Gaming for Sustainability: How Balaji Prabhakar’s Lottery Beats Traffic Congestion
|INSINC poster at Singapore's train stations|
I was especially intrigued by the ways in which Balaji applies principles, architectures and algorithms from computer networks to fundamentally redesign Societal Networks. Societal Networks are networks that are vital for a society's functioning. They include transportation networks, waste management systems, energy networks and health-care systems. Balaji’s current major focus is on transportation networks, and he’s making strides in redesigning them to be more scalable and efficient.
In January 2012, Balaji launched INSINC jointly with the National University of Singapore and with support by Singapore’s Land Transport Authority (LTA). Using a cleverly playful scheme, the joint study experiments with reducing overall traffic congestion and with better managing crowdedness on Singapore’s rail system by incentivizing commuters to shift some of the peak travel demand to off-peak periods. INSINC allows commuters to earn credits proportional to the distance they travel on the rail system, with extra credits rewarded for off-peak journeys. But studies have shown that, while incentives can generate positive behavior, guaranteed small rewards don’t generate significant behavior changes and, accordingly, that guaranteed rebates are too low amounts to convince people to alter their commuting habits. Many commuters don’t even notice they’re paying less for their train rides. They will, however, be far more inclined to take “decongestion” trips during off-peak hours and, in the long run, change their commuting habits if they stand a chance to win larger prizes.
Balaji’s INSINC idea draws on this risk-seeking effect from behavioral economics. Participants can exchange their off-peak commute credits for chances to win up to $100 by playing a game on the INSINC website, and the prizes are then credited to their transportation card every month. Moreover, Balaji’s work shows that this risk-seeking effect is amplified in small networks: regularly hearing about other winners leads individuals to overestimate their own chances of success. The scheme’s lure therefore strengthens when participants go online to compare their results with those of friends and colleagues. This already worked particularly well in Bangalore, where Balaji ran a pilot project in collaboration with the Indian software company Infosys Technologies. That scheme, in which winners were advertised through Infosys, doubled the number of off-peak commuters to the company’s main research site, significantly reducing congestion on the Infosys peak-time buses (and I assume lessening the overall time spent by their employees on buses). INSINC aims to create a social network among commuters to produce a similar effect. The success of the Bangalore study has also led to a similar program that Balaji is running at Stanford University.
|Visual of updated INSINC game board|
Businesses and policymakers are becoming increasingly aware that psychology plays a central role in the long journey towards a sustainable future, because a key aspect of sustainability is widespread behavior change. The beauty about Balaji’s random payoff scheme is that it generates behavior change in a way that’s both engaging and cost-effective. It not only maximizes small amounts of money, but also redesigns transportation networks to be “smarter” without the need to reengineer them, drawing on the insight that it takes many people to cause congestion, but a surprisingly small number to reduce it. As Balaji says,
“congestion is an 80-20 type of problem. In other words, if you get rid of 20 percent of the load, then the congestion measures will drop down potentially 80 percent. The question is: Which 20 percent is going to yield the road at the peak time? Somebody may value time more and somebody may value money more, and there’s a trade that’s set up.”Blending technology, economics, and policy, Balaji hit upon a bright idea that establishes the right tradeoff to create the desired 80-20 effect. If it proves successful at city-scale, this approach may well be applicable to other large societal problems of the 21st century, such as energy consumption, water conservation, health and wellness.