Stochastic modelling of maintenance flexibility in Value for Money assessment of PPP road projects

Abstract

Maintenance flexibility has been promoted as a value driver for long-term public–private partnerships (PPPs). However, the value and risk associated with this value driver have not been properly quantified in the Value for Money (VfM) assessment literature. To bridge the gap, a novel stochastic modelling methodology is proposed to characterize the complex interactions among the lifecycle cost (LCC), performance deterioration and maintenance strategies. Four different maintenance strategies are designed to emulate the practice in the traditional and PPP delivery methods. The LCC includes the direct maintenance cost, user cost, residual value, and payment deduction, the last three often being neglected in VfM assessments. Simulation-based optimization and dynamic programming analysis are used to determine the probability distributions of the LCC and the VfM. A hypothetical highway PPP project under an availability payment model is selected as a case study. The results show that maintenance flexibility is indeed able to reduce the LCC for the private party. However, this private efficiency, if not properly regulated, could cause a reduced asset residual value and an increased user cost, making the public party worse off. In addition, for all potential maintenance strategies, the public sector is found to retain significant lifecycle cost risk, largely in the form of user cost.