Education, Science, Technology, Innovation and Life
Open Access
Sign In
  1. Home
  2. Journals
  3. Accounting and Corporate Management
  4. Vol 8, Issue 1, 2026

Artificial Intelligence-driven on Digital Transformation: A Strategic Framework for International Port Operation Competitiveness

Download as PDF

DOI: 10.23977/acccm.2026.080103 | Downloads: 1 | Views: 19

Author(s)

Xiao Yu 1, Tachakon Wongkumchai 1

Affiliation(s)

1 Faculty of Management Science, Dhonburi Rajabhat University, Bangkok, Thailand

Corresponding Author

Tachakon Wongkumchai

ABSTRACT

This study aims to analyze the key factors influencing the success of BBW Port Group's AI-driven digital transformation and to develop a strategic framework for its implementation. The study employs a quantitative research methodology, utilizing data collected from 212 personnel at BBW Port Group who are engaged in digital transformation and AI technology applications. The research instrument underwent rigorous testing for Item-Objective Congruence (IOC), validity, and reliability. Data analysis was conducted using descriptive statistics, correlation analysis, and regression analysis. The results indicate that AI system integration capabilities, data quality and validity, technology adoption and innovation, AI-driven automation levels, AI system scalability and flexibility, change management and senior management support, and market and policy pressures all have a significant positive impact on international port operational competitiveness. This research enriches the theoretical framework regarding AI applications in port operations and holds significant theoretical and practical value for promoting the comprehensive upgrading and development of China's port industry.

KEYWORDS

Artificial Intelligence, International Port Operation Competitiveness, Digital Transformation Strategy

CITE THIS PAPER

Xiao Yu, Tachakon Wongkumchai. Artificial Intelligence-driven on Digital Transformation: A Strategic Framework for International Port Operation Competitiveness. Accounting and Corporate Management (2026). Vol. 8, No. 1, 18-25. DOI: http://dx.doi.org/10.23977/acccm.2026.080103.

REFERENCES

[1] Lee, S.-Y., Tongzon, J. L., & Kim, Y. (2015). Port e-Transformation, customer satisfaction and competitiveness. Maritime Policy & Management, 43(5), 630–643. 
[2] Tran Hung Nguyen, Xuan Cu Le, Thi Hai Ly Vu,(2022）An Extended Technology-Organization-Environment (TOE) Framework for Online Retailing Utilization in Digital Transformation: Empirical Evidence from Vietnam,Journal of Open Innovation: Technology, Market, and Complexity,8（4），200
[3] Tornatzky, L. G., & Fleischer, M. (1990). The processes of technological innovation. Lexington Books.
[4] Popa, Catalin, Stefanov, Ovidiu and Goia, Ionela, (2025), Multimodal Livestock Operations Analysis Using Business Process Modeling: A Case Study of Romanian Black Sea Ports, Economies, 13（3), 1-22
[5] N. Al-Ajmi; Abbod Naseb Abbod Al-Tamimi. Mohamed Khudari.(2025).Advancing The Oman Shipping Industry: A Comprehensive Review of Digital Transformation Adoption and Regulatory Integration Using The Extended TOE Framework.  International Journal of Environmental Sciences, 11( 9s) 347-366.
[6] Jin J, Guo Y (2025) Exploring the drivers of digital transformation in Chinese port and shipping enterprises: A machine learning approach. PLoS One 20(5): e0322872.
[7] Gillani, F., Chatha, K. A., Jajja, S. S., Cao, D., & Ma, X. (2024). Unpacking Digital Transformation: Identifying key enablers, transition stages and digital archetypes. Technological Forecasting and Social Change, 203, 123335.
[8] Veera Venkata Subrahmanyam Kommireddy. (2025). AI-Driven Process Automation in Product Lifecycle Management: A Transformative Approach. Journal of Computer Science and Technology Studies, 7(7), 91–100.
[9] Joshi, R., Singh, V., & Sehgal, U. (2025). A Systematic Review of Artificial Intelligence Enabled Data Driven Decision Making in Management and IT. Journal of Neonatal Surgery, 13, 1334–1342.
[10] Tan, F., Zhang, Q., Mehrotra, A., Attri, R., & Tiwari, H. (2024). Unlocking venture growth: Synergizing big data analytics, artificial intelligence, new product development practices, and inter-organizational digital capability. Technological Forecasting and Social Change, 200, 123174.
[11] Yang, J., Blount, Y., & Amrollahi, A. (2024). Artificial intelligence adoption in a professional service industry: A multiple case study. Technological Forecasting and Social Change, 201, 123251.
[12] Zheng, Q., Gou, J., Camarinha-Matos, L. M., Zhang, J. Z., & Zhang, X. (2023). Digital capability requirements and improvement strategies: Organizational socialization of AI teammates. Information Processing & Management, 60(6), 103504.
[13] Park, D. H., Jiang, Q., Ko, E., Son, S. C., & Kim, K. H. (2025). AI transformation and AI adoption intention in B2B environment. Journal of Global Scholars of Marketing Science, 35(4), 439–457.
[14] Xu, H., Liu, J., Xu, X., Chen, J., & Yue, X. (2024). The impact of AI technology adoption on operational decision-making in competitive heterogeneous ports☆. Transportation Research Part E: Logistics and Transportation Review, 183, 103428.
[15] Bécue, A., Gama, J. & Brito, P.Q.(2024). AI’s effect on innovation capacity in the context of industry 5.0: a scoping review. Artif Intell Rev,57, 215
[16] Khan, A. N., Mehmood, K., & Kwan, H. K. (2024). Green knowledge management: A key driver of green technology innovation and sustainable performance in the construction organizations. Journal of Innovation & Knowledge, 9(1), 100455.
[17] Shang, Y., Zhou, S., Zhuang, D., Żywiołek, J., & Dincer, H. (2024). The impact of artificial intelligence application on enterprise environmental performance: Evidence from microenterprises. Gondwana Research, 131, 181–195.
[18] Madanaguli, A., Sjödin, D., Parida, V., & Mikalef, P. (2024). Artificial intelligence capabilities for circular business models: Research synthesis and future agenda. Technological Forecasting and Social Change, 200, 123189. 
[19] Sakai, T., Romano Alho, A., Bhavathrathan, B. K., Chiara, G. D., Gopalakrishnan, R., Jing, P., Hyodo, T., Cheah, L., & Ben-Akiva, M. (2020). SimMobility Freight: An agent-based urban freight simulator for evaluating logistics solutions. Transportation Research Part E: Logistics and Transportation Review, 141, 102017.
[20] Poulose, S., Bhattacharjee, B., & Chakravorty, A. (2024). Determinants and drivers of change for digital transformation and digitalization in human resource management: a systematic literature review and conceptual framework building. Management Review Quarterly, 75(3), 1911–1936.
[21] Raza, Z., Woxenius, J., Vural, C. A., & Lind, M. (2023). Digital transformation of maritime logistics: Exploring trends in the liner shipping segment. Computers in Industry, 145, 103811.
[22] Zhang, L., & Zhang, X. (2025). Impact of digital government construction on the intelligent transformation of enterprises: Evidence from China. Technological Forecasting and Social Change, 210, 123787.Zhang, L., & Zhang, X. (2025). Impact of digital government construction on the intelligent transformation of enterprises: Evidence from China. Technological Forecasting and Social Change, 210, 123787.

Subscription
E-Mail Alert
Most popular papers
Call for Special Issue
Publication Ethics & OA Statement
Plagiarism Policy
Contact Us
Downloads: 44105
Visits: 850565

All published work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2016 - 2031 Clausius Scientific Press Inc. All Rights Reserved.