How fast is this novel technology going to be a hit? Antecedents predicting follow-on inventions
研究了新技术被后续发明再利用的速度和程度，发现复杂、跨领域且基于科学的新技术虽起步慢但影响大，而熟悉相似的技术则起步快但影响小。
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.