How fast is this novel technology going to be a hit? Antecedents predicting follow-on inventions

Michele Pezzoni, Reinhilde Veugelers, Fabiana Visentin*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Despite scholars’ high interest in identifying inventions that have a big impact, little attention has been devoted to investigating what drives how (fast) novel technologies embodied in these inventions are re-used in subsequent inventions. We overcome this limitation by empirically identifying novel technologies, mapping their re-use trajectories, and examining the characteristics of the novel technologies affecting trajectories’ shape. Using patent data, we identify on a large scale novel technologies as new combinations of existing technological components. The first invention using the new combination marks the origin of the trajectory, while all the subsequent inventions re-using the same new combination shape the technological trajectory. In our study sample, we identify 10,782 technological trajectories. For each of these trajectories, we identify its take off time and its maximum technological impact, as defined by its maximum number of follow-on inventions. We find that an S-shaped curve provides high goodness of fit for our trajectories, but that there is substantial heterogeneity in take off time and maximum technological impact. In searching for the antecedent characteristics of the novel technologies shaping their trajectories, we find that complex novel technologies resulting from combining dissimilar technological components with strong science-based content are associated with trajectories showing a long take off time but with a high technological impact. In contrast, combining similar components that are familiar to inventors, results in a short take off time but a low technological impact.
Original languageEnglish
Article number104454
JournalResearch Policy
Volume51
Issue number3
Early online date2022
DOIs
Publication statusPublished - Apr 2022

JEL classifications

  • o33 - "Technological Change: Choices and Consequences; Diffusion Processes"

Keywords

  • novel technologies
  • technological trajectories
  • antecedents
  • take off time
  • technological impact

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