Online cash-back shopping with network externalities

Chen, Chen; Duan, Yongrui

doi:10.1080/03155986.2020.1774300

Cited by 3 publications

(3 citation statements)

References 19 publications

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“…Thus, this study considers that consumers purchasing products through the tradein are influenced by the total number of consumers.) and 𝛽 is the effect of network externalities (Chen and Duan, 2021). Based on the positive effect of network externality, consumers engaged in the tradein program benefit from the online recycling services, which in turn increases their overall utility.…”

Section: Model Description and Assumptionsmentioning

confidence: 99%

“…Xu et al (2018) categorized network externality into fixed and variable instances, probing their effects on repurchase contracts involving returns. In the pursuit of profit maximization, Chen and Duan (2021) examined the relationship between network externalities and cashback policy. Recently, Wei et al (2023) found that network externality arising from consumers in bilateral markets do not consistently yield positive outcomes.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Consistent with Chen and Duan (2021), parameters are generalized with the assumptions 𝜃 = 0.6, 𝜇 = 0.05, 𝜆 = 0.005, 𝑏 = 0.05, 𝑡 = 100, and 𝛽 ∈ (0,0.3). The market demands of direct purchase and trade-in in both the platform model and manufacturer model are illustrated in Figure 3.…”

Section: Corollarymentioning

confidence: 99%

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Trade-in program in online platforms considering network externalities and recycling services

Yu,

Li,

2024

Preprint

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Consumers trade their used products for new ones through online platforms, thereby integrating internet shopping and recycling. Two trade-in models are developed, i.e., the platform model where the manufacturer cooperates with an online retail platform to sell products and the online retail platform introduces trade-in program and manufacturer model where the manufacturer's own platform introduces trade-in program. This study examines the trade-in program offered by online platforms with a consideration of network externalities and heterogeneous consumers, and analyzes the decisions of pricing and recycling service. The research indicates that heightened network externalities can enhance recycling services, promote trade-in program development, and increase the demand for trade-in. The trade-in recycling service gets higher in the manufacturer model, whereas the sales price in the platform model is elevated due to sales commission rates. However, the manufacturer model does not always have higher market demand than the platform model, when both the commission rate and recycling revenue are high, the platform model have higher market demand. Although the manufacturer profits more than the online retail platform in the platform model, it is suggested that the manufacturer should introduce the trade-in program on the self-owned platform since the profit of manufacturer is larger under the manufacturer model.

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Section: Model Description and Assumptionsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

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Trade-in program in online platforms considering network externalities and recycling services

Yu,

Li,

2024

Preprint

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Pricing and matching for on-demand platform considering customer queuing and order cancellation

Sun

Zhang

et al. 2022

INFOR: Information Systems and Operational Research

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De que forma os preços variam em sites de comparação? influência do cashback e da estrutura de mercado na dinâmica de preços

Costa Oliveira,

Almeida,

Isabella

2024

Rev. Bras. Mark.

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Objetivo: Este artigo analisa como as ofertas com cashback e a estrutura de mercado influenciam os níveis de dispersão de preços em sites de comparação no comércio eletrônico brasileiro. Método: Com uma base de 210 observações extraídas de sites brasileiros de comparação de preços, desenvolvemos quatro modelos de Análise de Regressão Múltipla com termo interativo, para testar as cinco hipóteses do estudo. Resultados: Suportamos cinco hipóteses que revelam como a dispersão de preços é influenciada por estratégias diferenciadas de preços no comércio eletrônico. Como resultado principal temos que a presença de um maior número de ofertas com cashback em uma lista de preços está associada a níveis ampliados de dispersão de preços nos sites de comparação. A introdução de novos concorrentes exerce uma influência redutora sobre a dispersão de preços, em virtude da maior transparência e competitividade resultantes. Contribuições teóricas: Este estudo contribui no campo dos estudos de marketing voltados para estratégias de precificação, com destaque para a dispersão de preços relacionada à estratégia de cashback no ambiente do comércio eletrônico. Implicações gerenciais: Com os resultados da pesquisa, os gestores de preços de sites de comparação e de lojas terão informações mais transparentes para administrar a implementação da estratégia de cashback. Originalidade: Distinto dos estudos anteriores, que estudam a dinâmica de preços no ambiente digital, nosso estudo acrescenta evidências da influência da estratégia cashback a essa dinâmica em sites de comparação de preços.

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Online cash-back shopping with network externalities

Cited by 3 publications

References 19 publications

Trade-in program in online platforms considering network externalities and recycling services

Trade-in program in online platforms considering network externalities and recycling services

Pricing and matching for on-demand platform considering customer queuing and order cancellation

De que forma os preços variam em sites de comparação? influência do cashback e da estrutura de mercado na dinâmica de preços

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