IDEAS home Printed from https://ideas.repec.org/p/exc/wpaper/2025-05.html

Congestion Information and Eciency: An Experiment

Author

Listed:
  • Charles N. Noussair
  • Liang Qiao

Abstract

Users are now typically able to access historical data in traffic, restaurant, and retailing contexts. This availability of information can be viewed as a means to reduce congestion. However, scientific support for this notion is weak. We investigate, using a laboratory experiment, whether an intermediate level of information provision might reduce congestion. We also study how the effect of making more information available changes over time. We show that providing all users with information is counterproductive in the short run. In the long run, users\' behavior adjusts so that providing some or all individuals with information leads to more efficient outcomes than when no information is made available. The incidence of group over-and under-reaction to congestion cost differences is only mildly responsive to the information level, a pattern consistent with Small Sample models, which do not assume sequential adjustment.

Suggested Citation

  • Charles N. Noussair & Liang Qiao, 2025. "Congestion Information and Eciency: An Experiment," Experimental Economics Center Working Paper Series 2025-05, Experimental Economics Center, Andrew Young School of Policy Studies, Georgia State University.
    • Handle: RePEc:exc:wpaper:2025-05
    as

    Download full text from publisher

    File URL: http://excen.gsu.edu/workingpapers/GSU_EXCEN_WP_2025-05.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Julian Romero & Yaroslav Rosokha, 2019. "The Evolution of Cooperation: The Role of Costly Strategy Adjustments," American Economic Journal: Microeconomics, American Economic Association, vol. 11(1), pages 299-328, February.
    2. Erev, Ido & Roth, Alvin E, 1998. "Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria," American Economic Review, American Economic Association, vol. 88(4), pages 848-881, September.
    3. repec:hal:journl:halshs-00069584 is not listed on IDEAS
    4. Ido Erev & Eyal Ert & Alvin E. Roth, 2010. "A Choice Prediction Competition for Market Entry Games: An Introduction," Games, MDPI, vol. 1(2), pages 1-20, May.
    5. Urs Fischbacher & Simon Gachter, 2010. "Social Preferences, Beliefs, and the Dynamics of Free Riding in Public Goods Experiments," American Economic Review, American Economic Association, vol. 100(1), pages 541-556, March.
    6. Christos A. Ioannou & Julian Romero, 2012. "Strategic Learning With Finite Automata Via The EWA-Lite Model," Purdue University Economics Working Papers 1269, Purdue University, Department of Economics.
    7. Denant-Boèmont, L. & Petiot, R., 2003. "Information value and sequential decision-making in a transport setting: an experimental study," Transportation Research Part B: Methodological, Elsevier, vol. 37(4), pages 365-386, May.
    8. Fischbacher, Urs & Gachter, Simon & Fehr, Ernst, 2001. "Are people conditionally cooperative? Evidence from a public goods experiment," Economics Letters, Elsevier, vol. 71(3), pages 397-404, June.
    9. A. Colin Cameron & Jonah B. Gelbach & Douglas L. Miller, 2008. "Bootstrap-Based Improvements for Inference with Clustered Errors," The Review of Economics and Statistics, MIT Press, vol. 90(3), pages 414-427, August.
    10. Ido Erev & Eyal Ert & Alvin E. Roth, 2010. "Erev, I. et al . A Choice Prediction Competition for Market Entry Games: An Introduction. Games 2010, 1 , 117-136," Games, MDPI, vol. 1(3), pages 1-5, July.
    11. Fudenberg, Drew & Levine, David K., 1995. "Consistency and cautious fictitious play," Journal of Economic Dynamics and Control, Elsevier, vol. 19(5-7), pages 1065-1089.
