Abstract
Energy consumption impacts the environment, humans’ well-being, comfort and quality of life. The article aimed to develop the original model of energy consumer segmentation, based on behavioural variables, which influence consumer decisions and motivations regardless of demographic, geographic and socio-cultural differences. The innovative contribution is the segmentation procedure, which fills the existing research gap and can be treated as a universal tool serving various groups of stakeholders for creating and implementing sustainable development policies. The methodology used for the segmentation is based on the original algorithm and involves classifying a consumer into the most appropriate group based on the measurement of the distance between the ideal class representative and a particular respondent. Several distance measures (e.g., Sokal−Michener, Goodall, Lin) were used, while the similarity of those classifications was verified using the adjusted Rand index. The segmentation involved adopting—a priori—five basic classes of consumers, varying in terms of motivation to save energy. The validation performed on a sample of 1606 respondents, carried out as part of the eco-bot project, verified both the classification approach adopted in the study and the accuracy of the assumptions. The application of the distance measures chosen for the study allowed for the assignment of 96.1% of the respondents to the appropriate classes, which yielded the following distribution: EI (33.9% of the respondents); DS (33.1%), AE (17.2%), O (7%) and I (4.9%).