Diffusion of multi-generational high-technology products

Xiaohui Shi, Kiran Fernandes, Pattarin Chumnumpan

    Research output: Contribution to journalArticlepeer-review

    507 Downloads (Pure)

    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
    JournalTechnovation
    Volume34
    Issue number3
    Early online date30 Dec 2013
    DOIs
    Publication statusPublished - Mar 2014

    Keywords

    • Diffusion models
    • Multi-generational
    • High-technology products
    • Forecasting

    Fingerprint

    Dive into the research topics of 'Diffusion of multi-generational high-technology products'. Together they form a unique fingerprint.

    Cite this