PhD candidate Sicheng Wang is recipient of IACP Best Student Paper Award

November 9, 2020

The International Association for China Planning (IACP) recently announced that Ph.D. candidate Sicheng Wang is the recipient of the IACP Karen Polenske IACP Best Student Paper Award for his paper, “What is the elasticity of sharing a ride-sourcing trip?”  The paper was co-authored with Bloustein professor Robert Noland, who also serves as Sicheng’s dissertation chair.

The IACP is an independent non-profit organization of scholars, students, and practitioners interested in China’s planning issues. Founded in Washington DC, USA, in 2005, IACP has more than 2000 members and friends, including professors and students at universities, planners and managers from international institutions, government agencies and consulting firms, and other professionals. The IACP Best Student Paper Award, established in honor of Massachusetts Institute of Technology Professor Karen R. Polenske, a prominent regional economist and a leading scholar of China’s sustainable development, is given annually to student IACP members who present excellent research at major international planning conferences. Its website is:

The paper examines the temporal and spatial distribution of authorized ride-splitting trips in 2019. Transportation network companies (TNCs) offer a ride-splitting option for ride-sourcing trips, allowing users to share the vehicle with others at a lower fare. While encouraging shared rides has environmental benefits, little is known about how price affects the decision to share. Using TNC trip data from Chicago, they found that the willingness to share TNC trips differed across neighborhoods with different demographics, socioeconomic status, and built environment characteristics. The willingness to share was related to price and time factors, such as price per mile, total price, and trip duration.

The results indicate the probability of authorizing a ride-splitting trip is highly elastic to the price per mile – the most important predictor in the random forest model, which had better accuracy than the logistic model. Additionally, they examined the importance and marginal effects of the total price and trip duration. The results suggest trip duration is positively associated with the willingness to share. Policy implications for increasing shared trips are also discussed based on the findings.

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