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Designing Large-scale Nudge Engines

Influencing Commuter Behavior in Transportation Systems!

!   Presented at Transformin...
Designing	
  Large-­‐scale	
  Nudge	
  Engines:	
  
	
  

Influencing	
  Commuter	
  Behavior	
  in	
  Transporta>on	
  Sys...
Urban	
  overload	
  
•  Real	
  world	
  systems	
  are	
  constrained	
  	
  

China	
  

India	
  

USA	
  

Japan	
  
...
Two	
  Kinds	
  of	
  Problem	
  in	
  Urban	
  Systems	
  
1.  Broken	
  hydrants:	
  visible,	
  large	
  faults	
  	
  ...
Transporta>on	
  architecture	
  now	
  
Commuters	
  

Network	
  

Operators	
  
Transporta>on	
  in	
  the	
  Future	
  
Commuters	
  

Network	
  

User	
  behavior	
  
data	
  

Real-­‐>me	
  
usage	
...
Main	
  elements	
  of	
  approach	
  
•  Random	
  rewards	
  and	
  redemp>on	
  games	
  
‒  Small	
  determinis>c	
  r...
Insinc
	
  
Jurong	
  East	
  

Outram	
  Park	
  

Commu>ng	
  History	
  
Electronic	
  Ticket	
  
kms	
  to	
  credits	...
Insinc:	
  Incen>ves	
  Singapore’s	
  Commuters
	
  
•  Goals:	
  
−  Incen>vize	
  offpeak	
  travel	
  
−  Mode	
  shiWi...
0.70
FRACTION OF COMMUTERS IN 5-MINUTE SLOTS

FRACTION OF COMMUTERS IN 5-MINUTE SLOTS

0.45

Before
After

0.40
0.35
0.30
...
Type	
  of	
  
par*cipants	
  

	
  
All	
  in	
  the	
  group	
  

Mild	
  
peakers	
  

Medium	
  
peakers	
  

Heavy	
 ...
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Designing Large-scale Nudge Engines - Influencing Commuter Behavior in Transportation Systems - Balaji Prabhakar - Stanford University - Transforming Transportation 2014 - EMBARQ The World Bank

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Influencing commuter behavior in transportation systems, presented by Balaji Prabhakar, Stanford University at Transforming Transportation 2014.

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Transcript of "Designing Large-scale Nudge Engines - Influencing Commuter Behavior in Transportation Systems - Balaji Prabhakar - Stanford University - Transforming Transportation 2014 - EMBARQ The World Bank"

  1. 1. Designing Large-scale Nudge Engines
 Influencing Commuter Behavior in Transportation Systems! !   Presented at Transforming Transportation 2014! ! Balaji Prabhakar! !   Departments of Computer Science and Electrical Engineering! !   Stanford University! Transforming Transportation 2014"
  2. 2. Designing  Large-­‐scale  Nudge  Engines:     Influencing  Commuter  Behavior  in  Transporta>on  Systems   Balaji  Prabhakar   Departments  of  Computer  Science  and  Electrical  Engineering   Stanford  University    
  3. 3. Urban  overload   •  Real  world  systems  are  constrained     China   India   USA   Japan   Korea  
  4. 4. 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  
  5. 5. Transporta>on  architecture  now   Commuters   Network   Operators  
  6. 6. Transporta>on  in  the  Future   Commuters   Network   User  behavior   data   Real-­‐>me   usage  data   Operators   Incen>ve   money  for   users   Micro-­‐targeted  real-­‐ >me  incen>ves   Real-­‐>me  analy>cs     Incen>ve  engine     Social  s>muli   Ever-­‐smarter  big  data  analy>cs   Behavior  s>mulus/response   pa[erns  
  7. 7. Main  elements  of  approach   •  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  
  8. 8. Insinc   Jurong  East   Outram  Park   Commu>ng  History   Electronic  Ticket   kms  to  credits   3x  for  off-­‐peak   Commuter   The  Insinc  portal     Credit  History   Date 15th June 16th June 16th June 18th June Time Credits 2010 09:00:19 20 2010 08:10:45 10 2010 16:20:17 22 2010 06:15:20 20 Rewards  
  9. 9. Insinc:  Incen>ves  Singapore’s  Commuters   •  Goals:   −  Incen>vize  offpeak  travel   −  Mode  shiWing:    Move  people  from  private  to  public  transporta>on     •  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  o  o  o  160,000+  registered  par>cipants   Over  70%  sign-­‐ups  due  to  friend  recommenda>ons   >10%  shiW  in  peak  load,  depending  on  commuter  segment   Engagement:  ~35%  weekly  users,  ~50%  monthly  users  
  10. 10. 0.70 FRACTION OF COMMUTERS IN 5-MINUTE SLOTS FRACTION OF COMMUTERS IN 5-MINUTE SLOTS 0.45 Before After 0.40 0.35 0.30 0.25 0.20 0.15 0.10 0.05 -7.49% 0.50 0.40 0.30 0.20 0.10 -10.1% 0.00 0.00 5 5 6 7 8 9 TRIP START TIME 10 11 6 7 12 0.80 8 9 TRIP START TIME 10 11 12 1.00 FRACTION OF COMMUTERS IN 5-MINUTE SLOTS FRACTION OF COMMUTERS IN 5-MINUTE SLOTS Before After 0.60 Before After 0.70 0.60 0.50 0.40 0.30 0.20 0.10 -10.65% 0.00 0.90 Before After 0.80 0.70 0.60 0.50 0.40 0.30 0.20 -11.27% 0.10 0.00 5 6 7 8 9 TRIP START TIME 10 11 12 5 6 7 8 9 TRIP START TIME 10 11 12
  11. 11. 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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