Dual Decision-Making Processes Enhanced by Transfer Learning for Intuitive Reasoning

Making the right decisions remains a significant challenge for most managers, as it often requires a deep understanding of multiple domain-specific areas of knowledge. While managers may possess expertise in one or more domains, decision-making becomes even more complex in a cross-domain context, where integrating knowledge from diverse fields is essential. This study aims to develop an AI-based intuitive reasoning decision-making model by extending the dual-process theory. It is expected to contribute to academia by advancing theoretical development and enhancing managers’ intuitive reasoning and decision-making capabilities in practical applications across various cross-domain tasks.