Prioritizing construction delay types and mitigation strategies using an integrated RCA-FAHP-RII framework
DOI:
https://doi.org/10.15587/1729-4061.2026.357222Keywords:
construction delay, FAHP, project management, RCA, RII, road constructionAbstract
The object of this study is completed road construction projects in East Kalimantan that experienced negative schedule deviations during the 2022–2024 period. The problem addressed in this study is the persistence of construction delays that remain unresolved despite the frequent application of time extensions, indicating systemic weaknesses in planning, control, and governance. The results show that the most significant delay factors from RCA (root cause analysis) are weak project control and operational planning, unreliable material and procurement supply chains, unstable productivity in critical on‑site activities, and unanticipated external constraints. The fuzzy analytics hierarchy process (FAHP) results indicate that the adoption of digital-based project management and scheduling systems is the most effective mitigation strategy, achieving the highest synthesis score of 0.599 compared to other alternatives. This result is further supported by sensitivity analysis, confirming the stability of the ranking. From the relatives importance index (RII) analysis, weather-related factors emerge as the most significant contributors to delays, with a factor-level score of 0.729, followed by time factors (0.662) and equipment factors (0.643). At the indicator level, delays in material delivery show the highest individual impact, with an RII value of 0.779. Overall, five out of six major delay factor groups fall within the “high importance” category, highlighting the dominant role of systemic and operational issues rather than isolated technical problems. These results are explained by deficiencies in preventive planning and integrated control mechanisms, which lead to delayed decision‑making and reactive project management practices. The distinctive feature of the proposed results lies in the integration of causal identification, priority weighting, and policy‑oriented decision support, enabling delays to be addressed systematically rather than administratively. The results can be applied by public infrastructure agencies using digital scheduling systems, performance‑based evaluations, and stronger accountability mechanisms, especially in regions with fast infrastructure development
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