Business Research Help on Impact of COVID-19 on Retailers
1.0 Introduction
Retail sector holds a paramount importance across developing and developed nations as it operates as the gateway to consumers from upstream sectors. The recent outbreak of COVID-19 has dramatically upset the retail sector as consumers drifted towards online shops as opposed to brick-and-mortar shopping (Shahbaz, et al., 2020). The impact of COVID-19 on retail sector depends upon the social distancing measures, ability of businesses to weather the crisis and lockdowns. According to IDC (2020), COVID-19 outbreak is impacting the consumer behavior, product demand and the availability of logistics services across the globe. Amongst all the retailers, fashion, electronics and furniture businesses are most likely to hit hardest as consumers are foregoing discretionary purchases for stocking up on household supplies and food staples. Goldberg (2020) argued that if COVID-10 pandemic continues, the retailers will be forced to remain closed whilst facing the challenges associated with health and safety, labor force, cash flow and supply chain.
The COVID-19 pandemic is accelerating up the transition of consumers to digital commerce. The buyers are required to practice social distancing due to which e-commerce orders for groceries and other household essentials have become a survival tool. According to report by Apptopia (2020), the average daily downloads for the retailers online applications like Instacart, Shipt and Walmart have surged during February 2020. Apart from this digital transition, the post COVID-19 situation is likely to be dominated by germaphobia amongst buyers. According to Goldberg (2020), consumers are likely to become more germs cautious even after COVID-19 subsides in near future. No-touch deliveries and cashless transactions might become the new normal while buffets and salad bars might become less popular (Parimala, 2020). According to Sibel (2020), consumers might become less receptive to the in-store food sampling and resist the public touch keypads. In this instance, the retailers are required more than ever to offer no-touch customer experience with huge emphasis on hygiene (GFK, 2020).
The report by Deloitte (2020) indicated that consumers are forgoing cash in favor of digital and contactless payments since the outbreak of COVID-19. The report also indicated that more than 33% of the respondents of the survey opted for digital payments through debit cards at the supermarkets during COVID-19 pandemic. Moreover, it was also seen that over 50% of respondents reduced use of cash and carried on transactions through smartphones due to COVID-19. However, the study’s results were varying based on generational and gender distribution. Hence, apart from cleanliness, social distancing and online shopping behavior, cashless transactions are also expected to shape up future of retailers after COVID-19 has subsided (Deloitte, 2020).
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Based on the above discussion, this report is carried on for assisting Retailers Association for developing a plan related to offering safe in-store environment for shoppers post COVID-19. The report will be focusing on four factors namely social distancing in-store, self-check-out options, cashless transactions and hand sanitizer availability. The retailers will be able to utilize the results obtained from this research in order to regain the number of in-store visitors after the pandemic subsides in future. The first section of the report will discuss the research design followed by hypothesis, technique and results discussion.
2.0 Research Design
A research design is the set of procedures that are used for collecting and measuring the factors specified in the problem of research (Creswell, 2015). It includes the research methods chosen by researcher for carrying on with the study. The type of the research of this study is survey research that is a form of quantitative research in which the researchers administer a survey to a sample for describing the attitudes, opinions and characteristics of the whole population (Bell, et al., 2018). Under this procedure, the researchers collect the quantitative numbered data using the questionnaires (or interviews) and then statistically analyze the data for describing the trend about responses to each question. The responses are then used for testing the research question or hypothesis formulated by the researchers. This report used an online questionnaire based on 8 questions associated with consumer behavior. The target audience for the survey was 2000 retail store customers randomly drawn from the database of retail stores.
The current study will be using the cross-sectional survey method for collecting the insights from targeted audience during the COVID-19 pandemic. This survey research method is quick and will help the researcher in collecting information in a brief time span. Random sampling method was used for drawing the sample of 2000 customers from retail database. This method ensures that every item in the population has an equal chance of being selected in the sample. Random sampling technique is a fair method that might reduce the biases involved in the sampling. The data collected through this sampling method is well informed that improves the overall quality of the data. The current study drew a sample of 2000 retail customers of which only 527 customers completed the online survey questions. The responses of the customers were tabulated in the excel form and the data was scrutinized using SPSS software.
