Pandemic Risk Management in Operations and Finance: Modeling the Impact of COVID-19 (Computational Risk Management) - Tapa dura

Libro 10 de 10: Computational Risk Management

Wu, Desheng Dash; Olson, David L.

 
9783030521967: Pandemic Risk Management in Operations and Finance: Modeling the Impact of COVID-19 (Computational Risk Management)
Tapa dura
ISBN 10: 3030521966 ISBN 13: 9783030521967
Editorial: Springer, 2020

Sinopsis

COVID-19 has spread around the world, causing tremendous structural change, and severely affecting global supply chains and financial operations. As such there is a need for analytic tools help deal with the impact of the pandemic on the world's economies; these tools are not panaceas and certainly won't cure the problems faced, but they offer a means to aid governments, firms, and individuals in coping with specific problems.
 
This book provides an overview of the COVID-19 pandemic and evaluates its effect on financial and supply chain operations. It then discusses epidemic modeling, presenting sources of quantitative and text data, and describing how models are used to illustrate the pandemic impact on supply chains, macroeconomic performance on financial operations. It highlights the specific experiences of the banking system, which offers predictions of the impact on the Swedish banking sector. Further, it examines models related to pandemic planning, such as evaluation of financial contagion, debt risk analysis, and health system efficiency performance, and addresses specific models of pandemic parameters.
 
The book demonstrates various tools using available data on the ongoing COVID-19 pandemic. While it includes some citations, it focuses on describing the methods and explaining how they work, rather than on theory. The data sets and software presented were all selected on the basis of their widespread availability to any reader with computer links.

"Sinopsis" puede pertenecer a otra edición de este libro.

Acerca del autor

Desheng Wu is a Special-term Professor at University of Chinese Academy of Sciences, Beijing, China, and a Professor at Stockholm University, Sweden. He has published over 150 ISI-indexed papers in refereed journals, such as Production and Operations Management, Decision Sciences, Risk Analysis, and IEEE Transactions on Systems, Man, and Cybernetics, as well as 7 books with publishers like Springer. He is an elected member of Academia Europaea (The Academy of Europe), the European Academy of Sciences and Arts, and the International Eurasian Academy of Sciences. He has served as an associate editor and a guest editor for several journals, such as Risk Analysis, IEEE Transactions on Systems, Man, and Cybernetics, the Annals of Operations Research, Computers and Operations Research, the International Journal of Production Economics, and Omega. He is the editor of Springer’s book series on computational risk management.

 

David L. Olson is the James & H.K. Stuart Professor andChancellor’s Professor at the University of Nebraska, USA.  He has published research in over 200 refereed journal articles and has authored over 40 books, including Decision Aids for Selection Problems, Introduction to Information Systems Project Management, Managerial Issues of Enterprise Resource Planning Systems, Supply Chain Risk Management, and Supply Chain Information Technology.  He has served as associate editor of Service Business, Decision Support Systems, and Decision Sciences and co-editor in chief of International Journal of Services Sciences. He is a member of the Decision Sciences Institute, the Institute for Operations Research and Management Sciences, and the Multiple Criteria Decision Making Society.  He was a Lowry Mays endowed Professor at Texas A&M University from 1999 to 2001.  He has named the Raymond E. Miles Distinguished Scholar award for 2002 and was a James C. and Rhonda Seacrest Fellow from 2005 to 2006.  He was named Best Enterprise Information Systems Educator by IFIP in 2006.  He is a Fellow of the Decision Sciences Institute.

De la contraportada

COVID-19 has spread around the world, causing tremendous structural change, and severely affecting global supply chains and financial operations. As such there is a need for analytic tools help deal with the impact of the pandemic on the world’s economies; these tools are not panaceas and certainly won’t cure the problems faced, but they offer a means to aid governments, firms, and individuals in coping with specific problems.
 
This book provides an overview of the COVID-19 pandemic and evaluates its effect on financial and supply chain operations. It then discusses epidemic modeling, presenting sources of quantitative and text data, and describing how models are used to illustrate the pandemic impact on supply chains, macroeconomic performance on financial operations. It highlights the specific experiences of the banking system, which offers predictions of the impact on the Swedish banking sector. Further, it examines models related to pandemic planning, such as evaluation of financial contagion, debt risk analysis, and health system efficiency performance, and addresses specific models of pandemic parameters.
 
The book demonstrates various tools using available data on the ongoing COVID-19 pandemic. While it includes some citations, it focuses on describing the methods and explaining how they work, rather than on theory. The data sets and software presented were all selected on the basis of their widespread availability to any reader with computer links.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Springer
Año de publicación
2020
Idioma
Inglés
ISBN 10 
3030521966
ISBN 13 
9783030521967
Encuadernación
Tapa dura
Número de edición
1
Número de páginas
156
Contacto del fabricante
no disponible
Persona responsable
CMN Printpool Inh. Mathis Neumann
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Hamburg
Alemania

Otras ediciones populares con el mismo título

9783030521981: Pandemic Risk Management in Operations and Finance: Modeling the Impact of COVID-19

Edición Destacada

ISBN 10:  3030521982 ISBN 13:  9783030521981
Editorial: Springer, 2020
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