A Framework for Designing Sustainable Supply Chains in the Digital Transformation Era

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Authors: Lydia Bennett
Cited by: 1

Abstract

This study aimed to develop a comprehensive framework for designing sustainable supply chains in the digital transformation era, addressing the growing need for integration between technological capabilities and sustainability objectives. The research employed a qualitative approach, using semi-structured interviews with industry professionals, supply chain managers, technology experts, and academic researchers, supplemented by secondary data from industry reports and scholarly publications. Thematic analysis of the collected data identified key dimensions of sustainable supply chains, including environmental, social, and economic sustainability, alongside enablers such as digital technologies, collaboration, governance, innovation, and human and organizational capabilities. Findings revealed that digital tools, including artificial intelligence, IoT, blockchain, and big data analytics, play a critical role in enhancing visibility, optimizing operations, supporting ethical practices, and enabling proactive risk management. Collaboration among supply chain partners and strong governance mechanisms were identified as essential for effective implementation, while challenges such as high costs, skill gaps, and infrastructure limitations must be addressed strategically. The study contributes a robust conceptual framework that integrates sustainability principles with digital transformation strategies, offering practical guidance for organizations seeking to enhance resilience, efficiency, and ethical performance in their supply chains. The findings also provide theoretical insights for future research on sustainable supply chain design in digitally-driven contexts.

Fields of Study & Subjects

Sustainable Supply Chain Management Supply Chain Resilience and Risk Management Digital Transformation in Industry

Publication details

Journal / source
Preprints.org
Publisher
MDPI AG
Publication date
25 March 2026
Document type
Preprint