Understanding Residential Waste Sorting Behavior with Situational Factors: A Data-Driven Approach

Preprint, 2024

Waste separation at source is perceived as an effective Municipal Waste Management strategy, and the success of such a strategy 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, the TPB is typically applied starting from pre-defined items assigned to its constructs. 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 top-down approach. This study surveyed residents of Gothenburg, Sweden, to capture empirical data on factors known to affect the planned behaviour of waste separation. Structural Equation Modelling (SEM) is used to develop the extended TPB model and extract the drivers of waste sorting behaviour. Results from the study can extend the application of TPB to inform decision-making processes in residential waste sorting.