How Customer Artificial Intelligence Technology Drives Supplier Green and Low‐Carbon Efforts: Insights From Green Demand Forcing and Green Knowledge Spillover
顧客の人工知能技術はサプライヤーのグリーン・低炭素努力をどう促進するか：グリーン需要強制とグリーン知識スピルオーバーの視点から (AI 翻訳)
Guangqian Ren, Man Jing, Peitong Liu, Xiaoxiao Chen
🤖 gxceed AI 要約
日本語
中国A株上場企業の2011-2024年データを用い、顧客企業のAI技術がサプライヤーのグリーン・低炭素努力（GLE）を高めることを実証。経路はグリーン需要強制とグリーン知識スピルオーバー。共通所有による関係的埋め込みや顧客依存度が効果を増幅し、非重汚染産業・国有サプライヤーで顕著。
English
Using Chinese A-share listed firms from 2011-2024, this study shows that customer AI technology significantly boosts suppliers' green and low-carbon efforts (GLE) via green demand forcing and green knowledge spillover. Effects are amplified by relational embeddedness (common ownership) and supplier dependence, and are stronger for non-heavy-polluting and state-owned suppliers.
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
日本企業もScope3対応でサプライチェーン排出削減が課題。中国サプライヤーを抱える企業にとって、AI技術を活用した顧客主導のグリーン化圧力の実証結果は、調達戦略や協働の参考になる。
In the global GX context
This paper provides novel empirical evidence on AI technology as a lever for supply chain decarbonization, relevant to global Scope 3 disclosure and net-zero supply chain strategies. It extends the literature on customer-supplier green collaboration, with implications for ISSB-aligned value chain reporting.
👥 読者別の含意
🔬研究者:Provides a theoretical framework linking customer AI adoption to supplier green efforts, with novel mechanisms and moderators for supply chain decarbonization research.
🏢実務担当者:Corporate sustainability teams can learn how AI-driven customer demands and knowledge sharing can be leveraged to green their supplier base.
🏛政策担当者:Offers evidence that promoting AI technology adoption among anchor firms could accelerate supply chain decarbonization, informing industrial and climate policy design.
📄 Abstract（原文）
ABSTRACT Against the backdrop of increasingly severe climate change threats and the global commitment to achieving net‐zero emissions by 2050, supply chain decarbonization has emerged as a critical climate mitigation strategy. Using data from Chinese A‐share listed companies between 2011 and 2024, this study examines how customer artificial intelligence (AI) technology drives suppliers to adopt green and low‐carbon efforts (GLE). The findings reveal that customer AI technology significantly enhances supplier GLE through two key mechanisms: green demand forcing, where suppliers respond to customers' environmental requirements; and green knowledge spillover, where suppliers absorb and apply customers' green expertise. Further analysis from the supplier‐customer relationship perspective indicates that relational embeddedness, reflected in common ownership, helps align interests and strengthens collaboration between parties, thereby amplifying the positive spillover effects of customer AI technology on supplier GLE. Additionally, these positive effects are more pronounced when structural embeddedness, reflected in high supplier dependence on customers, is present. Heterogeneity tests show that this effect is stronger for suppliers in non‐heavy‐polluting industries and state‐owned suppliers. This study offers a novel theoretical perspective on AI‐driven supply chain decarbonization and provides practical implications for Chinese policymakers striving to achieve net‐zero goals.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1111/beer.70145first seen 2026-08-01 05:33:29
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