Stackelberg Pricing Game for Ride-Hailing Platforms With Combined Travel Modes
Pages 15856 - 15870
Abstract
This paper proposes a pricing strategy based on the variable-ratio charging-compensation scheme for a ride-hailing platform with combined travel modes (Express or Carpool) of riders in a general network composed of multiple corridors. We establish a Stackelberg game model with the platform as a leader and the riders as followers to capture the decision-making process of stakeholders, in which the pricing decision is determined by the platform in the upper level taking each rider’s optimal response into account and travel modes are selected by riders independently in the lower level. The built model is a mixed-integer bilevel programming problem, which is difficult to solve due to its inherent hierarchical structure and discrete variables. By means of some mathematical techniques, we transform the bilevel model equivalently into a single-level mixed-integer nonlinear programming problem. Based on the numerical examples and results analysis, we bring some interesting managerial insights into the pricing of ride-hailing platforms, one of which is that booking fees of Express, unit time and distance fees of Express, compensations for Express riders and Express drivers are the core pricing factors to affect travel mode choices of riders.
References
[1]
Facts & Factors. (2020). Shared Mobility Market By Service (Ride Hailing, Bike Sharing, Ride Sharing, Car Sharing, and Others), By Vehicle (Cars, Two-Wheelers, and Others), and By Bus. Model (P2P, B2B, and B2C)—Global Industry Perspective. [Online]. Available: https://www.fnfresearch.com/shared-mobility-market-by-service-ride-hailing-bike-1240
[2]
(2020). China’s Sharing Economy Development. [Online]. Available: https://www.sic.gov.cn/News/568/10429.htm
[3]
(2020). China Shared Mobility Development. [Online]. Available: https://www.iimedia.cn/c400/75039.html
[4]
M. Armstrong, “Competition in two-sided markets,” RAND J. Econ., vol. 37, no. 3, pp. 668–691, Sep. 2006.
[5]
J.-C. Rochet and J. Tirole, “Two-sided markets: A progress report,” RAND J. Econ., vol. 37, no. 3, pp. 645–667, Sep. 2006.
[6]
X. (Jeff) Ban, M. Dessouky, J.-S. Pang, and R. Fan, “A general equilibrium model for transportation systems with e-hailing services and flow congestion,” Transp. Res. Part B, Methodol., vol. 129, pp. 273–304, Nov. 2019.
[7]
Zebra. (2021). Ways to Create an Income With Your Car. [Online]. Available: https://www.thezebra.com/resources/personal-finance/13-ways-to-create-income-with-car/
[8]
Y.-C. Tseng and C.-L. Chan, “When the sharing economy meets established institutions: Uber and airbnb in Taiwan,” IEEE Trans. Eng. Manag., vol. 68, no. 6, pp. 1895–1906, Dec. 2021.
[9]
H. Wang and H. Yang, “Ridesourcing systems: A framework and review,” Transp. Res. B, Methodol., vol. 129, pp. 122–155, Nov. 2019. 10.1016/j.trb.2019.07.009.
[10]
Y. Zhang, X. Li, and H. Ma, “Can ride-hailing platforms be immune to dual-fairness concerns?,” IEEE Trans. Eng. Manag., vol. 70, no. 3, pp. 1124–1146, Mar. 2023.
[11]
D. Y. Mo, Y. Wang, Y. C. E. Lee, and M. M. Tseng, “Mass customizing paratransit services with a ridesharing option,” IEEE Trans. Eng. Manag., vol. 67, no. 1, pp. 234–245, Feb. 2020.
[12]
FHWA. (2006). Integrated Corridor Management Concepts Development and Foundational Research. [Online]. Available: https://rosap.ntl.bts.gov/view/dot/3684
[13]
M. J. Beck, S. Hess, M. O. Cabral, and I. Dubernet, “Valuing travel time savings: A case of short-term or long term choices?,” Transp. Res. Part E, Logistics Transp. Rev., vol. 100, pp. 133–143, Apr. 2017.
[14]
H.-J. Huang, H. Yang, and M. G. H. Bell, “The models and economics of carpools,” Ann. Regional Sci., vol. 34, no. 1, pp. 55–68, Mar. 2000.
