This study addresses the challenges of strategic problem-solving, emphasizing hierarchical interactions between problem-solvers and decision-makers. Drawing on behavioral theory, we examine how conflicts streaming from differences in the interpretation of information between actors can be effectively managed by acquiring a hierarchical integration capability through training and using generative AI tools, leading to improved solution quality and decision-maker's decision speed when solving strategic problems. Additionally, we explore the role of a hierarchical integration capability in further facilitating the use of generative AI tools. We conduct a multi-stage vignette experiment with 140 middle managers (problem-solvers) and 178 senior managers (decision-makers). We contribute to the literature on problem-solving by highlighting the importance of managing hierarchical interactions and demonstrating the effectiveness of a trained hierarchical integration capability and generative AI use in this process. Additionally, we contribute to the growing body of research on hybrid problem-solving between generative AI and humans, by showing that generative AI not only improves creative and generative aspects of the problem-solving process but also plays a significant role in reducing misinterpretation between problem-solvers and decision-makers, especially when humans possess a complementary hierarchical integration capability.
