Explicitly searching for useful inventions: Dynamic relatedness and the costs of connecting versus synthesizing

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Abstract

Inventions combine technological features. When features are barely related, burdensomely broad knowledge is required to identify the situations that they share. When features are overly related, burdensomely broad knowledge is required to identify the situations that distinguish them. Thus, according to my first hypothesis, when features are moderately related, the costs of connecting and costs of synthesizing are cumulatively minimized, and the most useful inventions emerge. I also hypothesize that continued experimentation with a specific set of features is likely to lead to the discovery of decreasingly useful inventions; the earlier-identified connections reflect the more common consumer situations. Covering data from all industries, the empirical analysis provides broad support for the first hypothesis. Regressions to test the second hypothesis are inconclusive when examining industry types individually. Yet, this study represents an exploratory investigation, and future research should test refined hypotheses with more sophisticated data, such as that found in literature-based discovery research. © 2010 The Author(s).

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Hsieh, C. (2011). Explicitly searching for useful inventions: Dynamic relatedness and the costs of connecting versus synthesizing. Scientometrics, 86(2), 381–404. https://doi.org/10.1007/s11192-010-0290-9

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