Factors influencing the adoption of Digital Twin technology in Vietnamese seaports
Published: August 3, 2026
doi:10.62831/nckh.2026.371.v1
Abstract
This study investigates the factors influencing field workers’ readiness to adopt Digital Twin technology in Vietnamese seaports. Based on 320 valid responses and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM), the findings reveal that perceived usefulness is a key driver of adoption readiness. Field workload is found to play a significant positive moderating role, strengthening the relationship between perceived usefulness and readiness to adopt. In addition, management support and data quality significantly contribute to the acceptance of Digital Twin technology, highlighting the importance of organizational commitment and reliable information systems in facilitating technology adoption in seaport operations.
Keywords
digital twintechnology acceptance model (TAM)seaport logisticsfield worker readinessPLS-SEM
References
1.
Al-Adwan A., Li N., Al-Adwan A., Abbasi G., Albelbis N., & Habibi A. (2023). Extending the Technology Acceptance Model (TAM) to Predict University Students’ Intentions to Use Metaverse-Based Learning Platforms. Education and Information Technologies, 1-33. https://doi.org/10.1007/s10639-023-11816-3.
Al-Ateeq B., Sawan N., Al‐Hajaya K., Altarawneh M., & Al-Makhadmeh A. (2022). Big data analytics in auditing and the consequences for audit quality: A study using the technology acceptance model (TAM). Corporate Governance and Organizational Behavior Review. https://doi.org/10.22495/cgobrv6i1p5.
Brunila O., Kunnaala-Hyrkki V., & Inkinen T. (2021). Hindrances in port digitalization? Identifying problems in adoption and implementation. European Transport Research Review, 13, 1-10. https://doi.org/10.1186/s12544-021-00523-0.
Dihan M., Akash A., Tasneem Z., Das P., Das S., et al. (2024). Digital twin: Data exploration, architecture, implementation and future. Heliyon, 10. https://doi.org/10.1016/j.heliyon.2024.e26503.
Fam K., Liu Y., Wei S., Edu T., Zaharia R., & Negricea C. (2024). Modeling New Technology Readiness and Acceptance in the Case of B2B Marketing Employees. Journal of Business-to-Business Marketing, 32, 1-30. https://doi.org/10.1080/1051712x.2024.2364699.
Galkin A., Samchuk G., Kopytkov D., & Thompson R. (2025). Digital twins in logistics: a comprehensive bibliometric analysis for advancing smart cities and sustainable development. Discover Sustainability, 6. https://doi.org/10.1007/s43621-025-01754-0.
Gardas B., Gunasekaran A., & Narwane V. (2023). Unlocking factors of digital twins for smart manufacturing: a case of emerging economy. International Journal of Computer Integrated Manufacturing, 37, 1463 - 1493. https://doi.org/10.1080/0951192x.2023.2257655.
Kim D., Kim G., Noh S. (2025). Digital Twin-Based Prediction and Optimization for Dynamic Supply Chain Management. Machines. https://doi.org/10.3390/machines13020109.
Liu Y., Zhao S. (2025). Adoption of digital logistics platforms in the maritime logistics industry: based on diffusion of innovations and extended technology acceptance. Humanities and Social Sciences Communications, 12. https://doi.org/10.1057/s41599-025-04969-8.
Moshood T., Nawanir G., Sorooshian S., & Okfalisa O. (2021). Digital Twins Driven Supply Chain Visibility within Logistics: A New Paradigm for Future Logistics. Applied System Innovation, 4, 29. https://doi.org/10.3390/asi4020029.
Nguyen H. P., Nguyen P. Q. P., & Nguyen T. P. (2022). Green Port Strategies in Developed Coastal Countries as Useful Lessons for the Path of Sustainable Development: A case study in Vietnam. International Journal of Renewable Energy Development. https://doi.org/10.14710/ijred.2022.46539.
Nguyen Trung Hieu (2024). Investigating Driving Factors of Digital Transformation in the Vietnam Shipping Companies: Applied for TOE Framework. SAGE Open, 14. https://doi.org/10.1177/21582440241301210.
Nikou S., Reuver M., & Kanafi M. (2022). Workplace literacy skills - how information and digital literacy affect adoption of digital technology. Journal of Documentation, 78, 371-391. https://doi.org/10.1108/jd-12-2021-0241.
Shamsi M., Iakovleva T., Olsen E., & Bagozzi R. (2021). Employees’ Work-Related Well-Being during COVID-19 Pandemic: An Integrated Perspective of Technology Acceptance Model and JD-R Theory. International Journal of Environmental Research and Public Health, 18. https://doi.org/10.3390/ijerph182211888.
Siagian H., Tarigan Z., Basana S., & Basuki R. (2022). The effect of perceived security, perceived ease of use, and perceived usefulness on consumer behavioral intention through trust in digital payment platform. International Journal of Data and Network Science. https://doi.org/10.5267/j.ijdns.2022.2.010.
Turner J., Vorraro G., Liu H., Rockstroh T. et al. (2023). Blue Seaports: The Smart, Sustainable and Electrified Ports of the Future. Smart Cities. https://doi.org/10.3390/smartcities6030074.
Ullah S., Kiani U., Raza B., & Mustafa A. (2022). Consumers’ Intention to Adopt m-payment/m-banking: The Role of Their Financial Skills and Digital Literacy. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.873708.
Wang W., Chen L., Xiong M., & Wang Y. (2021). Accelerating AI Adoption with Responsible AI Signals and Employee Engagement Mechanisms in Health Care. Information Systems Frontiers, 25, 2239 - 2256. https://doi.org/10.1007/s10796-021-10154-4.
Ward R., Choudary R., Singh M., Roumpani F. et al. (2023). The challenges of using live-streamed data in a predictive digital twin. Journal of Building Performance Simulation, 16, 609 - 630. https://doi.org/10.1080/19401493.2023.2187463.
Warsono H., Yuwono T., & Putranti I. (2022). Analyzing technology acceptance model for collaborative governance in public administration: Empirical evidence of digital governance and perceived ease of use. International Journal of Data and Network Science. https://doi.org/10.5267/j.ijdns.2022.12.008.
Zaidi S., Khan S., & Chaabane A. (2024). Unlocking the Potential of Digital Twins in Supply Chains: A Systematic Review. Supply Chain Analytics. https://doi.org/10.1016/j.sca.2024.100075.
Zhou F., Yu K., Xie W., Lyu J., Zheng Z., Zhou S. (2024). Digital Twin-Enabled Smart Maritime Logistics Management in the Context of Industry 5.0. IEEE Access, 12, 10920-10931. https://doi.org/10.1109/access.2024.3354838.
