Narrow Results

The aim of this research is to examine how the daily growth in COVID-19 confirmed cases and deaths in 15 African nations affects stock market returns, employing both time series and panel methods. This study uses robust ordinary least squares (ROLS) and dynamic ordinary least squares (DOLS) for time series. It uses Pooled OLS, Fixed Effects, Feasible Generalized Least Squares, Two-Stage Least Squares (2SLS), and panel vector autoregressive (PVAR) with respect to panel data. These methodologies help in addressing some econometric issues regarding the relationship between COVID-19 confirmed cases, deaths and stock returns in the panel of 15 African nations, which enhances our research and findings. The effects of confirmed COVID-19 cases and deaths on stock returns are not uniform among countries, according to the results of a time series analysis. Precisely, the rise of COVID-19 confirmed cases has had a detrimental impact on stock returns in nations including Botswana, Cote d’Ivoire, Morocco, Uganda, and Zambia. Similarly, COVID-19 confirmed deaths have a detrimental impact on the stock returns of nations like Botswana, Morocco, and Zambia. Even though COVID-19 confirmed cases have a negative impact on stock returns in the 15 African countries that make up the panel study, this effect is not statistically significant except when FGLS is applied. In a similar vein, stock returns in African nations are not significantly impacted by COVID-19 confirmed deaths. The results of FEVD support these findings. According to IRF findings, stock returns respond unfavorably to the shock of COVID-19 confirmed cases. The negative, nevertheless, quickly subsided as stock returns bounced back to positive returns until eventually reaching equilibrium. The stock returns, on the other hand, initially respond favorably to the shock of the COVID-19 confirmed deaths, then take a negative turn before returning to normal returns. Our study emphasizes the significance of examining each country’s socioeconomic response to the COVID-19 epidemic rather than grouping countries together.

This chapter addresses the key issues impacting the adoption of information technology (IT) in healthcare organizations. Four case studies were developed from different hospitals through a series of in-depth interviews to determine the factors affecting their IT adoption. The findings reveal that, at the organization level, these hospitals primarily make decisions to adopt new technologies based on project-related costs. At the individual level, the complications in the implementation process play a major role as they are influenced by human-related issues. Apart from the identification of key factors from the case studies, the latter part of this chapter also presents the mental framework of IT adoption for healthcare organizations developed based on the technology acceptance model.