Nur Mohammad

University of California, Irvine, Clifford Chance

Papers

2

Total Citations

6

H-Index

2

About

Nur Mohammad is a forward-thinking researcher at the intersection of artificial intelligence, enterprise systems, and industrial automation. His work primarily focuses on the strategic integration of AI into complex operational environments, with key contributions to the conceptualization of "dark factories"—fully autonomous industrial settings where human intervention is minimal. In his most cited paper (4 citations), Mohammad proposes a novel framework that synthesizes the Technology-Organization-Environment (TOE) model, the Technology Acceptance Model (TAM), and the Information Systems Success Model to guide sustainable AI-ERP integration, offering a roadmap for next-generation manufacturing. Beyond industrial applications, he applies AI to the banking sector, demonstrating how advanced IT solutions, robotization, and machine learning can enhance regulatory compliance and fraud detection (2 citations). Though early in his career, Mohammad’s work is already shaping discussions on how AI can drive both operational excellence and ethical governance. His interdisciplinary approach—bridging technology adoption theory with real-world automation challenges—positions him as an emerging voice in the future of intelligent, self-regulating industrial and financial systems.

Research Focus

Key Achievements

2
H-Index
2
Papers
6
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
A Conceptual Framework for Sustainable AI-ERP Integration in Dark Factories: Synthesising TOE, TAM, and IS Success Models for Autonomous Industrial Environments
4 citations · 2025
📈 Most Prolific Year: 2025 (2 Papers)
🤝 Key Collaborators: 10
🏛 Institutions: University of California, Irvine, Clifford Chance

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago