No abstract

Solar energy generated by grid-connected photovoltaic (GCPV) systems is considered an important alternative electric energy source because of its clean energy production system, easy installation, and low operating and maintenance costs. This has led to it becoming more popular compared with other resources. However, finding optimal sites for the construction of solar farms is a complex task with many factors to be taken into account (environmental, social, legal and political, technical-economic, etc.), which classic site selection models do not address efficiently. There are few studies on the criteria that should be used when identifying sites for solar energy installations (large grid-connected photovoltaic systems which have more than 100 kWp of installed capacity). It is therefore essential to change the way site selection processes are approached and to seek new methodologies for location analysis. A geographic information system (GIS) is a tool which can provide an effective solution to this problem. Here, we combine legal, political, and environmental criteria, which include solar radiation intensity, local physical terrain, environment, and climate, as well as location criteria such as the distance from roads and the nearest power substations. Additionally, we use GIS data (time series of solar radiation, digital elevation models (DEM), land cover, and temperature) as further input parameters. Each individual site is assessed using a unique and cohesive approach to select the most appropriate locations for solar farm development in the Valencian Community, a Spanish region in the east of Spain.

The estimation of the discount rate is decisive for a reliable economic valuation. The discount rate has to be adjusted for the risks related to the company, the sector which the company has its market, and the risks related to the investment project. We present a proposal to incorporate the risk premium to the discount rate. The novelty of the methodology is that difference risk groups according to activity as a factor to adjust the cost of capital to companies. The study applies the methodology to the Agro-Industrial Complex (AIC) in Spain. The AIC is formed by industries that add value to farming production. This sector's economic success demands financial management techniques that assess risk. The conventional method responds neither to the heterogeneity of the economic activities that make up the AIC, nor to differentiating risk by groups. The proposed methodology distinguishes activity groups in accordance with the NACE (National Code of Economic Activities) and uses net profitability variability to distinguish the risk in each group. Our results demonstrate the various levels of risk per group. The results show that among all the groups that form the AIC there are wide differences between levels of risk; thus, the risk neutral groups present risk levels on the order of 150 times lower than the groups extreme risk levels.Additional key words: discount rate; cash flow discount; capital asset pricing model agro-industry.

The widespread use of renewable energy sources and the growing concern about climate change, together with Spain’s exceptional weather and solar radiation conditions, have led to an increase in the use of photovoltaics for energy production in the country. Solar power generation has been tightly regulated, although the legal framework has changed frequently over the years. When assessing the potential financial performance of any business venture, legal as well as financial aspects must be considered, but a critical factor is the discount rate used, which must reflect the company’s capital cost. Other factors are the period of interest, the firm’s activity, market risk, and the level of debt of firms in the sector. The main objective of this study is thus to estimate the discount rate for companies using photovoltaics to produce solar power. We calculate it by employing two financial techniques: capital asset pricing model and historical return analysis. We then evaluate the investment in a photovoltaic plant with a capacity of 5000 kW located in eastern Spain, assuming it started its activity in different years which coincide with changes in the regulatory framework. The results show the relevance of the initial outlay costs for the profitability of photovoltaic power plants.

This study aims to highlight the usefulness of studying the performance of supply chains (SC) at the sectoral level in greater detail through the combination of a disaggregated supply chain operations reference (SCOR) model, with a multicriteria decision-making approach, specifically using an AHP, to adjust the analysis to the particularities of the sector under study by stakeholders’ judgements. The methodology was applied to the Ecuadorian flower industry, and the data for the analysis was from a survey of a group of companies that represent this sector. In addition, a focus group of SC experts weighted the model constructs as part of the analytic hierarchy process (AHP), and then the performance level for each construct was determined. According to the results methodologies, this model allows the classification of companies by their performance, as well as the performance of the aggregate sector. The processes that Ecuadorian flower companies need to improve on are planning, procurement, and manufacturing. The study’s main contribution is developing a general framework for measuring the overall performance of SCs and how the results are obtained. This tool could help managers, consultants, industries, and governments to assess the performance of SCs, as well as improving SC management in order to increase the sector’s competitiveness in the international market.