Creating Commuting Change: How behavioral economics can influence mobility decision-making

Download RMI’s new report Mapping Incentives to Change: How Commutifi’s Commuter Score can Influence Sustainable Commuting

Have you considered whether your commute to work is the cheapest, fastest, and most environmentally friendly option available to you? In fact, when was the last time you even thought about your commute-mode choice? Over 85 percent of Americans commute by car— but why? Personal car ownership is so engrained in all facets of society that we tend to overlook some of the objectively negative aspects of car ownership: it’s expensive, we’re wasting time sitting in traffic, and most cars on the road today burn fossil fuels resulting in significant greenhouse gas (GHG) emissions.

Research suggests that longer commute times can lead to increased stress and reduced physical and mental health. Adding only 10 minutes to a one-way commute time has the same negative effect on job satisfaction as a 19 percent reduction in gross income. Moreover, parking our cars at work can affect our pocketbooks directly through high monthly parking costs, or indirectly through the reduction of annual salaries or other benefits. If increased stress and wasted money are not enough, commuting contributed to approximately 15 percent of all transportation-based GHG emissions in 2016.

Despite the high expense of single-occupant vehicle (SOV) commuting for individuals and employers, and the environmental harm it causes, people rarely think about the broader impacts of their commutes, nor the benefits of available alternatives. Behavioral economics is a powerful framework for designing strategies that encourage mobility behavior change—and this is something Rocky Mountain Institute’s mobility team has been focused on in order to move us more quickly toward a new, shared, electric, and autonomous mobility paradigm that benefits people and our planet. Behavioral economics (BE) is the application of psychology principles and insights to economic decision making. In contrast to traditional economic theory, which assumes people make rational choices based on logic and objectivity, BE posits that people are irrational actors who make decisions based on emotion and biases. Moreover, according to Nobel Prize–winning economist Richard Thaler, subtle hints and suggestions can have a substantial influence on the decisions we make. In short, BE can be used to both explain interesting phenomena—like why people buy lottery tickets despite insurmountable odds of winning—and also to encourage people to modify their behaviors. To date, these wide-ranging principles have not been comprehensively applied to improve personal mobility choice.

Cheaper and faster alternatives to driving are not the panacea that many transportation planners believe. As more alternatives such as rideshare, carshare, bikeshare, and even scootershare become available, people still overwhelmingly choose to commute by SOV. While SOV alternatives often offer distinct benefits, they also often require trade-offs in areas such as time, cost, comfort, or convenience. Weighing the pros and cons of each option and determining the best one for each situation can take significant time and effort. Choosing a car to buy is hard enough, so simply adding additional options—even if they do offer unique benefits—to the equation is not the answer. RMI believes that BE is a critical missing piece in shifting people toward less carbon-intensive shared mobility options.

A deeper understanding of how people make transportation-related decisions, grounded in BE, is essential to transforming personal mobility and should be more explicitly incorporated in all future mobility transformation programs and projects. That is why RMI recently partnered with Commutifi to review its Commuter Score tool and help incorporate BE concepts into Commutifi’s survey, scoring, and user dashboard.

Designing Solutions That Drive Real Change

Coupled with a scoring system like Commutifi’s Commuter Score, BE can help design solutions that actually drive real change. RMI’s new paper, Mapping Incentives to Change: How Commutifi’s Commuter Score can Influence Sustainable Commuting, discusses how commuting managers (a person in charge of understanding, planning, and/or improving commutes for companies, cities, campuses, or other entities) can use reference points—the frames of comparison that affect our perceptions, e.g., $4 peanuts are expensive in a supermarket but cheap in a stadium—and BE-inspired incentive programs to encourage positive commuting change. The consistency and frequency of commuting makes it a perfect initial testing ground for this application, as well-designed nudges by a commuting manager can result in a large-scale positive impact. The paper identifies tangible use cases that describe how Commutifi’s Commuter Score can drive positive commuter change, suggests a structure for commuting incentive programs tied to the Commuter Score, and discusses key BE concepts that need to be considered when developing commuting incentive programs.

BE principles can inform strategies that target behaviors at exactly the right moment for change. How the positive and negative attributes of alternatives are framed, and the context in which they are presented, are key aspects of choice architecture—the practice of influencing decisions by changing the way options are presented. Failure to present options in an easily understood way can lead to individuals making a bad choice, or even no choice at all.

Imagine your company has just implemented a new parking cash-out policy—if you stop commuting by SOV, you will get a $75 bonus each month. An extra $900 per year would be nice, so you decide to look into alternate options. But the task is more daunting than you thought: there are a growing number of options, all with different costs, times, and emissions. Overwhelmed with all of the information, you decide to forgo the cash-out bonus and continue driving to work. This process of making an easier decision (in this case, sticking with your traditional commute) in the face of many complicated choices is known in behavioral economics as choice overload. To avoid this, the employer could have provided you with all of the necessary information to make a good choice, limited the number of choices you could make, or even made the choice for you.

Let’s say your employer offers three commuting benefit options instead of just one: you can receive an individual parking space for free, receive $50 per month for a carpool parking space, or receive $100 per month for a public transit pass. An employee who has always driven an SOV to work will likely choose an individual parking space. However, the employer can introduce an important BE concept—the default option—to nudge the employee toward the more sustainable and cost-friendly selection: in this case, the public transit pass. Default options are preset selections that take effect if no action is taken. They are often selected by individuals simply because they require little thought, they are implicitly endorsed, and they provide social proof that others are likely making the same decision. Many employees in this situation will accept the transit pass simply because it is the option suggested by their employer. Many others will take the carpool space instead, but fewer will opt for the individual parking space because they will want to avoid the reputational damage that might come with taking two steps backward. Setting defaults can effectively guide decision-making without reducing the number or quality of alternatives.

But how do we get those carpoolers to take that final step? Think about the reasons why you have chosen not to take public transit. Specifically, think about a time that you had a particularly bad experience with public transportation, like waiting in the rain for a bus that was supposed to arrive 15 minutes ago. Such a single bad experience features prominently in your mind and makes future transportation decisions simple. Instead of checking bus schedules, having exact change, and calculating walk and wait times, you reason that buses are always late, and driving is better because it is less stressful. Reliance on this easily recalled event to generalize on-time reliability is an example of a heuristic, or mental shortcut. Mental shortcuts substitute complex decisions for easier ones that can be answered with minimal effort. Simple BE concepts and technology can be integrated to unwire these shortcuts and change perceptions about public transit wait times and reliability. Apps that show a bus’s exact location in real time can eliminate stress and help riders know when they need to reach the bus stop. By lessening these concerns and reducing wait times, riders may develop a more positive view of public transportation and be more inclined to ride again.

With the majority of Americans still preferring SOVs, a new approach is needed to encourage adoption of alternative forms of transportation. RMI believes behavioral economics can identify underlying barriers to change and unlock the full benefits of mobility alternatives. The potential applications of behavioral economics to personal mobility are substantial, and the above examples—as well as those discussed in the white paper—only scratch the surface.

Collaboration with municipalities, transportation service providers, and transportation technology companies is essential to identifying and refining the most impactful BE principles in order to adapt them to mobility decision-making. RMI is dedicated to leading this conversation and bringing BE to the forefront of the mobility transformation discussion. By working together, we can successfully implement these innovative concepts and help ensure the success of future mobility programs aimed at replacing SOVs with less carbon-intensive options.