Research on Cost Control of Railway Engineering Based on Grounded Theory

Abstract

An analysis of cost management within railway construction projects has been conducted using the Analytic Hierarchy Process (AHP) and a regression analysis to evaluate and rank key financial and operational factors affecting project costs. This research assesses the impact of various metrics, such as Safety Inspections, Emergency Preparedness, and Equipment Maintenance, along with financial indicators such as Actual Cost and Variance, on cost control strategies by building a hierarchical model and implementing AHP. The results indicate a clear preference for Financial Metrics, with a priority vector of 0.667, over Operational Metrics, which have a priority vector of 0.334. Among the Financial Metrics, Actual Cost, with a priority vector of 0.565, is identified as the most influential, underscoring the importance of direct cost management. Among the Operational Metrics, Emergency Preparedness is the most important, with a priority vector of 0.540, emphasizing the importance of effective risk management. A regression analysis confirms these priorities, with significant correlations presented between these metrics and variances in costs. According to this study, changes in Emergency Preparedness and Equipment Maintenance can predict cost fluctuations, aligning with the findings of the AHP study. The AHP evaluations are demonstrated to be reliable, with consistency ratios significantly below the 0.1 benchmark (0.043 for Financial Metrics and 0.008 for Operational Metrics), indicating a high degree of consistency in judgment. The statistical validation enhances the framework’s effectiveness in steering strategic decisions regarding cost management. This paper discusses the implications of these results to reduce financial risks and improve project outcomes.