Decision-Making Process in E-Commerce and Social Networks

Dear Colleagues,

The rapid evolution of digital platforms has transformed how individuals and organizations make decisions in online environments. E-commerce systems and social networks now serve as dynamic ecosystems where consumer behavior, algorithmic influence, and real-time feedback loops converge to shape decision-making processes. Understanding these mechanisms is crucial for enhancing user experience, refining business strategies, and ensuring ethical and transparent digital interactions.

Over the past two decades, research in this domain has explored behavioral economics, recommender systems, trust modeling, and sentiment analysis. However, emerging challenges — such as algorithmic bias, misinformation propagation, and privacy-aware personalization — demand fresh perspectives and interdisciplinary approaches. The intersection of data science, psychology, marketing, and computational modeling offers fertile ground for innovation.

This Special Issue aims to bring together cutting-edge research that advances our understanding of decision-making in e-commerce and social networks. We welcome contributions that explore theoretical frameworks, empirical studies, and applied methodologies. Topics may encompass individual and group decision dynamics, platform design, AI-driven personalization, and the impact of social influence on digital choices.

Topics of Interest (include but are not limited to):

• Decision-making models in online shopping and social platforms;
• Influence of recommender systems and personalization algorithms;
• Trust, reputation, and credibility in digital environments;
• Behavioral economics and cognitive biases in e-commerce;
• Sentiment analysis and opinion mining for decision support;
• Social contagion and network effects on consumer behavior;
• Privacy-aware decision modeling and ethical AI;
• Real-time decision analytics and adaptive systems;
• Multi-agent decision-making in social commerce;
• Case studies in platform design and user engagement.

Dr. Ai Ren
Prof. Dr. Xiaodong Li
Guest Editors

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