designing large-scale nudge engines - influencing commuter behavior in transportation systems -...
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Designing Large-scale Nudge Engines Influencing Commuter Behavior in Transportation Systems!
Transforming Transportation 2014"
! Presented at Transforming Transportation 2014!
! Balaji Prabhakar!! Departments of Computer Science and Electrical Engineering!! Stanford University!
Designing Large-‐scale Nudge Engines: Influencing Commuter Behavior in Transporta>on Systems
Balaji Prabhakar Departments of Computer Science and Electrical Engineering
Stanford University
Two Kinds of Problem in Urban Systems
1. Broken hydrants: visible, large faults Fukushima, BP oil spill
2. Leaky faucets: a billion trickles of waste Road conges>on
─ US-‐wide $110B p.a. in wasted >me and fuel ─ Per trip: less than $1 à commuter not incen>vized
• Difference ─ With leaky faucets, need to shiW human behavior
Incen>ve engine
Transporta>on in the Future
User behavior data
Micro-‐targeted real-‐>me incen>ves
Real-‐>me usage data
Incen>ve money for users
Real-‐>me analy>cs
Ever-‐smarter big data analy>cs Behavior s>mulus/response pa[erns
Commuters Network Operators
Social s>muli
• Random rewards and redemp>on games ‒ Small determinis>c rewards don’t incen>vize change, we use a raffle-‐like system ‒ Games of chance are essen>ally “self-‐administered” raffles: intui>ve, fun and engaging
• Social nudging ‒ Is powerful: friends significantly affect behavior shiW
• Personalized recommenda>ons ‒ Incen>vize customer segments depending on impact on conges>on and propensity for shiWing
• Detailed analy>cs ‒ Commuter behavior is analyzed along temporal, spa>al and behavioral axes
• Smartphone apps ‒ Act as sensor; give real-‐>me informa>on, recommenda>ons to users
Main elements of approach
Insinc
Commu>ng History
Commuter
Electronic Ticket
Credit History
kms to credits 3x for off-‐peak
Outram Park Jurong East
The Insinc portal
Rewards Date Time Credits 15th June 2010 09:00:19 20 16th June 2010 08:10:45 10 16th June 2010 16:20:17 22 18th June 2010 06:15:20 20
• Goals: − Incen>vize offpeak travel − Mode shiWing: Move people from private to public transporta>on
Insinc: Incen>ves Singapore’s Commuters
• Launch and current status − Stanford + NUS, Jan 10, 2012 to July 10, 2012 − Extended to more par>cipants from July 11, 2012 by LTA/MoT, Singapore − Currently:
o 160,000+ registered par>cipants o Over 70% sign-‐ups due to friend recommenda>ons o >10% shiW in peak load, depending on commuter segment o Engagement: ~35% weekly users, ~50% monthly users
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0.45
5 6 7 8 9 10 11 12
FRAC
TION
OF
COM
MUT
ERS
IN 5
-MIN
UTE
SLOT
S
TRIP START TIME
BeforeAfter
-7.49%0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
5 6 7 8 9 10 11 12
FRAC
TION
OF
COM
MUT
ERS
IN 5
-MIN
UTE
SLOT
S
TRIP START TIME
BeforeAfter
-10.1%
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
5 6 7 8 9 10 11 12
FRAC
TION
OF
COM
MUT
ERS
IN 5
-MIN
UTE
SLOT
S
TRIP START TIME
BeforeAfter
-10.65%
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
1.00
5 6 7 8 9 10 11 12
FRAC
TION
OF
COM
MUT
ERS
IN 5
-MIN
UTE
SLOT
S
TRIP START TIME
BeforeAfter
-11.27%
Type of par*cipants
All in the group
Mild peakers
Medium peakers
Heavy peakers
All par>cipants
-‐ 7.49
-‐ 10.10
-‐ 10.65
-‐ 11.27
Those with Insinc friends
-‐ 9.70
-‐ 10.61
-‐ 11.14
-‐ 11.41
Those without Insinc friends
-‐ 3.70
-‐ 9.00
-‐ 9.69
-‐ 10.75
Game players
-‐ 8.40
-‐ 10.79
-‐ 10.92
-‐ 11.32
Fixed exchange
-‐ 5.07
-‐ 10.24
-‐ 10.96
-‐ 12.19
Short distance commuters
-‐ 4.96
-‐ 10.49
-‐ 10.83
-‐ 11.88
Long distance commuters
-‐ 9.13
-‐ 9.77
-‐ 10.51
-‐ 10.81
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