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Mitigating Traffic Congestion: The Role of Intelligent Transportation Systems

Author

Listed:
  • Zhi (Aaron) Cheng

    (Department of Management, London School of Economics, WC2A 2AE London, United Kindom)

  • Min-Seok Pang

    (Fox School of Business, Temple University, Philadelphia, Pennsylvania 19122)

  • Paul A. Pavlou

    (C. T. Bauer College of Business, University of Houston, Houston, Texas 77204)

Abstract

Despite massive investments in transportation infrastructure, traffic congestion remains a major societal and public policy problem. Intelligent transportation systems (ITS) have been proposed as a potential solution to this challenge, but their effectiveness has remained unclear in both research and practice. To understand whether and how ITS affect traffic congestion, we consolidate a unique longitudinal data set on road traffic and the deployment of a large federally supported ITS program in the United States—511 systems—in 99 urban areas between 1994 and 2014. The difference-in-differences estimates show that the adoption of 511 systems is associated with a significant decrease in traffic congestion, saving over $4.7 billion dollars and 175 million hours in travel time annually in U.S. cities. 511 systems also reduce about 53 million gallons of fossil fuel consumption and over 10 billion pounds of CO 2 emissions. We offer two theoretical explanations for this effect: (i) ITS help individual commuters to make better travel decisions, and (ii) ITS help local governments to develop an urban traffic management capability. Empirical evidence supports the underlying theoretical mechanisms and shows that ITS help commuters to schedule travel more efficiently, choose better navigation routes, and optimize their work-trip transportation mode. Second, the effect of ITS is contingent on road supply and public transit services. We also find that the traffic-reducing effect of ITS is larger when commuters use more online services for traffic information and when state governments incorporate more functionalities into their 511 systems. This study contributes to the literature on IT capabilities, public-sector IT value, and the societal impact of IT, while also extending the transportation economics to IT-enabled traffic interventions. Finally, we inform policymakers of ITS as a cost-effective means to mitigating traffic congestion.

Suggested Citation

  • Zhi (Aaron) Cheng & Min-Seok Pang & Paul A. Pavlou, 2020. "Mitigating Traffic Congestion: The Role of Intelligent Transportation Systems," Information Systems Research, INFORMS, vol. 31(3), pages 653-674, September.
    • Handle: RePEc:inm:orisre:v:31:y:2020:i:3:p:653-674
    DOI: 10.1287/isre.2019.0894
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    5. Ismail Shah & Izhar Muhammad & Sajid Ali & Saira Ahmed & Mohammed M. A. Almazah & A. Y. Al-Rezami, 2022. "Forecasting Day-Ahead Traffic Flow Using Functional Time Series Approach," Mathematics, MDPI, vol. 10(22), pages 1-16, November.
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    8. Ma. Janice J. Gumasing & Frances Jeann Charlize S. Bermejo & Keisha Taranee C. Elpedes & Lady Fatima E. Gonzales & Aaron Chastine V. Villajin, 2023. "Antecedents of Waze Mobile Application Usage as a Solution for Sustainable Traffic Management among Gen Z," Sustainability, MDPI, vol. 15(13), pages 1-18, June.
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