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2020 | Book | 1. edition

Pandemic Risk Management in Operations and Finance

Modeling the Impact of COVID-19

Authors: Desheng Dash Wu, David L. Olson

Publisher: Springer International Publishing

Book Series : Computational Risk Management

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About this book

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.

Table of Contents

Frontmatter
Chapter 1. Introduction
Abstract
This book presents a variety of operations research modeling initiatives related to pandemic planning. This chapter briefly reviews the progress of Coronavirus disease 2019 (COVID-19) and outlines the content of the remainder of the book. COVID-19 has shut down a large part of the global economy for months since early 2020, causing health ramifications including over 100,000 deaths globally. The tools presented in this book offer a means to prepare or cope with pandemics.
Desheng Dash Wu, David L. Olson
Chapter 2. Comparison with Past Pandemics
Abstract
This chapter reviews three recent pandemics—SARS, MERS, and Ebola, with the intent of seeing the scope of the health impact of these pandemics and the control mechanisms applied. COVID-19 is different in major ways—much more contagious, with health effects less impactful for most of the population. There is no comparison in impact, but coping with pandemics includes some commonality. Some basic pandemic statistics are reviewed.
Desheng Dash Wu, David L. Olson
Chapter 3. System Dynamics Modeling of Contagion Effects
Abstract
Financial contagion has been with us as long as there has been an economy. The system of collective human behavior usually creates stable markets, but occasionally, this collective behavior results in various bubbles. Financial contagion specifically deals with the domino effect of one banking institution failure, which, due to interrelationships with other banks, leads to further failures. A decision support model of accounts receivable risk management is presented. Financial contagion and bubbles are discussed. The year 1929 was a very bad year, but 2008 had its moments as well. These financial contagions result in undermining confidence in similar institutions. Our research question is to examine the role of accounts receivable payments that are affected by the social interaction of those holding loans from a lending institution. System dynamics modeling is used to demonstrate the impact of word-of-mouth social contacts on accounts receivable and the ensuing increase in financial risk. This was proposed as a decision support tool for a common banking risk-management problem: Accounts Receivable risk management.
Desheng Dash Wu, David L. Olson
Chapter 4. Text Mining Support to Pandemic Planning
Abstract
Text mining is a useful tool to identify sentiment. Not only it is widely used in stock market operations but it can also be applied to analyze Web content or other documents related to pandemic operations. A support vector machine is a data mining algorithm useful for certain types of data. This chapter demonstrates the use of a Web crawler to identify financial sentiment, a process that would also work for pandemic management. A support vector model is applied to a Chinese stock market index, demonstrating that technology also could be extended to pandemic planning and control.
Desheng Dash Wu, David L. Olson
Chapter 5. Macroeconomic Impact
Abstract
Pandemics create strain on economies, due to the need to provide medical resources as well as the need to control the population to halt disease spread. COVID-19 created an extremely severe strain on economies throughout the world due to its high degree of contagion and governmental response advocated by the World Health Organization stressing lockdowns. The governmental financial response has been extreme. This chapter reviews macroeconomic policy options to combat pandemics.
Desheng Dash Wu, David L. Olson
Chapter 6. Supply Chain Impact
Abstract
Network analysis was applied using Citespace software applied to downloaded data of Web-of-Science Publications. Search terms “SARS & Risk”, “MERS & Risk,” and “Ebola & Risk” were used. For each experiment, the network analysis used both abstract and article clustering. Tools such as risk, clinical, and healthcare are common hot spot words that were employed. Research topics focused on health care, disease, influenza, and infection. Research on economy and epidemics is not in the core of the network analysis results, identifying a need for research effort.
Desheng Dash Wu, David L. Olson
Chapter 7. Debt Risk Analysis Using Two-Tier Networks
Abstract
COVID-19 has dealt a major blow to the global economy. It would help the efforts to cope with this strain by having studies of how risk affects operations. This chapter deals with risk in the financial arena, which has been heavily hit by COVID-19. But the analysis can aid in other arenas as well, to include health-care planning and management. This study found that expansion of regional guarantee circle networks need to be controlled, as external guarantees are important to control risk contagion. Identification of key nodes in risk-contagion networks need to consider exposure and external relevance. The government should concentrate on group investment and financing platforms. And supervision of disorderly external guarantees of small- and medium-sized issuers is needed.
Desheng Dash Wu, David L. Olson
Chapter 8. The Effect of COVID-19 on the Banking Sector
Abstract
The COVID-19 pandemic has had a massive impact on the global economy. The impact COVID-19 has had on the Chinese banking sector consists of three aspects: short-term, long-term, and systemic risks. Support for differentiated financial services for pandemic prevention and control is needed, with increased credit support. Medium-to-small enterprises need to be supported through special credit lines, reduced interest rates on loans, deferred repayments, and establishment of long-term credit systems. Digital transformation needs to take place at a faster rate to improve intelligent risk control systems.
Desheng Dash Wu, David L. Olson
Chapter 9. Assessment of Smart Healthcare Services
Abstract
This chapter considers organizational adoption of smart healthcare services. Pandemic planning would benefit from accessing some of the many technology systems available to aid in operations and planning. A technical acceptance model is adopted as a means to consider factors important in the adoption of technology. Chinese doctors were surveyed to gain attitudes and perceptions of usefulness of healthcare technology. Perceived usefulness and experience were found to be important in intention to adopt healthcare systems.
Desheng Dash Wu, David L. Olson
Chapter 10. Healthcare Efficiency Modeling
Abstract
Pandemic planning depends a great deal on hospital capacity. COVID-19 created great strain on hospital bed resources in Wuhan, Milan, New York City, and elsewhere. Hospitals today need to provide basic services to satisfy community demands, and at the same time offer specialization, to enhance their competitiveness. From a management perspective, measuring and ranking the hospital’s efficiency appropriately is complex because their funding is affected by many factors. This chapter presents a DEA model to assess capacity to accept new patients considering resource costs.
Desheng Dash Wu, David L. Olson
Chapter 11. Recapitulation
Abstract
This chapter reviews the coverage of the book, sorting out the models presented and the potential they have relative to pandemic response planning. We began the book discussing the initial view of the impact of COVID-19. It has been much less deadly than the black plague but has contagion properties reminiscent of that dreaded disease. It has created dramatic problems for government health systems and has severely cramped economic performance. As Chap. 1 noted, what is needed are analytic tools to aid in dealing with the pandemic impact on our economies. These analytic tools are not panaceas and certainly won’t cure the problems we face. But they offer tools that might be useful in aiding governments, firms, and individuals to cope with the problems created by pandemics.
Desheng Dash Wu, David L. Olson
Metadata
Title
Pandemic Risk Management in Operations and Finance
Authors
Desheng Dash Wu
David L. Olson
Copyright Year
2020
Publisher
Springer International Publishing
Electronic ISBN
978-3-030-52197-4
Print ISBN
978-3-030-52196-7
DOI
https://doi.org/10.1007/978-3-030-52197-4

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