Solar energy investment represents currently a valid reason to support sustainable economic development. In fact, over the last few years, governments have applied different measures to incentivize private consumers and firms to use renewable energies. Photovoltaic (PV) projects are characterized by uncertainty due to meteorological conditions, the unpredictable behavior of government, and managerial flexibility. Since the Net Present Value (NPV) approach is not able to capture these uncertain factors, it was replaced with the Real Options Approach (ROA). The latter method manages to embed flexibility in PV investment using binomial trees. This paper valuates PV investment in all regional areas in Italy using an integrated approach between the discounted cash flows method and real option value, called Expanded Net Present Value (ENPV). We fit the probability of tax benefits into a binomial lattice model after analyzing the geographical position and weather conditions of all regional capitals of Italy. The results show that the cities with high irradiance/temperature have positive NPV and high investment values. On the other hand, while most cities have negative NPV, the inclusion of the flexibility in investment decisions gives additional value to the project, making the ENPV positive and implying an attractive investment opportunity with the possibility of delaying the project. We also propose a sensitivity analysis that shows how the real option value changes when incentive policies of the government become more attractive. This paper contributes to the existing literature in the way of considering financial, meteorological/geographical, and political factors to valuate PV investment.

The need to obtain financial funds to pursue public utility investments implies the generation of Public-Private Partnership (PPP) projects. The PPP framework can involve risk-sharing mechanisms between public administration and private sector to encourage private investors to fund these projects. However, these risk-sharing mechanisms, such as Minimum Revenue Guarantee or Revenue Cap (RC), could generate opportunistic behaviors. For this reason, we can set this problem as a game in which government and private investors would act as players. This paper proposes a mathematical model to evaluate the PPP projects through a combination of Game Theory (GT) and Real Options Approach (ROA). The ROA is needed to price the uncertainty that affects PPP investments, and the GT captures the strategic interactions between public and private sectors. A case study on a wastewater treatment project is developed to apply the model we proposed.

In most cases, the valuation of the investments characterized by various stages with a high level of uncertainty is done through the compound real option valuation (ROV). This decision making support can consider various types of uncertainty that can affects these investment phases, such as that linked to technology. Specifically, within the category of uncertain investments there are the broadband opportunities that can be valued as real options in order to quantify the risks associated with the investment. However, since ROV theory has no definitive way to determine model parameters based on market information, we propose one that can adjust them dynamically. In this paper, to include this aspect in the project valuation, we have unified the ROV with the sentiment analysis, a natural language processing technique that allows us to quantify the polarity of expressions in natural language numerically. In particular, the inherent risks related to the different phases of the project can be extracted from the information present in the surrounding environment and published in newspapers. From there, we obtain a sentiment score which, through appropriate manipulations, manages to modify the evaluation of the success probabilities of each stage. Then, we embed these success probabilities in the ROV in order to provide a valuation methodology that includes the impact of information on the investment decision.