Diffusion of multi-generational high-technology products

Xiaohui Shi, Kiran Fernandes, Pattarin Chumnumpan

Research output: Contribution to journalArticlepeer-review

32 Citations (Scopus)

Abstract

Previous multi-generational product diffusion (MGPD) models were developed based on the diffusion patterns at that time, but may not be adopted in today's cases. By incorporating the effect of customers' forward-looking behaviour, this paper offers a parsimonious and original model that captures the dynamics of MGPD in current high-technology markets. We empirically examine the feasibility of using previous MGPD models and our suggested model to explain the market growth of new products from high-technology industries. The results show that the new model exhibits better curve fitting and forecasting performance than the prior MGPD models in the cases of this study. For marketing researchers, our model and its results suggest customers' forward looking behaviour is perhaps one of the key sales affecting factors that are missing in previous MGPD models in explaining nowadays' cases. For marketing practitioners, this study offers a valuable tool for marketing strategies in high-tech industries.

Original languageEnglish
Pages (from-to)162-176
Number of pages15
JournalTechnovation
Volume34
Issue number3
Early online date30 Dec 2013
DOIs
Publication statusPublished - Mar 2014

Keywords

  • Diffusion models
  • Multi generational
  • high technology products
  • forecasting

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