Abstract
As public perception about the shared economy evolves, peer-to-peer ridesharing has been gaining increased attention worldwide. Both private and public sector entities have launched mobile app-based ridesharing services, while a range of methodologies and system architectures have been proposed in academia. Whereas traditional ridesharing methods match drivers and riders when their origin and destination are similar, recently proposed algorithms often feature multi-hop and multimodal properties that allow riders to be connected by multiple modes. Such algorithms can reduce travel time and/or travel cost; however, they may also add other travel impedances, such as requiring multiple transfers. Understanding user behavior toward such new ridesharing systems is essential for successful service design. For policymakers and service planners, identifying factors that impact traveler choices can lead to better design and improved services. This research involved a web-based survey to capture traveler preferences using a conjoint analysis framework. A choice-based method was adopted to identify factors for the estimation model and to analyze traveler willingness to pay. Among the proposed factors, the number-of-transfers was shown to be the most important, as was expected. When a multimodal ridesharing system provides less travel time, low travel cost, and sufficient ridesharing incentive, people are more likely to pay for the service.
Highlights
As a part of the newly developing shared economy, ridesharing systems (RSS) are becoming popular throughout the world, providing sustainable transportation that fills empty seats in existing vehicles
In previous studies that were completed at UC Irvine [1,7], a multimodal ridesharing system was proposed to enhance the use of the LA Metro Red Line, allowing transfers between shared-ride cars and the LA
The statistical significance test was conducted for the four defined impact factors for a multimodal ridesharing system
Summary
As a part of the newly developing shared economy, ridesharing systems (RSS) are becoming popular throughout the world, providing sustainable transportation that fills empty seats in existing vehicles. A combination of public transit and ridesharing can impact mobility; for example, one study [2] reported that 30% of shared mobility users reported driving to work less often In line with these findings, research on mobility platforms suggests that these can lead to enhanced urban mobility, which can create a dynamic multimodal lifestyle by integrating. If commuters who currently ride public transit want to use multimodal RSS to reduce travel time, they might need to pay more and, may not be willing to accept this option if they are not compensated with some type of incentive. We summarize the findings and conclude the paper with a discussion on future research opportunities (Section 6)
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