A Study on Information Search Behavior Using AI-Powered Engines: Evidence From Chatbots on Online Shopping Platforms

Abstract

The development of Artificial Intelligence (AI) has significantly influenced how consumers search for information. However, there is a lack of comprehensive models based on theoretical foundations that specifically address AI-powered information search behavior. This study draws on psychological motivation, information processing, and information economics theories to develop a theoretical model of consumer AI-powered information search behavior. The study aims to identify the main factors affecting consumer search behavior, offering a more holistic understanding of consumer behavior in the context of AI. Analyzing 512 valid questionnaires, the study shows that search motivation not only had the most significant impact on search behavior but also served as a mediator between other variables and search intensity. Additionally, perceived search ability had a direct and the greatest indirect impact on search behavior, while other variables such as perceived search costs and benefits also had indirect effects on search behavior. Practically, the study offers valuable insights for businesses and AI developers. Understanding the factors that drive AI-powered search behavior can inform the design of more effective AI systems and marketing strategies.