Peer pressure enables actuation of mobility lifestyles

Abstract This paper explores the utility of peer pressure as an actionable mechanism to induce socially responsible and environmentally-conscious mobility habits. We adopt a two-stage game theoretic model of peer pressure to investigate feedback between social, geographic, and temporal dimensions of agent choices in a hyper-realistic micro-simulation of travel. The results show that peer pressure helps in achieving desirable equilibrium properties while reducing congestion and emissions due to sustained mode shift. With a way to initiate the required social norming and a proper concern for privacy and ethics, these cost-effective mechanisms may soon begin to find use in improving community welfare.

[1]  Kai Nagel,et al.  The Internalization of Congestion and Air Pollution Externalities: Evaluating Behavioral Impacts , 2015 .

[2]  A. Páez,et al.  A Discrete-Choice Approach to Modeling Social Influence on Individual Decision Making , 2008 .

[3]  D. Kahneman,et al.  Duration neglect in retrospective evaluations of affective episodes. , 1993, Journal of personality and social psychology.

[4]  B. Kickhöfer,et al.  Optimal Public Transport Pricing: Towards an Agent-based Marginal Social Cost Approach , 2015 .

[5]  Nicholas A. Christakis,et al.  Social contagion theory: examining dynamic social networks and human behavior , 2011, Statistics in medicine.

[6]  John L. Bowman,et al.  The Day Activity Schedule Approach to Travel Demand Analysis , 1998 .

[7]  K. Nagel,et al.  Towards High-Resolution First-Best Air Pollution Tolls An Evaluation of Regulatory Policies and a Discussion on Long-Term User Reactions , 2012 .

[8]  Erik T. Verhoef,et al.  External effects and social costs of road transport , 1994 .

[9]  K. Axhausen,et al.  Activity Spaces, Biographies, Social Networks and their Welfare Gains and Externalities: Some Hypotheses and Empirical Results , 2005 .

[10]  Satish V. Ukkusuri,et al.  Experimental Economics and choice in transportation: Incentives and context☆ , 2017 .

[11]  Joan L. Walker,et al.  Discrete choice with social and spatial network interdependencies: An empirical example using mixed generalized extreme value models with field and panel effects , 2005 .

[12]  Christos H. Papadimitriou,et al.  Worst-case equilibria , 1999 .

[13]  Kevin Waugh,et al.  A Practical Use of Imperfect Recall , 2009, SARA.

[14]  Cosma Rohilla Shalizi,et al.  Homophily and Contagion Are Generically Confounded in Observational Social Network Studies , 2010, Sociological methods & research.

[15]  J. Thøgersen,et al.  Activation of social norms in social dilemmas: A review of the evidence and reflections on the implications for environmental behaviour , 2007 .

[16]  Florian K. Diekert,et al.  The Tragedy of the Commons from a Game-Theoretic Perspective , 2012 .

[17]  Felix Walter,et al.  Sustainable transport pricing: from theory to application , 2005 .

[18]  David Gaker,et al.  Experimental Economics in Transportation , 2010 .

[19]  M. Delucchi.  ENVIRONMENTAL EXTERNALITIES OF MOTOR-VEHICLE USE IN THE US. IN: THE AUTOMOBILE , 2000 .

[20]  Kenneth A. Small,et al.  On the Costs of Air Pollution from Motor Vehicles , 2018, Controlling Automobile Air Pollution.

[21]  Gunnar Flötteröd,et al.  Choice Models in MATSim , 2016 .

[22]  Kenneth E. Train,et al.  Discrete Choice Methods with Simulation , 2016 .

[23]  E. Ostrom.  COPING WITH TRAGEDIES OF THE COMMONS , 1999 .

[24]  Kay W. Axhausen,et al.  A Framework to Represent Joint Decisions in a Multi‐Agent Transport Simulation , 2013 .

[25]  J. Garvill,et al.  Acceptability of travel demand management measures: The importance of problem awareness, personal norm, freedom, and fairness , 2006 .

[26]  G. Hardin,et al.  The Tragedy of the Commons , 1968, Green Planet Blues.

[27]  W. Harrington,et al.  Automobile Externalities and Policies , 2007 .

[28]  R. Thaler,et al.  Nudge: Improving Decisions About Health, Wealth, and Happiness , 2008 .

[29]  Syngjoo Choi,et al.  Social learning in networks: a Quantal Response Equilibrium analysis of experimental data , 2012 .

[30]  John M. Quigley,et al.  Political and Public Acceptability of Congestion Pricing: Ideology and Self Interest , 2009 .

[31]  C. Manski.  Identification of Endogenous Social Effects: The Reflection Problem , 1993 .

[32]  Satoshi Fujii,et al.  Mass effects and mobility decisions , 2013 .

[33]  Andrea Liverani,et al.  Climate Change and Individual Behavior: Considerations for Policy , 2009 .

[34]  E. Lazear,et al.  Peer Pressure and Partnerships , 1992, Journal of Political Economy.

[35]  I. Mayeres,et al.  THE MARGINAL EXTERNAL COSTS OF URBAN TRANSPORT , 1996 .

[36]  T. Leonard,et al.  Richard H. Thaler, Cass R. Sunstein, Nudge: Improving decisions about health, wealth, and happiness , 2008 .

[37]  Yoav Shoham,et al.  Multiagent Systems - Algorithmic, Game-Theoretic, and Logical Foundations , 2009 .

[38]  I. Walker,et al.  Context change and travel mode choice : Combining the habit discontinuity and self-activation hypotheses , 2008 .

[39]  Mark Bradley,et al.  Activity-Based Travel Demand Models: A Primer , 2014 .

[40]  Akshay Vij,et al.  The power and value of green in promoting sustainable transport behavior , 2011 .

