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Innovation Mode and Optimization Strategy of B2C E-Commerce Logistics Distribution under Big Data

Author

Listed:
  • Yingyan Zhao

    (College of Business Administration, Ningbo Polytechnic, Ningbo 315800, China)

  • Yihong Zhou

    (Office of Educational Administration, Ningbo Polytechnic, Ningbo 315800, China)

  • Wu Deng

    (School of Software Engineering, Dalian Jiaotong University, Dalian 116028, China)

Abstract

With the advent of big data era and rapid development of Internet technology, e-commerce has had a strong development tendency that causes many problems, such as redundant and complex business processes, low efficiency and a high cost for e-commerce logistics in the distribution sector. It is not difficult to conclude that the key to improving logistics distribution efficiency—and reduce logistics distribution costs—is to optimize logistics distribution under big data. In this study, the management model, influence factors and development status of B2C e-commerce logistics distribution under big data are analyzed in detail. Then big data processing, business process and route optimization strategies for B2C e-commerce logistics distribution under big data are deeply studied. Furthermore, an optimization model of product sales and logistics distribution of B2C e-commerce by big data platform is discussed in order to propose an innovative optimization strategy for B2C e-commerce logistics distribution under big data. Big data technology is applied in B2C e-commerce logistics business management, which is studied in detail. These findings achieve the optimal distribution of B2C e-commerce, reduce the B2C e-commerce logistics distribution cost and improve the B2C e-commerce logistics distribution efficiency under big data. In addition, enhanced competitiveness of B2C e-commerce logistics distribution is examined in this study. This study provides a reference for follow-up big data studies in the field of e-commerce.

Suggested Citation

  • Yingyan Zhao & Yihong Zhou & Wu Deng, 2020. "Innovation Mode and Optimization Strategy of B2C E-Commerce Logistics Distribution under Big Data," Sustainability, MDPI, vol. 12(8), pages 1-13, April.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:8:p:3381-:d:348402
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    Cited by:

    1. Jingbo Hu & Taohua Ouyang & William X. Wei & Jiawei Cai, 2020. "How Do Manufacturing Enterprises Construct E-Commerce Platforms for Sustainable Development? A Case Study of Resource Orchestration," Sustainability, MDPI, vol. 12(16), pages 1-18, August.
    2. Pham Quang Huy & Vu Kien Phuc, 2023. "Big data in relation with business intelligence capabilities and e-commerce during COVID-19 pandemic in accountant’s perspective," Future Business Journal, Springer, vol. 9(1), pages 1-21, December.
    3. Veronika Svatošová & Jaroslava Rajchlová, 2022. "The Importance of Determinants of Strategic Development in E-commerce," Journal of Economics / Ekonomicky casopis, Institute of Economic Research, Slovak Academy of Sciences, vol. 70(9-10), pages 768-792, August.
    4. Junhai Wang & Yiman Zhang, 2021. "Using cloud computing platform of 6G IoT in e-commerce personalized recommendation," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(4), pages 654-666, August.
    5. Snezhana Sulova, 2023. "A Conceptual Framework for the Technological Advancement of E-Commerce Applications," Businesses, MDPI, vol. 3(1), pages 1-11, March.
    6. Shaoqing Geng & Hanping Hou & Jiaxin Geng, 2021. "The Mechanism of Operation Effectiveness of Emergency Shelter Rescue Systems," Sustainability, MDPI, vol. 13(10), pages 1-16, May.
    7. Qi, Bitian & Shen, Yanbo & Xu, Tieyu, 2023. "An artificial-intelligence-enabled sustainable supply chain model for B2C E-commerce business in the international trade," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    8. Yu Zhang & Nan Liu, 2021. "Optimal Internet of Things Technology Adoption Decisions and Pricing Strategies for High-Traceability Logistics Services," Sustainability, MDPI, vol. 13(19), pages 1-33, September.

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