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Information adoption in commuters’ route choice in the context of social interactions

Author

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  • Zhang, Guijie
  • Wei, Fangfang
  • Jia, Ning
  • Ma, Shoufeng
  • Wu, Yi

Abstract

The rapid development of information technology has significantly promoted social interactions among people. Social interactions may have become an important channel for commuters to obtain traffic information. Although commuters’ own travel experience and Advanced Traveller Information Systems (ATIS) are acknowledged as two common traffic information sources that can impact commuters’ route choice, the possible influence of social interactions has not yet been empirically confirmed. Therefore, an empirical study is conducted in this paper to explore whether and how social interactions affect commuters’ route choice. The presented study is divided into two phases. First, 1000 commuters are surveyed about their social interactions with other commuters. A total of 809 valid questionnaires are returned from the commuters. The survey confirms that social interactions among the commuters are very common and indeed influence commuters’ route choice. Second, because the essence of the influence of social interactions on commuters’ route choice is an information-adoption process, partial least squares (PLS) component-based structural equation modelling (SEM) is employed to study the key success factors that influence information adoption in commuters’ route choice in the context of social interactions. In the second phase, 236 valid questionnaires were returned. The obtained results demonstrate that information relevance, information accuracy, source expertise, source integrity, usefulness and extraversion are the factors that have significant influence on commuters’ information adoption in the context of social interactions; while the roles of responding, trust and field dependence are not significant. Finally, some discussion and inspirations are provided based on the data analysis results. The findings in the presented study offer some insights into using social interaction information to guide commuters’ route choice.

Suggested Citation

  • Zhang, Guijie & Wei, Fangfang & Jia, Ning & Ma, Shoufeng & Wu, Yi, 2019. "Information adoption in commuters’ route choice in the context of social interactions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 300-316.
  • Handle: RePEc:eee:transa:v:130:y:2019:i:c:p:300-316
    DOI: 10.1016/j.tra.2019.09.041
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    References listed on IDEAS

    as
    1. Fischer, Eileen & Reuber, A. Rebecca, 2011. "Social interaction via new social media: (How) can interactions on Twitter affect effectual thinking and behavior?," Journal of Business Venturing, Elsevier, vol. 26(1), pages 1-18, January.
    2. Dholakia, Ruby Roy & Sternthal, Brian, 1977. "Highly Credible," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 3(4), pages 223-232, March.
    3. Di Ciommo, Floridea & Comendador, Julio & López-Lambas, María Eugenia & Cherchi, Elisabetta & Ortúzar, Juan de Dios, 2014. "Exploring the role of social capital influence variables on travel behaviour," Transportation Research Part A: Policy and Practice, Elsevier, vol. 68(C), pages 46-55.
    4. Stephanie Watts Sussman & Wendy Schneier Siegal, 2003. "Informational Influence in Organizations: An Integrated Approach to Knowledge Adoption," Information Systems Research, INFORMS, vol. 14(1), pages 47-65, March.
    5. Hudson, Simon & Huang, Li & Roth, Martin S. & Madden, Thomas J., 2016. "The influence of social media interactions on consumer–brand relationships: A three-country study of brand perceptions and marketing behaviors," International Journal of Research in Marketing, Elsevier, vol. 33(1), pages 27-41.
    6. Barbara H. Wixom & Peter A. Todd, 2005. "A Theoretical Integration of User Satisfaction and Technology Acceptance," Information Systems Research, INFORMS, vol. 16(1), pages 85-102, March.
    7. Ayako Taniguchi & Satoshi Fujii, 2007. "Promoting Public Transport Using Marketing Techniques in Mobility Management and Verifying their Quantitative Effects," Transportation, Springer, vol. 34(1), pages 37-49, January.
    8. Richard L. Daft & Robert H. Lengel, 1986. "Organizational Information Requirements, Media Richness and Structural Design," Management Science, INFORMS, vol. 32(5), pages 554-571, May.
    9. Chandra Bhat, 2015. "A new spatial (social) interaction discrete choice model accommodating for unobserved effects due to endogenous network formation," Transportation, Springer, vol. 42(5), pages 879-914, September.
    10. Ettema, Dick & Arentze, Theo & Timmermans, Harry, 2011. "Social influences on household location, mobility and activity choice in integrated micro-simulation models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(4), pages 283-295, May.
    11. Xiao, Yu & Lo, Hong K., 2016. "Day-to-day departure time modeling under social network influence," Transportation Research Part B: Methodological, Elsevier, vol. 92(PA), pages 54-72.
    12. Vicki McKinney & Kanghyun Yoon & Fatemeh “Mariam” Zahedi, 2002. "The Measurement of Web-Customer Satisfaction: An Expectation and Disconfirmation Approach," Information Systems Research, INFORMS, vol. 13(3), pages 296-315, September.
    13. Kumar, Amit & Peeta, Srinivas, 2015. "A day-to-day dynamical model for the evolution of path flows under disequilibrium of traffic networks with fixed demand," Transportation Research Part B: Methodological, Elsevier, vol. 80(C), pages 235-256.
    14. Eran Ben-Elia & Ido Erev & Yoram Shiftan, 2008. "The combined effect of information and experience on drivers’ route-choice behavior," Transportation, Springer, vol. 35(2), pages 165-177, March.
    15. Sunitiyoso, Yos & Avineri, Erel & Chatterjee, Kiron, 2011. "The effect of social interactions on travel behaviour: An exploratory study using a laboratory experiment," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(4), pages 332-344, May.
    16. Wei, Fangfang & Jia, Ning & Ma, Shoufeng, 2016. "Day-to-day traffic dynamics considering social interaction: From individual route choice behavior to a network flow model," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 335-354.
    17. Sherwin, Henrietta & Chatterjee, Kiron & Jain, Juliet, 2014. "An exploration of the importance of social influence in the decision to start bicycling in England," Transportation Research Part A: Policy and Practice, Elsevier, vol. 68(C), pages 32-45.
    18. Han, Qi & Arentze, Theo & Timmermans, Harry & Janssens, Davy & Wets, Geert, 2011. "The effects of social networks on choice set dynamics: Results of numerical simulations using an agent-based approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(4), pages 310-322, May.
    19. Sunitiyoso, Yos & Matsumoto, Shoji, 2009. "Modelling a social dilemma of mode choice based on commuters' expectations and social learning," European Journal of Operational Research, Elsevier, vol. 193(3), pages 904-914, March.
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