Matching supply and demand on ride-sharing platforms with permanent agents and competition

Zhong, Yuanguang; Lin, Zhaozhan; Zhou, Yong; Cheng, T.C.E.; Lin, Xiaogang

doi:10.1016/j.ijpe.2019.07.009

Cited by 58 publications

(24 citation statements)

References 10 publications

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“…Existing research has taken competition as the research background and quantitatively considered platform decision-making in a competitive environment. For example, Zhong et al (2019) determined the subsidy level of temporary providers and/or the employment level of permanent providers in monopolistic and duopoly competitive environments and analyzed the impact of the employment level of permanent providers and platform competition on the platform's subsidy strategies and profitability, participant surplus and social welfare. Zhong et al (2021) studied how on-demand ride-hailing platforms that compete with the traditional taxi industry design their pricing strategies under irregular and regulated pricing scenarios and focused on government regulatory strategies to develop the transportation industry.…”

Section: Multiple Platformsmentioning

confidence: 99%

“…PricewaterhouseCoopers predicted that service platforms would generate over US$330 billion in revenues worldwide by 2025(Federal Trade Commission, 2016. Notably, in the last decade, the on-demand economy has experienced rapid growth and accumulated a large consumer base (Zhong et al, 2019). The on-demand economy is supported by online platforms that match consumers' demands with service offerings upon receiving the order of consumers (Taylor, 2018).…”

Section: Introductionmentioning

confidence: 99%

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On-demand service platform operations management: a literature review and research agendas

Yan

Liu²,

Shi³

et al. 2022

MSCRA

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PurposeThe literature review aims to facilitate a broader understanding of on-demand service platform operations management and proposes potential research directions for scholars.Design/methodology/approachThis study searches four databases for relevant literature on on-demand service platform operations management and selects 72 papers for this review. According to the research context, the literature can be divided into research on “a single platform” and research on “multiple platforms”. According to the research methods, the literature can be classified into “Mathematical Models”, “Empirical Studies”, “Multiple Methods” and “Literature Review”. Through comparative analysis, we identify research gaps and propose five future research agendas.FindingsThis paper proposes five research agendas for future research on on-demand service platform operations management. First, research can be done to combine classic research problems in the field of operations management with platform characteristics. Second, both the dynamic and steady-state issues of on-demand service platforms can be further explored. Third, research employing mathematical models and empirical analysis simultaneously can be more fruitful. Fourth, more research efforts on the various interactions among two or more platforms can be pursued. Last but not least, it is worthwhile to examine new models and paths that have emerged during the latest development of the platform economy.Originality/valueThrough categorizing the literature into two research contexts as well as classifying it according to four research methods, this article clearly shows the research progresses made so far in on-demand service platform operations management and provides future research directions.

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Section: Multiple Platformsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

On-demand service platform operations management: a literature review and research agendas

Yan

Liu²,

Shi³

et al. 2022

MSCRA

View full text Add to dashboard Cite

show abstract

“…Recent literature has paid increasing attention to shared platforms. Zhong et al (2019) shared platforms that recruit permanent or temporary agents to provide car services for passengers. They find that the subsidy level of temporary agents or the employment of permanent agents is determined to balance agent supply and rider demand to maximize platform profit.…”

Section: Literature Reviewmentioning

confidence: 99%

Pricing strategy for logistics service platforms with competition and user distance preference

Hou

Lin

et al. 2021

Int Trans Operational Res

Self Cite

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In practice, the demanders (customers) and providers (sellers) of logistics service platforms not only care about prices but also are sensitive to the spatial distance between each other (because longer distance would lead to longer service waiting time). We study the impacts of spatial distance preference on two competing logistics platforms' pricing strategies. Two groups of agents (demanders and providers) are required to pay the logistics service platform a fixed (registration) fees to gain access. We analyze two commonly seen scenarios in practice: (i) the single-homing model-both demanders and providers can only join one of the platforms; (ii) the competitive bottleneck model-demanders (providers) can join only one of the platforms while providers (demanders) are allowed to join both platforms. We find that under the single-homing setting, an increase in demanders' (providers') distance preference would lead to higher but lower (lower but higher) prices charged to demanders and providers, respectively, and higher profits of both platforms. Under the competitive bottleneck model, however, the price charged to demanders (providers) might decrease (increase) in demanders' (providers') distance preference. Finally, compared to the case in which both sides single homing, we find that allowing providers or demanders to join both platforms would decrease the profits of both platforms if users' distance preference is sufficiently low or high.

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“…Even when dynamic pricing is limited, our research can be a reference for a platform's static pricing decisions, for example, in regard to the range of static prices based on different regions' market demand. Some of the ride-hailing platform's social responsibilities are to reduce traffic congestion, make travel better, and help users improve the travel efficiency (e.g., Didi Chuxing and Meituan; Zhong et al [59]). From this perspective, the platform can change service quality or improve its fixed commission rate to achieve the purpose of improving traffic conditions when market demand is increasing.…”

Section: Managerial Insightsmentioning

confidence: 99%

Dynamic Pricing of Ride-Hailing Platforms considering Service Quality and Supply Capacity under Demand Fluctuation

Sun

Shi

2020

Mathematical Problems in Engineering

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Increasing attention is being paid to the pricing decisions of ride-hailing platforms. These platforms usually face market demand fluctuation and reflect supply and demand imbalances. Unlike existing studies, we focus on the optimal dynamic pricing of the platforms under imbalance between supply and demand caused by market fluctuation. Dynamic models are constructed based on the state change of supply and demand by using optimal control theory, with the aim of maximizing the platform’s total profit. We obtain the optimal trajectories of price, supply, and demand under three ride demand situations. The effects of some key parameters on pricing decisions, such as coefficient of demand fluctuation, service quality, and fixed commission rate, are examined. We find the optimal dynamic price can improve the match of supply-demand in ride-hailing market and enhance the revenue of platform.

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Matching supply and demand on ride-sharing platforms with permanent agents and competition

Cited by 58 publications

References 10 publications

On-demand service platform operations management: a literature review and research agendas

On-demand service platform operations management: a literature review and research agendas

Pricing strategy for logistics service platforms with competition and user distance preference

Dynamic Pricing of Ride-Hailing Platforms considering Service Quality and Supply Capacity under Demand Fluctuation

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