[15]
S. Rajendran and S. Srinivas, “Air taxi service for urban mobility: A critical review of recent developments, future challenges, and opportunities,” Transp. Res. Part E, Logistics Transp. Rev., vol. 143, Nov. 2020, Art. no.
[16]
Q. Tian, P. Liu, G. P. Ong, and H.-J. Huang, “Morning commuting pattern and crowding pricing in a many-to-one public transit system with heterogeneous users,” Transp. Res. Part E, Logistics Transp. Rev., vol. 145, Jan. 2021, Art. no.
[17]
X. Wang, H. Yang, and D. Zhu, “Driver-rider cost-sharing strategies and equilibria in a ridesharing program,” Transp. Sci., vol. 52, no. 4, pp. 868–881, Aug. 2018.
[18]
Y. Yu, R. B. Machemehl, and C. Xie, “Demand-responsive transit circulator service network design,” Transp. Res. Part E, Logistics Transp. Rev., vol. 76, pp. 160–175, Apr. 2015.
[19]
K. Zhang and Y. Nie, “Inter-platform competition in a regulated ride-hail market with pooling,” Transp. Res. Part E, Logistics Transp. Rev., vol. 151, Jul. 2021, Art. no.
[20]
X. Di, R. Ma, H. X. Liu, and X. Ban, “A link-node reformulation of ridesharing user equilibrium with network design,” Transp. Res. Part B, Methodol., vol. 112, pp. 230–255, Jun. 2018.
[21]
H. Xu, F. Ordóñez, and M. Dessouky, “A traffic assignment model for a ridesharing transportation market,” J. Adv. Transp., vol. 49, no. 7, pp. 793–816, Nov. 2015.
[22]
H. Xu, J.-S. Pang, F. Ordóñez, and M. Dessouky, “Complementarity models for traffic equilibrium with ridesharing,” Transp. Res. Part B, Methodol., vol. 81, pp. 161–182, Nov. 2015.
[23]
I. Contrerasa and E. Fernándezb, “General network design: A unified view of combined location and network design problems,” Eur. J. Oper. Res., vol. 219, no. 3, pp. 680–697, 2012.
[24]
T. L. Magnanti and R. T. Wong, “Network design and transportation planning: Models and algorithms,” Transport. Sci., vol. 18, no. 1, pp. 1–55, 1984.
[25]
M. Minoux, “Networks synthesis and optimum network design problems: Models, solution methods and applications,” Networks, vol. 19, no. 3, pp. 313–360, May 1989.
[26]
G. Guo, Y. Hou, and T. Sun, “Fleet sizing for reservation-based car-sharing services allowing cruise parking,” IEEE Intell. Transp. Syst. Mag., vol. 15, no. 4, pp. 106–120, Nov. 2023.
[27]
M. P. Fanti, A. M. Mangini, G. Pedroncelli, and W. Ukovich, “Fleet sizing for electric car sharing systems in discrete event system frameworks,” IEEE Trans. Syst. Man, Cybern. Syst., vol. 50, no. 3, pp. 1161–1177, Mar. 2020.
[28]
J. E. Hughes and D. Kaffine, “When should drivers be encouraged to carpool in HOV lanes?,” Econ. Inquiry, vol. 57, no. 1, pp. 667–684, Jan. 2019.
[29]
J. V. Hall and A. B. Krueger, “An analysis of the labor market for Uber’s driver-partners in the United States,” ILR Rev., vol. 71, no. 3, pp. 705–732, 2018.
[30]
Y. Sun, Z.-L. Chen, and L. Zhang, “Nonprofit peer-to-peer ridesharing optimization,” Transp. Res. Part E, Logistics Transp. Rev., vol. 142, Oct. 2020, Art. no.
[31]
F. Leurent, “Cost versus time equilibrium over a network,” Eur. J. Oper. Res., vol. 71, no. 2, pp. 205–221, Dec. 1993.
[32]
P. S. Lavieri and C. R. Bhat, “Modeling individuals’ willingness to share trips with strangers in an autonomous vehicle future,” Transp. Res. Part A, Policy Pract., vol. 124, pp. 242–261, Jun. 2019.
