A New Methodology for Citation Dependent Patent Evaluations

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  • Patent evaluation methodologies reveal hidden information that enables business decisions. Many of these methodologies may be grouped into a prior art citation dependent category. The problem with this category is citation noise. Citation noise obscures an evaluation leading to very limited and erroneous results. Citation noise is also a gap not well understood by scholars. The empirical multi-case explanatory approach of this research examined 719 citations and found 87% of the citations were noise and 13% had interdependence with a patent. This research further found that interdependency between a citation and patent eliminates citation noise and identifies pertinent and dominant citations. The theoretical implications are a new understanding of citation noise and dependence, a novel interdependency framework and noise pertinence and dominant citation constructs. The practice implications are a novel unencumbered patent evaluation methodology where pertinent and dominant citations provide useful, meaningful evaluations and enable better stakeholder decision-making capabilities.

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  • Copyright © 2014 the author(s). Theses may be used for non-commercial research, educational, or related academic purposes only. Such uses include personal study, research, scholarship, and teaching. Theses may only be shared by linking to Carleton University Institutional Repository and no part may be used without proper attribution to the author. No part may be used for commercial purposes directly or indirectly via a for-profit platform; no adaptation or derivative works are permitted without consent from the copyright owner.
Date Created
  • 2014


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