Research Ethics in Digital Supply Chain Management: Transparency Strategies for Big Data Utilization

Purpose: This study aims to analyze the ethical challenges arising from big data utilization in digital supply chain management and to propose strategies for enhancing both academic integrity and social trust through the assurance of data transparency. Research design, data and methodology: A systematic literature review (SLR) was conducted, analyzing publications retrieved from Google Scholar between 2010 and 2025. While the historical origins of research ethics were broadly reviewed for contextual grounding, the analysis focused on studies published after 2010, when discussions on big data, AI ethics, and supply chain transparency became more prominent. Results: Clarifying data provenance contributes to preventing manipulation and enhancing trust, systematic documentation of data processes strengthens reproducibility in both research and industry, and honest disclosure of results sustains credibility across academic and corporate domains. Furthermore, technologies such as blockchain and IoT have been validated as effective tools for safeguarding data integrity. Conclusions: The assurance of data transparency is not merely a technical requirement but an act of research ethics and a foundation for ESG compliance and corporate sustainability. Unlike prior studies that separately addressed big data applications and research ethics, this paper provides one of the first integrative frameworks directly applying research ethics principles to supply chain data management.