Forecasting technology success based on patent data

Abstract

A novel method for forecasting technology success based on patent data is proposed. Four criteria, technology life cycle, diffusion speed, patent power, and expansion potential are considered for technology forecasting. Patent power and expansion potential are considered as technology scope indicators. A data fusion algorithm is applied to combine the results obtained from different criteria. The usefulness and potential of the proposed forecasting approach has been demonstrated using all U.S. patents related to three technologies, namely thin film transistor-liquid crystal display, flash memory system, and personal digital assistant. The results obtained from these patents demonstrate that the personal digital assistant technology is preferred over other technologies. Investments in thin film transistor liquid-crystal display and flash memory system technologies have equal priority. (C) 2015 Elsevier Inc. All rights reserved.