Leveraging AI to Build Agile and Resilient Healthcare Supply Chains for Sustainable Performance: A Systematic Scoping Review and Future Directions
医療サプライチェーンにおける持続可能なパフォーマンスのためのアジャイルでレジリエントな構築におけるAI活用：系統的スコーピングレビューと将来の方向性 (AI 翻訳)
Senthilkumar Thiyagarajan, E. Cudney, Pranay Chimmani, Lionel Henry D’silva, Chad M. Laux
🤖 gxceed AI 要約
日本語
本論文は、医療サプライチェーン（HSC）のアジリティ、レジリエンス、持続可能なパフォーマンス向上におけるAIの役割を系統的レビューで分析。3つの主要テーマ（持続可能性志向の設計、混乱とレジリエンス管理、ヘルスケアのデジタル変革）が特定され、AI、デジタルツイン、IoTが戦略的イネーブラーとして進化しているが、データ品質やガバナンスの課題が残る。
English
This systematic review analyzes how AI enhances agility, resilience, and sustainable performance in healthcare supply chains (HSCs). Three thematic clusters emerge: sustainability-oriented design, disruption/resilience management, and digital transformation. AI, digital twins, and IoT are evolving from efficiency tools to strategic enablers, but barriers like data quality and governance persist.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本の医療サプライチェーンは高齢化や災害リスクに直面しており、AI活用によるレジリエンス強化はGX文脈でも重要。ただし、本論文は日本固有の分析ではなく、一般論に留まる。
In the global GX context
This review offers a global perspective on how AI can build sustainable and resilient supply chains, relevant to GX as climate-driven disruptions increase. It highlights the need for integrated digital, resilience, and sustainability strategies.
👥 読者別の含意
🔬研究者:Identifies research gaps in human-AI collaboration and trust calibration within sustainable supply chains.
🏢実務担当者:Provides practical guidance for healthcare organizations to leverage AI for agile and sustainable supply chain ecosystems.
🏛政策担当者:Emphasizes need for governance frameworks to support AI adoption in critical infrastructure supply chains.
📄 Abstract（原文）
Ongoing global disruptions, including pandemics, geopolitical tensions, and climate-driven events, have exposed vulnerabilities in healthcare supply chains (HSCs). This study examines how artificial intelligence (AI) is reshaping HSCs to improve agility, resilience, and sustainable performance. Using a systematic literature review with PRISMA-style screening across Scopus and Web of Science, the study is complemented by bibliometric analysis and latent Dirichlet allocation topic modeling to analyze peer-reviewed articles. The results indicate an exponential increase in AI-enabled HSC research, concentrated in a small number of journals and spanning a globally diverse author community. Three dominant thematic clusters emerged: (1) sustainability-oriented supply chain design, (2) disruption and resilience management, and (3) healthcare-focused digital transformation. Across these themes, AI, digital twins, Internet of Things, and simulation are evolving from efficiency tools to strategic enablers of decision intelligence, supporting real-time sensing, scenario analysis, and proactive risk mitigation. The study highlights a convergence of “triple transformation” in which digitalization, resilience, and sustainability are increasingly co-dependent capabilities in HSCs. However, persistent barriers exist, including data quality issues, legacy systems, workforce skill gaps, limited model interpretability, and incomplete governance frameworks, which constrain large-scale adoption. The findings indicate a need for longitudinal and multi-method studies on human–AI collaboration, trust calibration, and leadership in AI-enabled HSCs. This study provides practical guidance for healthcare organizations looking to leverage AI in developing agile, resilient, and sustainable supply chain ecosystems.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.3390/su18031434first seen 2026-05-05 22:10:46
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gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。