Modelling Customer Preference for Sustainability Information via Clustering Analysis

Individual purchasing behavior has substantial impact on the environment and our society. To encourage sustainable consumption, this paper explores the application of clustering analysis techniques for modelling customer preference for sustainability information. This study has analyzed sales data provided by a furniture company that covers a one-year period and 7602 customer accounts. The analysis focused on the purchases of office chairs. Clustering analysis was applied to build preference models of the customers. This study has identified 3 typical customer behavior signatures w.r.t. the sustainability categories used in a sustainability index. We have shown how these models can be used to predict new customers’ sustainability preferences. The stability of the proposed solutions has been studied by comparing the preference models generated on different product groups. The results can provide insights for designing sustainability communication strategies to attract potential customers.