Digitalization of Railway Processes in the Age of AI technologies, a Bibliometric Review

Document Type : Original Article

Authors
Abdolhadi Zarrabi 1
Mohammad Taghi Taghavifard 2
Iman Raeesi Vanani 3
Manoochehr Najmi 4
1 PhD Candidate, Department of IT Management, Faculty of Management and Accounting, Allameh Tabataba'i University, Tehran, Iran
2 Prof., Department of Information Technology and Operations Management, Faculty of Management and Accounting, Allameh Tabataba'i University, Tehran, Iran
3 Associate Prof., Department of Information Technology and Operations Management, Faculty of Management and Accounting, Allameh Tabataba'i University, Tehran, Iran
4 Associate Prof., Department of Industrial Engineering, Faculty of Management and Economics, Sharif University of Technology, Tehran, Iran
10.22034/aimj.2025.518293.1634
Abstract
The digital transformation of the railway transportation industry—particularly through the integration of artificial intelligence (AI) technologies—has emerged as a key driver of innovation within critical infrastructure sectors. This study aims to map the knowledge landscape and identify prevailing trends, technologies, challenges, and key stakeholders in the application of AI within the railway domain by employing a bibliometric approach. Research data were collected from the Scopus database, and following a screening process, a total of 1,202 articles published between 2010 and 2025 were analyzed using VOSviewer software. The findings reveal that technologies such as machine learning, deep learning, genetic algorithms, and digital twins are most prominently represented in the literature, with the primary application areas including predictive maintenance, health monitoring, and intelligent scheduling. In terms of scientific output structure, China and Beijing Jiaotong University have demonstrated leading positions, while countries such as Iran, despite contributing to the scientific output, have shown weaker performance in international research collaborations. Furthermore, the gap analysis highlights that several strategic topics—such as cyber-resilience, change management, and supply chain optimization—have received comparatively limited attention. Finally, by synthesizing the bibliometric results and cluster analyses, a conceptual framework is proposed along four dimensions: technology-oriented, application-oriented, outcome-oriented, and challenge-oriented. Based on this framework, five research propositions are offered to guide future investigations in the field.

Keywords

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  • Receive Date 22 April 2025
  • Revise Date 04 June 2025
  • Accept Date 11 June 2025