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Decision-Making Behavior Analysis and Empirical Study under Information Intervention in a Cold Environment

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  • Wenbo Huang

    (Key Laboratory of Traffic Engineering, College Metropolitan Transportation, Beijing University of Technology, 100 Pingleyuan, Chaoyang District, Beijing 100124, China)

  • Yanyan Chen

    (Key Laboratory of Traffic Engineering, College Metropolitan Transportation, Beijing University of Technology, 100 Pingleyuan, Chaoyang District, Beijing 100124, China)

  • Shushan Chai

    (Research Institute for Road Safety of MPS, Beijing 100062, China)

Abstract

Some mega-sport events such as the Winter Olympics are usually held in areas accompanied by cold environment, which has a great risk of frostbite and safety for pedestrians. Releasing guidance information have become a good way for managers to reduce freezing time, improve travel efficiency and prevent safety accidents. In this article, the 2022 Winter Olympics were taken as an example to discuss influence of information intervention on TDMB (travel decision-making behavior). The mechanism of the TDMB was explored, and a survey of pedestrian behavior was carried out in the area. In particular, the influence of the subjective perception and objective factors on the RDMB (route decision-making behavior) was analyzed based on the SEM-logit model. The results show that information, congestion and the cold have an impact on the decision-making behavior. The path coefficient values of the pedestrians’ perception of information, congestion and the cold were 0.557, 0.216 and 0.324, respectively, which indicates that guidance information has the most serious impact on the pedestrians’ comprehensive perception. The objective factors including outdoor walking time, information intervention frequency, distance to a heated space had a significant impact on the RDMB. Indeed, when information intervention frequency is 2, the compliance rate of pedestrians to the information can be effectively increased. If the manager wants to alleviate traffic congestion, setting up heated spaces within a radius of 1 km is a good way to divert pedestrians. This study can provide a scientific reference for the sustainable development of mega-sport events, long-term construction of service facilities and the passenger flow management in a cold environment.

Suggested Citation

  • Wenbo Huang & Yanyan Chen & Shushan Chai, 2021. "Decision-Making Behavior Analysis and Empirical Study under Information Intervention in a Cold Environment," Sustainability, MDPI, vol. 13(20), pages 1-16, October.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:20:p:11522-:d:659248
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    References listed on IDEAS

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    1. Lam, William H.K. & Shao, Hu & Sumalee, Agachai, 2008. "Modeling impacts of adverse weather conditions on a road network with uncertainties in demand and supply," Transportation Research Part B: Methodological, Elsevier, vol. 42(10), pages 890-910, December.
    2. Golob, Thomas F., 2003. "Structural equation modeling for travel behavior research," Transportation Research Part B: Methodological, Elsevier, vol. 37(1), pages 1-25, January.
    3. Vedel, Suzanne Elizabeth & Jacobsen, Jette Bredahl & Skov-Petersen, Hans, 2017. "Bicyclists’ preferences for route characteristics and crowding in Copenhagen – A choice experiment study of commuters," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 53-64.
    4. Jiwang Yin & Xiaodong Qiu, 2021. "AI Technology and Online Purchase Intention: Structural Equation Model Based on Perceived Value," Sustainability, MDPI, vol. 13(10), pages 1-16, May.
    5. Koppelman, Frank S. & Wen, Chieh-Hua, 2000. "The paired combinatorial logit model: properties, estimation and application," Transportation Research Part B: Methodological, Elsevier, vol. 34(2), pages 75-89, February.
    6. Golob, Thomas F., 2000. "A simultaneous model of household activity participation and trip chain generation," Transportation Research Part B: Methodological, Elsevier, vol. 34(5), pages 355-376, June.
    7. Guang Yang & Yan Han & Hao Gong & Tiantian Zhang, 2020. "Spatial-Temporal Response Patterns of Tourist Flow under Real-Time Tourist Flow Diversion Scheme," Sustainability, MDPI, vol. 12(8), pages 1-28, April.
    8. Jing Peng & Juan Zhi-cai & Gao Lin-jie, 2014. "Application of the Expanded Theory of Planned Behavior in Intercity Travel Behavior," Discrete Dynamics in Nature and Society, Hindawi, vol. 2014, pages 1-10, March.
    Full references (including those not matched with items on IDEAS)

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