Extending the TPB of residential waste sorting with situational factors using a data-driven approach: The case of Gothenburg, Sweden

Path diagram resulting from the Structural Equation Model presented in the article. • Extension of core TPB model with Knowledge and situational factors. • SEM validate TPB for waste sorting behaviour. • Relevance of perceived knowledge and convenience in waste sorting. • Convenience as distance to bins impacts waste sorting. • Recommendations for integrated models in urban waste management policy. Waste separation at source is perceived as an effective Municipal Waste Management strategy, and the success depends on understanding the drivers of proper waste sorting behaviour. The Theory of Planned Behaviour (TPB) has been extensively applied to determining the importance of different psychological constructs in waste sorting behaviour. Despite evidence of its validity in specific contexts, in urban contexts, one requires an understanding of how the built environment affects waste sorting behaviour. Furthermore, this study introduces the use of Exploratory Factor Analysis as a data-driven approach to define various TPB constructs from a collection of items, including situational factors such as distance to waste bins or the condition of recycling facilities. It shows how this technique outperforms the typical top-down approach of starting from pre-defined items assigned to its constructs. This study surveyed residents of Gothenburg, Sweden, to capture empirical data on factors that affect the planned behaviour of waste separation. Structural Equation Modelling (SEM) is used to evaluate the extended TPB model and extract the drivers of waste sorting behaviour. Results from the study can extend the application of TPB to inform urban planners about the location and maintenance of waste management infrastructure.