Impact of knowledge search practices on the originality of inventions: A study in the oil & gas industry through dynamic patent analysis

Quentin Plantec, Pascal Le Masson and Benoît Weil

Technological Forecasting and Social Change, 2021, vol. 168, issue C

Abstract: The paper suggests a new taxonomy of knowledge search modes to describe the creative process of new invention design, in particular how firms combine knowledge components from their own knowledge base—taking into account both the components and the structures of knowledge bases—with those from newly acquired or newly internally developed. Using network theory techniques, we defined four knowledge search modes: (1) refinement, (2) clustering, (3) absorption and (4) recomposition. We conducted an exploratory study on the oil & gas industry, reviewing 50,776 utility patents filed by 16 major firms between 1989 and 2016. The results showed, first, that firms relied to varying extents on different knowledge search modes in their invention design processes. Second, reviewing the technological originality of the designed inventions showed that simply absorbing new knowledge components, without major changes in knowledge base structure, was associated with low technological originality, but constituted one of the main knowledge search modes used by the analyzed firms. In contrast, major changes in knowledge base structure favored technological originality, with or without new knowledge components, but were nevertheless the least used mode. Understanding organizational learning practices associated with the phenomena described here can foster innovation performance in firms.

Keywords: Knowledge search; Patent analytics; Oil & gas industry; Technological originality; Knowledge base (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:168:y:2021:i:c:s0040162521002146

DOI: 10.1016/j.techfore.2021.120782

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