No master key: A scoping review of paradigms for modelling homeowner energy refurbishment

Accelerating the residential energy transition is critical for global climate goals, yet an “energy efficiency gap” persists because homeowners frequently underinvest in available upgrades. While psychological theories explain this reluctance, current modelling tools often struggle to accurately represent it. This paper fills a methodological gap by providing a comparative scoping review of how well existing modelling paradigms capture complex homeowner refurbishment decisions. I evaluate four primary approaches – optimization, econometrics, system dynamics, and agent-based modelling – against key criteria including structural, dynamic, causal, and diagnostic validity, as well as empirical grounding. My findings reveal that no single method serves as a complete solution. Optimization models identify ideal technical pathways but lack behavioural realism. Econometric approaches offer statistical rigor but suffer from static, aggregated assumptions. System dynamics captures macro-level feedback but misses individual heterogeneity. Agent-based modelling represents bottom-up social dynamics but faces severe challenges regarding validation. I conclude that moving beyond methodological purism is essential. To design highly effective energy transition policies, the field must develop dynamically coupled hybrid models and apply them to cover existing implementation gaps such as process friction, event-based triggers, social network modelling, and supply-side constraints.