Impact of Covid-19 on Online Shopping: Rise and Changing Trends

This report analyzes the impact of Covid-19 on online shopping trends and changing behavior of customers. It compares data of online shopping before, during and after Covid-19 to measure the difference. The report also discusses the rise of e-commerce and its impact on offline stores. It includes descriptive statistical measures and association by using statistical inference techniques.

Management: Putting Theory into Practice
INTRODUCTION
Online shopping is a process by which customers buy goods and services directly from seller over the internet. As with increased technology, rate of online shopping has
increased to the great extent. The reason behind increment in online shopping include: easy access to digital media platforms, time and cost saving. Covid-19 was the main changing
factor that affected companies to the great extent (Rita, Oliveira and Farisa, 2019). On the basis of secondary data, it is found that after covid-19, people started shopping online rather
purchasing products offline.
The reason behind it was because of fear of getting affected from corona virus. People was not allowed to gather at one place so, as per this, online shopping rate increased. The
reason behind selecting this topic is knowing changing environment and impact of technology on E-commerce companies. This study is going to compare data of online shopping
before, during and after covid-19 in order to know changing behavior of people and impact of technologies. It will also help out in knowing rise of E-commerce. On the basis of results
and outcomes, we can help offline stores in going online along with reasons. It can increase employment opportunities and economic condition as well. It is one of my interesting topics
and it is another reason of selecting this topic. It will increase knowledge regarding online shopping, new current trends and others.
This report will gather secondary data because of easy access. Collecting secondary data is better than collection of primary data as it saves time and cost as well. There are some
online sites where data has been published about online shopping and it would be easier to compare and knowing whether there is a rise or decline in online shopping (Tzeng and et.al.,
2021). It would help out in accomplishing goal. Further, it will measure overall performance by statistical method such as mean, mode and median. It will further discuss rise in online
activities by children during and after covid-19.
Association by using statistical inference techniques
While this both play the important through which the growth and development
for the organization and countries that could be take place. Education system
that have been also changes due to having the huge technology and becoming
more high digitally online through which many of the students are using many
more other platforms (Deo, 2020). Therefore, online shopping rate with 1.3500
this could be mean and std, deviation about how year that could led them with
having the .48936 data. According to the above data, this could be showing
more about the descriptive statistics data for online shopping through which
they can clear many more concepts and usually make sure about how this
could deal with them and keeping the high growth for their organization. On
the basis of above data, it can be said that online shopping trend is related with
gender, age and educational factors. Male bachelor customers of 25 age are
more likely to focus on online shopping. This data shows reasons and
interrelation of online shopping with other factors.
DATA INTERPRETATION
Rise of online shopping before, during and after Covid-19 in the UK
Online shopping trend is increasing day by day and year by year. One of the main reason behind it
is: easier accessibility. There are some data that also show changes in online shopping. By
comparing rate of online shopping before, during and after covid-19, we can measure difference.
Some data on which basis, it can be measured as whether there is rise in online shopping after
convid-19 or not.
On the basis of above data, it can be said that there is rise in online shopping in retail sector,
departmental stores, food stores household and other stores. Only non-store retailing was the sector
where there was no growth or rise in online shopping after covid-19 (Ali, 2020). Household goods
stores was the sector where there was great rise in online shopping and decline in offline shopping.
It is the sector that provides all essential or basic needs of items to people and after covid-19, people
became afraid to go outside. so, they started buying products online. So, on the basis of this data, it
can clearly be said that there is growth in online shopping.
Food stores was the one that have seen the largest increase in online sales at the time of Covid-19.
At the time of Covid-19 and in the month of July and August when people were allowed to buy food
online, sales of food stores in online shopping was nearly doubled as compared to data before
Covid-19 (Dalgleish,2020. How the Covid 19 Pandemic has Accelerated the Shift to Online
Spending.). Along with this large supermarket also shown a huge surge in click and collect and
delivery orders. Employees took risk at the time of Covid-19 by delivering products to customers.
But it was the only source of income for them. 3 months of strict lockdown affected people as they
lost their jobs so, they were bind to do such jobs. It changed behaviour of customers of buying
products online. So, after covid-19, online shopping rate is increasing because it has made easier for
people to get products at their home door. Overall, it can be said that covid-19 as well as advanced
technologies has changed behaviour of customers and it has increased online shopping trends
(Naeem, 2021).
REFERENCES
Ali, B., 2020. Impact of COVID-19 on consumer buying behavior toward online shopping in Iraq. Ali, BJ (2020). Impact of COVID-19 on consumer buying behavior toward online
shopping in Iraq. Economic Studies Journal, 18(42), pp.267-280.
Deo, B., 2020. Assessing Optimal Employee Density & Shrink at Retail Chain Level. In IIE Annual Conference. Proceedings (pp. 586-591). Institute of Industrial and Systems
Engineers (IISE).
Flynn, D. and et.al., 2020. COVID-19 pandemic in the United Kingdom. Health Policy and Technology. 9(4). pp.673-691.
Descriptive statistical measures
In 2019, this could be seems that United Kingdom have keep their growth
with internet sales nearly represented by 20% of retail sales. The most figures
that can recent figures about the office national statistics (UK), the country
with having e-commerce in 2019, about the 693 million GDP. The office for
national statistics shows about the august data in 2021, online sales
department that have been increased and declined by 14.3%, online food
selling that have been increased which have been showed no changes to the
same month as previous years (Oxford Analytica, 2020).
Figure 1: Average value of sales of 2019 and 2020
Interpretation of data
While this could be states about how the people have changes their mind in shopping and prefer
to online shopping, in having such kind of data this could represent about the shopping online and
this could raise due to having covid-19. This have been also seems that before covid-19, no raise
in data of the online shopping and this could led many of the business for working with many
efforts for keeping their customer as long term (Flynn and et.al., 2020). Along with this have been
seems that many of the customer have become online shopping king and they are purchasing huge
amount of products and services. While this could also led them for knowing about how the how
the rates of online shopping percent that have been increasing day-by-day within year. E-
commerce have also taken the huge place through which the people have selected the online
payment mode and this could be more easier for them.
Conclusion
From the above report it had been concluded that, online shopping rate that have been increased
due to having the covid-19 and this could also help the business for working with many things.
Along with this also discussed about the derivation and correlation for which the concepts about
how this could work for them and make their business for working with business economy growth
and developments.

