Enterprise Risk Management Process

Olson, David L.; Wu, Desheng

doi:10.1007/978-3-642-11474-8_2

Cited by 6 publications

(9 citation statements)

References 0 publications

(9 reference statements)

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“…In addition to all aforementioned approaches, the Chance Constrained Programming is also an alternative modeling method, which in turn combines a mathematical programming model with chance constraints in the form of probability levels of attainment. 22 A typical mathematical programming model often follows the following structure:…”

Section: Industrial and Engineering Chemistry Researchmentioning

confidence: 99%

“…Chance constrained models can be utilized in many applications. 22 The objective function f(x) can be a profit function that needs to be maximized. It consists of n variables x and includes the profit contribution rate constants.…”

Section: Industrial and Engineering Chemistry Researchmentioning

confidence: 99%

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Capturing the Effects of Oil Price Uncertainty in Carbon Integration Network Design

Malaeb

Tarhini

Alnouri

2019

Ind. Eng. Chem. Res.

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Carbon integration is a novel concept that targets the recovery and allocation of industrially emitted CO 2 streams into CO 2 -using sinks, with the goal of attaining a CO 2 allocation strategy that meets a desired carbon dioxide emission reduction target and an ultimate aim of minimizing the cost of the network while maximizing any revenue. Enhanced oil recovery (EOR) is considered one of the most attractive CO 2 sink options. CO 2 streams that are delivered and injected into EOR sites are great revenue sources for CO 2 -supplying entities. Since oil pricing heavily affects the revenue generated via CO 2 streams injected into EOR sites, this paper studies the effect of oil price fluctuations onto the design of carbon integration networks. Hence, oil pricing has been selected as the main uncertainty parameter and has been fed into a linearized multiperiod carbon integration model using stochastic data. Since oil prices vary periodically, this model has been formulated over several time periods, in which the oil pricing parameters are allowed to change over time. The proposed model has been optimized using two different approaches: (1) the binomial lattice approach, which primarily utilizes average uncertainties as expected values, and (2) the multiscenario approach.

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“…During emergencies, a variety of organizations are often involved, which incurs the necessity of system thinking. At the governmental level, one would expect cooperation in attaining a common goal, but often many diverse agencies get involved dimming attention to overriding shared goals (Olson and Wu, 2008).…”

Section: Introductionmentioning

confidence: 99%

Simulation Decision System on the Preparation of Emergency Resources Using System Dynamics

Liu

Olson

2014

Syst. Res

Self Cite

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This paper establishes a simulation decision system for both emergency resource preparation and emergency resource replenishment. The decision system uses both system dynamics and goal programming. A system dynamics model is then developed and validated with real case data as simulation decision support to emergency resource replenishment. An optimization simulation using the data from the emergency resource preparation process in the Ya'an earthquake in China is reported.

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“…(7) Time and risk preferences are combined in the expected discounted utility model. 3 While uncertain intertemporal choices or temporal risk evaluations are often observed in practice, the research toward time and probability tradeoff is limited. Rotter (8) first found the similarity between risky choice and temporal choice and argued that individuals encode temporal effect in a probabilistic manner.…”

Section: Introductionmentioning

confidence: 99%

General Probability-Time Tradeoff and Intertemporal Risk-Value Model

She¹,

Ma²,

Wu³

2010

Risk Analysis

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This article proposes an intertemporal risk-value (IRV) model that integrates probability-time tradeoff, time-value tradeoff, and risk-value tradeoff into one unified framework. We obtain a general probability-time tradeoff, which yields a formal representation form to reflect the psychological distance of a decisionmaker in evaluating a temporal lottery. This intuition of probability-time tradeoff is supported by robust empirical findings as well as by psychological theory. Through an explicit formalization of probability-time tradeoff, an IRV model taking into account three fundamental dimensions, namely, value, probability, and time, is established. The object of evaluation in our framework is a complex lottery. We also give some insights into the structure of the IRV model using a wildcatter problem.

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Enterprise Risk Management Process

Cited by 6 publications

References 0 publications

Capturing the Effects of Oil Price Uncertainty in Carbon Integration Network Design

Simulation Decision System on the Preparation of Emergency Resources Using System Dynamics

General Probability-Time Tradeoff and Intertemporal Risk-Value Model

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