[33]
Z. Jiang, G. Kong, and Y. Zhang. (2019). A Behavioral Investigation of Workers’ Relocation in on-Demand Platforms. [Online]. Available: https://ssrn.com/abstract=3226727
[34]
J. Forlizzi and S. Ford, “The building blocks of experience: An early framework for interaction designers,” in Proc. 3rd Conf. Designing Interact. Syst., Processes, Practices, Methods, Techn., Aug. 2000, pp. 1–15.
[35]
T. Olsson, E. Lagerstam, T. Kärkkäinen, and K. Väänänen-Vainio-Mattila, “Expected user experience of mobile augmented reality services: A user study in the context of shopping centres,” Pers. Ubiquitous Comput., vol. 17, no. 2, pp. 287–304, Feb. 2013.
[36]
G. Guo and T. Sun, “Selective multi-grade charging scheduling and rebalancing for one-way car-sharing systems,” IEEE Trans. Intell. Transp. Syst., vol. 24, no. 4, pp. 4391–4402, Apr. 2023.
[37]
S. Kujala, V. Roto, K. Väänänen-Vainio-Mattila, E. Karapanos, and A. Sinnelä, “UX curve: A method for evaluating long-term user experience,” Interacting Comput., vol. 23, no. 5, pp. 473–483, Sep. 2011.
[38]
J. Ke, X. Li, H. Yang, and Y. Yin, “Pareto-efficient solutions and regulations of congested ride-sourcing markets with heterogeneous demand and supply,” Transp. Res. Part E, Logistics Transp. Rev., vol. 154, Oct. 2021, Art. no.
[39]
E. Özkan, “Joint pricing and matching in ride-sharing systems,” Eur. J. Oper. Res., vol. 287, no. 3, pp. 1149–1160, Dec. 2020.
[40]
L. Zha, Y. Yin, and Y. Du, “Surge pricing and labor supply in the ride-sourcing market,” Transp. Res. Proc., vol. 23, pp. 2–21, Sep. 2017.
[41]
H. Guda and U. Subramanian, “Your Uber is arriving: Managing on-demand workers through surge pricing, forecast communication, and worker incentives,” Manag. Sci., vol. 65, no. 5, pp. 1995–2014, 2019.
[42]
Z. Q. Luo and R. Saigal. (2017). Dynamic Pricing for on-Demand Ride-Sharing: A Continuous Approach. [Online]. Available: https://papers.ssrn.com/sol3/papers.cfm?abstract=3056498
[43]
G. Guo and Y. Xu, “A deep reinforcement learning approach to ride-sharing vehicle dispatching in autonomous mobility-on-demand systems,” IEEE Intell. Transp. Syst. Mag., vol. 14, no. 1, pp. 128–140, Jan. 2022.
[44]
G. Guo and X. Li, “A scientometric review of mobility-on-demand car-sharing systems,” IEEE Intell. Transp. Syst. Mag., vol. 15, no. 1, pp. 212–229, Jan. 2023.
[45]
G. Guo and T. Xu, “Vehicle rebalancing with charging scheduling in one-way car-sharing systems,” IEEE Trans. Intell. Transp. Syst., vol. 23, no. 5, pp. 4342–4351, May 2022.
[46]
Deloitte. (2016). Economic Effects of Ridesharing in Australia. [Online]. Available: https://www2.deloitte.com/content/dam/
[47]
J. G. Wardrop, “Some theoretical aspects of road traffic research,” Proc. Inst. Civil Eng., vol. 1, pp. 325–378, Sep. 1952.
[48]
Y. Tu, M. Khaloei, N. Zuniga-Garcia, and D. MacKenzie, “Understanding working time and relocation choices of ridehailing drivers,” 2024, arXiv:2401.04755.
[49]
X. Di and X. J. Ban, “A unified equilibrium framework of new shared mobility systems,” Transp. Res. Part B, Methodol., vol. 129, pp. 50–78, Nov. 2019.
