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Research on Pricing Strategy of Online and Offline Supply Chain Based on Channel Preference in the Context of New Retail

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  • Qingtong Wu
  • Huihua Chen

Abstract

In recent years, brick-and-mortar retail has continuously encountered setbacks in the context of the rapid development of the Internet, and many brick-and-mortar stores cannot withstand losses and were closed down. E-commerce also seems to be able to intuitively understand the needs and preferences of consumers. With the continuous competition of online retail, the undifferentiated production of online retail has slowed down the development of e-commerce. The rise of the new retail model has promoted the production of high-quality products, which has greatly stimulated supply and demand. The new retail model is able to make better use of existing human and material resources and maximize the use of resources in today’s era of rapid technological changes. Online and offline network competition channels also exert different competitive advantages for different consumers. This paper studies the competition between physical retail and e-commerce retail and combines centralized decision-making and decentralized decision-making for analysis. It also calculates the relative optimal pricing price of e-commerce retail through numerical simulation calculations. Although the best pricing price is obtained after a series of calculations, it is still necessary to comprehensively consider and analyze multiple factors rationally to promote the long-term development of the enterprise. Although supply chain pricing strategies can solve certain problems in market sales to a certain extent, comprehensive analysis and scientifically formulating corporate development strategies are the guarantee of sustainable business operations.

Suggested Citation

  • Qingtong Wu & Huihua Chen, 2021. "Research on Pricing Strategy of Online and Offline Supply Chain Based on Channel Preference in the Context of New Retail," Complexity, Hindawi, vol. 2021, pages 1-9, September.
  • Handle: RePEc:hin:complx:5211642
    DOI: 10.1155/2021/5211642
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    Cited by:

    1. Lu, Hsi-Peng & Cheng, Hsiang-Ling & Tzou, Jen-Chuen & Chen, Chiao-Shan, 2023. "Technology roadmap of AI applications in the retail industry," Technological Forecasting and Social Change, Elsevier, vol. 195(C).

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