Abstract
Background: In this paper, a crowd-based social interaction framework is developed to assess the potential increase in the use of sustainable transportation modes – such as walking, bicycling and public transit. Methods: The empirical data were used to validate mode shift behaviors for 77 participants from California State University Long Beach. Data collection spanned over two phases, Phase I followed by Phase II. Each study phase lasted a month. Participants used one of the four modes – personal car, walking, bicycling and public transit - to arrive at the university campus. During Phase I, a control group was created, and individual mode choice of participants were obtained. Individual participants in Phase II were assigned short-encrypted distinct names and were asked to post a daily comment on the quality of experience using the mode that was used to arrive at the campus. The participants were asked to post the comments over a “Twitter” page that was used as the crowdsourcing platform for this study. The encrypted name masked the individual identity of the user. Analysis at the end of Phase II showed that there was an overall mode-shift of almost 19% of personal car users to other sustainable modes of walking, bicycling and transit. Results: Results show very important policy implications of using crowdsourcing as a social interaction tool to influence mode choice behavior of commuters, especially among college students and young adults. Conclusion: A crowd-based social interaction framework is developed to assess potential increase in the use of sustainable transportation modes – such as walking, bicycling, and public transit. Results showed that providing advanced information on traffic and parking problems can result in a mode shift to active transportation modes.
Highlights
Crowdsourcing is emerging as a significant social interaction tool to provide possible solutions to problems that are traditionally expensive to solve individually [1,2]
The empirical exercise is carried out to assess any mode shift observed among four different transportation modes - car, transit bus, bicycling and walking - for 77 students from California State University, Long Beach (CSULB)
The data collection was carried out spanning over a two-month period divided into two phases of one month each Phase I and Phase II
Summary
Crowdsourcing is emerging as a significant social interaction tool to provide possible solutions to problems that are traditionally expensive to solve individually [1,2]. When used effectively, crowdsourcing can use the public’s intelligence and skills to solve complex issues [4]. The collection of information through crowdsourcing is often facilitated by Crowdsourcing can be used to determine human behavior on transportation choice decision making. In transportation, crowdsourcing, when used as social media, can be used to obtain real-time conditions of nearby public transit and rail lines, traffic delays, and parking conditions [6]. Inherent complexities involved in capturing human behavior make surveys and interviews the best approach for understanding mode choice. A crowd-based social interaction framework is developed to assess the potential increase in the use of sustainable transportation modes – such as walking, bicycling and public transit
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
