Author(s)

Xuanmin Che ¹

Affiliation(s)

¹ R&T Logistics Inc, 4882W145th St Hawthorne, CA90250, America

Corresponding Author

Xuanmin Che

ABSTRACT

This review paper explores the evolving landscape of human-machine collaboration in logistics risk decision-making, focusing on the integration of multi-source behavioral data. The increasing complexity of modern logistics necessitates sophisticated risk management strategies. Traditionally, these decisions relied heavily on human expertise, but the advent of advanced sensors, IoT devices, and data analytics provides opportunities for integrating machine intelligence. By fusing data from various sources, including operational systems, environmental sensors, and human behavioral patterns, decision-making processes can become more informed and robust. This review examines existing methodologies for data acquisition, processing, and integration, with a particular emphasis on behavioral data originating from human operators and intelligent machines alike. We analyze the strengths and weaknesses of various machine learning techniques applied to risk prediction and mitigation within logistics, considering their adaptability to different operational contexts. Furthermore, we address the challenges related to data privacy, security, and the ethical considerations of using behavioral data in automation systems. This paper identifies key research gaps and outlines potential directions for future research, emphasizing the need for explainable AI, robust human-machine interfaces, and adaptive risk management frameworks that can effectively handle the dynamic nature of logistics operations. The ultimate goal is to provide a comprehensive overview of the current state-of-the-art and offer insights for advancing human-machine collaborative solutions for enhanced logistics risk management.

KEYWORDS

Human-Machine Collaboration; Logistics Risk Management; Behavioral Data Fusion; Decision-Making; Machine Learning; Risk Prediction; Explainable AI

CITE THIS PAPER

Xuanmin Che. A Study on Human–Machine Collaborative Logistics Risk Decision-Making Methods Based on Multi-Source Behavioral Data Fusion. Journal of Artificial Intelligence Practice (2026). Vol. 9, No. 1, 68-75. DOI: http://dx.doi.org/10.23977/jaip.2026.090109.

REFERENCES

[1] C. Li, H. Zhu, and D. Li, "A Systematic Review of Human‐Aware Systems in Manufacturing and Logistics: Overcoming Obstacles With Advanced Modeling Techniques," Engineering Reports, vol. 7, no. 12, pp. e70513, 2025.
[2] S. Carpitella, F. Carpitella, and J. Izquierdo, “Human–Machine Integration to Strengthen Risk Management in the Winemaking Industry," in Analytics Modeling in Reliability and Machine Learning and Its Applications, 2025, pp. 91-116.
[3] N. Kumar and R. R. Kumar, "Human–AI collaboration in operations and supply chain management: a systematic literature review," Management Review Quarterly, pp. 1-34, 2025.
[4] A. O. John, E. K. Adejumo, and S. Y. Larbi, “AI-Driven Supply Chain Risk Management in the Manufacturing Sector: Tackling Data Bias, Ensuring Algorithmic Transparency, and Enhancing Human-AI Collaboration," Iconic Research and Engineering Journals (IRE Journal), vol. 8, no. 11, pp. 77-94, 2025.
[5] S. Panigrahy, "Human-AI Interaction in Logistics: Augmenting Human Capabilities for Supply Chain Excellence," Journal Of Multidisciplinary, vol. 5, no. 7, pp. 289-295, 2025.
[6] J. Sun and L. Qiu, "Human-Machine Collaboration: Definitions, Models, and Socio-Economic Impacts," International Journal of Crowd Science, vol. 9, no. 3, pp. 149-163, 2025.
[7] J. Wei, S. Qi, W. Wang, L. Jiang, H. Gao, F. Zhao, et al., "Decision-Making in the Age of AI: A Review of Theoretical Frameworks, Computational Tools, and Human-Machine Collaboration," Contemporary Mathematics, pp. 2089-2112, 2025.
[8] N. Berti and S. Finco, “Digital twin and human factors in manufacturing and logistics systems: State of the art and future research directions," IFAC-PapersOnLine, vol. 55, no. 10, pp. 1893-1898, 2022.
[9] M. J. Alenjareghi, S. Keivanpour, Y. A. Chinniah, S. Jocelyn, and A. Oulmane, "Safe human-robot collaboration: a systematic review of risk assessment methods with AI integration and standardization considerations," The International Journal of Advanced Manufacturing Technology, vol. 133, no. 9, pp. 4077-4110, 2024.
[10] Y. Zhao, J. Gou, Z. Wang, and Y. Wen, "Emotional Impact Analysis of Human-Machine Collaborative Decision-Making," in 2024 7th International Conference on Artificial Intelligence and Big Data (ICAIBD), 2024, pp. 572-577.
[11] S. Nixdorf, M. Zhang, E. H. Grosse, and F. Ansari, "Reciprocal learning in human–machine collaboration: a systematic literature review and implications for production and logistics," International Journal of Production Research, pp. 1-25, 2025.

Sponsors, Associates, and Links

---

• Power Systems Computation
  
  
• Internet of Things (IoT) and Engineering Applications
  
  
• Computing, Performance and Communication Systems
  
  
• Advances in Computer, Signals and Systems
  
  
• Journal of Network Computing and Applications
  
  
• Journal of Web Systems and Applications
  
  
• Journal of Electrotechnology, Electrical Engineering and Management
  
  
• Journal of Wireless Sensors and Sensor Networks
  
  
• Journal of Image Processing Theory and Applications
  
  
• Mobile Computing and Networking
  
  
• Vehicle Power and Propulsion
  
  
• Frontiers in Computer Vision and Pattern Recognition
  
  
• Knowledge Discovery and Data Mining Letters
  
  
• Big Data Analysis and Cloud Computing
  
  
• Electrical Insulation and Dielectrics
  
  
• Crypto and Information Security
  
  
• Journal of Neural Information Processing
  
  
• Collaborative and Social Computing
  
  
• International Journal of Network and Communication Technology
  
  
• File and Storage Technologies
  
  
• Frontiers in Genetic and Evolutionary Computation
  
  
• Optical Network Design and Modeling
  
  
• Journal of Virtual Reality and Artificial Intelligence
  
  
• Natural Language Processing and Speech Recognition
  
  
• Journal of High-Voltage
  
  
• Programming Languages and Operating Systems
  
  
• Visual Communications and Image Processing
  
  
• Journal of Systems Analysis and Integration
  
  
• Knowledge Representation and Automated Reasoning
  
  
• Review of Information Display Techniques
  
  
• Data and Knowledge Engineering
  
  
• Journal of Database Systems
  
  
• Journal of Cluster and Grid Computing
  
  
• Cloud and Service-Oriented Computing
  
  
• Journal of Networking, Architecture and Storage
  
  
• Journal of Software Engineering and Metrics
  
  
• Visualization Techniques
  
  
• Journal of Parallel and Distributed Processing
  
  
• Journal of Modeling, Analysis and Simulation
  
  
• Journal of Privacy, Trust and Security
  
  
• Journal of Cognitive Informatics and Cognitive Computing
  
  
• Lecture Notes on Wireless Networks and Communications
  
  
• International Journal of Computer and Communications Security
  
  
• Journal of Multimedia Techniques
  
  
• Automation and Machine Learning
  
  
• Computational Linguistics Letters
  
  
• Journal of Computer Architecture and Design
  
  
• Journal of Ubiquitous and Future Networks