Public private partnership contracts tend to have longer contract durations compared to other conventional procurement methods. A contract renegotiation becomes inevitable in most of the cases. The renegotiation process usually develops a number of scenarios in order to regain the contract equilibrium. The purpose of this paper is to facilitate the renegotiation process by offering an automated system to select the optimum renegotiation scenario that preserves the rights and the interests of the project stakeholders.
The common renegotiation scenarios used are: increasing the service charges, increasing the concession period or paying a lump sum amount to the party of concern in order to maintain a fixed rate of return and keep the return on equity constant. In this paper, a method of selecting the optimum scenario among the different scenarios is proposed. This is done using a weighted sum model to calculate the weights and ranks of a number of factors influencing the stakeholders’ decisions. A DSS is developed with the aid of Microsoft Excel, VBA programming language, and the Precision Tree 5.5 for Excel add-in.
The renegotiation process has been facilitated by using an automated system that maximizes the benefits of both the public sector and the private sector. The optimum renegotiation scenario has been selected for the case of the model.
The developed framework is of great benefit to project stakeholders, including the private sector, the public sector and the users of the service. It saves time and money invested in lengthy negotiations, and it enforces transparency and mutual trust between the different parties by providing a tool that significantly minimizes conflicts during the renegotiation process and defines clear steps to be followed in order to reach an agreement that will maximize the benefits for both the private and the public sectors.
Shalaby, A. and Hassanein, A. (2019), "A decision support system (DSS) for facilitating the scenario selection process of the renegotiation of PPP contracts", Engineering, Construction and Architectural Management, Vol. 26 No. 6, pp. 1004-1023. https://doi.org/10.1108/ECAM-01-2018-0010
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