & Berend Wierenga, 2000. "MOVIEMOD: An Implementable Decision-Support System for Prerelease Market Evaluation of Motion Pictures," Marketing Science, INFORMS, vol. 19(3), pages 226-243, January.
    11. Urban, Glen L. & Hulland, John S. & Weinberg, Bruce., 1990. "Modeling, categorization, elimination, and consideration for new product forecasting of consumer durables," Working papers 3206-90., Massachusetts Institute of Technology (MIT), Sloan School of Management.

    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:inm:ormksc:v:1:y:1982:i:1:p:1-29. 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 Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.