TY - JOUR
T1 - Analysis of multi-modal commute behavior with feeding and competing ridesplitting services
AU - Zhu, Zheng
AU - Qin, Xiaoran
AU - Ke, Jintao
AU - Zheng, Zhengfei
AU - Yang, Hai
N1 - Funding Information:
The work described in this paper is partially supported by Hong Kong Research Grants Council under projects HKUST16222916 and NHKUST627/18, and is partially supported by the Hong Kong University of Science and Technology - DiDi Chuxing (HKUST-DiDi) Joint Laboratory. The opinions in this paper do not necessarily reflect the official views of HKUST-DiDi Joint Laboratory. The authors are responsible for all statements. The authors would also like to acknowledge all the reviewers for their constructive comments.
Funding Information:
The work described in this paper is partially supported by Hong Kong Research Grants Council under projects HKUST16222916 and NHKUST627/18 , and is partially supported by the Hong Kong University of Science and Technology - DiDi Chuxing (HKUST-DiDi) Joint Laboratory. The opinions in this paper do not necessarily reflect the official views of HKUST-DiDi Joint Laboratory. The authors are responsible for all statements. The authors would also like to acknowledge all the reviewers for their constructive comments. Appendix A
Publisher Copyright:
© 2019 Elsevier Ltd
PY - 2020/2
Y1 - 2020/2
N2 - Public transit is an essential travel mode in many urban areas. Emerging dynamic ridesplitting programs provided by transportation network companies (TNCs) can be a double-edged sword to public transit. On the one hand, the program provides convenient services to solve first- and last-mile problems. On the other hand, long-distance ridesplitting services may also draw passengers away from public transit. In this paper, we propose a network model to analyze multi-modal commute behavior with ridesplitting programs as both feeders and competitors to public transit, which is with limited accessibility to passengers. The ridesplitting priority and ridesplitting fare ratio (i.e., ridesplitting fare over non-ridesplitting fare) are incorporated as operational strategies of the TNC. Through numerical studies, we find that a significant number of public transit passengers will shift to long-distance ridesplitting services under low fare ratios; and a high ridesplitting priority can lead to a demand drawback for long-distance ridesplitting, which raises public transit ridership. To maintain public transit ridership, the TNC needs to keep a high fare ratio and a high priority; meanwhile, the number of short-distance ridesplitting orders can also decrease dramatically, which may lead to a loss in unit time revenue of the TNC. We note that a win–win condition can be reached through a separated discount strategy for first- and last-mile ridesplitting services. Such a strategy can both increase the number of short-distance ridesplitting orders for the TNC and boost transit ridership for the government, as well as provide low-cost services to passengers.
AB - Public transit is an essential travel mode in many urban areas. Emerging dynamic ridesplitting programs provided by transportation network companies (TNCs) can be a double-edged sword to public transit. On the one hand, the program provides convenient services to solve first- and last-mile problems. On the other hand, long-distance ridesplitting services may also draw passengers away from public transit. In this paper, we propose a network model to analyze multi-modal commute behavior with ridesplitting programs as both feeders and competitors to public transit, which is with limited accessibility to passengers. The ridesplitting priority and ridesplitting fare ratio (i.e., ridesplitting fare over non-ridesplitting fare) are incorporated as operational strategies of the TNC. Through numerical studies, we find that a significant number of public transit passengers will shift to long-distance ridesplitting services under low fare ratios; and a high ridesplitting priority can lead to a demand drawback for long-distance ridesplitting, which raises public transit ridership. To maintain public transit ridership, the TNC needs to keep a high fare ratio and a high priority; meanwhile, the number of short-distance ridesplitting orders can also decrease dramatically, which may lead to a loss in unit time revenue of the TNC. We note that a win–win condition can be reached through a separated discount strategy for first- and last-mile ridesplitting services. Such a strategy can both increase the number of short-distance ridesplitting orders for the TNC and boost transit ridership for the government, as well as provide low-cost services to passengers.
KW - Choice modeling
KW - First-mile and last-mile problem
KW - Public transit ridership
KW - Ridesplitting program
UR - http://www.scopus.com/inward/record.url?scp=85077182287&partnerID=8YFLogxK
U2 - 10.1016/j.tra.2019.12.018
DO - 10.1016/j.tra.2019.12.018
M3 - Journal article
AN - SCOPUS:85077182287
SN - 0965-8564
VL - 132
SP - 713
EP - 727
JO - Transportation Research Part A: Policy and Practice
JF - Transportation Research Part A: Policy and Practice
ER -