Abstract
Managers dealing with new products need to forecast sales growth, especially the time at which the sales would reach the peak, known as the peak sales time (T*). In most cases, they only have a few initial years' data to predict T*. Although product managers manage to predict T*, there is no method to date that can predict T* accurately. In this paper, we develop a new metric based on the diffusion modeling framework that can help in assessing the prediction accuracy of T*. This metric is built on the premise that observed sales growth is affected both by the force that systematically varies with time and by the non-systematic random forces. We show that the two forces must be carefully combined to assess if a predicted T* is accurate enough. In addition, we empirically prove the efficacy of the proposed metric.
Original language | English |
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Article number | 114054 |
Number of pages | 11 |
Journal | Journal of Business Research |
Volume | 165 |
DOIs | |
Publication status | Published - Oct 2023 |
Keywords
- New product diffusion
- Peak sales time
- Prediction accuracy
Indexed by
- ABDC-A
- SSCI
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Krishnan, T. V., Feng, S., & Jain, DC. (2023). Peak sales time prediction in new product sales: Can a product manager rely on it? Journal of Business Research, 165, Article 114054. https://doi.org/10.1016/j.jbusres.2023.114054