A data-driven analysis of quality management impacts on energy supply chain performance
Energy supply chains increasingly adopt digital quality management systems, but research on their performance impact remains limited, especially in emerging markets. While individual digital quality dimensions exist in literature, his study provides empirical validation of an integrated framework of seven dimensions specifically for energy supply chain contexts. Using survey data from 120 supply chain professionals at Ghana National Gas Company, we examine relationships between digital quality analytics implementation and supply chain performance through factor analysis and multiple regression. Results suggest digital quality analytics implementation is associated with 65.3% of supply chain performance variance within this organizational context (R 2 = 0.653, F 7 , 112 = 30.13, p < 0.001), with all seven factors showing significant positive relationships. Digital customer analytics proves the strongest predictor ( β = 0.243), followed by blockchain integration ( β = 0.171) and data-driven improvement ( β = 0.156). Digital maturity shows no moderation association, suggesting consistent effectiveness across organizational readiness levels. Implementation patterns across maturity groups align with institutional theory predictions about technology adoption in emerging markets. While findings are based on a single organization and require broader validation, results offer a preliminarily tested framework that may inform digital quality analytics in similar energy supply chain contexts, extending quality management theory and suggesting potential guidance for digital transformation efforts in similar organizational settings. • Present a novel framework linking digital quality and supply chain performance. • Analyze seven dimensions influencing digital transformation effectiveness. • Identify digital customer analytics as the top performance predictor. • Show the consistent impact of digital tools across readiness levels. • Provide actionable insights for energy sector technology investments.
Authors
- Ruhaimatu Abudu (ORCID: https://orcid.org/0000-0002-6870-8465)
- Beatrice Agbeko
Institutions
- North Dakota State University (US)
- Ghana Communication Technology University (GH)
- Shanghai Maritime University (CN)
Publication Details
- Journal
- Supply Chain Analytics
- Published
- 2025-11-20
- DOI
- https://doi.org/10.1016/j.sca.2025.100175
- Citations
- 2
- Primary Topic
- Digital Transformation in Industry
- Type
- article
- Field-Weighted Citation Impact
- 2.48