Identifying utility maximizers and regret minimizers in zero-energy house adoption by using individual-specific heterogeneous alternative decision rules

The transition to zero-energy houses (ZEHs) is a crucial step toward carbon neutrality in the residential sector. Yet, despite rising awareness and policy incentives, adoption remains limited due to the complex and heterogeneous decision-making processes involved in evaluating ZEH options. This study develops a hybrid choice modeling framework to examine how consumers apply different decision rules to ZEH attributes. Unlike conventional models that assume a uniform strategy, the proposed approach distinguishes between utility-maximizing and regret-minimizing behavior at the attribute level. It incorporates Bayesian stochastic search variable selection and sociodemographic characteristics to capture heterogeneity across individuals. Simulation results using synthetic data show that the model surpasses RUM- and RRM-only benchmarks in predictive accuracy and model fit. An empirical application with stated preference data from South Korean consumers reveals that regret minimization drives decisions on accessibility and CO₂ emissions, while utility maximization governs preferences for cost savings and price. Furthermore, residential location, housing type, commuting time, and household size significantly shape decision rules. These insights provide practical implications by clarifying which decision rule applies to which attribute, enabling policymakers and practitioners to design more targeted incentives and communications. A clearer understanding of consumer decision-making can accelerate ZEH adoption and support national decarbonization.