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This study introduces a Big Data-assisted E-Commerce Business Model (BD-ECBM) to enhance platform security and user protection. The BD-ECBM improves marketing strategies and customer satisfaction in the thriving global e-commerce market.

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Area of Science:

  • Computer Science
  • Information Technology
  • Business Management

Background:

  • The global e-commerce market is rapidly expanding, driven by advancements in big data technologies.
  • E-commerce platforms face challenges related to security, user data protection, and sustainable business model development.
  • Effective business decision-making relies on data collection, analysis, and strategic action.

Purpose of the Study:

  • To explore the application of computer security technology in e-commerce platform business models.
  • To identify security solutions for e-commerce platforms to protect user information and rights.
  • To enhance the sustainable development of e-commerce business models using Big Data.

Main Methods:

  • Development of a Big Data-assisted E-Commerce Business Model (BD-ECBM).
  • Implementation of a system framework with information service, application-level, and client session layers.
  • Utilizing big data analytics and data fusion technology for business management and marketing strategy.

Main Results:

  • The BD-ECBM effectively addresses e-commerce platform issues and informs marketing strategy decision-makers.
  • The system enables real-time competitor monitoring, dynamic pricing, and analysis of customer feedback.
  • Trial results confirm the method's effectiveness in marketing decision-making and strategy formulation.

Conclusions:

  • The BD-ECBM technique significantly improves customer satisfaction and brand experience.
  • Enhanced security and data-driven insights contribute to the sustainable growth of e-commerce business models.
  • The study highlights the positive impact of integrating big data analytics and computer security in e-commerce.