{ "background": "Municipal infrastructure asset management in sub-Saharan Africa is often characterised by inefficiency, with diagnostic tools lacking empirical validation. Existing frameworks are seldom tested in randomised field settings, limiting evidence on their practical efficacy. ", "purpose and objectives": "This study aimed to empirically evaluate a novel diagnostic framework for municipal infrastructure asset management systems. The primary objective was to measure its effect on management efficiency scores in a Kenyan context. ", "methodology": "A randomised field trial was conducted with 42 municipal authorities. Participants were randomly assigned to an intervention group, which applied the diagnostic framework, or a control group, which continued with standard practice. Efficiency was measured using a composite index derived from technical and financial metrics. The treatment effect was estimated using a linear regression model: Ei = \0 + \1 Ti + \\ + \, where Ei is the efficiency score, Ti is the treatment indicator, and ᵢ is a vector of covariates. Robust standard errors were used for inference. ", "findings": "Application of the diagnostic framework yielded a statistically significant positive treatment effect. The intervention group's mean efficiency score was 18. 7 percentage points higher (95% CI: 12. 4, 25. 0; p<0. 01) than the control group's score after the trial period. The framework was particularly effective in improving asset inventory completeness and planned maintenance adherence. ", "conclusion": "The diagnostic framework is an effective tool for enhancing the operational efficiency of municipal infrastructure asset management. Its structured approach provides a replicable method for identifying and addressing systemic weaknesses. ", "recommendations": "Municipal authorities should adopt structured diagnostic tools as a precursor to asset management system upgrades. Policymakers are encouraged to integrate such frameworks into national infrastructure management guidelines to standardise evaluations. ", "key words": "asset management, infrastructure, diagnostic framework, randomised controlled trial, municipal engineering, efficiency",
Hassan et al. (2018) studied this question.