From Transparency to Circularity
透明性から循環性へ (AI 翻訳)
Shakerod Munuhwa
🤖 gxceed AI 要約
日本語
本書章は、ビッグデータ分析がサプライチェーンの透明性向上と循環経済への移行をどう支援するかを検討する。資源効率、廃棄物削減、製品ライフサイクル最適化に焦点を当て、食品、アパレル、製造業の事例を紹介。ガバナンスや相互運用性などの障壁を議論し、統合のための実践的枠組みを提供する。
English
This chapter examines how big data analytics supports the shift from linear to circular supply chains, focusing on resource efficiency, waste reduction, and life-cycle optimization. It presents case examples from food, apparel, and manufacturing, and discusses barriers such as governance and interoperability, offering a practical framework for integration.
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
日本では、サプライチェーン全体での温室効果ガス排出削減が求められており、循環経済への移行は重要な政策課題。本稿は、ビッグデータを活用したトレーサビリティ向上や資源効率化の実践的枠組みを提供し、日本企業のサプライチェーン対応に示唆を与える。
In the global GX context
Globally, the shift to circular supply chains is gaining momentum as part of ESG and climate action. This chapter provides a framework for leveraging big data to enhance transparency and circularity, relevant to companies facing disclosure requirements and sustainability mandates.
👥 読者別の含意
🔬研究者:Provides a conceptual framework linking big data and circular supply chains, useful for further empirical research.
🏢実務担当者:Offers practical guidance and case examples for integrating big data into circular supply chain strategies.
🏛政策担当者:Highlights the role of data governance and interoperability in enabling circular economy transitions.
📄 Abstract（原文）
Global supply chains are under increasing scrutiny to address environmental, social, and governance (ESG) challenges while maintaining competitiveness and resilience. Big data has emerged as a transformative tool that not only improves transparency but also enables the transition towards circular economy models. This chapter investigates how big data analytics can support the shift from linear practices to circular supply chains that prioritise resource efficiency, waste reduction, and product life-cycle optimisation. It examines the role of big data in enhancing supply chain visibility, enabling predictive decision-making, and fostering collaboration across stakeholders. Case examples will demonstrate how industries such as food, apparel, and manufacturing are using big data to achieve traceability, reduce carbon footprints, and enable closed-loop systems. The chapter will also critically discuss barriers, including governance, interoperability, and ethical concerns, while offering a practical framework for integrating big data into circular supply chain strategies.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.4018/979-8-3373-6896-2.ch008first seen 2026-08-02 17:23:14
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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。