A Longitudinal Study of the Impact of the COVID-19 Pandemic on the Managerial Effectiveness of the "Magnificent Seven" Stocks Firms: An Economic Value-Added Approach.

This longitudinal study investigated the managerial effectiveness of the "Magnificent Seven" stock firms in enhancing Economic Value Added (EVA) before and after the COVID-19 pandemic. Utilizing a within-subject ANOVA analysis on data spanning from 2016 to 2023, this research aimed to explore how managerial decisions within these firms influenced economic profits over time. The study utilized the Stern-Stewart formula for EVA to calculate the average EVA data from 10-K filings of these technology-oriented firms, representing a significant portion of the S&P 500 index, to determine the impact of the COVID-19 pandemic on their financial performance. Results indicated a large significant effect difference in EVA pre- and post-COVID-19 pandemic, with an increase in both the mean value and variability of EVA. The partial eta squared value indicated that the time period accounted for approximately 26.4% of the variance in EVA. This suggested that the COVID-19 pandemic had a significant impact on these firms' EVA, reflecting positively on their managerial decision-making effectiveness in creating economic value. The conclusion highlighted the importance of management efficiency key decisions included leveraging artificial intelligence, maintaining operational agility to mitigate supply chain disruptions, and fostering a culture of innovation in navigating the complexities introduced by the pandemic. It underscored the significant role of external factors such as consumer behavior changes and government policies in influencing company performance. The study recommended exploring how different sectors responded to the pandemic's challenges, particularly those hit hardest by the crisis. This study contributed to the understanding of EVA as a reliable measure of a company's financial health and managerial effectiveness in uncertain times. [ABSTRACT FROM AUTHOR]