Patent Valuation - Impact Factors Through Business Intelligence

Abstract

This paper describes a way to analyze through the use of Business Intelligence (BI), the United States Patent & Trademark Office (USPTO) data base for patent impact valuation. The research covers the entire data base since 1976 - about 3.5 million patents and 18 million citations.

The article presents modified algorithms first constructed by the pioneers Jaffe & Trajtenberg (2002) that quantify and measure constructed forward and backward patent-importance values based on patent citation data. The new algorithms contribute a better analysis of patent-importance values. The modified algorithms which express the values "Forward Importance Patent" (FIP) and "Backward Importance Patent" (BIF) are calculated by citation information backward and forward, based on the first and second generation patent counts. Furthermore, we have replaced the artificial λ factor used in the previous algorithms with a measured factor. The outcome of these two modified indicators is the Patent Importance Factor (PIF). The new quantified impact figure better expresses the patent-valuation importance values. The modified algorithm particularly enlightens significant changes over time in patent innovation dynamic values and in the known Patent Impact Factor Indicators (PIFI).

Keywords: Business Intelligence, BI, Forward importance, Backward Importance Patent, Impact Factor

JEL Classification: C43