    12. Ofir Yakobi & Doron Cohen & Eitan Naveh & Ido Erev, 2020. "Reliance on small samples and the value of taxing reckless behaviors," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 15(2), pages 266-281, March.
    13. Laurent Denant-Boemont & Romain Petiot, 2003. "Information value and sequential decision-making in a transport setting: an experimental study," Post-Print hal-02422690, HAL.
    14. Cheung, Yin-Wong & Friedman, Daniel, 1997. "Individual Learning in Normal Form Games: Some Laboratory Results," Games and Economic Behavior, Elsevier, vol. 19(1), pages 46-76, April.
    15. Wei Chen & Shu-Yu Liu & Chih-Han Chen & Yi-Shan Lee, 2011. "Bounded Memory, Inertia, Sampling and Weighting Model for Market Entry Games," Games, MDPI, vol. 2(1), pages 1-13, March.
    16. Ho, Teck H. & Camerer, Colin F. & Chong, Juin-Kuan, 2007. "Self-tuning experience weighted attraction learning in games," Journal of Economic Theory, Elsevier, vol. 133(1), pages 177-198, March.
    17. Vincent Mak & Eyran J. Gisches & Amnon Rapoport, 2015. "Route vs. Segment: An Experiment on Real-Time Travel Information in Congestible Networks," Production and Operations Management, Production and Operations Management Society, vol. 24(6), pages 947-960, June.
    18. Roth, Alvin E. & Erev, Ido, 1995. "Learning in extensive-form games: Experimental data and simple dynamic models in the intermediate term," Games and Economic Behavior, Elsevier, vol. 8(1), pages 164-212.
    19. Selten, R. & Chmura, T. & Pitz, T. & Kube, S. & Schreckenberg, M., 2007. "Commuters route choice behaviour," Games and Economic Behavior, Elsevier, vol. 58(2), pages 394-406, February.
    20. Kasun P Wijayaratna & Vinayak V Dixit & Laurent Denant-Boemont & S Travis Waller, 2017. "An experimental study of the Online Information Paradox: Does en-route information improve road network performance?," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-17, September.
    21. Sruthi Ashraf & Alexander L. Brown & Mark W. Burris & Valon Vitaku, 2023. "Aggregate and individual effects of information in a coordination (traffic) game," Economic Inquiry, Western Economic Association International, vol. 61(4), pages 818-850, October.
    22. Colin Camerer & Teck-Hua Ho, 1999. "Experience-weighted Attraction Learning in Normal Form Games," Econometrica, Econometric Society, vol. 67(4), pages 827-874, July.
    23. S Travis 2☯ & Kasun P Wijayaratna & Vinayak V Dixit & Laurent Denant-Boemont & S. Travis Waller, 2017. "An experimental study of the Online Information Paradox: Does en-route information improve road network performance?," Post-Print halshs-02439201, HAL.
    24. Laurent Denant-Boemont & R. Petiot, 2003. "Information value and sequential decision-making in a transport setting: an experimental study," Post-Print halshs-02439268, HAL.
    25. Camerer, Colin F. & Ho, Teck-Hua & Chong, Juin-Kuan, 2002. "Sophisticated Experience-Weighted Attraction Learning and Strategic Teaching in Repeated Games," Journal of Economic Theory, Elsevier, vol. 104(1), pages 137-188, May.
    26. Yakobi, Ofir & Cohen, Doron & Naveh, Eitan & Erev, Ido, 2020. "Reliance on small samples and the value of taxing reckless behaviors," Judgment and Decision Making, Cambridge University Press, vol. 15(2), pages 266-281, March.
    27. Urs Fischbacher, 2007. "z-Tree: Zurich toolbox for ready-made economic experiments," Experimental Economics, Springer;Economic Science Association, vol. 10(2), pages 171-178, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Charles N. Noussair & Liang Qiao, 2026. "Congestion Information and Efficiency: An Experiment," Management Science, INFORMS, vol. 72(7), pages 6229-6250, July.
    2. Ioannou, Christos A. & Romero, Julian, 2014. "A generalized approach to belief learning in repeated games," Games and Economic Behavior, Elsevier, vol. 87(C), pages 178-203.
