Evaluating Digital Transformation Risks in Logistics and Supply Chain Management with PLS-SEM-ANN-fsQCA

This study investigates the risks associated with digital transformation (DT) implementation in Vietnam’s logistics and supply chain management (SCM) sector, utilizing a hybrid PLS-SEM-ANN-fsQCA methodology to analyze data from 243 valid questionnaires. Anchored in the Technology-Organization-Environment framework augmented with human factors (TOE+H), the research aims to examine how technological, organizational, environmental, and human factors influence DT adoption and associated risks, including financial, operational, cybersecurity, and reputational risks, while exploring the moderating roles of firm size and digital literacy. Findings reveal that TOE+H factors significantly drive DT implementation, but misalignment, ineffective management, market volatility, and limited digital literacy amplify risks, particularly cybersecurity vulnerabilities. Moderation analyses indicate that high digital literacy, larger firm size, and regulatory compliance mitigate these risks. Artificial neural network (ANN) analysis highlights non-linear relationships, emphasizing technological and human factors as key drivers, while fuzzy-set qualitative comparative analysis (fsQCA) identifies configurations, such as strong technological-human factor alignment, linked to successful DT outcomes. Importance-Performance Map Analysis (IPMA) prioritizes technological and human factors for resource allocation to enhance sustainability. This study advances the TOE+H framework by integrating a hybrid methodology, offering novel insights into DT risk dynamics and practical strategies for sustainable logistics in Vietnam’s SCM sector.