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March 13, 20260 citationsOpen Access

A Multilevel Regression Analysis of Maintenance Depot Systems for Transport Risk Reduction in South Africa, 2000–2026

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TNThandiwe NkosiHuman Sciences Research CouncilPMPieter van der MerweUniversity of Johannesburg

Key Points

  • This research aims to quantify the relationship between depot system characteristics and the reduction of transport risk in South Africa.
  • Employed multilevel regression analysis with depots nested within provinces.
  • Utilized a longitudinal dataset of depot performance and incident records.
  • Fitted a statistical model to estimate the impact of operating variables on provincial-level incident rates.
  • A one-standard-deviation increase in preventive maintenance compliance correlates with a 15.2% decrease in major incident rates.
  • Significant variation in incident rates is attributable to provincial-level clustering, as indicated by an intra-class correlation of 0.31.

Abstract

"background": "The efficacy of maintenance depot systems is critical for transport infrastructure reliability and safety. In the South African context, systematic evaluations of how depot-level interventions translate into network-wide risk reduction have been limited, with a paucity of quantitative, hierarchical models linking operational factors to safety outcomes. ", "purpose and objectives": "This case study aims to methodologically evaluate the relationship between depot system characteristics and transport risk reduction. Its objective is to quantify the impact of key depot-level operational and resource variables on provincial-level incident rates, controlling for network and traffic covariates. ", "methodology": "A multilevel regression analysis was employed, treating depots as nested within provinces. The model, y{ij = \0 + \1Xij + uj + eij, where i denotes depots and j provinces, was fitted to a longitudinal dataset of depot performance and incident records. Estimation used restricted maximum likelihood with robust standard errors to account for heteroskedasticity. ", "findings": "Analysis indicates that a one-standard-deviation increase in depot preventive maintenance compliance is associated with a 15. 2% reduction in major incident rates at the provincial level (95% CI: 11. 8% to 18. 6%). The intra-class correlation coefficient of 0. 31 confirms significant variation attributable to provincial-level clustering. ", "conclusion": "The findings demonstrate that depot system performance is a statistically significant predictor of broader transport network risk. The multilevel approach effectively captures the hierarchical structure of the infrastructure system. ", "recommendations": "Infrastructure policy should mandate the collection of standardised, depot-level performance indicators. Investment should prioritise enhancing preventive maintenance capacity at the depot level, as it yields disproportionate system-wide safety benefits. ", "key words": "multilevel regression, infrastructure maintenance, transport risk, depot systems, engineering management", "contribution statement": "This study provides a novel hierarchical modelling framework for infrastructure safety analytics, demonstrating a quantifiable

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Cite This Study

Nkosi et al. (2014) studied this question.

synapsesocial.com/papers/69b3ad0502a1e69014ccf3d8https://doi.org/10.5281/zenodo.18964340
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