A System Dynamics Model for Studying the Resiliency of Supply Chains and Informing Mitigation Policies for Responding to Disruptions

Economic shocks are unanticipated events that have widespread impact on an economy and can lead to supply chain disruptions that propagate from one region to another. The COVID-19 pandemic is a recent example. Simulations have been applied to study the impact of COVID-19 shocks on supply chains at the macro level using various approaches. This research has developed a hybrid System Dynamics and Input/Output simulation to model the economic impact of various types of supply chain disruptions. The hybrid model provides results that match historical performance of the U.S. economy under COVID-19 shocks and provides reasonable results when applied to investigate U.S. dependence on foreign trade. Its graphical nature also supports a decision support tool that will allow policymakers to explore the costs and benefits of various policy decisions designed to mitigate the impact of a broad set of potential supply chain disruptions. © 2022 IEEE.

The crisis of US neoliberalism and the risk of current economic stagflation

Purpose>Since the outbreak of COVID-19, tremendous changes have taken place in the US economy – the economic growth in the whole year of 2020 was negative, and though it enjoyed a significant rebound for the first half of 2021, the growth rate began to decline rapidly by the third quarter, and inflation suddenly rises rapidly, which after came the all-time highs of the “misery index” consisted of the inflation rate and unemployment rate. All signs indicate that the US economy will likely enter a “stagflation” crisis.Design/methodology/approach>This paper analyzes the institutional and social contradictions in the United States during the neoliberal era from the perspectives of domestic social structure of accumulation (SSA) and international SSA based on the SSA theory.Findings>The current risk of stagflation in the US economy is a concentrated outbreak of the long-term accumulated contradictions in neoliberal SSA under the impact of the epidemic, which is the product of the irreconcilable contradictions inherent in the capitalist mode of production.Originality/value>Based on this analysis, the paper points out that with the deepening of the crisis, the neoliberal SSA is likely to end and a new SSA will be established gradually.

Intelligent Analysis Impact of the COVID-19 Pandemic on Juvenile Drug Use and Proliferation

This paper examines the state of drug use and sales during a lockdown caused by a pandemic COVID-19. The focus group is juveniles in the United States, as there has been a sharp change in drug mortality for this group in the United States during quarantine. The change in the death rate from drugs among minors has been identified. The impact of drug prohibition and legalization in the US economy on the level of drug use has been studied. Data on drug use and distribution by juveniles were analyzed using descriptive statistics, data visualization, smoothing (Kendall, Pollard, median, exponential), data correlation, and cluster analysis. The results show that for minors aged 12-16, quarantine conditions have benefited by reducing the trend of drug use, not only after quarantine but also in later life, and confirm the hypothesis of a positive effect of lockdown on drug use reduction among minors in the United States. Recommendations are proposed to increase the attention of the state and its implementation of additional control measures, including conducting political and educational measures among adolescents to prevent drug use and reduce the popularity of drug use for each succeeding generation. It will positively benefit young people as drug prevention, and it will help reduce drug mortality in the United States. © 2022 Copyright for this paper by its authors.

The Consumer Deviation Index: A Method for Identifying Changing Behaviors and Market Opportunities

The increasing availability of behavioral data about consumers offers great promise for understanding their shifting preferences over time. This poses an important challenge for business practitioners - particularly entrepreneurs and investors - who wish to be the first to identify and satisfy consumers' unmet needs. Here, we introduce the Consumer Deviation Index (CDI) as a means of generating forecasts from historical time series data in order to isolate emerging behaviors that fall outside the realm of expectation. These deviations serve as leading indicators of market opportunities to fulfill pockets of "latent demand"before they fully manifest across a consumer population. We illustrate the application of this methodology to behavior change during the height of COVID-19 stay-at-home restrictions, and to the initial reopening of the U.S. economy post-pandemic. We discuss implications for optimizing product development and innovation to better serve consumers' ever-changing needs. © 2022 ACM.

Using machine learning techniques to study economic trends in various U.S. industries in the post-epidemic era

The aim of the project is to predict and analyse broad trends across the US economy using stock data from mainstream companies in six industries on Forbes 2000 and data from COVID-19. A time series analysis approach was used to predict the daily increases in each company's share price. The following five supervised learning techniques (logistic regression, random forest, decision tree, neural network and XGBoost) were used. As the accuracy of the results predicted by the different models for each company varies considerably, only the results predicted by the most accurate model for each company have been selected for analysed. The results show that the Electronic Pleased Technology Industry and the Social Entertainment Internet Industry remain break-even for COVID-19;the E-Commerce Industry shows a significant increase;The Financial Services Industry shows a significant drop in share price, while the Insurance Industry and Pharmaceutical Industry show a small drop in share price. © COPYRIGHT SPIE. Downloading of the is permitted for personal use only.

Forecasting Recessions in the US Economy Using Machine Learning Methods

A quantitative analysis of socio-economic characteristics, the set of which is typical in the pre-crisis periods of a market economy, is carried out. An indicator for forecasting the onset of a recession in the US economy over the next 6, 12 and 24 months has been constructed using machine learning methods (k-nearest neighbors, support vector machine, fully connected neural network, LSTM neural network, etc.). Using roll forward cross-validation, it is shown that the smallest error in predicting the onset of future recessions was obtained by a fully connected neural network. It is also shown that all three constructed indicators successfully predict the onset of each of the last six recessions that occurred in the United States from 1976 to 2021 (Early 1980s recession, Recession of 1981-82, Early 1990s recession,.COM bubble recession, Great Recession, COVID-19 recession). The resulting indicators can be used to assess future economic activity in the United States using current macroeconomic indicators. © 2021 IEEE

Analysis of the Impact of COVID-19 on the U.S. Economy Based on Big Data Processing and Experimental Analyses

With the outbreak of COVID-19, the world has experienced unprecedented crises especially in economy. The United States is more seriously affected. In order to more clearly show the current situation of the U.S. economy affected by the epidemic from the data level, the author completes the paper by using the research method of big data processing and experimental analyses to show that how Coronavirus influences economy, that is, the impact on GDP and the exchange of volume of stock shares and the impact on unemployment rate which can be shown in specific data. The author also discusses the degree of influence on different industries. The result shows that COVID-19 has seriously affected the overall economy of America. The specific data performance is the decline of GDP (about 5%) and the rise of unemployment (about 15%). The stock price has dropped significantly, even affecting the overall stock trading volume (declined by 55%). The purpose of this paper is to clearly show the specific influence on the US economy from the data level. The result can provide a specific data reference for the formulation of American economic policy in the next few years and provide a data basis for the study of the economic situation after the epidemic in the United States. © 2021 IEEE.