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Comments on “A New Product Growth for Model Consumer Durables The Bass Model”

Bass, Frank M.·2004·Management Science

Abstract

The paper that I authored and that was published in Management Science in 1969 (Bass 1969) has become widely known as the “Bass Model” (see Morrison and Raju 2004). The model of the diffusion of new products and technologies developed in the paper is one of the most widely applied models in management science. It was especially gratifying for me to learn that INFORMS members have voted the “Bass Model” paper as one of the Top 10 Most Influential Papers published in the 50-year history of Management Science in connection with the 50th anniversary of the journal. In this commentary on the paper I shall discuss some background and history of the development of the paper, the reasons why the model has been influential, some important extensions of the model, some examples of applications, and some examples of the frontiers of research involving the Bass Model. In the current period, in which there is much discussion about the marketing of applications of management science methods and practice, I hope that this commentary will be useful in providing insights about some of the properties of models that will be applied.

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Metadata

Authors
Bass, F. M.
Venue
Management Science
Published
2004-12
Volume
50
Issue
12_supplement
Pages
1833-1840
ISSN
  • 0025-1909 (ISSN-L)
  • 1526-5501
OpenAlex
W2069860303
Cited by
505
References
0
FWCI
4.72
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Comments on “A New Product Growth for Model Consumer Durables The Bass Model”. https://app.cochat.ai/papers/10.1287/mnsc.1040.0300
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Bass, F. M. (2004). Comments on “A New Product Growth for Model Consumer Durables The Bass Model”. Management Science. https://doi.org/10.1287/mnsc.1040.0300

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.