The influence of risk on the equity share of build-operate-transfer projects

Marco, Alberto De; Mangano, Giulio; Narbaev, Timur

doi:10.1108/bepam-02-2016-0003

Cited by 16 publications

(13 citation statements)

References 45 publications

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“…The capital structure is designed to satisfy both the investor’s expected return on investment and the lender’s cover ratios (Marco et al , 2017). There are few studies conducted to determine the optimal capital structure in BOT contracts quantitatively.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Iyer and Sagheer (2012) presented a genetic algorithm model to extract a set of optimal solutions for the key decision variables including grant, debt and equity in Indian BOT highway projects. Marco et al (2017) represented a regression analysis model to address the relationship between risk factors and capital structure in BOT projects. Chen and Liou (2017) introduced optimal capital structure on the basis of cooperative bargaining game model between project company and loan providers.…”

Section: Literature Reviewmentioning

confidence: 99%

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Financial conflict resolution model in BOT contracts using bargaining game theory

Bayat

Khanzadi

Nasirzadeh

et al. 2019

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Purpose This study aims to determine the optimal value of concession period length in combination with capital structure in build–operate–transfer (BOT) contracts, based on direct negotiation procurement and considering the conflicting financial interests of different parties involved in the project. Design/methodology/approach The financial model of a BOT project is developed considering all the influencing factors. Then, fuzzy set theory is used to take into account the existing risks and uncertainties. Bilateral bargaining game based on alternating-offers protocol is applied between the government and the sponsor to divide project financial benefit considering the lender’s requirements. Finally, concession period and equity level will be determined simultaneously according to the sponsor’s and government’s share of project financial benefit and the lender’s requirements. Findings The proposed model is implemented on a real case study, and a fair and efficient agreement on concession period length and capital structure is achieved between the government and the sponsor considering the lender’s requirements. It is revealed that being the first proposer in the bargaining process will affect the concession period length; however, it will not affect the equity level. Moreover, it is shown that considering income tax as a part of government’s financial benefit increases the length of concession period. Research limitations/implications The presented model concentrates on direct negotiation procurement in BOT projects where the sponsor and government bargain on dividing financial benefits of project. It is assumed that the product/service price is determined before according to market analysis or users’ affordability. All the revenue of project during concession period is assumed to belong to the sponsor. Practical implications The proposed model provides a practical tool to aid BOT participants to reach a fair and efficient agreement on concession period and capital structure. This could prevent failing or prolonging the negotiation and costly renegotiation. Originality/value By investigation of previous studies, it is revealed that none of them can determine the optimal value of concession period length and capital structure simultaneously considering the BOT negotiation process and different financial interests of parties involved in the project. The proposed model presents a new approach to determine the financial variables considering the conflicting interests of involved parties. The other novelty aspects of the presented model are as follows: introducing a new approach for calculating the sponsor and the government’s share of project financial benefit that will affect the determination of the concession period length and considering the effect of existing risks and uncertainties on final agreement between the involved parties using fuzzy set theory.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Financial conflict resolution model in BOT contracts using bargaining game theory

Bayat

Khanzadi

Nasirzadeh

et al. 2019

View full text Add to dashboard Cite

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“…Therefore, the success of PF is based, on the one hand, on an increasing demand for infrastructures (De Marco et al , 2012a) and, on the other hand, on public financial and budgetary constraints. Furthermore, a successful PF initiative is based on the consideration of all risks that a project faces during its life cycle (De Marco et al , 2017) together with a proper allocation among the parts involved in the project (Carbonara et al , 2015; Li et al , 2005). Unexpected changes related to project costs, debt servicing, dividend payments, construction delays, cash flow generated by the project can bring to heavy deficits (Nikolìc et al , 2011).…”

Section: Literature Reviewmentioning

confidence: 99%

“…This revenue risk is here measured via the gross domestic product (GDP) growth rate to represent either positive or negative commercial spending environments. A high level of GDP growth rate stands for a less risky environment (De Marco et al , 2017) in the sense that positive GDP rates are associated with increased demands of energy that reduces the risk associated with the market demand for a power plant project (Sekhara Rao et al , 2015). The higher are the expected revenues the more willing are the lending institutions to inject debt in a project.…”

