Titlebook: Enterprise Risk Management Models; Focus on Sustainabil David L. Olson,Desheng Wu Textbook 2023Latest edition Springer-Verlag GmbH Germany,

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Value at Risk Models,Financial risk management has been analyzed using the value at risk methodology. The method is described, evolving from variance-covariance analysis. Monte Carlo simulation is applied to demonstrate calculations with Crystal Ball software.

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Chance-Constrained Models,Linear programming is a traditional means of optimizing many supply chain decisions. However, linear programming assumes linear relationships, yielding extreme solutions that become risky. Chance constraints are a way to incorporate variance-covariance measures into such optimi9zation models, which this chapter describes and demonstrates.

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Data Mining Models and Enterprise Risk Management,Data mining is the application of statistical and artificial intelligence models to decisions and is used in a wide variety of fields. This chapter describes the Rattle open-source software for data mining, applied to a financial risk management decision. Classification models are demonstrated.

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Balanced Scorecards to Measure Enterprise Risk Performance,Balanced scorecards are tools to monitor the relative performance of organizational units over multiple dimensions. Traditionally, the four dimensions of learning and growth, internal business processes, customer satisfaction, and financial performance have been used. The concept is demonstrated with multiple business contexts.

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Machine Learning and Artificial Intelligence Risk,The development of artificial intelligence is reviewed. It includes a variety of computer-driven methods. Those applying to risk management data mining applications are reviewed, to include a number of classification models. The expected impact of AI/machine learning on future human activity is discussed.

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Enterprise Risk Management in Projects,Project management is a major activity in many domains. They involve many risks due to their being one-time events. Risk management tools are presented and demonstrated.

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Natural Disaster Risk Management,Nature is a complex system with many powerful physical events caus8ing disruption of human activities. Emergency management systems are described and modeling options demonstrated.

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Sustainability and Enterprise Risk Management,In addition to natural disasters, there is a systemic continuous challenge to natural environments from developments such as global warming, and from epidemic health risks such as COVID-19. The United Nations view of sustainable development goals is described. Data mining and multi-criteria modeling of sustainability goals are presented.

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Environmental Damage and Risk Assessment,Methods to assess and evaluate environmental damage are presented, to include cost-benefit analysis, contingent evaluation, conjoint analysis, and habitat equivalency analysis. Methods are demonstrated with risk management contexts.