A MODELLING FRAMEWORK FOR DATA-DRIVEN DESIGN FOR SUSTAINABLE BEHAVIOUR IN HUMAN-MACHINE INTERACTIONS

As the society is already permeated by data, a data-driven approach to inform design for sustainable behaviour can help to identify misbehaviours and target sustainable behaviours to achieve, as well as to select and implement the most suitable design strategies to promote a behavioural change and monitor their effectiveness. This work addresses the open challenge of providing designers with a model for Human-Machine Interactions (HMI) that helps to identify relevant data to collect for inferring user behaviour related to environmental sustainability during product use. We propose a systematic modelling framework that combines constructs from existing representation techniques to identify the most critical variables for resources consumption, which are the determinants of potential misbehaviours related to HMI. The analysis is represented as a Behaviour-Inefficiency Model that graphically supports the analyst/designer to link user behaviours with a quantitative representation of resources consumption. The paper describes the model through an example of the use of a kettle and an additional application of the same approach to a washing machine, in order to point out its versatility for modelling more complex interactions.