B2C car-sharing services: Sharing mode selection and value-added service investment

The e‐commerce platform has been adopting the agency mode to sell the products of the national brand manufacturer (NBM) while introducing its own store brand and obtaining the consumer's preference information (CPI) to reinforce the competitiveness of the store‐brand products. This paper investigates the platform's decisions on whether to share the CPI with the NBM and its impact on the production timing decisions of the platform and the NBM. The results show that the platform may benefit from CPI sharing which may also change the equilibrium production timing of the platform and the NBM from sequential decision to simultaneous decision. In addition, the equilibria of the joint decision between the CPI sharing and the production timing are obtained, which is related to the market acceptance uncertainties of the products and the competitiveness of the national brands.

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“…(2021), Guo et al. (2022), and Shi et al. (2022), among others, we assume that the commission rate ρ is an exogenous variable with

\rho \le 0.3,

which is in line with practice.…”

Section: Modelmentioning

confidence: 99%

“…Referring to Qin et al (2021), Guo et al (2022), andShi et al (2022), among others, we assume that the commission rate ρ is an exogenous variable with ρ ≤ 0.3, which is in line with practice. The platform often charges the same commission rate for the NBMs under the same product category (Rule.jd.com, 2022).…”

Section: Modelmentioning

confidence: 99%

Information sharing and production timing strategy in a platform‐based supply chain

Zhao

Fan

Wang

2023

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%

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

Guo

Fan

Liu

2023

Int Trans Operational Res

Self Cite

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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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“…(2020a, b) study the logistics service sharing strategy of e-commerce platforms and analyze the interaction mechanism among e-commerce platforms, sellers and 3PLs. Guo et al. (2022a, b) considering logistics services capacity sharing between the manufacturer and the e-commerce seller, investigate the impact of sharing logistics services capacity on firms' decisions and profit.…”

Section: Literature Reviewmentioning

confidence: 99%

“…(2021) take the car-sharing industry as an example and study the supplier's pricing decisions and the selection of the supplier's sales and sharing strategies. Guo et al. (2022a, b) further consider the impact of platform commission rates and offline operating costs and study whether the supplier shares capacity directly offline or through the third-party platform.…”

Section: Literature Reviewmentioning

confidence: 99%

Research on sales and sharing decisions of the equipment supplier under shared manufacturing environment

Li,

Dan,

Zhang

et al. 2023

IMDS

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PurposeWith the rapid development of the sharing economy in manufacturing industries, manufacturers and the equipment suppliers frequently share capacity through the third-party platform. This paper aims to study influences of manufacturers sharing capacity on the supplier and to analyze whether the supplier shares capacity as well as its influences.Design/methodology/approachThis paper deals with conditions that the supplier and manufacturers share capacity through the third-party platform, and the third-party platform competes with the supplier in equipment sales. Considering the heterogeneity of the manufacturer's earning of unit capacity usage and the production efficiency of manufacturer's usage strategies, this paper constructs capacity sharing game models. Then, model equilibrium results under different sharing scenarios are compared.FindingsThe results show that when the production or maintenance cost is high, manufacturers sharing capacity simultaneously benefits the supplier, the third-party platform and manufacturers with high earnings of unit capacity usage. When both the rental efficiency and the production cost are low, or both the rental efficiency and the production cost are high, the supplier simultaneously sells equipment and shares capacity. The supplier only sells equipment in other cases. When both the rental efficiency and the production cost are low, the supplier’s sharing capacity realizes the win-win-win situation for the supplier, the third-party platform and manufacturers with moderate earnings of unit capacity usage.Originality/valueThis paper innovatively examines supplier's selling and sharing decisions considering manufacturers sharing capacity. It extends the research on capacity sharing and is important to supplier's operational decisions.

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B2C car-sharing services: Sharing mode selection and value-added service investment

Cited by 14 publications

References 40 publications

Information sharing and production timing strategy in a platform‐based supply chain

Information sharing and production timing strategy in a platform‐based supply chain

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

Research on sales and sharing decisions of the equipment supplier under shared manufacturing environment

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