Industry 4.0 for passenger railway companies: A maturity model proposal for technology management

The railway sector is a relevant segment for the transportation of people and goods, and its efficiency and sustainability are crucial for fostering economic development and minimizing environmental impact. This research proposes an Industry 4.0 maturity model for passenger railway companies to manage emerging technologies, aiming to enhance them holistically to leverage the internal and external business dimensions. An exploratory and qualitative approach was employed, involving semi-structured interviews with experts in Brazilian railway transport. Based on the opportunities and Key Performance Indicators identified within the sector, the authors developed an Industry 4.0 maturity model for companies and subsequently tested it in collaboration with a transport operator. The findings suggest that the proposed Industry 4.0 maturity model can effectively guide practitioners in applying advanced technologies for robust and efficient train operations, prescriptive maintenance, strong supply chain management, and improved passenger experience and worker performance. This research provides a noteworthy and substantial contribution by introducing unprecedented frameworks that offer a holistic view of Industry 4.0 in the context of passenger railways. The study's practical impact is aiding passenger railway companies to navigate their Industry 4.0 journey. Academically, the research contributes to advancing the holistic understanding of Industry 4.0 as an ongoing phenomenon, enriching the academic discourse by discussing published works and presenting empirical data from railway companies.

• Record URL:
  • https://doi.org/10.1016/j.jrtpm.2024.100480
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S2210970624000507
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/22109706
• Supplemental Notes:
  • © 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies. Abstract reprinted with permission of Elsevier.
• Authors:
  • Chaves Franz, Michael Luciano
  • 0009-0002-6016-3744
  • Ayala, Néstor Fabián
  • 0000-0001-8888-9227
  • Larranaga, Ana Margarita
  • 0000-0001-7504-2369
• Publication Date: 2024-12

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: 100480
• Serial:
  • Journal of Rail Transport Planning & Management
  • Volume: 32
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 2210-9706
  • Serial URL: http://www.sciencedirect.com/science/journal/22109706

Subject/Index Terms

• TRT Terms: Internet of things; Management information systems; Passenger transportation; Railroads; Sustainable development; Technological innovations
• Geographic Terms: Brazil
• Subject Areas: Administration and Management; Data and Information Technology; Economics; Planning and Forecasting; Railroads;

Filing Info

• Accession Number: 01933954
• Record Type: Publication
• Files: TRIS
• Created Date: Oct 17 2024 9:15AM