Mapping energy-efficiency technological advances in home appliances.

The present study uses an original dataset on four large energy-efficient appliances and provides a methodology for: i) mapping components related to energy efficiency improvements; ii) mapping their evolution over time; iii) testing the technological fungibility of these components. Our analysis model exploits an original patent selection process and the concept of technological relatedness using co-occurrence analysis of patent classes as input for Self-Organising Maps, an unsupervised artificial neural network able to represent high-dimensional data in visually attractive and low-dimensional distance-based maps. The results confirm the pervasive nature of energy efficiency to be nested in many technological components. In addition, we show that a dematerialisation process has affected the evolution of energy efficiency technologies over time, in a technological space characterised by a high level of complexity and variety.