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All Journal Emerging Science Journal
Nguyen, P. V.
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Environmental Science

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Journal : Emerging Science Journal

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Evaluating Digital Transformation Risks in Logistics and Supply Chain Management with PLS-SEM-ANN-fsQCA Nguyen, H. T. M.; Dang, H. B.; Nguyen, A. V. T.; Nguyen, H. Ngoc; Nguyen, P. V.
Emerging Science Journal Vol. 9 No. 6 (2025): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2025-09-06-023

Abstract

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.
Dynamic Customer Experience, Satisfaction, and Word-of-Mouth in Telecom-IT Sector Nguyen, Hung Q.; Nguyen, Hau V.; Nguyen, P. V.
Emerging Science Journal Vol. 10 No. 1 (2026): February
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2026-010-01-026

Abstract

This study examines how Dynamic Customer Experience (DCX) affects Customer Satisfaction (CS) and Word-of-Mouth (WOM) intentions among VNPT customers in Vietnam, identifying AI-Driven Service Personalization (AISP), Integrated Service Quality (ISQ), Cultural Resonance (CR), and Sustainable IT-Telecom Practices (SITP) as key antecedents, with Customer Empowerment (CEMP), Perceived Value Co-Creation (PVCC), Emotional Engagement (EE), and CS as mediators, and AI Trust (AIT), Service Innovation Maturity (SIM), and Regional Cultural Dynamics (RCD) as moderators. A multi-theoretical framework (Customer Experience Framework, Social Exchange Theory, Expectancy-Disconfirmation Theory, TAM, SERVQUAL) guided the research. Survey data from 677 VNPT customers were analysed using hybrid PLS-SEM (SmartPLS 4.0) for explanatory power and Artificial Neural Network (ANN) in SPSS 25.0 for predictive accuracy. PLS-SEM confirmed significant positive effects of AISP, ISQ, CR, and SITP on DCX (β = 0.24–0.33, p < 0.01), and DCX on CS (β = 0.43) and WOM (β = 0.30). CS was the strongest mediator (indirect effect = 0.20, VAF = 67%). Moderation analyses showed stronger effects in rural areas due to cultural dynamics. ANN validated results with high predictive power (R² testing = 0.83–0.87), identifying AISP and CS as top predictors. This is the first study to integrate sustainability and cultural resonance into DCX for Vietnam's collectivist telecom market using a hybrid PLS-SEM-ANN approach, outperforming single-method studies and providing VNPT actionable strategies for AI personalization and green 5G deployment. JEL Code: M14, M30, M31, M37.
Co-Authors Dang, H. B. Nguyen, A. V. T. Nguyen, H. Ngoc Nguyen, H. T. M. Nguyen, Hau V. Nguyen, Hung Q.