The topics of interest include, but are not limited to:

1. AI in Consumer Behavior Analysis and Personalization

    Understanding Consumer Preferences with AI
    Personalized Marketing Strategies using Machine Learning
    AI for Dynamic Pricing Models in E-Commerce
    Behavioral Segmentation Using AI Tools

2. AI for Optimizing E-Commerce Supply Chain and Inventory Management

    Demand Forecasting using AI and Big Data
    AI for Inventory Optimization and Stock Replenishment
    Smart Logistics: AI and Automation in E-Commerce Shipping
    AI-Driven Supply Chain Resilience

3. AI in E-Commerce Fraud Detection and Cybersecurity

    Machine Learning for Fraud Detection in Digital Transactions
    AI for Cybersecurity: Protecting Data and Consumer Trust
    AI-Enhanced Identity Verification Systems
    Predictive Risk Analysis for E-Commerce

4. AI-Enhanced Smart Commerce Systems

    Generative AI for Cross-Border Supply Chain Optimization
    Intelligent Pricing Algorithms and Dynamic Market Forecasting
    Blockchain-AI Synergy in Transparent Trade Systems
    Smart Decision Models for Sustainable Energy Economics

5. Secure AI-Driven Transactions

    Privacy-Preserving User Analytics via Federated Learning
    Cryptographic Solutions for Cross-Border Payments and Smart Contracts
    AI-Powered Fraud Detection and Digital Identity Verification
    E-Commerce Security Architectures in the Quantum Computing Era

6. Cognitive Technologies in Business Intelligence

    Multimodal Cognitive Computing for Consumer Behavior Prediction
    Large Language Models (LLMs) in Intelligent Customer Service Systems
    Neuroeconomics and Brain-Computer Interface Integration
    Explainable AI (XAI) for Financial Auditing and Decision Support

7. Intelligent Automation in Business Process Management

    AI-Driven Workflow Automation for Supply Chain Resilience
    Robotic Process Automation (RPA) in Financial Auditing and Compliance
    Natural Language Processing (NLP) for Contract Analysis and Risk Mitigation
    Ethical AI Governance in Automated Decision-Making Systems

8. Computational Intelligence for Sustainable E-Commerce

    AI-Optimized Carbon Footprint Tracking in Global Trade
    Reinforcement Learning for Energy-Efficient Logistics Networks
    Predictive Analytics in Circular Economy Business Models
    Bias Mitigation in AI-Driven Consumer Demand Forecasting

9. Industry-Specific Empirical Studies: Implementation Cases of Intelligence-Driven Business and Economic Value

    Manufacturing industry: Practical pathways of "production data-efficiency improvement-cost optimization" in smart factories (including industrial internet and predictive maintenance)
    Financial industry: Data-driven balance between risk and return: Empirical research on intelligent risk control, algorithmic wealth management, and digital payment
    Retail industry: Omnichannel data collaboration: Case analysis of precision marketing, inventory optimization, and customer Lifetime Value (LTV) enhancement
    Healthcare and agriculture: Intelligent conversion of health data (personalized diagnosis and treatment) and value realization of agricultural data (yield prediction, pest and disease monitoring)

Other related issues