Rethinking cost–benefit analysis for transformative cycling policies: Integrating behavioral change and the logsum method

Transforming urban transport systems toward sustainability requires a critical re-evaluation of the appraisal methods used in policy analysis. While cycling infrastructure offers clear environmental, health, and livability benefits, its economic evaluation through cost–benefit analysis (CBA) remains underdeveloped. This paper presents a CBA of the “E-Bike City” concept in Zurich, which involves a radical reallocation of road space from cars to bicycles and e-bikes, implemented within a large-scale MATSim agent-based transport model. We address methodological challenges in applying CBA to cycling projects, specifically demand forecasting, valuing consumer surpluses, and treating subjective safety. Consumer surpluses are calculated using both the conventional value of travel time savings (VTTS) rule-of-half approach and the logsum method derived from discrete choice models. We compare results with and without assuming behavioral change in response to the new transport supply. Our findings demonstrate that the transport demand model as well as the consumer surplus methodology significantly affect appraisal outcomes. Without accounting for preference change, both methods yield negative net present values (NPVs). In contrast, when behavioral adaptation is included, the logsum method produces strongly positive NPVs. The analysis also reveals substantial reductions in external costs, crashes, and greenhouse gas emissions. However, long-term decarbonization goals remain out of reach without further systemic changes, given projected population growth. We conclude that CBAs focusing on transformative, sustainable mobility policies require methodologies that reflect long-term behavioral adaptation and utility beyond travel time savings, making the logsum method a more suitable tool for sustainable transport appraisal.