Leveraging dynamic capabilities for green transformation: A strategic path to sustainable supply chain performance in the Nigerian cement industry
動的ケイパビリティを活用したグリーン変革：ナイジェリアセメント産業における持続可能なサプライチェーンパフォーマンスへの戦略的経路 (AI 翻訳)
Favour Iretomiwa Remi-Aworemi, Akeem Olanrewaju Salami
🤖 gxceed AI 要約
日本語
本研究は、ナイジェリアのセメント産業において、動的ケイパビリティ（センシング、捕捉、再構成）が持続可能なサプライチェーンパフォーマンスに与える影響を検証した。385人の従業員調査とSEM分析の結果、3つの能力すべてが有意な正の効果を示し、特にセンシング能力が最も強い予測因子であった。新興国におけるグリーン変革に向けた実践的示唆を提供する。
English
This study examines how dynamic capabilities (sensing, seizing, reconfiguring) influence sustainable supply chain performance (SSCP) in the Nigerian cement industry. Using survey data from 385 employees and SEM analysis, all three capabilities significantly positively affect SSCP, with sensing capability being the strongest predictor. The findings provide actionable guidance for firms and policymakers pursuing green transformation in emerging economies.
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、セメント業界がグリーン変革の対象となっているが、本稿はナイジェリアを対象としており、日本企業のサプライチェーンにおいて新興国との連携を考える際の参考となる可能性がある。ただし、日本の制度や市場とは直接関係しない。
In the global GX context
While focused on Nigeria, this study offers a dynamic capabilities framework that can inform sustainable supply chain strategies in other emerging markets. For global readers, it provides empirical evidence on the micro-foundations of green transformation in a heavy-industry context.
👥 読者別の含意
🔬研究者:Tests dynamic capabilities theory in a green transformation context, providing empirical evidence from Sub-Saharan Africa.
🏢実務担当者:Guidance on building environmental intelligence and green technology investment for sustainable supply chain.
🏛政策担当者:Suggests capacity-building and green financing to support industrial greening.
📄 Abstract（原文）
Purpose: This study examines the whether the dimensions of the Dynamic Capabilities View (DCV), sensing, seizing, and reconfiguring capabilities, directly predict sustainable supply chain performance (SSCP) in the Nigerian Cement industrial. Design/methodology/approach: The quantitative cross-sectional survey of 385 employees across Dangote Cement Plc., Lafarge Africa Plc., and BUA Cement Plc. was analysed through structural equation modelling (SEM) implemented in IBM SPSS AMOS version 23. A two-stage analytical procedure encompassing confirmatory factor analysis (CFA) for measurement model evaluation and structural path estimation was adopted. Bias-corrected bootstrap confidence intervals from 5,000 resamples were used to verify the robustness of all structural paths. Findings: The result demonstrated excellent psychometric properties and outstanding fit. All the three capability dimensions exerted significant positive direct effects on SSCP: sensing capability was the strongest predictor, followed by seizing capability and reconfiguring capability. Bootstrap confidence intervals confirmed the reliability of all three structural paths. Limitations and Research implications: The cross-sectional, single-industry design limits causal inference and generalisability. Longitudinal designs incorporating objective emissions and efficiency data across multiple sectors are warranted. Practical Implications: Nigerian cement industry should build formal environmental intelligence systems, invest deliberately in green technology, and restructure supply chain governance to institutionalise sustainability. Policymakers should complement regulatory enforcement with capacity-building support and green financing instruments aligned with Sustainable Development Goal 9. Originality/value: This study provides the first SEM-based empirical test of all three DCV micro-foundations as independent direct predictors of SSCP in Sub-Saharan Africa, contributing both theoretical extension and actionable guidance for an underrepresented industrial context.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://journal.uir.ac.id/index.php/kiat/article/download/28245/9919first seen 2026-07-04 05:15:59
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