Abstract

Patents represent one of the most complete sources of information related to technological change, and they also contain much detailed information not available anywhere else. Thus, patents are the ‘big data’ source most closely related to future-oriented technology analysis (FTA). Not surprisingly, therefore, there is very significant practical and academic use of the patent database for understanding past technical change and attempting to forecast future change. This paper summarizes several new methods and demonstrates their combined effectiveness in establishing a cutting-edge capability for patent study not previously available. This capability can be stated as a link between the information in patents and the dynamics of technological change. The demonstrated capability relies upon the use of a database containing the rates of improvement for various technologies. We also specify the term we use for the analysed units of technology: a technological domain is a set of artefacts that meets a specific generic function while utilizing a specific set of engineering and scientific knowledge. This definition is unambiguous enough so technological domains can be linked with progress rates and are sufficiently flexible to accommodate the large scale and complexity of the patent database. The existence of an improvement rate database and its quality is a critical foundation for this paper. Establishing the overall capability also involves relating the rate of improvement of a technological domain to the patents in that domain. We show that a recently developed method called the classification overlap method (COM) provides a reliable and largely automated way to break the patent database into understandable technological domains where progress can be measured. In this paper, we show how this method overcomes the third limitation of the patent database. The major conclusion of the paper is that there is now an overall objective method named Patent Technology Rate Indicator (PTRI) for using just patent data to reliably estimate the rate of technological progress in a technological domain. Thus, the first link between the patent database information and the dynamics of technological change is now firmly established; robustness and back-casting tests have shown that the assertion of reliability is meaningful and that the estimate has predictive value. We demonstrate the key methodology of new elements (use of COM and rate estimation from the selected patent sets) for 15 technologies that some have thought have possible future importance. The 15 cases also demonstrate the usefulness of the overall method by estimating technological improvement rates that are significantly different for this group of technologies.

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