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Experimental Evaluation of Information Interventions to Encourage Non-Motorized Travel: A Case Study in Hefei, China

Author

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  • Jichao Geng

    (School of Economics and Management, Anhui University of Science and Technology, Huainan 232001, China)

  • Ruyin Long

    (School of Management, China University of Mining and Technology, Xuzhou 221116, China)

  • Li Yang

    (School of Economics and Management, Anhui University of Science and Technology, Huainan 232001, China)

  • Junqi Zhu

    (School of Economics and Management, Anhui University of Science and Technology, Huainan 232001, China)

  • Getnet Engeda Birhane

    (School of Economics and Management, Anhui University of Science and Technology, Huainan 232001, China)

Abstract

This study aims at presenting an experimental evaluation of the different effects of environmental and health information on encouraging car owners to travel on foot and by bicycle. Health information consists of a high and a low target setting. One hundred and forty-six participants in Hefei city reported their travel behaviors in terms of mode, time, and trip before and after the experiment. Their cognitive and emotional processes with regard to the protection motivation theory (PMT) that determine their potential travel behavior changes in response to information intervention are also identified. Three experimental groups and one control group based on a between-group design are adopted and the methodology of paired sample chi-squared tests and stepwise linear regressions are used. The results show that environmental information alone fails to encourage car owners’ non-motorized travel. When health information is added, information intervention can effectively encourage a time increase in walking and cycling as well as a time and trip decrease in car use in the short term. But the long-term effect is not significant after a year and a half. Moreover, there are no significant differences between the high and the low target settings in health information for encouraging non-motorized travel. In terms of PMT constructs, severity has a significant relationship with the change of time or trip on foot and by bicycle. Vulnerability emerges as a non-effective predictor. Reward, self-efficacy, response efficacy, and response cost are more remarkable in predicting the change of time or trip by car. This study recommends that (1) health information with a target setting is superior to environmental information, (2) reduction strategy is potentially superior to transfer strategy to control car usage, (3) policymakers should design intervention strategies relevant to the coping appraisal rather than to the threat appraisal.

Suggested Citation

  • Jichao Geng & Ruyin Long & Li Yang & Junqi Zhu & Getnet Engeda Birhane, 2020. "Experimental Evaluation of Information Interventions to Encourage Non-Motorized Travel: A Case Study in Hefei, China," Sustainability, MDPI, vol. 12(15), pages 1-19, July.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:15:p:6201-:d:393001
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    References listed on IDEAS

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    1. Sendy Farag & Glenn Lyons, 2010. "Explaining public transport information use when a car is available: attitude theory empirically investigated," Transportation, Springer, vol. 37(6), pages 897-913, November.
    2. Jichao Geng & Ruyin Long & Hong Chen & Ting Yue & Wenbo Li & Qianwen Li, 2017. "Exploring Multiple Motivations on Urban Residents’ Travel Mode Choices: An Empirical Study from Jiangsu Province in China," Sustainability, MDPI, vol. 9(1), pages 1-16, January.
    3. Clark, Ben & Chatterjee, Kiron & Melia, Steve, 2016. "Changes to commute mode: The role of life events, spatial context and environmental attitude," Transportation Research Part A: Policy and Practice, Elsevier, vol. 89(C), pages 89-105.
    4. Marcel Paulssen & Dirk Temme & Akshay Vij & Joan Walker, 2014. "Values, attitudes and travel behavior: a hierarchical latent variable mixed logit model of travel mode choice," Transportation, Springer, vol. 41(4), pages 873-888, July.
    5. Chorus, Caspar G. & Arentze, Theo A. & Timmermans, Harry J.P., 2008. "A Random Regret-Minimization model of travel choice," Transportation Research Part B: Methodological, Elsevier, vol. 42(1), pages 1-18, January.
    6. Geng, Jichao & Long, Ruyin & Chen, Hong, 2016. "Impact of information intervention on travel mode choice of urban residents with different goal frames: A controlled trial in Xuzhou, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 91(C), pages 134-147.
    7. Graham-Rowe, Ella & Skippon, Stephen & Gardner, Benjamin & Abraham, Charles, 2011. "Can we reduce car use and, if so, how? A review of available evidence," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(5), pages 401-418, June.
    8. Jörgen Garvill & Agneta Marell & Annika Nordlund, 2003. "Effects of increased awareness on choice of travel mode," Transportation, Springer, vol. 30(1), pages 63-79, February.
    9. Frank J. van Rijnsoever & Jacco Farla & Martin J. Dijst, 2009. "Consumer Car Preferences and Information Search Channels," Innovation Studies Utrecht (ISU) working paper series 09-07, Utrecht University, Department of Innovation Studies, revised Apr 2009.
    10. Feiyu Chen & Hong Chen & Jiahui Yang & Ruyin Long & Qianwen Li, 2018. "Impact of Information Intervention on the Recycling Behavior of Individuals with Different Value Orientations—An Experimental Study on Express Delivery Packaging Waste," Sustainability, MDPI, vol. 10(10), pages 1-20, October.
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