MIT 11.478 Spring 2016

Behavior and Policy: Connections in Transportation TR 9:30-11:00, MIT 10-401, Prof. Jinhua Zhao

This course examines the behavioral foundation for transportation system and policy

design, including four aspects:

sensing travel behavior with new data technology and measurement instruments

understanding travel by incorporating behavioral economics and data analytics

nudging travel behavior through preference shaping and demand management

regulating travel by developing behavior-sensitive transport policies

We introduce multiple frameworks of explaining travel behavior, rational or irrational,

contrasting the perspectives of classic economic theory with behavioral economics and

social psychology, and suggest corresponding policy interventions: a behavior-- theory--

policy mapping. Then we present a spectrum of ten instruments for positively influencing

behavior and improving welfare: from manipulating information and changing perceptions

of time and space, to pricing and framing, to inducing emotions of pride and shame, and

exploiting peer pressure or enhancing self-control and motivation.

Most importantly the course challenges students to critique, design, implement and

interpret experiments that nudge travel behavior; and to bring behavioral insights to

creative design of transport policies, programs and systems—making them not only

efficient and equitable but also simpler, consistent, transparent, acceptable, and adaptive

to behavioral changes.

Logistics

TR 9:30-11:00; 10-401; Credits: 3-0-9

Instructor: Jinhua Zhao jinhua@mit.edu; Office 9-523, Office Hour: W 2:00-3:30;

Assistant: Phil Sunde, 9-316, psunde@mit.edu

TA: Joanna Moody jcmoody@mit.edu

TA: Tim Scully timscul@mit.edu

Public: http://dusp.mit.edu/behavior-and-policy

Stellar: http://stellar.mit.edu/S/course/11/sp16/11.478

Readings

The full reading list is here. All readings will be posted at Stellar.

Recommended Books

Daniel Kahneman (2011) Thinking, Fast and Slow

Richard Thaler and Cass R. Sunstein (2008) Nudge: Improving Decisions About

Health, Wealth, and Happiness

Eldar Shafir (2013) The Behavioral Foundations of Public Policy

Elinor Ostrom (1990) Governing the Commons: The Evolution of Institutions for

Collective Action

Steven Pinker (2003). The blank slate: The modern denial of human nature

Dan Ariely (2008) Predictably Irrational

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Schedule Date Topics Out In

Part I BP In a Nutshell

Feb 02 “Unreturned Trays” in Transportation 1

Feb 04 Instruments for Changing Behavior

Feb 09 Explicit, Implicit and Neuroscience Measures 2 1

Feb 11 Behavior Foundation of Public Policy

Part II Behavioral Theory: from Simon to Kahneman

Feb 18 Choice Architecture: Nudges and Nudging 3 2

Feb 23 Prospect Theory

Feb 25 Maps of Bounded Rationality

Mar 01 Artificial Intelligence (Prof. Patrick Winston) 4 3

Part III Time, Space and Information

Mar 03 Re­Interpreting Time: Dali and Einstein

Mar 08 Power of Information and Nudging with Maps

Mar 10 Debate: Behavioral Aspects of Autonomous Vehicles 5 4

Part IV Policy Design One

Mar 15 Salience in Transportation Pricing Idea

Mar 17 Managing Cars in Mega­Cities 6 5

Mar 29 Travel Demand Management in Public Transit

Part V Emotion Travel

Mar 31 Happiness: experience and memory Proposal

Apr 05 Transport and Emotion: Contribution of Neuroscience

Apr 07 Cross­Cultural Comparison of Car Pride 6

Part VI Is Travel Social?

Apr 12 Sociology of Transportation

Apr 14 Transport Network Companies

Apr 21 Preference of Mobility Sharing Interim

Part VII Policy Design Two

Apr 26 Market Failure and Governing the Common

Apr 28 Clearinghouse for Urban Mobility Service

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May 03 Collective Phenomena in Complex Networks (Prof. Ali Jadbabaie)

May 05 Positive Utility of Travel Time (Prof. Pat Mokhtarian)

Part VIII Course summary

May 10 Two Selves, Two species and Two Systems Full

May 12 The Blank Slate: The Modern Denial of Human Nature

May 17 Student Project Showcase (12:00­2:00, lunch served) Revised

Student Expectations

Items %

Class Participation and In­Class Idea Notes 25%

Problem Sets 5%, 5%, 5%, 5%, 5%, 10%

35%

Team Project (Idea 1%; Proposal 4% Interim 5%; Full 20%; Revised 10%)

40%

Part 1. Class Participation and In­Class Idea Notes Active class participation is THE ESSENTIAL part of the course. Please complete the readings before each class. I persist in encouraging everyone to be part of the dialogue.

Capture the moment: I hope that some parts of each class inspire you to think and like you to capture these moments. At the end of each class I allocate 5 minute for everyone to write or draw a half­page idea note reflecting on the dialogue that you just participate in. Literally you may write or draw anything you like and everyone gets the full score as long as you submit it (one point per class). A few thoughts on what you may write (don’t feel constrained by them):

What does the talk inspire you to think? Either as a practitioner, as a researcher, as a citizen, or as a decision maker

Any personal experience related to the discussion today? Did the dialogue today change any of your prior notions of human behavior? How so? How does the lecture connect to any of your research, other courses, public events, or

transportation planning or policy debates? Do you learn any new data source or data collection method that might be of use for

your future work? Anything you’ve learned as research design to whatever depths one class can offer? Any ideas for your term project topics?

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Part 2. Six Problem Sets

1. Tell a story: “Unreturned Trays” in Transportation 2. Experiment with a new method: IAT Survey Design and Implementation 3. Prospect Theory or Nudge Design (either a or b)

a. Prospect Theory b. A Nudge Design

4. Join a debate: Behavioral Aspects of Autonomous Vehicles 5. Mathematize a Concept or Theorize an Idea (either a or b)

a. Mathematize a Behavioral Concept: Salience and Congestion Charging b. Develop a Theoretical Idea: Behavioral Interpretation of a Planning Idea

6. Envision a new mobility paradigm (any one of the following) a. Cap and Trade: Green Travel Budget b. Congestion Pricing 2.0: the first best pricing with comprehensive sensing c. Mobility as a Service: embedding AV, TNC and Transit d. Peak Hour Crowding: full price discrimination possibility and concerns

Notes: 1. We encourage group work but individual submissions are required; please write down

your collaborators’ names. 2. Please submit a hard copy to the TAs at the beginning of lecture as well as submit an

electronic copy online at Stellar. 3. Late policy: Late assignments will receive a 20% deduction per day up to two days.

After 2 days, late assignments will not be accepted and a 0 will be given.

Part 3. Team Project Students deliver the project as a team. Each team will have two to three students including at least one engineer and one planner. The team will determine the project topics collectively with the guide of the instructor. We’ll distribute the Term Paper Guide with detailed instruction and clear expectations.

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