Sustainability and risk

Meins, Erika; Sager, Daniel

doi:10.1108/jerer-05-2014-0019

Cited by 3 publications

(3 citation statements)

References 11 publications

(8 reference statements)

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“…A primary objective of the analysis was to elucidate the financial risks of SAF production, thereby providing insight into potential mitigation strategies should they be deemed necessary. The framework was designed to allow many simulations with random variables simulating market risks to be sampled efficiently and formatted as input to the refinery model (Meins and Sager, 2015). Resulting NPV distributions would then offer insights into the expected economic performance (weighted 4) The jet debottlenecking strategy was implemented via constraints and the PIMS model was reoptimized for each of the same 31 individual cases to have alternative cash flows extracted.…”

Section: Methodsmentioning

confidence: 99%

Economic impact and risk analysis of integrating sustainable aviation fuels into refineries

Carlson,

Talmadge,

Singh

et al. 2023

Front. Energy Res.

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The growth of the aviation industry coupled with its dependence on energy dense, liquid fuels has brought sustainable aviation fuel (SAF) research to the forefront of the biofuels community. Petroleum refineries will need to decide how to satisfy the projected increase in jet fuel demand with either capital investments to debottleneck current operations or by integrating bio-blendstocks. This work seeks to compare jet production strategies on a risk-adjusted, economic performance basis using Monte-Carlo simulation and refinery optimization models. Additionally, incentive structures aiming to de-risk initial SAF production from the refiner’s perspective are explored. Results show that market sensitive incentives can reduce the financial risks associated with producing SAFs and deliver marginal abatement costs ranging between 136-182 $/Ton-CO2e.

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Section: Methodsmentioning

confidence: 99%

Economic impact and risk analysis of integrating sustainable aviation fuels into refineries

Carlson,

Talmadge,

Singh

et al. 2023

Front. Energy Res.

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“…Other authors in the industry of real estate apply the risk analysis for evaluating portfolios as (Amédée-Manesme et al 2013). Also, analysis on sustainability and risk in Swiss residential buildings has been developed by Meins and Sager (2015).…”

Section: Literature Reviewmentioning

confidence: 99%

Customer Concentration Versus Fragmentation and Its Implications in Corporate Risk

Hurtado¹,

Business²

2018

EJBM

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This research explores on one side, the composition and structure of databases of clients in a total of 204 multi-sectorial companies based in Spain, Thailand and Indonesia. The criterion used to differentiate a customer´s database structure relates to its degree of "fragmentation" versus "concentration". Also, the research has determined a risk model using a statistical Monte Carlo simulation method in each company. Both, risk levels expressed as certainty to obtain levels of profits and type of customer´s database structure have been analyzed under an Anova test and multiple correlation analysis exploring a total data of N=1020. Results are quite relevant with a conclusion that the volatility of sales affects significantly the changes in the values of certainty of profits, (although not directly to the levels of risk or certainty) related to the achievement of certain results in profits. Consequently, managers should be aware of the importance of a robust quantitative and qualitative accurate sales forecasting method which will contribute with no doubt to decrease corporate risk being extremely helpful when presenting plans or forecasts in front of any kind of stakeholders.

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“…In [24], the authors investigated the relationship between banks' capital ratios and riskiness through extensive Monte Carlo experiments. In the paper [25], the Monte Carlo simulation method was used to identify the relative contribution of sustainability criteria to property value risk. Monte Carlo simulation is used in decision-making in combination with other methods as well.…”

Section: Introductionmentioning

confidence: 99%

Selection of Optimal Investment Variant Based on Monte Carlo Simulations

Janeková¹,

Fabianová²,

Kádárová³

2021

Int. j. simul. model.

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This paper presents a methodology for the selection of an optimal investment variant using Monte Carlo simulation and OptQuest optimization. The decision-making process also includes risk analysis. Investment variants involve renewal and development of production equipment. Two approaches to investment decision making are introduced. The first approach is based on the analysis of the distribution function of Net Present Value (NPV), and the rule of mean value and coefficient of variation is used as the decision criterion for determining the profitability of investment variants. The second approach, based on the cumulative probability distribution of NPV, provides a comparative assessment of the investment variants using stochastic dominance rules. Both approaches lead to the choice of the same investment variant. In order to increase the profitability of the selected investment variant and reduce its risk, OptQuest optimization is subsequently implemented. The introduced approaches can be a useful support tool in investment decision-making.

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Sustainability and risk

Cited by 3 publications

References 11 publications

Economic impact and risk analysis of integrating sustainable aviation fuels into refineries

Economic impact and risk analysis of integrating sustainable aviation fuels into refineries

Customer Concentration Versus Fragmentation and Its Implications in Corporate Risk

Selection of Optimal Investment Variant Based on Monte Carlo Simulations

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