gxceed
← 論文一覧に戻る

Blockchain-enabled multi-information disclosure in fresh E-commerce: management for balancing economic and environmental performance

ブロックチェーン対応の生鮮Eコマースにおけるマルチ情報開示:経済的・環境的パフォーマンスを両立する管理 (AI 翻訳)

Yingmei Jiang, Jinjin Mou, Xin Yang, Jinyu Wei

Industrial Management & Data Systems📚 査読済 / ジャーナル2026-04-21#サプライチェーン対象セクター: retail
DOI: 10.1108/imds-07-2025-1004
原典: https://doi.org/10.1108/imds-07-2025-1004

🤖 gxceed AI 要約

日本語

本論文は、ブロックチェーン技術(BT)を用いた生鮮Eコマースのサプライチェーンにおいて、品質・低炭素・環境属性の多次元情報開示が経済・環境パフォーマンスに与える影響をモデル化した。分散・統合意思決定の枠組みで価格・手数料・炭素削減・BT投資の最適戦略を導出し、開示の信頼性とレベルが利益と炭素削減感度に影響することを示した。部分的開示は統合の利点を弱め、BTのデータ維持費が開示の方向を左右する。

English

This paper models a two-echelon fresh e-commerce supply chain (supplier-platform) with blockchain technology (BT) for multi-dimensional disclosure of quality, low-carbon, and environmental attributes. Under decentralized/integrated decision frameworks, it derives optimal pricing, commission, carbon reduction, and BT investment strategies. Results show that full disclosure enhances integrated decision-making profits but raises prices, while partial disclosure weakens this advantage and reduces carbon reduction sensitivity. BT maintenance costs solely determine disclosure direction under 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

日本の生鮮Eコマース(例えば、楽天やAmazon Japanなど)では、産地・品質・環境情報の開示が消費者の信頼獲得に重要となっている。本論文はブロックチェーンによる開示が経済性と環境性能の両立にどのように寄与するかを理論的に示しており、日本企業のサプライチェーン透明性向上やSSBJ開示対応の戦略立案に示唆を与える。

In the global GX context

In global e-commerce, fresh produce platforms face increasing pressure to disclose quality and environmental information. This study provides a theoretical framework for using blockchain to balance economic performance with carbon reduction through strategic disclosure. The findings contribute to the literature on blockchain-enabled supply chain sustainability and offer insights for companies adopting TCFD/ISSB-aligned disclosure practices.

👥 読者別の含意

🔬研究者:The model offers a formal analysis of how blockchain-based disclosure interacts with supply chain power structures and carbon reduction, useful for extending to empirical or multi-tier settings.

🏢実務担当者:Platform and supplier managers can use the insights on disclosure levels and trust gaps to design blockchain-based information systems that balance profit and sustainability.

📄 Abstract(原文)

In e-commerce, eco-conscious consumers' focus on fresh produce has shifted from singular quality/safety to a composite dimension of quality, low-carbon and environmental attributes. This elevates information screening difficulty and disclosure management complexity, with blockchain technology (BT) offering a breakthrough for such issues. We model a two-echelon supply chain (supplier-platform) under decentralized/integrated decision frameworks, constructing profit models with/without BT-based disclosure to derive optimal pricing, commission, carbon reduction and BT investment strategies. Under any power structure, information disclosure motivation is jointly determined by information credibility and disclosure level: Full disclosure enhances the profit advantage of integrated decision-making while driving up prices; partial disclosure weakens this advantage and reduces carbon emission reduction sensitivity; BT's unit data maintenance cost solely influences the disclosure motivation's direction in integrated decision-making; platforms exhibit stronger disclosure willingness than suppliers when the pre- and post-disclosure trust gap is significant; and under specific conditions, BT-based integration outperforms decentralized decision-making in economic and environmental performance. This study explores how BT-enabled multi-information disclosure affects fresh e-commerce optimization and management, advances BT's expanded application in e-commerce supply chains and provides theoretical guidance for balancing economic and environmental performance in sustainable fresh e-commerce by adjusting strategic information disclosure in complex scenarios.

🔗 Provenance — このレコードを発見したソース

🔔 こうした論文の新着を逃したくない方は キーワードアラート に登録(無料・3キーワードまで)。

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。