Information technology has become a primary environment where human behavior is formed, expressed, and shaped. As algorithms personalize information and platforms mediate attention, trust, and interaction, understanding how people think, feel, decide, and behave in digital contexts is essential for designing technologies that are effective, trustworthy, and socially responsible.

This Topical Collection aims to advance research that explains and predicts human behavior in IT-enabled environments, such as generative AI, big data–based decision support, and SNS/platform ecosystems. We welcome studies that examine fundamental behavioral mechanisms in IT contexts, including how people evaluate, adopt, use, and respond to digital technologies, covering perceptions, attitudes, decision processes, and interaction patterns in IT environments. Both empirical and computational approaches are encouraged, including experiments, surveys, field data, digital trace data, and machine learning/text-mining methods that provide strong behavioral inference.

By bringing together theory-driven and data-driven evidence across these core domains, this collection will help the research community build cumulative knowledge on how IT and AI shape human behavior, and how human behavior, in turn, determines the success and impact of emerging digital technologies.