Driving impact? How imperfect displacement shapes heterogeneous rebound in carsharing

Green technologies, products, and services, such as carsharing, are commonly promoted as pathways to lower environmental impacts by increasing efficiency. Yet rebound effects, behavioral and economic responses to improved efficiency, may erode these environmental impact reductions. Many rebound studies assume perfect displacement, where a new technology or mode of service provision fully replaces an existing service on a one-to-one basis. While analytically convenient, this assumption overlooks real-world complexity and consumer heterogeneity. Using survey data from nearly 4500 Belgian carsharing users, we compare rebound estimates under perfect displacement with those based on reported shifts in mobility. Under the perfect displacement assumption, we find a 53% rebound effect. When accounting for imperfect displacement, however, rebound effects vary widely across users. While median effects remain positive (20%–46%), at the individual level rebound effects range from substantial net benefits to strong rebound (5th–95th percentile: −331% to 147%). A cluster analysis further reveals distinct user groups with systematically different impacts, underscoring that displacement patterns vary not only in scale but also in direction. These findings suggest that carsharing's environmental impact is highly user-dependent, and that relying on a single aggregate estimate may mask critical behavioral variations. As this case study demonstrates, accounting for imperfect displacement in rebound analysis is critical for advancing theory and for tailoring more effective policy interventions.