日本自動車産業のサプライチェーン強靭性を機械学習で解明——大学院生手嶋逸貴らの研究成果が国際誌に掲載されました（指導教員：平田燕奈教授）

神戸大学大学院海事科学研究科の研究グループ（大学院生：手嶋　逸貴、I Made Raditya Wicaksana、CAI ZHUJIJIE、LIU XIAOYU、YEN CHEN、田　元弘、指導教員：平田燕奈教授）は、日本の自動車7社を対象に2015～2024年のデータを用いてサプライチェーン強靭性を分析した論文が、国際学術誌 International Journal of Disaster Risk Reduction に掲載されました。ロジスティック回帰とLSTMを組み合わせた分析により、長い勤続年数・安定生産・品質管理が災害後の収益回復に重要であることを明らかにしました。企業の財務・操業データと自然災害・パンデミック指標を一体的に分析した本研究は、防災政策と企業の事業継続計画の双方に実践的な示唆を与えるものです。

Machine Learning Reveals Supply Chain Resilience in Japan's Automotive Industry — Graduate Student Ikki Teshima et al.’s Research Published in International Journal (Supervisor: Professor Enna Hirata)

A research group from the Graduate School of Maritime Sciences at Kobe University — comprising graduate students Ikki Teshima, I Made Raditya Wicaksana, Zhujijie Cai, Xiaoyu Liu, Yen Chen, and Yuanhong Tian, supervised by Professor Enna Hirata — has published a paper analyzing supply chain resilience across seven major Japanese automakers using data from 2015 to 2024 in the International Journal of Disaster Risk Reduction. Combining logistic regression and LSTM neural networks, the study identifies long employee tenure, stable production, and quality control as key drivers of post-disaster profit recovery. By integrating firm-level financial and operational data with natural disaster and pandemic indicators, the research offers practical implications for both disaster risk reduction policy and corporate business continuity planning.

Ikki Teshima, I Made Raditya Wicaksana, Zhujijie Cai, Xiaoyu Liu, Yen Chen, Yuanhong Tian, Enna Hirata. Measuring and predicting supply chain resilience under disaster and pandemic disruptions: Evidence from Japan's automotive sector. International Journal of Disaster Risk Reduction, 136 (2026) 106062. https://doi.org/10.1016/j.ijdrr.2026.106062