Human–Technology Synergies in AI-Driven E-Commerce Environments

Dear Colleagues,

In recent years, the development of e-commerce has expanded globally, providing consumers with a more convenient shopping experience and a wider range of product choices. However, this growth does not guarantee profitability for all e-commerce businesses, which still face numerous challenges, including the absence of online identity verification, poor customer experience, lack of competitor analysis, reliance on outdated sales methods, high cart-abandonment rates, difficulties in customer loyalty management, intense price and shipping competition, and data security concerns. These challenges often arise due to insufficient business, product, and service information management.

The applications of big data and artificial intelligence (AI) have become a crucial factor driving innovation in e-commerce. By analyzing business operations, product information, and customer behavior, AI can accurately predict market trends, consumer demand, and competitor strategies, helping businesses offer highly personalized shopping experiences. Additionally, AI-driven technologies such as self-learning algorithms, natural language processing (NLP), and intelligent recommendation systems enable e-commerce businesses to adapt marketing strategies more flexibly, improving customer engagement and loyalty.

Moreover, the advent of live streaming e-commerce has revolutionized the digital retail landscape by creating an immersive, interactive shopping ecosystem. Through real-time video broadcasting, consumers now engage in dynamic two-way communication with hosts, instantly posing product inquiries and receiving tailored demonstrations that transcend static product listings. AI-driven algorithms further amplify this experience by curating personalized recommendations based on individual browsing patterns and purchase histories, effectively bridging the gap between mass marketing and bespoke service. The integration of social media dynamics transforms passive viewers into active participants, as KOL endorsements and user-generated content fuel viral product discovery while fostering emotional connections.

This Special Issue centers on big data and AI-driven e-commerce management, investigating innovative strategies for digital commerce to adapt and thrive amidst dynamic market shifts. It seeks to establish an interdisciplinary forum for cutting-edge research and industry practices that address emerging challenges in intelligent commerce ecosystems, while fostering resilient and ethical frameworks for technology-enhanced retail operations in the digital age.

Topics of Interest

We welcome original research and practical applications related to (but not limited to) the following areas:

1. Natural Language Processing (NLP) in E-Commerce
   • Applications of NLP in personalized shopping experiences;
   • Sentiment analysis and opinion mining for product/service feedback;
   • Text summarization and content generation for marketing automation;
   • Voice and chatbot-based intelligent customer service systems;
   • Multilingual processing for global e-commerce platforms.
2. NeuroIS and Consumer Behavior in Digital Commerce
   • Neurophysiological approaches to understanding online decision making;
   • Brain–computer interfaces (BCIs) in e-commerce experiences;
   • Emotional AI and its role in customer trust and engagement;
   • Cognitive load and attention analysis in online shopping;
   • Neuromarketing applications in interface and content design.
3. AI and Big Data Applications in E-Commerce
   • AI-powered recommendation systems and customer profiling;
   • Machine learning for dynamic pricing and inventory optimization;
   • Predictive analytics for consumer behavior and sales forecasting;
   • Data-driven segmentation and personalization strategies;
   • Privacy-preserving AI and ethical data use in digital commerce.
4. Intelligent Interaction and UX in Digital Commerce
   • Conversational commerce and deep learning-based chatbots;
   • Emotion-aware interfaces and adaptive user experiences;
   • Human–computer interaction design in online retail;
   • Cross-platform personalization and multi-device user tracking;
   • Gamification and immersive experiences in online shopping;
   • User or consumer psychology and behavior in AI-assisted service.
5. Emerging Trends in Technology-Enhanced E-Commerce
   • Integration of NLP, AI, and NeuroIS in virtual commerce;
   • Affective computing and real-time feedback systems;
   • Digital twins and simulations in consumer journey modeling;
   • Explainable AI (XAI) for transparency in recommendation and decision support;
   • Hybrid models combining symbolic reasoning and neural learning in e-commerce.

Dr. Chienliang Lin
Dr. Wuke Zhang
Dr. Sung-Wen Yu
Dr. Xu Hanqing
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Theoretical and Applied Electronic Commerce Research is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• natural language processing (NLP) in e-commerce
• artificial intelligence applications
• neuroIS and consumer behavior
• intelligent customer service
• sentiment analysis
• user interaction and experience
• personalized recommendation systems
• emotional AI and neuromarketing