Unveiling adoption dynamics:Psychological and contextual factors in sustainable technology transitions

Understanding how the adoption of sustainable technologies evolves over time is important to advancing sustainability transitions. This research develops an agent-based model (ABM) to explore adoption dynamics. It incorporates findings from a systematic meta-analysis of psychological factors and empirical data on decision-making in households and organisations. The conceptual framework underlying the model captures adoption as a gradual process that is influenced by psychological drivers, structural barriers and technology-specific characteristics. It therefore combines contextual, intrapersonal and technological levels and reflects the diversity of motivations and barriers in different contexts and for different adoption types. The ABM simulates emergent behaviours, feedback loops and system-wide dynamics, offering insights into how targeted interventions can influence the trajectory of adoption and accelerate the transition to sustainability. By capturing the interplay between adopter heterogeneity, contextual variability and dynamic phases, the framework provides a nuanced understanding of how individual choices lead to collective outcomes. This dynamic approach emphasises how motivations and barriers evolve over the course of the adoption process and highlights critical points where interventions can have the greatest impact. This research provides actionable recommendations for policymakers and practitioners and helps to develop strategies that address different needs and improve adoption rates. At a scientific level, it advances the integration of psychological insights with computational modelling, highlighting the value of interdisciplinary approaches to tackling complex societal challenges. By linking micro-level decision-making with macro-level outcomes, this study provides a comprehensive framework<br/>for understanding and promoting the adoption of sustainable technologies.