IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v39y1993i11p1319-1333.html
   My bibliography  Save this article

High-Definition Television: Assessing Demand Forecasts for a Next Generation Consumer Durable

Author

Listed:
  • Barry L. Bayus

    (Kenan-Flagler Business School, University of North Carolina, Carroll Hall, CB #3490, Chapel Hill, North Carolina 27599)

Abstract

High-Definition Television promises to be the next generation of television. This technology has broad implications for consumer markets, as well as the underlying manufacturing, technology development, and R&D activities of firms. Under increasing pressure from various groups, the U.S. government must make major policy and funding decisions based on its assessment of the likely demand for HDTV. Three published reports which forecast sales of HDTV after its scheduled introduction in the mid-1990s are available. Unfortunately, these forecasts offer widely differing perspectives on HDTV's potential. This paper presents an approach that links product segmentation (based on historical demand parameters, and marketing and manufacturing related variables) and demand forecasting for new products. The published HDTV forecasts are then assessed using this segmentation scheme. Differing from the Congressional Budget Office's earlier evaluation, this analysis indicates that one report is consistent with historical data from the home appliance industry.

Suggested Citation

  • Barry L. Bayus, 1993. "High-Definition Television: Assessing Demand Forecasts for a Next Generation Consumer Durable," Management Science, INFORMS, vol. 39(11), pages 1319-1333, November.
  • Handle: RePEc:inm:ormnsc:v:39:y:1993:i:11:p:1319-1333
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.39.11.1319
    Download Restriction: no

    Citations

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


    Cited by:

    1. repec:pal:jorsoc:v:59:y:2008:i:8:d:10.1057_palgrave.jors.2602457 is not listed on IDEAS
    2. Kim, Namwoon & Srivastava, Rajendra K. & Han, Jin K., 2001. "Consumer decision-making in a multi-generational choice set context," Journal of Business Research, Elsevier, vol. 53(3), pages 123-136, September.
    3. Goodwin, Paul & Meeran, Sheik & Dyussekeneva, Karima, 2014. "The challenges of pre-launch forecasting of adoption time series for new durable products," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1082-1097.
    4. Scott A. Shane & Karl T. Ulrich, 2004. "50th Anniversary Article: Technological Innovation, Product Development, and Entrepreneurship in Management Science," Management Science, INFORMS, vol. 50(2), pages 133-144, February.
    5. Kim, Moon-Soo & Kim, Ho, 2007. "Is there early take-off phenomenon in diffusion of IP-based telecommunications services?," Omega, Elsevier, vol. 35(6), pages 727-739, December.
    6. repec:eee:joinma:v:38:y:2017:i:c:p:12-28 is not listed on IDEAS
    7. Huh, Sung-Yoon & Lee, Chul-Yong, 2014. "Diffusion of renewable energy technologies in South Korea on incorporating their competitive interrelationships," Energy Policy, Elsevier, vol. 69(C), pages 248-257.
    8. Aydin, R. & Kwong, C.K. & Ji, P., 2015. "A novel methodology for simultaneous consideration of remanufactured and new products in product line design," International Journal of Production Economics, Elsevier, vol. 169(C), pages 127-140.
    9. Sachin Gupta & Dipak C. Jain & Mohanbir S. Sawhney, 1999. "Modeling the Evolution of Markets with Indirect Network Externalities: An Application to Digital Television," Marketing Science, INFORMS, vol. 18(3), pages 396-416.
    10. Cantamessa, Marco & Valentini, Carlo, 2000. "Planning and managing manufacturing capacity when demand is subject to diffusion effects," International Journal of Production Economics, Elsevier, vol. 66(3), pages 227-240, July.
    11. Kretschmer, Tobias & Rösner, Mariana, 2010. "Increasing Dominance - the Role of Advertising, Pricing and Product Design," Discussion Papers in Business Administration 11500, University of Munich, Munich School of Management.
    12. Shin, Jungwoo & Lee, Chul-Yong & Kim, Hongbum, 2016. "Technology and demand forecasting for carbon capture and storage technology in South Korea," Energy Policy, Elsevier, vol. 98(C), pages 1-11.
    13. Jonathan Lee & Peter Boatwright & Wagner A. Kamakura, 2003. "A Bayesian Model for Prelaunch Sales Forecasting of Recorded Music," Management Science, INFORMS, vol. 49(2), pages 179-196, February.
    14. repec:wsi:ijitdm:v:16:y:2017:i:06:n:s021962201550011x is not listed on IDEAS
    15. Lee, Chul-Yong & Huh, Sung-Yoon, 2017. "Forecasting new and renewable energy supply through a bottom-up approach: The case of South Korea," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 207-217.
    16. Lee, Hakyeon & Kim, Sang Gook & Park, Hyun-woo & Kang, Pilsung, 2014. "Pre-launch new product demand forecasting using the Bass model: A statistical and machine learning-based approach," Technological Forecasting and Social Change, Elsevier, vol. 86(C), pages 49-64.
    17. Gilvan C. Souza & Barry L. Bayus & Harvey M. Wagner, 2004. "New-Product Strategy and Industry Clockspeed," Management Science, INFORMS, vol. 50(4), pages 537-549, April.

    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:ormnsc:v:39:y:1993:i:11:p:1319-1333. 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). General contact details of provider: http://edirc.repec.org/data/inforea.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.