A model for the effective design of customized recycling programs through audience segmentation and modularity approaches

Abstract

One-size-fits-all approaches to encouraging household recycling behavior remain ineffective in densely populated urban areas due to their failure to address the heterogeneity in household needs/motivations for recycling. In contrast, extensive service customization escalates costs, requiring finding ways to use available resources effectively. We aim to develop a model to resolve this dilemma based on empirical research on 526 households sampled from a densely populated district of İzmir, Turkey. We applied a model-based recursive partitioning method to identify recycling behavior segments with their critical determinant factors. We then conducted a focus group study to investigate strategies for exploiting commonalities and considering differences across segments regarding their determinant factors. The decision tree analysis revealed the existence of 12 segments differentiated by the determinant factors of task knowledge, perceived convenience, moral norms, social norms, how to dispose of waste, and marital status. The focus group study suggested a range of informative, operational, and social intervention methods that address these factors in pairs or individually. Drawing on these findings, we develop a model that guides the design of recycling programs in which customized intervention methods can influence multiple segments simultaneously. Our empirical analysis shows that the methods elevating ‘perceived convenience’ and ‘task knowledge’ even slightly above the moderate level would increase the likelihood of recycling for more than half of households. Our model further suggests customized intervention methods which consider the segments' sizes, their current recycling likelihoods, and the potential improvements in these. This study contributes mainly by developing a model for designing customized recycling programs that maximize household contributions with the available budget/resources. Public managers can use our model to design effective recycling programs considering budget limitations.