Social media effects on sustainable mobility opinion diffusion: Model framework and implications for behavior change

E. Borowski, Ying Chen, H. Mahmassani*

*Corresponding author for this work

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

Opinions regarding emergent sustainable transportation alternatives, such as bikeshare and e-scooters, and more traditional green alternatives like public transit, spread through social networks via opinion diffusion mechanisms, like word-of-mouth and mass media. The impact of social media on diffusion of sustainable mobility opinions is not well-understood given the present lack of data. To address this gap, this paper introduces a modeling framework for the impact of social media on opinion diffusion. Inspired by Roger's diffusion theory, the framework applies different learning mechanisms (e.g., word-of-mouth and mass media) in network architectures to explore the effects of network topology on acceptance of green travel alternatives using conceptual idealizations of the complex processes involved in diffusion interactions. We present a dynamic agent-based simulation methodology capturing the impact of information and communications technology (ICT) like social media on diffusion of environmentally friendly travel mode consideration through social networks. The agent-based models provide visual comparisons of the effects of network structure and social media influence on opinion diffusion, the way opinions spread, and which agents exhibit the strongest influence. We identify types of social media influencers that most effectively encourage adoption of sustainable transportation alternatives and present an illustrative framework of the mechanisms that drive opinion diffusion. Exploratory findings suggest that: (1) scale-free networks provide the slowest initial diffusion rate but the greatest overall diffusion over time, (2) the most effective behavior incentivization strategies depend on network structure, (3) in scale-free networks, increasing the number of initial opinion leaders improves diffusion, while increasing the number of communication encounters within the network over the first year following product deployment does not noticeably improve diffusion, and (4) providing smaller financial incentives to a greater number of opinion leaders is the best strategy.

Original languageEnglish (US)
Pages (from-to)170-183
Number of pages14
JournalTravel Behaviour and Society
Volume19
DOIs
StatePublished - Apr 2020

Keywords

  • Agent-based modeling
  • Diffusion of innovation
  • Social influence
  • Social media
  • Social network
  • Travel behavior change

ASJC Scopus subject areas

  • Transportation

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