TY - GEN
T1 - Optimizing Ride-Hailing Supply Scale and Platform Revenue
T2 - 24th COTA International Conference of Transportation Professionals: Resilient, Intelligent, Connected, and Lowcarbon Multimodal Transportation, CICTP 2024
AU - Zhang, Xiaojun
AU - Liu, Yongwu
AU - Zhao, Jinqiu
AU - Yu, Le
AU - Xie, Binglei
N1 - Publisher Copyright:
© ASCE.
PY - 2024
Y1 - 2024
N2 - Ride-hailing services, an emerging model in the taxi market, have transformed passenger travel, challenging traditional taxis. However, current commission strategies on online platforms often neglect traditional taxis’ interests, reducing their willingness to accept orders. This paper explores commission strategies for platforms offering both traditional and non-traditional taxi services, aiming to optimize supply and platform revenue. We consider price-sensitive passengers and commission-sensitive drivers, constructing demand and supply functions for different services. We formulated revenue functions for ride-sharing services (comprising both ride-sharing taxis and other ride-sharing options) and traditional taxis (including ride-sharing taxis and other alternatives). We constructed a price competition game model and obtained price equilibrium solutions. By incorporating these price equilibrium solutions into the models mentioned earlier, we derived the supply-demand functions and revenue functions for ride-sharing services, with the commission rates as variables. Numerical experiments reveal that increasing ride-sharing service commissions at specific times decreases supply. Time-based commission strategies further optimize ride-sharing earnings.
AB - Ride-hailing services, an emerging model in the taxi market, have transformed passenger travel, challenging traditional taxis. However, current commission strategies on online platforms often neglect traditional taxis’ interests, reducing their willingness to accept orders. This paper explores commission strategies for platforms offering both traditional and non-traditional taxi services, aiming to optimize supply and platform revenue. We consider price-sensitive passengers and commission-sensitive drivers, constructing demand and supply functions for different services. We formulated revenue functions for ride-sharing services (comprising both ride-sharing taxis and other ride-sharing options) and traditional taxis (including ride-sharing taxis and other alternatives). We constructed a price competition game model and obtained price equilibrium solutions. By incorporating these price equilibrium solutions into the models mentioned earlier, we derived the supply-demand functions and revenue functions for ride-sharing services, with the commission rates as variables. Numerical experiments reveal that increasing ride-sharing service commissions at specific times decreases supply. Time-based commission strategies further optimize ride-sharing earnings.
UR - https://www.scopus.com/pages/publications/85213942426
U2 - 10.1061/9780784485484.139
DO - 10.1061/9780784485484.139
M3 - 会议稿件
AN - SCOPUS:85213942426
T3 - CICTP 2024: Resilient, Intelligent, Connected, and Lowcarbon Multimodal Transportation - Proceedings of the 24th COTA International Conference of Transportation Professionals
SP - 1466
EP - 1476
BT - CICTP 2024
A2 - Ma, Jianming
A2 - Luo, Qin
A2 - Sun, Lijun
A2 - Li, Baicheng
A2 - Chen, Jingjing
A2 - Zhang, Guohui
PB - American Society of Civil Engineers (ASCE)
Y2 - 23 July 2024 through 26 July 2024
ER -