Introduction
The use of past data is a standard part of any calculations for future business prospects, as it shows a pattern of human behavior and business progression. Nevertheless, the COVID-19 pandemic, which started affecting the United States industries in 2019 and continues to affect the national and global markets, has significantly changed people’s ability to predict the future of economic stability (Shawman, 2023). Thus, the change brought on by the pandemic has to be acknowledged when planning business expansion. In the case of Big D Incorporated, one should also pay specific attention to the impact of the coronavirus on the retail sector and how the trends in purchases were affected by the changes in customer behavior.
The Influence of the COVID-19 on the Retail Industry
First, one must consider the massive impact the pandemic has had on unemployment, income disruption, and recovery plans. Unemployment became one of the major issues during the pandemic due to several factors. First, a large part of the population was affected by the virus, leading to a large number of deaths and severe damage to people’s health, depleting the workforce (Barnes et al., 2021).
Second, the new social distancing policies led to business closures, leaving many people without jobs for prolonged periods of time (Barnes et al., 2021). As the businesses were not getting customers, the inability to pay workers also led to layoffs (Barnes et al., 2021). The recovery plans of different states depended on their financial abilities and the focus on specific services and industries.
After the main waves of the pandemic passed, the businesses started to open again, hiring new employees and solving the problem of unemployment. As a result, Ettlinger (2021) estimates that approximately 80% of the job losses were recovered, with some states performing better than others.
For example, while such states as Texas have recovered more than 90% of the jobs, other locations such as Hawaii and Wyoming were able to reopen only 30 to 40% of the positions (Ettlinger, 2021). This difference in rates may relate to the industries in the states – Texas likely has more opportunities to focus on highly demanded markets, including manufacturing and retail. In contrast, less affluent states rely on incoming visitors or industries with low demand during the pandemic. Thus, expanding one’s business should heavily depend on the state and its prognoses for further improvement.
The pandemic affected the retail sector significantly, as the customers’ needs have shifted due to the new lifestyle. Staying at home, buyers focused on essential categories such as foodstuffs and home goods while avoiding unnecessary purchases. Outdoor sporting goods are a category that lost a part of its demand during the pandemic. Still, its rise is predicted to increase as a consequence of people regaining the ability to travel and go outside (Barnes et al., 2021). Therefore, the business has an opportunity to contribute to job restoration and expand into other locations.
Conclusion
Discussing the effects of the pandemic, such variables as the number of total jobs in the sector and the ratio of employment to the population can be used to determine whether particular states are presenting an opportunity for expansion. According to Ettlinger (2021), the regression analysis of the jobs regained shows a great increase in the retail segment, signifying an almost complete return to pre-pandemic times. Similarly, job growth appears to be positive, demonstrating optimistic trends (Statistics How To, n.d.).
Thus, Big D Incorporated can expand into other states and use the remaining gap in job growth to hire new talent. The business may also utilize the stabilizing income of potential consumers and their increasing interest in outdoor sports goods.
References
Barnes, M., Bauer, L., & Edelberg, W. (2021). 11 facts on the economic recovery from the COVID-19 pandemic. Brookings. Web.
Ettlinger, M. (2021). COVID-19 economic crisis: By state. University of New Hampshire. Web.
Shawman, W. (2023). Trends in employment and hours worked. Bureau of Labor Statistics: Monthly Labor Review. Web.
Statistics How To. (n.d.). Regression analysis: Step by step articles, videos, simple definitions. Web.