This is the first in a series of blogposts on using behavioral design to improve the sharing economy.
Electronic scooter sharing has taken North American cities by storm: today, shared e-scooter systems are operating in approximately 100 cities in the region and growing. This new mode of transit is encouraging individuals to leave their cars at home and contributing to a more rational use of private vehicles, helping reduce emissions, providing low-income individuals with a low-cost transit option and is making commuting more efficient and enjoyable. On the whole, they are great news for our cities! Unfortunately, the increase in the use of shared scooters has been accompanied with a large number of accidents, many of them quite severe. Since late 2017, according to Consumer Reports, the US alone experienced approximately 1,500 e-scooter related accidents.
Most of the accidents that occur are caused or exacerbated by a few key behaviors on the part of riders (using mobile phones while riding; not wearing a helmet; riding under the influence) and on the part of drivers (not yielding to riders; texting while driving; speeding). These behaviors are relatively easy to identify, but because they are driven by cognitive biases, social norms and other unconscious drivers of behavior, these behaviors are not easy to change, certainly not through information campaigns, incentives or even stricter rules alone. Improving road safety for e-scooter riders will certainly require structural change—updating our laws, improving urban design and making our infrastructure safer and more inclusive—but that won’t be enough. We must also use insights from behavioral science to effectively identify and permanently change the behaviors that are leading to accidents and making them more severe. But, what is behavioral science anyway?
Traditional theories of human behavior assume that when faced with challenges requiring action we are able to obtain complete information, are capable of processing all of that information perfectly and that based on those flawless analyses are able to make rational choices that lead to behaviors that linearly reflect our intentions. In reality, we know from our own experience and from research in various behavioral disciplines (cognitive science, social psychology and behavioral economics) that we rarely have access to complete information, that oftentimes we are unable to even make a choice and that, when we do decide, our choices and behaviors may not always end up aligning with our self-interest. Most of us agree, for instance, that we should be saving at least some of the money we are earning today for our retirement and most of us claim this is something we want to do. And yet, in spite of our knowledge and good intentions, a lot of us have a hard time saving for the future, especially beyond our mandatory contributions—we would much rather enjoy our money today and let our future self figure it out on their own. Why do we do this to ourselves?
Behavioral science seeks to understand the choices and behaviors we observe in our everyday lives, taking into account all of the internal and external influences that affect our choices and actions, especially those of which we may not be fully aware: cognitive biases and mental shortcuts, emotions, social influences and, critically, the physical, environmental and institutional contexts in which we operate. Fundamentally, behavioral science teaches us that we are complex creatures and that our choices and behaviors often systematically deviate from what would be predicted by standard theories of behavior or even from what we might be able to predict about ourselves from our own experience.
Leveraging this understanding and operationalizing it through behavioral design allows us to “nudge” ourselves and others towards desired behaviors and to improve decision-making. And when it comes to road safety, we at the BVA Nudge Unit believe that these behavioral tools can become instrumental for reducing accidents and saving lives, in turn ensuring that electric modes of transport like e-scooters can survive in our cities and continue to thrive.
A Behavioral Design Approach for Improving Safety on E-Scooters
Our behavioral practice at the BVA Nudge Unit consists of using insights from behavioral science to obtain an in-depth understanding of the forces at play in a given problem, diagnosing the root causes of those problems and designing and experimenting with solutions that directly address the barriers and levers identified through the behavioral diagnosis. This approach allows us to produce a fresh set of design solutions, or nudges, specifically customized to address the behavioral problem at hand. This ensures that the solutions we design are much better suited for resolving those specific behavioral issues than solutions derived from “best practices” borrowed from other contexts.
By way of example, consider how we can improve e-scooter safety by addressing the helmet problem. Most of us agree that wearing a helmet while riding an e-scooter, e-bike or electric skateboard can reduce the severity of accidents and, in the most extreme cases, even save our life. And yet, in spite of laws, rules, incentives and widely-available information oriented to promoting the use of helmets, most e-riders do not wear one. This fact attests to the strength of the behavioral barriers at play as we make the decision to wear a helmet or not:
This is not a comprehensive list of barriers to wearing a helmet, of course, and there can never be an exhaustive single list of obstacles, as these will vary from one context to another (most of us in the US have access to decent helmets, for instance, but in some developing countries, even obtaining a helmet could be a key barrier). Systematically uncovering these behavioral barriers in a given context, however, affords us with a good basis from which we can begin to experiment with behavioral solutions for nudging people to wear a helmet.
Currently, companies such as Bird, Lime and now even Lyft that offer shared electronic scooters through mobile apps are employing traditional levers to encourage helmet use: sending riders free helmets (incentives) and occasionally exhorting them to use them through the app (information). But, even with these strategies, riders are on the whole not using helmets. This is ultimately because these “solutions” are incomplete and are not fully addressing the broad array of underlying barriers. A better investment of time and effort would be to take advantage of the available touchpoints (namely the apps and the e-scooters themselves) to create solutions that directly address the behavioral barriers to wearing a helmet identified above.
Consider the following sample nudges: to override cognitive biases and emotions, we can create an in-app game that rewards riders (“helmet points”) for uploading a picture of them wearing a helmet right before riding; to reorient social cues and influences, create super-short videos that play automatically as the app starts with a compelling messenger (e.g. celebrity) reminding us that “not wearing a helmet” on e-scooters is an uncool, socially frowned-upon behavior; to address contextual features, in addition to giving users helmets, or in its stead, give them stylish, multi-purpose “helmet bags” or helmet attachment clips for conventional bags and backpacks.
Ultimately, these sample nudges are only a starting point. To fully solve the helmet problem and to promote e-scooter safety over all, companies like Lime, Skip, Bird, Lyft, Spin and others that are promoting the use of shared e-scooters need to engage with behavioral designers to perform in-depth diagnoses that allow them to fully understand the forces at play influencing decisions that affect safety. Moreover, this needs to be done in a variety of contexts, taking into account differences in rider demographics and preferences, urban design, infrastructure, traffic laws and transit patterns, among other contextual considerations. Carrying out this process will allow these companies to determine what are the most relevant and prevalent drivers of behavior and, subsequently, to create and experiment with behavioral solution bundles that target all of the resulting key barriers and levers.
Ensuring rider safety on electronic scooters is a complex problem with many components: (1) a structural problem that demands better urban design, more inclusive infrastructure and updated traffic laws and (2) a behavioral problem that requires that, as we continue to operate in sub-optimal riding environments, we riders make choices and behavioral adjustments, like wearing a helmet, that allow us to use these efficient and environmentally-friendly modes of transport without jeopardizing our safety. It should be clear that admitting that there is a role for improving rider behavior and choices is not tantamount to attributing full blame to e-riders, nor is it an acceptance of how things are structured today. Rather, it is an acknowledgement that where we currently stand complementing existing efforts with behavioral design strategies that offer us a powerful, systematic approach for improving the safety of riders of non-traditional modes of transport will be our best bet going forward to ensure that these new modes of transport survive and grow.
Héber M. Delgado-Medrano is a Behavioral Design Consultant and currently serves as the VP of the BVA Nudge Unit in the United States. He is passionate about improving cities and transport and loves to ride electric scooters, e-bikes and his V2 Dual+ Boosted Board.
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