Scenarios for optimizing timing for new product exits: a trifecta of models' predictive performances
Benchmarking: An International Journal
ISSN: 1463-5771
Article publication date: 10 June 2022
Issue publication date: 11 May 2023
Abstract
Purpose
The purpose of the study is applying and comparing models that predict optimal time for new product exit based on its demand pattern and survivability. This is to decide whether or not to continue investing in new product development (NPD).
Design/methodology/approach
The study investigates the optimal time for new product exit within the hi-tech sector by applying three models: the dynamic learning demand model (DLDM), the generalized Bass model (GBM) and the hazard model (HM). Further, for inter- and intra-model comparison, the authors conducted a simulation, considering Weiner and exponential price functions to enhance generalizability.
Findings
While higher price volatility signifies an unstable technology, greater investment into research and development (R&D) and marketing results in higher product adoption rates. Imitators have a more prominent role than innovators in determining the longevity of hi-tech products.
Originality/value
The study conducts a comparison of three different models considering time-varying parameters. There are four scenarios, considering variations in advertising intensity and content, word-of-mouth (WOM) effect, price volatility effect and sunk cost effect.
Keywords
Acknowledgements
Erratum: It has come to the attention of the publisher that the article, Sharma, P. and Lichtenthal, D.J., “Scenarios for optimizing timing for new product exits: a trifecta of models’ predictive performances” published in Benchmarking: An International Journal listed the second author’s name incorrectly as David J. Lichtenthal. The second author’s name is J. David Lichtenthal. This article should now be cited as Sharma, P. and Lichtenthal, J.D. (2022), “Scenarios for optimizing timing for new product exits: a trifecta of models’ predictive performances”, Benchmarking: An International Journal, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/BIJ-01-2022-0038. This error was introduced in the editorial process and has now been corrected in the online version. The publisher sincerely apologises for this error and for any inconvenience caused.
The authors are highly thankful to the Editor and the editorial team for timely response and streamlined processing of the article. The authors also thank the anonymous reviewers for the salient feedback and suggestions that helped us to improve the structure, flow and articulation of our ideas through this article.
Citation
Sharma, P. and Lichtenthal, J.D. (2023), "Scenarios for optimizing timing for new product exits: a trifecta of models' predictive performances", Benchmarking: An International Journal, Vol. 30 No. 5, pp. 1506-1535. https://doi.org/10.1108/BIJ-01-2022-0038
Publisher
:Emerald Publishing Limited
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