[50]
H. Yang and M. G. H. Bell, “Transport bilevel programming problems: Recent methodological advances,” Transp. Res. Part B, Methodol., vol. 35, no. 1, pp. 1–4, Jan. 2001.
[51]
L. Zhao, X. Xu, H. O. Gao, J. Wang, and Y. Xie, “A bi-level model for GHG emission charge based on a continuous distribution of travelers’ value of time (VOT),” Transp. Res. Part D, Transp. Environ., vol. 47, pp. 371–382, Aug. 2016.
[52]
S. S. Mofidi and J. A. Pazour, “When is it beneficial to provide freelance suppliers with choice? A hierarchical approach for peer-to-peer logistics platforms,” Transp. Res. Part B, Methodol., vol. 126, pp. 1–23, Aug. 2019.
[53]
N. A. El-Taweel, H. E. Z. Farag, and M. Mohamed, “Integrated utility-transit model for optimal configuration of battery electric bus systems,” IEEE Syst. J., vol. 14, no. 1, pp. 738–748, Mar. 2020.
[54]
Z. H. Gümüş and C. A. Floudas, “Global optimization of nonlinear bilevel programming problems,” J. Global Optim., vol. 20, no. 1, pp. 1–31, 2001.
[55]
P. Fontaine and S. Minner, “Benders decomposition for discrete–continuous linear bilevel problems with application to traffic network design,” Transp. Res. Part B, Methodol., vol. 70, pp. 163–172, Dec. 2014.
[56]
V. DeMiguel and W. Murray, “A local convergence analysis of bilevel decomposition algorithms,” Optim. Eng., vol. 7, no. 2, pp. 99–133, Jun. 2006.
[57]
B. El-Sobky and Y. Abo-Elnaga, “A penalty method with trust-region mechanism for nonlinear bilevel optimization problem,” J. Comput. Appl. Math., vol. 340, pp. 360–374, Oct. 2018.
[58]
Z. Di and L. Yang, “Reversible lane network design for maximizing the coupling measure between demand structure and network structure,” Transp. Res. Part E, Logistics Transp. Rev., vol. 141, Sep. 2020, Art. no.
[59]
F. Facchinei, H. Jiang, and L. Qi, “A smoothing method for mathematical programs with equilibrium constraints,” Math. Program., vol. 85, no. 1, pp. 107–134, 1999.
[60]
Z. Q. Luo, J. S. Pang, and D. Ralph, Mathematical Programs With Equilibrium Constraints. Cambridge, U.K.: Cambridge Univ. Press, 1996.
Index Terms
- Stackelberg Pricing Game for Ride-Hailing Platforms With Combined Travel Modes
Index terms have been assigned to the content through auto-classification.
Recommendations
Comparison of three participation modes on ride-hailing platforms
Highlights- Compare and analyse three popular participation modes on the ride-hailing platform.
AbstractWith the rapid development of ride-hailing services, various participation modes have emerged on ride-hailing platforms that are recruiting drivers to serve the growing number of passengers. This paper investigates three popular ...
Pricing in Ride-Sharing Platforms: A Queueing-Theoretic Approach
EC '15: Proceedings of the Sixteenth ACM Conference on Economics and ComputationWe study optimal pricing strategies for ride-sharing platforms, using a queueing-theoretic economic model. Analysis of pricing in such settings is complex: On one hand these platforms are two-sided - this requires economic models that capture the ...
Promoting electric vehicle adoption in ride-hailing platforms: To control or subsidize?
Highlights- We study the policy choice for promoting the adoption of electric vehicles in ride-hailing platform.
- Control policy and subsidy policy are considered.
- We obtain optimal decisions of government and ride-hailing platform.
- We ...
AbstractTo promote ride-hailing platforms’ adoption of electric vehicles (EVs), two primary policies (i.e., control policy and subsidy policy) have been implemented by different governments in the real world. Which policy is more appropriate for the ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
1524-9050 © 2024 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See https://www.ieee.org/publications/rights/index.html for more information.
Publisher
IEEE Press
Publication History
Published: 01 November 2024
Qualifiers
- Research-article
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 0Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Reflects downloads up to 20 Jan 2025