Abstract
In a free market, the creation of hospitals, schools, sports and public residential facilities, requires the expertise—and possibly the capital—of the private sector. The traditional contract, in which the public administration pays private operators to make or maintain buildings and services, is flanked by public private partnership, in which the private operator is usually delegated to carry out the entire process receiving a fixed fee. For years, governments and administrations have been incentivized to use this kind of contract, assuming that it would increase the building qualities and reduce the risk of higher expenses. Empirical evidence refutes this assumption, and this can be caused by to the so-called moral hazard of the private operator. One of the main problem in public private partnership is the difficulty to define an optimal risk allocation, as there no formulas exist to simulate the performance of the contract in advance. In this paper, Evolutionary Algorithms are used to compute an optimal specifications document, while, at the same time, foreseeing an optimal effort in work. Experimental results clearly demonstrate the feasibility of this approach, also helping the public administration to check if their knowledge is sufficient to structure an efficient specifications document.
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Notes
- 1.
Drafting of this text various process managers of a large Italian administration that regularly uses the PPP were interviewed, and in all cases the matrix was presented as insignificant. In addition, more than 50,000 cases (not necessarily PPPs) present in the Lombardy Region Sintel aggregation center were automatically analyzed, noting that the matrix between the attachments was present in only about fifty cases.
- 2.
The tool manages the risk by associating a sensitivity multiplier and a optimism variance to some preset items (construction/start-up costs, project duration, operating costs excluding labor costs, labor costs, transaction transaction costs, costs for closing the relationship, proceeds for providing the service). The optimism bias is a fixed percentage of worsening of the parameter in question, justified by the fact that the conditions are always too optimistic. The sensitivity multiplier represents the possibility of the costs to fluctuate: each parameter is varied individually with discrete steps, showing the impact on the PSC.
- 3.
An activity is any action performed by the OP, with any level of detail. Ex: the design of the building, construction of walls, maintenance of the electrical system, pruning of green areas ...
- 4.
The ideal KPI function is the linear application of the identity matrix for the effort, which provides the administration with the real cash flow of the operator for each activity and for each period in order to guarantee a work of art realization. Note that the total flow of the operator for a certain task is influenced not only by the need to develop a work of art, but also by any externalities or exogenous factors discussed below. The KPI does not monitor how much the operator spends, but how much the operator spends in order for the work to be good. An increase in flows to face an unexpected event or to calm the results of a previous saving are not measured by the KPI.
- 5.
The externality functions must be modeled or customized by domain experts, and improve system predictions the more accurate they are.
- 6.
Example: if the operator has to buy goods for 100 euros but waits a year, he will pay around 102 euros (with an inflation rate of 2%).
- 7.
Example, if the operator in year 1 has a liability of €100 (which he asks the bank) and in year 2 an asset of €100 (which he pays to the bank), the total flow will not be zero. Assuming a \(ts_n\) = 5%, the discounted flow will be about −5 (that is, the bank demands another 5 euros).
- 8.
Remember that the externality is positive when the coefficient between effort costs and externality is positive: consequently a positive externality causes damage compared to a reduction costs.
- 9.
- 10.
Italian authority for supporting the drafting of PPPs.
- 11.
Affine periods are the periods that share the same raw psc, the same exogenous factors and the same externalities, according to the intuitive logic that under the same conditions, OP and PA will do the same actions. This compression is lossy, the model allows for partial or total compression as the user needs.
- 12.
Exogenous factor is reporting, according to Martiniello, as a percentage of same raw psc value (i.e. J1, J2...). In this way we don’t need other actualization or discounting.
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Pellegrino, S., Rebuglio, M., Squillero, G. (2022). Public-Private Partnership: Evolutionary Algorithms as a Solution to Information Asymmetry. In: Jiménez Laredo, J.L., Hidalgo, J.I., Babaagba, K.O. (eds) Applications of Evolutionary Computation. EvoApplications 2022. Lecture Notes in Computer Science, vol 13224. Springer, Cham. https://doi.org/10.1007/978-3-031-02462-7_8
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