Public Private Partnership (PPP) is adopted throughout the world for delivering public infrastructure. Despite the worldwide experience has shown that PPP can provide a variety of benefits to the government, to fully gain them several critical aspects related to a PPP project need to be managed, among these the determination of the concession period. This paper provides a methodology to calculate the concession period as the best instant of time that creates a 'win win' solution for both the concessionaire and the government and allows for a fair risk sharing between the two parties. In other words, the concession period is able to satisfy the private and the government by guaranteeing for both parties a minimum profit, and, at the same time, to fairly allocate risks between parties. In order to take into account the uncertainty that affects the PPP projects, the Monte Carlo simulation was used. To demonstrate the applicability of the proposed model, a Build Operate Transfer (BOT) port project in Italy has been used as case study. (C) 2014 Elsevier Ltd. APM and IPMA. All rights reserved

Public-private partnerships (PPPs) are adopted throughout the world for delivering public infrastructure. Despite the attractiveness of the PPP structure, its implementation has not been without trouble due to multiple uncertainties embedded with PPP projects. Private investors often require some mitigation of these risks through government support. One of the most common forms of government support is minimum revenue guarantee (MRG). A real option-based model is developed that uses a new mechanism for setting the revenue guarantee level secured by the government, which balances the private sector's profitability needs and the public sector's fiscal management interests and uses the concept of fairness for structuring MRGs. The model uses Monte Carlo simulation to take into account the uncertainty. The model is applied to the projected 1 kilometre long 'Camionale di Bari' toll road that will link the port of Bari (located in Puglia, Southern Italy) with the existing road network without affecting the urban traffic. It was found that government support is often needed to make the project attractive to private investors and that the developed model can be, for both public and private sectors, a valid tool for defining the fair value of the minimum amount of revenue secured by the government

The paper addresses the topic of supplier selection in public procurement. According to European directives, when tenders are awarded through the ‘‘Most Economically Advantageous Tender’’ (MEAT) criterion, the awarding committee has to decide the tender evaluation criteria of the presented bids in advance. The authors propose a decision making tool that is aimed at helping the awarding committee in this difficult task and, at the same time, maintaining a transparent procedure in accordance with governmental procurement regulations and requirements as well as guaranteeing fair and equal evaluation of all bids. In this regard, the decision problem of supplier selection is addressed by applying an extension of the DEA (data envelopment analysis) methodology. The cross-efficiency evaluation is used for selecting the best supplier among the eligible candidates. The proposed technique allows the evaluation of quantitative data related to vendor selection and keeps the transparency features requested by public procurement. In addition, all bids are equally assessed according to the same objectively defined weights without any subjective setting by the public officers. The effectiveness and efficiency of the approach is supported by a case study that pertains to the tender of an Italian public agency.

The paper addresses the optimal design of the last supply chain branch, i.e., the Distribution Network (DN), starting from manufacturers till the retailers. It considers a distributed system composed of different stages connected by material links labeled with suitable performance indices. A hierarchical procedure employing direct graph (digraph) modeling, mixed integer linear programming, and the Analytic Hierarchy Process (AHP) is presented to select the optimal DN configuration. More in detail, a first-level DN optimization problem taking into account the definition and evaluation of the distribution chain performance provides a set of Pareto optimal solutions defined by digraph modeling. A second level DN optimization using the AHP method selects, on the basis of further criteria, the DN configuration from the Pareto face alternatives. To show the method effectiveness, the optimization model is applied to a case study describing an Italian regional healthcare drug DN. The problem solution by the proposed design method allows improving the DN flexibility and performance.