Development of Maintenance Management Model for Enhancing Availability Performance of Passenger Terminal Facilities: A Case Study of Lake Tanganyika
Abstract
Purpose: Passenger terminal facilities along Lake Tanganyika face persistent challenges such as ageing infrastructure, misoperation, and inconsistent maintenance, resulting in frequent service disruptions. This study develops and validates a data-driven maintenance management model aimed at enhancing availability performance. Design/methodology/approach: A mixed-methods approach was applied, combining archival data (2020–2024) with user satisfaction surveys. Analytical tools included descriptive statistics, Relative Importance Index (RII), regression modelling, and hold-out validation. Findings: Results identified Workforce Competence B = 3.656, User Satisfaction B = 2.585, and Technology Advancement B = 1.993 as strong positive predictors of availability. In contrast, Misoperation B = -2.433, Maintenance Schedule Non-Compliance B = -2.151, and Ageing Infrastructure B = -0.001 exerted significant adverse effects. The developed regression model demonstrated excellent predictive power R² = 0.922; MAE = 1.92%, confirming robustness and practical applicability. Practical implications: The study concludes that prioritising workforce training, integrating predictive maintenance technologies, and rehabilitating ageing assets can substantially improve passenger terminal availability. Originality/value: This study presents a validated, data-driven model tailored to freshwater passenger terminals, integrating both technical and human dimensions of maintenance management
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