Predicting the Path of Technological Innovation: SAW vs. Moore, Bass, Gompertz, and Kryder
Ashish Sood (),
Gareth M. James (),
Gerard J. Tellis () and
Ji Zhu ()
Additional contact information
Ashish Sood: Goizueta School of Business, Emory University, Atlanta, Georgia 30322
Gareth M. James: Marshall School of Business, University of Southern California, Los Angeles, California 90089
Gerard J. Tellis: Marshall School of Business, University of Southern California, Los Angeles, California 90089
Ji Zhu: Department of Statistics, University of Michigan, Ann Arbor, Michigan 48109
Marketing Science, 2012, vol. 31, issue 6, 964-979
Abstract:
Competition is intense among rival technologies, and success depends on predicting their future trajectory of performance. To resolve this challenge, managers often follow popular heuristics, generalizations, or "laws" such as Moore's law. We propose a model, Step And Wait (SAW), for predicting the path of technological innovation, and we compare its performance against eight models for 25 technologies and 804 technologies-years across six markets. The estimates of the model provide four important results. First, Moore's law and Kryder's law do not generalize across markets; neither holds for all technologies even in a single market. Second, SAW produces superior predictions over traditional methods, such as the Bass model or Gompertz law, and can form predictions for a completely new technology by incorporating information from other categories on time-varying covariates. Third, analysis of the model parameters suggests that (i) recent technologies improve at a faster rate than old technologies; (ii) as the number of competitors increases, performance improves in smaller steps and longer waits; (iii) later entrants and technologies that have a number of prior steps tend to have smaller steps and shorter waits; but (iv) technologies with a long average wait time continue to have large steps. Fourth, technologies cluster in their performance by market.
Keywords: technology evolution; innovation; SAW model; Moore's law; Kryder's law; Bass model; technological prediction (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (14)
Downloads: (external link)
http://dx.doi.org/10.1287/mksc.1120.0739 (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:inm:ormksc:v:31:y:2012:i:6:p:964-979
Access Statistics for this article
More articles in Marketing Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().