Taxi in competition with online car-hailing drivers: Policy implication to operating strategies

Car-hailing and taxis coexist and constitute a healthy market in normal times when demand is sufficient for growing supplies. However, in a limited market influenced by disruptive issues such as COVID-19, drivers from online car-hailing and local taxi operators have been compelled to engage in compe...

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Main Authors: Tianqi Gu, Weiping Xu, Peijie Shi, Ruiyi Wang, Inhi Kim
Format: Article
Language:English
Published: Elsevier 2024-06-01
Series:Multimodal Transportation
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2772586324000108
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author Tianqi Gu
Weiping Xu
Peijie Shi
Ruiyi Wang
Inhi Kim
author_facet Tianqi Gu
Weiping Xu
Peijie Shi
Ruiyi Wang
Inhi Kim
author_sort Tianqi Gu
collection DOAJ
description Car-hailing and taxis coexist and constitute a healthy market in normal times when demand is sufficient for growing supplies. However, in a limited market influenced by disruptive issues such as COVID-19, drivers from online car-hailing and local taxi operators have been compelled to engage in competition due to the shrinking revenue. The distinct occupational characteristics and operation patterns of drivers in different groups directly influence their operational strategies (whether to operate or not), which remains an unexplored research area. To this end, this article analyzes the contrast in diverse operating indicators between the two service models before and following the outbreak of the epidemic based on a local case study in Suzhou. It establishes an income matrix for drivers in varied scenarios and employs evolutionary game theory (EGT) to dissect the dynamic operating strategies of taxi and online car-hailing drivers. Furthermore, considering the impact of disruptive issues on market demand, this study also introduces an optimized dynamic income incentive mechanism. The findings demonstrate that when disruptive issues arise and last for a considerable extended period, a 'winner-takes-all' market scenario might unfold - the potential monopoly of one service type. To circumvent this scenario, proactive human intervention can be employed at opportune moments, such as augmenting initial income, to establish the equilibrium state of ESS (1,1)—a balanced and robust coexistence of the two services. Overall, this paper provides a set of novel indicators to identify different drivers’ operation strategies, and applies EGT to analyze and estimate their operation strategies during disruptive events.
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spelling doaj.art-1aa7ef36c6574ad09d31f77b91d3852b2024-03-10T05:13:25ZengElsevierMultimodal Transportation2772-58632024-06-0132100129Taxi in competition with online car-hailing drivers: Policy implication to operating strategiesTianqi Gu0Weiping Xu1Peijie Shi2Ruiyi Wang3Inhi Kim4Monash Suzhou Research Institute, Monash University, Suzhou Industrial Park, Suzhou, ChinaTransport Research Center, CCDI (SuZhou) Exploration & Design Consultant CO., LtdTransport Research Center, CCDI (SuZhou) Exploration & Design Consultant CO., LtdSchool of Transport, Southeast University, Nanjing, ChinaCho Chun Shik Graduate School of Mobility, KAIST, Korea; Corresponding author.Car-hailing and taxis coexist and constitute a healthy market in normal times when demand is sufficient for growing supplies. However, in a limited market influenced by disruptive issues such as COVID-19, drivers from online car-hailing and local taxi operators have been compelled to engage in competition due to the shrinking revenue. The distinct occupational characteristics and operation patterns of drivers in different groups directly influence their operational strategies (whether to operate or not), which remains an unexplored research area. To this end, this article analyzes the contrast in diverse operating indicators between the two service models before and following the outbreak of the epidemic based on a local case study in Suzhou. It establishes an income matrix for drivers in varied scenarios and employs evolutionary game theory (EGT) to dissect the dynamic operating strategies of taxi and online car-hailing drivers. Furthermore, considering the impact of disruptive issues on market demand, this study also introduces an optimized dynamic income incentive mechanism. The findings demonstrate that when disruptive issues arise and last for a considerable extended period, a 'winner-takes-all' market scenario might unfold - the potential monopoly of one service type. To circumvent this scenario, proactive human intervention can be employed at opportune moments, such as augmenting initial income, to establish the equilibrium state of ESS (1,1)—a balanced and robust coexistence of the two services. Overall, this paper provides a set of novel indicators to identify different drivers’ operation strategies, and applies EGT to analyze and estimate their operation strategies during disruptive events.http://www.sciencedirect.com/science/article/pii/S2772586324000108TaxiCar-hailingDynamic operating strategyCOVID-19Evolutionary game theory
spellingShingle Tianqi Gu
Weiping Xu
Peijie Shi
Ruiyi Wang
Inhi Kim
Taxi in competition with online car-hailing drivers: Policy implication to operating strategies
Multimodal Transportation
Taxi
Car-hailing
Dynamic operating strategy
COVID-19
Evolutionary game theory
title Taxi in competition with online car-hailing drivers: Policy implication to operating strategies
title_full Taxi in competition with online car-hailing drivers: Policy implication to operating strategies
title_fullStr Taxi in competition with online car-hailing drivers: Policy implication to operating strategies
title_full_unstemmed Taxi in competition with online car-hailing drivers: Policy implication to operating strategies
title_short Taxi in competition with online car-hailing drivers: Policy implication to operating strategies
title_sort taxi in competition with online car hailing drivers policy implication to operating strategies
topic Taxi
Car-hailing
Dynamic operating strategy
COVID-19
Evolutionary game theory
url http://www.sciencedirect.com/science/article/pii/S2772586324000108
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