Section: Risk Modelmentioning

confidence: 99%

Risk factors influencing the debt leverage of project financing initiatives in the energy industry

Marco

Mangano

2017

IJESM

Self Cite

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Risk factors influencing the debt leverage of Project Financing initiatives in the energy industry Purpose-This paper contributes to understanding the crucial influence of risks on the capital structure of Project Financing (PF) initiatives in the energy sector. Design/methodology/approach-The debt leverage of a capital investment is selected as the response variable and its relation with select identified risk factors is examined using a regression analysis on a dataset of 72 projects carried out all over the world in the energy industry. Findings-Results have highlighted that the debt leverage is significantly influenced by several sources of risk. Country, Project, and Special Purpose Vehicle related risks have been shown to have an impact on the debt leverage of a PF scheme. Research limitations/ Implications-The results could support both investors and lenders to better define the financial leverage of projects delivered under a PF mechanism. In particular, the study could help to have a better understanding of the main factors that influence the debt leverage in PF initiatives. Originality/value-This paper contributes to filling the lack of works addressing the relationship between risk factors and capital structure in PF projects. In this way, this research leads to a better understanding of the risk factors that influence the capital structure of a PF initiative and they have therefore been proposed as a basis for the establishment of improved methods to design refined capital structures.

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“…So far, although many advantages have been expected to be achieved from the BOT mode application towards the solar PV power project, which include bringing in needed capital, improving the project operation efficiency, and promoting the technical progress, there exist multiple factors that influence the success of a BOT power project. For example, project feasibility, which includes the acceptability of end users [9,10], expected profitability of project [11,12], and the level of complexity for technologies that are adopted in the project [8]; policy environment, which includes the legislations of project [13], stability of political environment [14], and government incentives [15]; and also the project developers' business capacity, including both the government and private investors [16]. Hence, appropriate arrangements of BOT contracts play a strategic role in the development of solar PV power projects under BOT mode.…”

Section: Introductionmentioning

confidence: 99%

The Determination of Concession Period for Build-Operate-Transfer Solar Photovoltaic Power Project under Policy Incentives: A Case Study of China

Chen

2019

Energies

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Since the concession period is one of the most crucial variables influencing the success of a photovoltaic (PV) power project under build-operate-transfer (BOT) mode, this paper presents a real option game model—which integrates the real option and cooperative game theory—to determine the optimal concession period of the BOT solar PV power project under policy incentives by considering the value of the option to defer. In the proposed model, an effective interval of concession period for the BOT project was identified by using a real option, and the equilibrium value of the concession period was obtained by applying classical optimization theory. To evaluate our model, we empirically determined the optimal concession period for the BOT solar PV power project in China, and a sensitivity analysis was conducted to demonstrate how relevant influential factors, which are presented in the model, affect the equilibrium value of the concession period and its effective interval. The results indicate that the current investment environment in China could successfully implement the BOT solar PV power project under policy incentives, including initial cost subsidy and the feed-in tariffs mechanism. While the high volatility of electricity demand, investment cost, and land-use rent fee can lead the failure of the BOT solar PV project implementation, promoting the technological development of PV power generation, maintaining the market stability, and increasing the policy incentives can help the BOT power project to be arranged with an optimal concession period. In addition, the feed-in tariffs mechanism is more helpful than the initial cost subsidy for winning the BOT contract.

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The influence of risk on the equity share of build-operate-transfer projects

Abstract: A royalty negotiation model for BOT (build-500 operate-transfer) projects: The operational revenue-based model" Mathematical and 501

Cited by 16 publications

References 45 publications

Financial conflict resolution model in BOT contracts using bargaining game theory

Financial conflict resolution model in BOT contracts using bargaining game theory

Risk factors influencing the debt leverage of project financing initiatives in the energy industry

The Determination of Concession Period for Build-Operate-Transfer Solar Photovoltaic Power Project under Policy Incentives: A Case Study of China

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