[41]  Kenneth A. Small,et al.  Valuation of Travel Time , 2012 .

[42]  Torsten Hägerstraand.  WHAT ABOUT PEOPLE IN REGIONAL SCIENCE , 1970 .

[43]  K. Axhausen,et al.  An agent model of social network and travel behavior interdependence , 2006 .

[44]  George Poste,et al.  Big Data and Health , 2015 .

[45]  Kay W. Axhausen,et al.  The Multi-Agent Transport Simulation , 2016 .

[46]  David Watling,et al.  Mechanisms that Govern how the Price of Anarchy varies with Travel Demand , 2016 .

[47]  Mark D. Uncles,et al.  Discrete Choice Analysis: Theory and Application to Travel Demand , 1987 .

[48]  J. Viegas.  Making urban road pricing acceptable and effective: searching for quality and equity in urban mobility , 2001 .

[49]  J. Hackney,et al.  A coupled multi-agent microsimulation of social interactions and transportation behavior , 2011 .

[50]  Alexei Pozdnoukhov,et al.  Connected Population Synthesis for Urban Simulation , 2017 .

[51]  Peter Bonsall,et al.  Do we know whether personal travel planning really works , 2009 .

[52]  B. Kickhöfer,et al.  The correlation of externalities in marginal cost pricing: lessons learned from a real-world case study , 2018 .

[53]  Benjamin Kickhöfer,et al.  A joint internalization model for congestion and air pollution externalities : Is marginal cost pricing enough to comply with the EU CO 2 reduction targets ? , 2015 .

[54]  I. Kevrekidis,et al.  "Coarse" stability and bifurcation analysis using time-steppers: a reaction-diffusion example. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[55]  E. Avineri.  On the use and potential of behavioural economics from the perspective of transport and climate change , 2012 .

[56]  Johannes Illenberger,et al.  Social Networks and Cooperative Travel Behaviour , 2012 .

[57]  Werner Rothengatter,et al.  Do external benefits compensate for external costs of transport , 1994 .

[58]  A. Rubinstein.  Modeling Bounded Rationality , 1998 .

[59]  M. Jackson,et al.  Peer Pressure , 2008 .

[60]  Kai Nagel,et al.  An activity-based and dynamic approach to calculate road traffic noise damages , 2017 .

[61]  Víctor M. Eguíluz,et al.  Entangling Mobility and Interactions in Social Media , 2013, PloS one.

[62]  A. Pentland,et al.  Inducing Peer Pressure to Promote Cooperation , 2013, Scientific Reports.

[63]  Jerald Jariyasunant,et al.  Quantified Traveler: Travel Feedback Meets the Cloud to Change Behavior , 2013, J. Intell. Transp. Syst..

[64]  K. Nagel,et al.  Generating complete all-day activity plans with genetic algorithms , 2005 .

[65]  Mark S Handcock,et al.  Local dependence in random graph models: characterization, properties and statistical inference , 2015, Journal of the American Statistical Association.

[66]  Marco te Brömmelstroet,et al.  Sometimes you want people to make the right choices for the right reasons: potential perversity and jeopardy of behavioural change campaigns in the mobility domain , 2014 .

[67]  Joan L. Walker,et al.  Passengers’ Perception of and Behavioral Adaptation to Unreliability in Public Transportation , 2013 .

[68]  Zabe Bent.  San Francisco Mobility, Access, and Pricing Study , 2010 .

[69]  G. Brady.  Governing the Commons: The Evolution of Institutions for Collective Action , 1993 .

[70]  E. Ostrom,et al.  Covenants with and without a Sword: Self-Governance Is Possible , 1992, American Political Science Review.

[71]  Jean-François Paiement,et al.  A Generative Model of Urban Activities from Cellular Data , 2018, IEEE Transactions on Intelligent Transportation Systems.

[72]  Sandip Sen,et al.  Local Decision Procedures for Avoiding the Tragedy of Commons , 2003, IWDC.

[73]  Alexander Erath,et al.  A Bayesian network approach for population synthesis , 2015 .

[74]  S. Fujii,et al.  Determinants of the effectiveness of travel feedback programs—a review of communicative mobility management measures for changing travel behaviour in Japan , 2006 .

[75]  Marcel Rieser,et al.  Adding Transit to an Agent-Based Transportation Simulation: Concepts and Implementation , 2010 .

[76]  Alexandre Padilla.  Review of Richard H. Thaler and Cass R. Sunstein, Nudge: Improving decisions about health, wealth, and happiness , 2009 .

[77]  Benjamin Kickhöfer,et al.  Pricing local emission exposure of road traffic: An agent-based approach , 2015 .

[78]  W. Brög,et al.  Evaluation of voluntary travel behaviour change: Experiences from three continents , 2009 .

[79]  Eran Ben-Elia,et al.  Emergence of cooperation in congested road networks using ICT and future and emerging technologies: A game-based review , 2016 .

[80]  Feras El Zarwi,et al.  A discrete choice framework for modeling and forecasting the adoption and diffusion of new transportation services , 2017, 1707.07379.

[81]  Nicolas Coulombel,et al.  The marginal social cost of travel time variability , 2014 .

[82]  Eran Ben-Elia,et al.  An agent-based model of the emergence of cooperation and a fair and stable system optimum using ATIS on a simple road network , 2018 .

[83]  A. Páez,et al.  Social Influence on Travel Behavior: A Simulation Example of the Decision to Telecommute , 2007 .

[84]  K. Nagel,et al.  Towards High-Resolution First-Best Air Pollution Tolls , 2016 .

[85]  Akshay Vij,et al.  You Can Lead Travelers to the Bus Stop, But You Can’t Make Them Ride , 2013 .