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New-product success in the pharmaceutical industry: how many bites at the cherry?

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  • Marcel Corstjens
  • Edouard Demeire
  • Ira Horowitz

Abstract

Using quarterly data for 56 new ethical-drug products launched between 1989 and 1996, we estimate the coefficients of a regression equation that has cumulative future sales beyond the forecast period as its dependent variable and third-quarter sales, post-launch product improvements and promotional activities, pre-launch product quality and speed to market, and market growth as the independent variables. We find the future success of a new product to be detectable as early as the third quarter after launch, and that while post-launch promotional activities can contribute to that success, if the product has not shown signs of life by the third quarter it is unlikely to do so afterwards. The implication is that being first to the market can contribute to the success of a new drug, as can having the highest-quality drug, though neither being first nor being best is necessary. Rather, a new drug can be both the first and the best in its product category, but if strong signs of success do not appear within nine months after launch, the drug is likely to be fighting a losing uphill battle thereafter, even in a growing market. Or, at least in pharmaceuticals, you get only one bite at the cherry.

Suggested Citation

  • Marcel Corstjens & Edouard Demeire & Ira Horowitz, 2005. "New-product success in the pharmaceutical industry: how many bites at the cherry?," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 14(4), pages 319-331.
    • Handle: RePEc:taf:ecinnt:v:14:y:2005:i:4:p:319-331
    DOI: 10.1080/1043859042000312729
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    References listed on IDEAS

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    Cited by:

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    3. Fraenkel, Stefan & Haftor, Darek M. & Pashkevich, Natallia, 2016. "Salesforce management factors for successful new product launch," Journal of Business Research, Elsevier, vol. 69(11), pages 5053-5058.
    4. Susan Brudvig & Michael J. Brusco & J. Dennis Cradit, 2019. "Joint selection of variables and clusters: recovering the underlying structure of marketing data," Journal of Marketing Analytics, Palgrave Macmillan, vol. 7(1), pages 1-12, March.

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