Improving decision-making in maintenance policies and contract specifications for infrastructure projects. Issue 8 (3rd August 2019)

• Record Type: Journal Article
• Authors: Lozano, Jorge-Mario; Sánchez-Silva, Mauricio
• Is Part Of: Structure and infrastructure engineering. Volume 15:Issue 8(2019)
• Page Start: 1087
• Page End: 1102
• Publication Date: 2019-08-03
• Subjects: Infrastructure systems -- flexibility -- public-private partnership -- decision-making -- system dynamics -- agent-based modeling -- infrastructure contract; Structural analysis (Engineering) -- Periodicals; Structural engineering -- Periodicals; Buildings -- Performance -- Periodicals; 620.005
• DOI: 10.1080/15732479.2019.1581818
• Languages: English
• ISSNs: 1573-2479

Abstract

Abstract: In large infrastructure projects, the government frequently delegates the execution and management to a private through Public–Private Partnerships (PPP) type contract. However, both parties often have conflicting interests; i.e. while the private wants to maximise the profit, the government aims at maintaining a high-performance level. This paper presents a model to define a set of contract parameters that maximise the utility of both entities in the long term, and at the same time optimise the system performance. Moreover, it proposes a strategy for the private to decide the optimal maintenance frequencies and achieve its target revenue. It also describes the complex interactions between the public, the private and nature (i.e. all environmental aspects that influence the system's performance). The model combines the advantages game theory, simulation, optimisation and agent-based modeling. A set of 72 types of Build-Operate-Transfer (BOT) contracts are simulated, with a sensitivity analysis on the main contract variables (i.e. minimum level of performance required, mean frequency of government inspections, and penalty fee in case of noncompliance). The results show the importance of flexibility in decisions when facing different sources of uncertainty, and in reducing information asymmetry between the parties to improve maintenance decisions.