The development of Brookline, MA local business in the COVID-19 pandemic
The quantitative understanding of the impact of the COVID-19 pandemic on local business has been studied deeply, both on a national and local level. Our goal is to investigate the qualitative impacts of the COVID-19 pandemic on Brookline business, such as the opinions of employees towards their business, that are hard to quantify and generalize. To do this we conducted a survey of all Brookline businesses asking 17 questions relating to their business and the COVID-19 pandemic. We also incorporated their google ratings and the number of reviews the business received. We received 36 responses and compared them with quantitative statistics from the Brookline government to achieve a more comprehensive understanding of how COVID-19 has shaped Brookline’s local businesses.
Authored by: Diego Luca Gonzalez Gauss, Robert Rogers, Benjamin Vyshedskiy, Matvey Borodin, and Matheus Nascimento
The current literature on the effects of the COVID-19 pandemic on small businesses is extensive. The US Bureau of Labor Statistics found that 14.5 percent of US businesses and 20.5 percent of businesses in the private sector, increased their base wages. 34.5 percent of establishments moved at least part of their workforce to a remote work model, and 60.2 percent of these establishments intend to retain the remote model after the end of the pandemic. 17.5 percent of establishments required vaccination for workers to return to in-person offices. Throughout mid-2020, 52 percent of businesses told employees not to work, of whom only half continued to be paid. In the same time period, 62 percent of businesses received government loans to help pay workers. On average sales dropped 27 percent from pre-pandemic levels until rebounding by January 2021. While 65 percent of businesses adjusted payroll through reduced wages, hours, or leave, only 11 percent of companies had to lay off workers. A full 34 percent of companies increased their use of the internet and social media. [2]
Small business activity greatly diminished during the early pandemic, with active business owners dropping from 15.0 to 11.7 million (22%) over February to April 2020. Losses were exaggerated among populations such as owners working 2 days a week (28%) and 4 days a week (31%); 29 percent fewer hours were worked by business owners. [5]
Covid-19 had a significant effect on the Brookline economy. Prior to the pandemic, Brookline enjoyed a generally low unemployment rate of 1.5 percent in February 2020, compared to 2.8 percent statewide and 3.5 percent nationwide. The peak unemployment rate for Brookline was 8.4 percent in June, compared to 16.4 percent statewide in April. Since then, Brookline’s unemployment rate has remained high but is comparably healthy, with 3.1 percent unemployed in November as opposed to 5.4 percent statewide. The total labor force of Norfolk County, which incorporates Brookline, was 392,848 in February 2020. After shrinking to 353,881 (losing 9.92% of the labor force) in April, the number of laborers rebounded to 391,765 (increasing by 10.7% relative to the pandemic labor force) in November 2021. [3]
For this survey, a total of 283 businesses within the Brookline area were contacted over a time span of three months (from November 16 to February 13). The primary method of contact was email, with 159 businesses being contacted using their email address; the vast majority of businesses without an available email address were contacted through their website’s contact page(s). Businesses that had neither an easily available email nor a contact page were contacted through other forms of media such as Facebook or Twitter; however, none of these responded. Businesses that did not respond to an email or contact were later contacted again in hopes of increasing the number of responses we received from businesses. We received 24 responses after contacting businesses once, a yield of 8.5%; after contacting again we totaled 36 responses, a yield of 13%. To gather an extensive list of businesses local to the Brookline area, we used the Brookline Chamber of Commerce’s business directory, an API to scrape information from Google Maps, and a manual search of remaining Brookline businesses on Google Maps.
Our survey asks 17 questions relating to the impact of the COVID-19 pandemic on their business. These questions holistically ask about employee opinions on the performance and operations of local businesses, the behaviors of customers and employees, and government compensation. We also incorporate additional data such as Google reviews for a deeper understanding of the businesses that we have surveyed. A copy of the survey can be found here.
Beyond what is intrinsic to online surveys, bias is introduced to our survey as not all businesses have an available email address or have set up a contact page and are therefore harder for us to access. These companies tended to be older and in industries that rely less on technology to operate. Businesses that failed during COVID-19 were also typically inaccessible by our survey, introducing a survivor bias. Despite these biases, the results of this survey give a notable insight into how the Brookline economy has performed and adapted during the pandemic. Though the data collected in our survey was roughly linear, it is categorical and inoperable. So, we cannot use methods of statistical analysis that rely on linear regression and other numerical techniques.
