Harnessing Big Data Analytics to Drive Supply Chain Advantage and Innovation: The Moderating Role of Green Supply Chain Management Perspective
ビッグデータ分析を活用したサプライチェーンの優位性と革新の推進：グリーンサプライチェーン管理の調整的役割 (AI 翻訳)
Md. Ashikur Rahman, Shahriar Hasan Ratul, Niamat Ullah Ibne Hossain, Kazrin Ahmad, Abdullah Al Sakib
🤖 gxceed AI 要約
日本語
本研究は、バングラデシュの製造業におけるビッグデータ分析能力（BDAC）がサプライチェーン革新（SCI）と競争優位（CA）に与える影響を調査し、グリーンサプライチェーン管理（GSCM）の調整効果を検証した。341件の有効回答をPLS-SEMで分析した結果、BDACはSCIとCAに有意な影響を与え、GSCMは一部の関係を調整することが示された。SCIはBDACとCAの関係を部分的に媒介する。
English
This study examines the impact of big data analytics capability (BDAC) on supply chain innovation (SCI) and competitive advantage (CA) with green supply chain management (GSCM) as a moderator. Based on 341 responses from manufacturing plants in Bangladesh and analyzed using PLS-SEM, results show that BDAC enhances SCI and CA, with GSCM moderating one of these relationships. SCI partially mediates the BDAC-CA link.
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
日本の企業にとって、バングラデシュなどの新興国におけるグリーンサプライチェーン管理の実践は、サプライヤー管理の参考となる可能性がある。ただし、直接的な日本のGX政策との関連は薄い。
In the global GX context
This paper provides empirical evidence from a developing country on how green supply chain management moderates the relationship between big data analytics and performance. It offers insights for global supply chain sustainability, though not directly linked to specific climate disclosure frameworks.
👥 読者別の含意
🔬研究者:Researchers interested in the moderating role of GSCM in the BDAC-SCI-CA relationship will find empirical evidence from an emerging economy.
🏢実務担当者:Supply chain managers can learn how to leverage BDAC for competitive advantage while integrating green practices, though the context is Bangladesh.
📄 Abstract（原文）
Abstract This research intends to analyze the impact of big data analytics capability (BDAC) toward supply chain innovation (SCI) and competitive advantage (CA) where green supply chain management (GSCM) performs the moderating role. A theoretical model was created, and hypotheses were formulated to investigate the links between these variables. Data collection was carried out through a survey of supply chain managers in manufacturing plants in Bangladesh. Total 341 valid responses were collected and analyzed with the method of partial least squares structural equation modeling (PLS-SEM) in WarpPLS. The findings of the study offer insights into how business can use BDAC to achieve SCI and CA. The results indicate that BDAC has a potential impact regarding a firm’s ability to enhance CA and SCI. Moreover, the moderating function of GSCM was examined, which was found to be a significant influence on one of these relationships. However, the industry age as a control variable was found to have no apparent impact on SCI or CA. The study also establishes the critical role of SCI in turning analytical skills into competitive results and partially mediates the relationship between BDAC and CA. In sum, this research illustrates how businesses can employ data-driven skills to increase productivity in complex and dynamic supply chain environments against the backdrop of a case study.
🔗 Provenance — このレコードを発見したソース
- crossref https://doi.org/10.1007/s40171-026-00499-7first seen 2026-05-14 23:15:40
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