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Fan, Y., Himanshu, S.K., Ale, S., DeLaune, P.B., Zhang, T., Park, S.C., et al. (2022) The Synergy between Water Conservation and Economic Profitability of Adopting Alternative Irrigation Systems for Cotton Production in the Texas High Plains. Agricultural Water Management, 262, Article ID: 107386.
https://doi.org/10.1016/j.agwat.2021.107386

has been cited by the following article:

• TITLE: Animal Feed Business Risk Assessment Quantification COVID-19 and Supply Chains Disruptions Losses

  AUTHORS: Kheiry Hassan M. Ishag

  KEYWORDS: Project Operation Efficiency, Dynamic Simulation Model, COVID-19, Supply Chain Disruption, Stochastic Efficiency with Respect to Function (SERF), Certainly Equivalent (CE), Risk Premiums (RP), Value at Risk (VaR)

  JOURNAL NAME: Journal of Mathematical Finance, Vol.14 No.3, August 14, 2024

  ABSTRACT: The animal feed business is facing the risk of raw material grain shortage due to global supply chain disruption during the COVID-19 pandemic, the Russia and Ukraine conflict and recently global shipping disruption at the Red Sea. These situations cause high increases in raw material prices and animal feed cost of production. The feed mills business plant demand uncertainty and material shortage reduced plants’ production capacity to 36% - 46%. The bounce back in animal feed consumer demand leads to more stress on supply chains and business sustainability. This study identifies and quantifies business risk due to low sale revenue and test subsidy program proposed for rebuilding plant capacity affected and caused by supply chain disruption. The study applied stochastic budgeting simulation method to evaluate risk and uncertain factors and calculate NPV probability distribution under different feed mill plant capacities generated by supply chain disruption pressures. Different feed mill plant capacities calculated and ranked across various risk aversion levels. The potential loss of COVID-19 and supply chain disruption of animal feed business and food security sustainability and the need to return the supply chain system to normal situation has not been quantified in a robust manner. Therefore, the stochastic budgeting simulation model performed to incorporate risk variables and draw NPV probability distributions to quantify COVID-19 and supply chain disruption effect on feed mill business under various risk preferences. The Government raw materials incentive strategies were evaluated for different coronavirus levels and ranked across absolute risk aversion coefficient levels. The study shows that raw material subsidy for feed mill business plants will reduce the expected loss probability due to COVID-19 and supply chain disruption challenges and increase NPV return above RO 2.00 million by 71%. The SERF analysis calculated certainty equivalent (CE) and risk premiums (RP) value to payoff for COVID-19 and supply chain disruption.