Risk and Predictive Analytics in Business with R

Supply chain operations face many risks, including political, environmental, and economic. This book presents data mining and analytics tools with R programming as well as a brief presentation of Monte Carlo simulation that can be used to anticipate and manage these risks.

Autorentext

Özgür M. Araz is the Ronald and Carol Cope Professor and Professor of Supply Chain Management and Analytics at the University of Nebraska-Lincoln. His research interests are systems simulation, business analytics, healthcare operations, and public health informatics.

David L. Olson is the James and H.K. Stuart Chancellor's Distinguished Chair in the Department of Supply Chain Management and Analytics at the University of Nebraska-Lincoln. His research interests are data mining, knowledge management, multiple criteria decision-making, and simulation modeling.

Inhalt

1. Measuring and Managing Risk. 2. R Programming Language and RStudio. 3. Risk Measures in Finance and Insurance. 4. Association Rule Modeling in Supply Chains. 5. Simulating Supply Chain Risks. 6. Regression. 7. Classification Tools. 8. Fraud Detection. 9. Mixed Data.