People do not change easily. They seem irrationally fond of the status quo and need a great deal of convincing before changing habits, even when the change appears beneficial. For instance, to get people to change modes of transportation, policymakers and researchers have thought up a great deal of incentives. Unfortunately, these incentives do not always have the desired effect or sometimes even have the adverse impact. Within the novel framework of Ergodicity Economics, it is possible to explains some of these failures by highlighting our overdependence on ensemble averages when designing incentives and judging the benefits of a modal shift. Indeed, when modelling human decision-making, ergodicity is often implicitly assumed. Consequently, ensemble averages judge the (ir)rationality of human decision-making. However, when we step away from this assumption, i.e., ensemble averages and time averages are no longer assumed to be equal, we can rationalize much of this seemingly irrational behaviour by looking at the time average of an individual in a dynamic and stochastic environment, instead of relying on the expected value of the process. Loss aversion, e.g., rather than being a compulsory drive to cling to what you already have, becomes a way of mitigating downside risk and eventual ruin. The status quo bias or the irrational hesitance towards change also makes sense in a non-ergodic world as uncertainty looms greater in a non-ergodic world than in an ergodic one. In this contribution, we will use transportation data to demonstrate that, we can shift the dialogue regarding strategies for inducing behavioural change from one that focuses on idiosyncratic preferences and irrationalities to one that enhances the objective drivers of change. Instead of looking into personal reasons for not opting for sustainable mobility, we look at the determining factors objectively keeping us from change in a non-ergodic world.