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3.0 Hypothesis Development
The following hypothesis has been developed for the current study.
Research Question 1:
Is the expected expenditure in the first month after stores reopen different from this past expenditure i.e. $180?
Hypothesis 1:
Ho: The expected expenditure in the first month after stores reopen is equal to $180
Ha: The expected expenditure in the first month after stores reopen is not equal to $180
Research Question 2:
Is there a significant difference in the expected future retail expenditure across demographic categories?
Hypothesis 2a:
H0: The expected future retail expenditure across age groups is similar to each other
Ha: The expected future retail expenditure across age groups is not similar to each other
Hypothesis 2b:
H0: The expected future retail expenditure across genders is similar to each other
Ha: The expected future retail expenditure across genders is not similar to each other
Research Question 3:
Does the migration to online shopping post COVID-19 depend on the demographic factors?
Hypothesis 3a:
H0: The likelihood of making more retail purchases online is similar across age groups
Ha: The likelihood of making more retail purchases online is not similar across age groups
Hypothesis 3b:
H0: The likelihood of making more retail purchases online is similar across genders
Ha: The likelihood of making more retail purchases online is not similar across genders
Research Question 4:
Is there any difference between customer’s satisfaction for plans on in-store social distancing procedures and the availability of hand sanitizer in-store?
Hypothesis 4:
H0: Customer’s satisfaction for plans on in-store social distancing procedures is equal to customer’s satisfaction for plans on in-store availability of hand sanitizer in store.
Ha: Customer’s satisfaction for plans on in-store social distancing procedures is not equal to customer’s satisfaction for plans on in-store availability of hand sanitizer in store.
Research Question 5:
Can a customer’s overall likelihood of shopping in bricks and mortar retail stores after COVID-19 be explained by retail store’s plans with regards to social distancing, cashless transaction, and self-check-out and hand sanitizer availability?
H0: Customer’s likelihood of shopping in bricks and mortar retail stores depend on social distancing, cashless transaction, and self-check-out and hand sanitizers’ availability.
Ha: Customer’s likelihood of shopping in bricks and mortar retail stores does not depend on social distancing, cashless transaction, and self-check-out and hand sanitizers’ availability.
4.0 Statistical Techniques and Justification
The analysis was conducted with the assistance of statistical package for social analysis (SPSS) version 25.0. Descriptive statistics were used to summarize variables in terms of means, standard deviations, frequencies, and percentages. A descriptive statistic is a summary statistic that demonstrates or summarizes characteristics quantitatively from a series of data, whereas descriptive statistics is the procedure to use and analyze those statistics. Means and standard deviations were presented for continuous variables such as expectation of bricks and mortar retail stores to spend in the first month following COVID-19 pandemic and questions related to likelihood of returning to retail (Questions 4-9). In addition, frequencies and percentages were used to summarize variables such as gender and age.
Similarly, statistical inference was used to test the hypotheses formulated for analyzing the relationship between retailers and post-COVID customer behavior. Statistical inference is the procedure to use data analysis for deducing features of an underlying distribution of probability. Inferential statistical analysis deduces characteristics of a population; for instance, by investigating hypotheses as well as deriving estimates.
In this regard, this study has planned to use one sample t-test or independent sample t-test for testing the hypotheses proposed. The purpose of using one sample t-test was to demonstrate whether the sample mean is statistically different from the identified or hypothesized population mean. Each hypothesis makes a statement whether the true population mean is associated to some hypothesized value M. With the help of one sample t-test, all the five hypotheses proposed were tested on a 95% confidence interval and 5% level of significance. The level of significance is a measure of the strength of evidence that must be presented in the sample prior rejecting the null hypothesis. For instance, a 5% risk to conclude that there is a difference when there is no actual difference is represented through a significance level of 0.05.
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