Data-Driven Modelling of Behavioural Cost–Carbon Trade-offs for Smart Environmental Decision Support

Achieving meaningful carbon reduction in business contexts requires more than technological solutions; it demands an understanding of how individuals perceive and negotiate cost–carbon trade-offs. This study presents a data-driven empirical analysis of behavioural factors influencing engagement with carbon-reduction practices using primary survey data (n = 38). The research develops a quantitative framework that operationalises subjective perceptions into measurable constructs, including a Cost Sensitivity Index and a logistic behavioural engagement model. Results reveal that perceived cost is the dominant barrier to action and operates as a behavioural threshold: once cost becomes salient, the probability of engagement declines sharply. Behavioural segmentation further identifies distinct respondent profiles, including environmentally motivated actors, structurally constrained participants, and cost-sensitive sceptics, highlighting the limitations of uniform sustainability interventions. The study contributes a novel integration of behavioural analytics and decision-support modelling for environmental management. By transforming perceptual data into actionable modelling outputs, the findings support the design of intelligent, adaptive sustainability systems that better align technological capability with human decision-making. The research offers practical implications for policymakers and business leaders seeking to develop more effective, data-informed carbon-reduction strategies.