The present study employs patent data on three groups of large energy-efficient appliances (i.e. freezers/refrigerators, washing machines and dishwashers) and provides a methodology for (i) mapping components related to energy efficiency improvements, (ii) mapping their evolution over time and (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 (SOMs), an unsupervised artificial neural network able to represent high-dimensional data in a visually attractive and two-dimensional distance-based map. 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 technology space characterised by a high level of complexity and variety. Energy efficiency has links with information technologies embodied in the appliances, which are far from their maturity path. Consequently, innovation and information policies are of utmost importance in order to achieve more ambitious energy efficiency targets in the groups of appliances analysed.
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