Knowledge structuring for initial response to the 2024 Noto Peninsula Earthquake in Japan

Abstract: Large-scale disasters impose an immense burden on affected municipal staff, as they are tasked with duties far exceeding their regular responsibilities, such as managing shelters and distributing aid supplies. While support personnel from other　municipalities are crucial in these situations, the valuable knowledge and experience they gain on-site are often not systematically retained by the supported municipality after their departure. This research addresses this critical gap by aiming to systematically organize and visually share the comprehensive disaster response experiences of dispatched personnel, including the challenges they faced and the solutions they implemented, thereby ensuring that this vital information remains with the affected municipalities for future use.Previous research has explored various aspects of disaster management, including knowledge accumulation from past events and the optimization of municipal staffing. However, there is a lack of research focused on structuring this critical knowledge in a format that can be used quickly and intuitively at all stages of a disaster response. Our study fills this void by proposing a novel system that structures knowledge into a mandala format, facilitating quick comprehension and informed decision-making. The mandala format, originally a symbolic diagram in Buddhist cosmology, has recently been adapted as a tool for idea generation and information organization in fields like education and business.Specifically, this research introduces the "Mandala" concept, focusing on the critical issue of delayed initial responses during disasters. The Mandala systematically organizes and visualizes the causes of these delays, which are derived directly from the experiences of dispatched personnel, thereby providing a clear roadmap for preventing similar issues in future events.To construct Mandala, we employed a hybrid analytical approach, combining both inductive and deductive reasoning. We utilized interview data from the 2024 Noto Peninsula Earthquake in Japan as our primary source. The methodology involved initial open coding to decontextualize the interview data, followed by thematic classification. The final step was the construction of the Mandala by reconfiguring the thematic classification results.Our analysis highlighted the profound importance of knowledge held by dispatched support personnel for streamlining operations during the initial stages of a disaster, especially considering the overwhelming demands on local municipal staff. Through this process, we successfully constructed a Mandala with "Causes for Delayed Initial Response" at its center. This Mandala effectively organizes multiple contributing factors and their interrelationships, systematically derived from the interview data. We anticipate that this Mandala will serve as an invaluable tool for municipal staff, enabling swift and effective decision-making during future disaster responses.In conclusion, this study was able to demonstrate the effectiveness of a hybrid qualitative data analysis approach in structuring knowledge from published text data into a visually intuitive mandala format. This research is expected to make a significant contribution to a more efficient, effective, and resilient initial response capacity in the event of future disasters, ultimately minimizing the impact on the community.

Keywords: disaster response, knowledge structuring, mandala format, decision-making, dispatched personnel

DOI: 10.54941/ahfe1007054

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