Global Tech Mining Conference September 5, 2012, Montreal, Quebec, Canada
Using the corpus of scientific and technical (S&T) publications as evidence, technology forecasting (TF) methodologies and indicators can be applied to reduce risks in the planning and development of research investment strategies. They complement methodologies based on expert opinions. The identification of emerging and potentially disruptive technologies is a core TF activity, yet a major challenge exists in the development of systematic and structured methods and processes. We report on a method that operationalizes the S-curve for the purpose of measuring technology readiness levels (TRL). This method consists of four steps including arithmetic standardization, linear regression, z-score normalization, and visualization using a four- quadrant bubble chart. In addition to the TRL indicator, we demonstrate with the example of another indicator namely R&D momentum that this method can be adapted to create new indicators. We explain the conceptual assumptions underlying the two indicators, and use examples to demonstrate how they have been applied to technology forecasting. This paper concludes with suggestions of how research can further develop the method and validate the indicators.