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

Year: 2025

Type: article

Abstract: 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.

Source: Journal of the Association for Information Systems

Authors: Hsieh, Pei-Hsuan, Launer, Markus Arthur

Institutions: National Chengchi University, Ostfalia University of Applied Sciences

Language: English

Topic: Decision-Making and Behavioral Economics

Subfield: General Decision Sciences

Field: Decision Sciences

Domain: Social Sciences

Open Access status: green

OpenAlex ID: W7009210263

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