The entry quality threshold setting and commission rate contract selection of a peer-to-peer service sharing platform

Chi, Xue; Fan, Zhi‐Ping; Wang, Xiaohuan

doi:10.1108/k-02-2022-0248

Cited by 5 publications

(5 citation statements)

References 46 publications

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“…Chi et al. (2023) explore investment strategies for a peer‐to‐peer sharing platform with risk prevention measures to address consumers’ perceived safety risks. They examine the conditions under which risk prevention measures benefit the platform, consumes, and service providers.…”

Section: Literature Reviewmentioning

confidence: 99%

Dynamic competition and market structure for platform‐based products: roles of product quality and indirect network effect

Dou,

Wei,

et al. 2024

Int Trans Operational Res

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We consider dynamic competition between two platform‐based products that exhibit two‐sided network effects, such as game consoles and intelligent hardware. Firms compete in terms of pricing and Research & Development investment, which are driven by consumers’ marginal utility of quality, indirect network effects, and the differentiation between consumers’ preference for the products. We find that with a small marginal utility of consumers, the equilibrium investment of one firm increases first and decreases later with its product quality but is not obviously sensitive to the rival's. In contrast, with a large marginal utility, if the quality of the two products is comparable, the equilibrium investment increases substantially. However, if one product pulls ahead, the other firm will stop investing. Besides, we find that when the intrinsic value and the network value coexist, the market becomes more concentrated, even when consumers’ marginal utility is small. The market concentration increases in both the consumers’ marginal utility and the indirect network effect but decreases in the degree of differentiation between consumers’ preference toward the two products. Interestingly, we show that differentiation plays an important role in shaping the market structure only when the network effect is weak. Counterintuitively, we show that the differentiation corrodes firms’ total profits, which demonstrates that less fierce competition resulting from low substitution leads to a lower profit. Additionally, we reveal that dynamic interaction between quality and installed base motivates firms to improve from a low quality, the first‐mover advantage does not ensure market dominance.

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Section: Literature Reviewmentioning

confidence: 99%

Dynamic competition and market structure for platform‐based products: roles of product quality and indirect network effect

Dou,

Wei,

et al. 2024

Int Trans Operational Res

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“…To facilitate the analysis, we consider that the basic valuation v obtained by each consumer is heterogeneous, and v is uniformly distributed in the whole consumer group, that is, v ∼ U [0, 1]. Without loss of generality, we normalize the total number of consumers in the market to 1 (Chi et al, 2022;Guo et al, 2022) and assume that the utility obtained by consumers leaving the platform is 0, which are widely used in the existing literature (Hall and Porteus, 2000;Jiang and Tian, 2016;Zhao et al 2021). Additionally, following Guda and Subramanian (2019) and Liu et al (2019), we consider that the potential number of h-type drivers and l-type drivers in the market is enough so that the platform can recruit S drivers, and S should satisfy S > 4kτ β 2 −4k to ensure the existence of the optimal solutions under the three service modes.…”

Section: Notations and Problem Descriptionmentioning

confidence: 99%

“…To facilitate the analysis, we consider that the basic valuation

v

obtained by each consumer is heterogeneous, and

v

is uniformly distributed in the whole consumer group, that is,

v\sim U[0,1]

. Without loss of generality, we normalize the total number of consumers in the market to 1 (Chi et al., 2022; Guo et al., 2022) and assume that the utility obtained by consumers leaving the platform is 0, which are widely used in the existing literature (Hall and Porteus, 2000; Jiang and Tian, 2016; Zhao et al. 2021).…”

Section: Notations and Problem Descriptionmentioning

confidence: 99%

The strategic analysis of service mode selection for a ride‐hailing platform

Guo

Fan

Liu

2023

Int Trans Operational Res

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This paper examines the service mode selection strategy of a ride‐hailing platform and analyzes the impact of the strategy on consumers and drivers. The platform has three service modes to select from, including Mode L (only low‐quality services), Mode H (only high‐quality services), and Mode HL (high‐ and low‐quality services). We find that each service mode does not affect the price and the wage of the low‐quality service but affects those of the high‐quality service. Additionally, the platform cannot optimally select Mode L. The platform is better off if the car quality difference between high‐ and low‐quality services (CQD) is small and is worse off otherwise, under Mode HL. Counter‐intuitively, it is conditional for Mode HL to bring the highest surpluses to both consumers and drivers, and the conditions are related to CQD, social status utility of consumers and cost ratio between the drivers providing the two types of services.

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“…With the development of information network technology and social media, service-sharing platforms have fourished in just a few years [1]. For example, these platforms include Airbnb, Uber, Upwork, TaskRabbit, and Tumbtack [2].…”

Section: Introductionmentioning

confidence: 99%

“…In P2P service-sharing markets, service providers' service quality is uneven [8], and consumers are unaware of this. As a result, there is information asymmetry between service providers and consumers, which makes it difcult for consumers to obtain accurate quality information before booking services [1]. Some drivers of ride-hailing platforms such as Uber and Didi may not be familiar with the roads or have detour issues.…”

Section: Introductionmentioning

confidence: 99%

Pricing Policy Selection in a Platform Service Supply Chain with Online Reviews

Tian,

Wang,

Meng

et al. 2023

Discrete Dynamics in Nature and Society

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In the operation of service-sharing platforms, online review information is crucial to attracting consumers. Considering consumers’ preference for online review information, this paper discusses the pricing policy selection for a service-sharing platform providing vertically differentiated services in sharing economy, which is worth studying. In this paper, a platform service supply chain composed of a high-quality service provider, a low-quality service provider, and a service-sharing platform is considered. For the two pricing policies of a platform: service provider pricing and platform pricing, the profit-maximizing models are constructed, and the optimal high-quality and the low-quality service prices are obtained. This paper also analyzes the effects of online review information on the profits of service providers, platform profits, consumer surplus, and social welfare under the two policies. The results show that under the platform pricing policy, the platform can gain more profits, while the surplus of consumers and service providers may decrease. When the online review information exceeds a threshold, the high-quality service provider profit under the service provider pricing policy is larger than that under the platform pricing policy. Under the platform pricing policy, the low-quality service provider can earn more profit. We also find that the low-quality service provider is more motivated to encourage consumers to provide online reviews regardless of the pricing policy.

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The entry quality threshold setting and commission rate contract selection of a peer-to-peer service sharing platform

Cited by 5 publications

References 46 publications

Dynamic competition and market structure for platform‐based products: roles of product quality and indirect network effect

Dynamic competition and market structure for platform‐based products: roles of product quality and indirect network effect

The strategic analysis of service mode selection for a ride‐hailing platform

Pricing Policy Selection in a Platform Service Supply Chain with Online Reviews

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