Enhancing the resilience of railway systems is an urgent problem to be solved since they provide the basic services that form the backbone of a country’s economy, security, and well-being. Based on a literature review, eleven variables were considered, and a Structural Equation model was estimated. Model calibration was carried out through the results of a survey. Specifically, a questionnaire was submitted to employees of Ferrovie dello Stato Italiane (the Italian state railway company). A total of 745 valid responses were received. The internal consistency reliability of the study was assessed by determining both Cronbach’s alpha and Jöreskog’s rho, as the former assumes that all variables are equally reliable. To evaluate the convergent validity of the model, the Average Variance Extracted (AVE) was used. Future research developments will consist in the possibility of introducing new variables such as the ‘monitoring of the environmental state’ to promptly detect and manage any environmental emergencies.

Key influencing factors identification of rail systems resilience: a structural equation model / Pagliara, F.; Aria, M.; Tartaglia, M.; Sacco, D.; De Iulio, G.. - In: TRANSPORTATION PLANNING AND TECHNOLOGY. - ISSN 0308-1060. - 49:2(2026), pp. 192-223. [10.1080/03081060.2024.2443676]

Key influencing factors identification of rail systems resilience: a structural equation model

PAGLIARA, F.;ARIA, M.;SACCO D.;
2026

Abstract

Enhancing the resilience of railway systems is an urgent problem to be solved since they provide the basic services that form the backbone of a country’s economy, security, and well-being. Based on a literature review, eleven variables were considered, and a Structural Equation model was estimated. Model calibration was carried out through the results of a survey. Specifically, a questionnaire was submitted to employees of Ferrovie dello Stato Italiane (the Italian state railway company). A total of 745 valid responses were received. The internal consistency reliability of the study was assessed by determining both Cronbach’s alpha and Jöreskog’s rho, as the former assumes that all variables are equally reliable. To evaluate the convergent validity of the model, the Average Variance Extracted (AVE) was used. Future research developments will consist in the possibility of introducing new variables such as the ‘monitoring of the environmental state’ to promptly detect and manage any environmental emergencies.
2026
Key influencing factors identification of rail systems resilience: a structural equation model / Pagliara, F.; Aria, M.; Tartaglia, M.; Sacco, D.; De Iulio, G.. - In: TRANSPORTATION PLANNING AND TECHNOLOGY. - ISSN 0308-1060. - 49:2(2026), pp. 192-223. [10.1080/03081060.2024.2443676]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/995273
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