    3. Chmura, Thorsten & Goerg, Sebastian J. & Selten, Reinhard, 2012. "Learning in experimental 2×2 games," Games and Economic Behavior, Elsevier, vol. 76(1), pages 44-73.
    4. Erhao Xie, 2019. "Monetary Payoff and Utility Function in Adaptive Learning Models," Staff Working Papers 19-50, Bank of Canada.
    5. Andreas Nicklisch, 2011. "Learning strategic environments: an experimental study of strategy formation and transfer," Theory and Decision, Springer, vol. 71(4), pages 539-558, October.
    6. Xie, Erhao, 2021. "Empirical properties and identification of adaptive learning models in behavioral game theory," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 798-821.
    7. Naoki Watanabe, 2022. "Reconsidering Meaningful Learning in a Bandit Experiment on Weighted Voting: Subjects’ Search Behavior," The Review of Socionetwork Strategies, Springer, vol. 16(1), pages 81-107, April.
    8. Thorsten Chmura & Werner Güth, 2011. "The Minority of Three-Game: An Experimental and Theoretical Analysis," Games, MDPI, vol. 2(3), pages 1-22, September.
    9. Eric Guerci & Nobuyuki Hanaki & Naoki Watanabe, 2017. "Meaningful learning in weighted voting games: an experiment," Theory and Decision, Springer, vol. 83(1), pages 131-153, June.
    10. Shachat, Jason & Swarthout, J. Todd, 2012. "Learning about learning in games through experimental control of strategic interdependence," Journal of Economic Dynamics and Control, Elsevier, vol. 36(3), pages 383-402.
    11. Anthony Ziegelmeyer & Frédéric Koessler & Kene Boun My & Laurent Denant-Boèmont, 2008. "Road Traffic Congestion and Public Information: An Experimental Investigation," Journal of Transport Economics and Policy, University of Bath, vol. 42(1), pages 43-82, January.
    12. Camerer, Colin F. & Ho, Teck-Hua, 2015. "Behavioral Game Theory Experiments and Modeling," Handbook of Game Theory with Economic Applications,, Elsevier.
    13. Jasmina Arifovic & John Ledyard, 2018. "Learning to alternate," Experimental Economics, Springer;Economic Science Association, vol. 21(3), pages 692-721, September.
    14. Terry E. Daniel & Eyran J. Gisches & Amnon Rapoport, 2009. "Departure Times in Y-Shaped Traffic Networks with Multiple Bottlenecks," American Economic Review, American Economic Association, vol. 99(5), pages 2149-2176, December.
    15. Zhang, Yang & Du, Xiaomin, 2017. "Network effects on strategic interactions: A laboratory approach," Journal of Economic Behavior & Organization, Elsevier, vol. 143(C), pages 133-146.
    16. repec:wyi:journl:002151 is not listed on IDEAS
    17. Wolf Ze'ev Ehrblatt & Kyle Hyndman & Erkut Y. ÄOzbay & Andrew Schotter, 2006. "Convergence: An Experimental Study," Levine's Working Paper Archive 122247000000001148, David K. Levine.
    18. Nick Feltovich, 2000. "Reinforcement-Based vs. Belief-Based Learning Models in Experimental Asymmetric-Information," Econometrica, Econometric Society, vol. 68(3), pages 605-642, May.
    19. Masiliūnas, Aidas, 2023. "Learning in rent-seeking contests with payoff risk and foregone payoff information," Games and Economic Behavior, Elsevier, vol. 140(C), pages 50-72.
    20. Yechiam, Eldad & Busemeyer, Jerome R., 2008. "Evaluating generalizability and parameter consistency in learning models," Games and Economic Behavior, Elsevier, vol. 63(1), pages 370-394, May.
    21. García-Pola, Bernardo & Iriberri, Nagore, 2019. "Naivete and Sophistication in Initial and Repeated Play in Games," CEPR Discussion Papers 14088, Centre for Economic Policy Research.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:exc:wpaper:2025-05. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: J. Todd Swarthout (email available below). General contact details of provider: https://edirc.repec.org/data/exgsuus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.