Identification of Influencing Variables on Improving Resilience of High-Speed Railway System

Abstract

In recent years, frequent natural disasters have brought great challenges to the stable operation of the high-speed railway (HSR). Improving the resilience of the HSR system is an urgent problem to be solved. This study aims to explore how to improve the resilience of the HSR system. Based on an in-depth literature review and case study, 11 variables and 15 hypothetical paths were proposed. Then the questionnaires were distributed to professionals from academia and industry. A total of 270 valid responses were received. Finally, the structural equation model was used to evaluate these variables’ influence degree and their influence path. The results indicated that the infrastructure components (i.e., quality control and equipment operation and maintenance) play a positive role in the persistence ability. The organizational operation and maintenance components (i.e., organizational structure and organizational efficiency) promote the speed of function restoration. The interactive system components (i.e., technical system and system operation and maintenance) also have a positive effect on adaptability and transformability. The three components of HSR system play a positive role in different resilience attributes (i.e., persistence ability, function restoration, adaptability, and transformability), which further positively impacts the effectiveness of improving resilience. Based on the accepted hypothetical paths, five strategies for improving resilience were discussed, such as a certain degree redundancy of key organizations or members, encouragement of self-organized decision-making, and establishment of the “health records” of each HSR line. This study would enrich the theoretical system of resilience and help practitioners better understand the influencing variables and influencing paths of the resilience of the HSR system.

Old Wine in New Bottles? Understanding Infrastructure Resilience: Foundations, Assessment, and Limitations

“…MCDA is designed to manage decisional processes characterised by multiple dimensions. MCDA methods, such as the Analytic Hierarchy Process (AHP) (Aziz et al, 2022;Mukesh et al, 2022;Chavoshy et al, 2018;Morshed et al, 2020), Analytic Network Process (ANP) , the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) (Tang et al, 2022b;Zhang and Ng, 2021), Principal Components Analysis (PCA) (Mohammed et al, 2022), Best-Worst method (Khan et al, 2022;Khan et al, 2023), Structural Equation Model (Zhang et al, 2022b), and Grey Relational analysis (Hu et al, 2020) are used to evaluate and rank the critical influential factors of system resilience. The fuzzy logic analysis is often used to convert qualitative descriptions of these factors into quantitative evaluation for assessing the performance of the factors (Jiao et al;Lad et al, 2022;Tang et al, 2022b) and the entropy weight method is adopted to allocate weights to the factors (Jiao et al;Li et al, 2022;Zhang and Ng, 2021).…”