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Subsidy strategy of pharmaceutical e-commerce platform based on two-sided market theory

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  • Chenshuo Li
  • Zhe Huang

Abstract

With the development of economic globalization and information technology, enterprises pay more attention to the sustainable development of their e-commerce. Under this trend, we study the subsidy strategy commonly used by pharmaceutical e-commerce platforms in two-sided market. Based on the two-sided market theory, we set up the two-sided user's utility function and formulate the subsidy strategy as the decision of platform profit optimization. We show that the platform chooses to subsidize consumers only if the net income from consumer is lower than the total revenue of drug retailers and platforms in each transaction; the maximum profit for platform increases with the intensity of the network externality. This study provides theoretical support and decision-making suggestions for the pharmaceutical e-commerce platforms to capture the market share, obtain higher profits and ultimately achieve the sustainable development goal.

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  • Chenshuo Li & Zhe Huang, 2019. "Subsidy strategy of pharmaceutical e-commerce platform based on two-sided market theory," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-15, October.
    • Handle: RePEc:plo:pone00:0224369
    DOI: 10.1371/journal.pone.0224369
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    References listed on IDEAS

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    Cited by:

    1. Hui Zhang & Kai Luo & Guanqun Ni, 2022. "The effects of price subsidy and fairness concern on pricing and benefits of take-away supply chain," Journal of Combinatorial Optimization, Springer, vol. 43(5), pages 1106-1124, July.
    2. Zhou, Wei & Zhang, Keang & Zhang, Ying & Duan, Yunlong, 2021. "Operation strategies with respect to insurance subsidy optimization for online retailers dealing with large items," International Journal of Production Economics, Elsevier, vol. 232(C).
    3. Hui Zhang & Kai Luo & Guanqun Ni, 0. "The effects of price subsidy and fairness concern on pricing and benefits of take-away supply chain," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-19.
    4. Liang Shen & Fei Lin & Yuyan Wang & Xin Su & Hua Li & Rui Zhou, 2022. "Advertising Decisions of Platform Supply Chains Considering Network Externalities and Fairness Concerns," Mathematics, MDPI, vol. 10(13), pages 1-21, July.

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