A review of methods to analyze technological change in industry

Abstract

There is an urgency to accelerate the innovation, development, and deployment of low-carbon industrial processes. Reviewing existing insights into how to achieve rapid technological change may be useful to assist this acceleration. Literature offers a set of approaches to model learning-by-doing and cost reductions, such as the learning curve methodology. However, it is debated if it can accurately describe and project cost reductions for low-carbon industrial processes. The goal of this work is threefold. First, to give more insight into what factors may explain the speed of innovation and technological change of low-carbon energy technologies. Second, to review existing approaches to model innovation and technological change of energy technologies and industrial processes. Third, to devise a framework to study technological learning of industrial processes. This work presents three main outcomes. First, we report more than 30 barriers and drivers of technological change. Second, we present a list of learning curve models and complementary methodologies to represent and/or explain these barriers and drivers. Third, we propose a framework to model technological learning of low-carbon industrial processes.