When comparing the sample of 36 businesses that responded to our survey and a random sample of 36 Brookline businesses, the businesses that responded have, on average, a higher star rating from Google reviews. The average star rating for businesses surveyed was 4.70 stars unweighted and 4.56 stars when considering the number of reviews each company received. The average star rating for businesses in the random sample was 4.41 stars when unweighted and 4.46 stars when weighted. The standard deviation for the random sample when not weighing for the number of reviews was .65 stars, and the resulting 95% confidence interval had an upper bound of 4.63 stars. We believe that difference between the weighted star averages between the sample surveyed and the random sample is also statistically significant given the difference between the two averages and the sheer number of total reviews (6284 total reviews for the sample surveyed and 6587 total for the random sample). However, without the specific reviews of each company, it is hard to calculate an accurate standard deviation for either sample.
With our sampling methods, the sample surveyed can be split into two groups: businesses that responded the first time they were contacted and those that responded the second time they were contacted. The average unweighted star rating for the first-response group was 4.73 and was 4.62 for the second-response group. Given the sample sizes (24 for first-response and 12 for second-response), there is no statistically significant difference between the averages. Similar to how the sample surveyed and random sample were compared, there is likely to be a statistically significant difference between the weighted star averages. For the first-response group, the weighted star average was 4.58, and for the second-response group, it was 4.49. The sample size for the first-response group was 5054 total reviews and for the second-response group, it was 1230 total reviews. The resulting standard deviation and 95% confidence interval using the second-response group will be relatively small and not cover the average star rating for the first-response group.
These differences suggest that businesses that put in the effort to respond to a survey and especially those that responded promptly were better businesses in the public eye. This observation makes sense intuitively as these businesses likely put high levels of effort into everything they do. So, we can interpret our responses as representing the opinions of higher-rated businesses.
The vast majority of our data saw employees rate aspects of the businesses they work with on a scale of 1 to 5. Of these questions, employees seemed generally optimistic in the performance of their business and the environment that their business cultivated. Many questions saw the majority of answers concentrate towards 3 on the scale, suggesting that employees thought business features such as customer spending were impacted by the COVID-19 pandemic in only limited ways. Businesses particularly agreed that they strongly enforced mask-wearing (mean score 4.69), they increased the use of technology due to the pandemic (mean score 4.31), and that the government was very justified in giving loans to local businesses (mean score 4.56). Businesses also agreed that hiring became significantly harder over the course of the pandemic (mean score 1.86).
When looking at associations between responses from businesses, a few stand out. The strongest association(s) are between how well-staffed a business is and employees’ belief that the government provided sufficient support to local business; between how well a business has performed and how much demand the business has received; between how reliant a business is on technology and the average spending of customers; between the number of reviews of businesses on Google and how much more demand they have when compared to pre-pandemic; and between how much compensation they have had and their support of mask-wearing.
The strong positive relationship between business staffing and employees’ belief that the government provided sufficient support suggests the government has disproportionately large support to Brookline businesses with a large amount of staff, independent of the sales of that business.
We see the two significantly different populations, confirming the association between business performance and demand. Similarly, the relationship between how reliant a business is on technology and the average spending of customers lets us extrapolate that online businesses get larger orders than storefronts. And, the negative relationship between government compensation and support of mask-wearing shows that government payment could potentially mollify otherwise hostile feelings towards government-supported programs.
Compared to the existing body of literature on the impact of the COVID-19 pandemic on local business, we show a more comprehensive view into the health and development of businesses local to the Brookline, MA area. We see performance associate highly with business demand and customer spending, confirming existing literature and conventional thought. But, we also see a high association with demand against customer attitude and against workplace attitude, an inference that would not be possible without inoperable data. As the COVID-19 pandemic progresses and ultimately subsides, inferences beyond purely quantitative data such as these are important to understanding how local business employees feel, think, and relate to the Brookline economic landscape.
Our exploration into the Brookline economy is continued here.
References:
- Bartik, Alexander W., et al. “The Impact of COVID-19 on Small Business Outcomes and Expectations.” Proceedings of the National Academy of Sciences of the United States of America, vol. 117, no. 30, July 2020, pp. 17656–66, https://doi.org/10.1073/pnas.2006991117.
- Belitski, Maksim, et al. “Economic Effects of the COVID-19 Pandemic on Entrepreneurship and Small Businesses.” Small Business Economics, vol. 58, no. 2, 2022, pp. 593–609, https://doi.org/10.1007/s11187-021-00544-y.
- Brookline Small Business Data Tool | Brookline, MA — Official Website. https://www.brooklinema.gov/1596/Small-Business-Data-Tool. Accessed 6 Mar. 2022.
- Fairlie, Robert. “The Impact of COVID‐19 on Small Business Owners: Evidence from the First 3 Months after Widespread Social‐distancing Restrictions.” Journal of Economics & Management Strategy, Aug. 2020, p. 10.1111/jems.12400, https://doi.org/10.1111/jems.12400.
- Results of the Business Response Survey : U.S. Bureau of Labor Statistics. https://www.bls.gov/brs/. Accessed 6 Mar. 2022.