Association by using statistical inference techniques
There are number of factors that shows relationship with online shopping such as:
Descriptive Statistics
Mean Std. Deviation N
Gender 1.4000 .50262 20
Age 2.4000 .99472 20
Education 2.4000 1.04630 20
onlineshopping 1.3500 .48936 20
Correlations
Control Variables Gender Age Education
onlineshopping
Gender
Correlation 1.000 -.047 .308
Significance (2-tailed) . .847 .199
df 0 17 17
Age
Correlation -.047 1.000 -.096
Significance (2-tailed) .847 . .695
df 17 0 17
Education
Correlation .308 -.096 1.000
Significance (2-tailed) .199 .695 .
df 17 17 0
Descriptive statistical measures
Likewise, household goods stores about remained stables with having some high increasing and make
sure about their 0.3 percent growth in that month. This have been also seems that, more than half of
the UK consumer are now shopping online and spend more forecast to increasing by 29.6% between
2019 and 2024, as per retail analysts at global data. The online shopping that have been increased due
to which the rate for the store have been also increased and that could also create huge amount of
discount for them. Along with this, network looks at the growth for the online shopping at UK using
some more high hosting of industry insights and data. The online shopping that have become so fast

within the market size (calculated as means with 25%) at least once per month (Hall and et.al., 2020).
The majority about 59% of these shoppers bought more about cloths items and keeping 47% from their
online websites. At 2019, the digital buyers that could penetration rate worldwide with 47.3% and this
could not create mush huge difference for shopping online which could make their retailing business.
In near future, small retailers that could keep about may be 30% higher rate than mobile conversion
rates rather than compared to keeping larger retailers. Shopping online, that have been increased their
sales and keeping them organization for working with their 30% rate for their customer. Along with this
also come to know about how basically, the concepts for the e-commerce sales account for 14.1% of
retail purchases worldwide. Since, online shopping that have been grown up with optimized for user
experience and something is so easiest for inconvenient return policy deters with having 80% of people
(Shahmohammadi and et.al., 2020). Moreover, including more about products and services 88% of the
customer think about detailed page products and make sure about how usually this could work for
them. This could be also seems that, 67 percent of the customer generally, prefer window shopping for
fun and sometime that could keep their shopping while by buying some products and services.
Therefore, 2020 data unsurprisingly saw clothing and fashion that could become the part with e-
commerce industry and household shopping with e-learning arrangements for worldwide share with
some online shopping data. This could be also seems that, in 2020, 99.31 sales in billion that could take
place through online shopping in UK. In 2019, 76.04 sales in billion which seems to be high than 2018
(69.71%) data.
CONCLUSION
This have been also seemed that office for national statistics which could help for knowing about the
percent for developing and how this could help them for knowing about many new things for their
countries and business or organization. In having such things this keep the estimation about many
concepts and make sure about how usually the growth and development for the objective and goals
about their organization at online shopping.
REFERENCES
Books and journals
Hall, S. and et.al., 2020. Prioritising business model innovation: What needs to change in the United
Kingdom energy system to grow low carbon entrepreneurship?. Energy Research & Social
Science. 60. p.101317.
Naeem, M., 2021. Do social media platforms develop consumer panic buying during the fear of Covid-19
pandemic. Journal of Retailing and Consumer Services, 58, p.102226.
Oxford Analytica, 2020. Retail sales will be key to global GDP recovery. Emerald Expert Briefings, (oxan-
es).
Rita, P., Oliveira, T. and Farisa, A., 2019. The impact of e-service quality and customer satisfaction on
customer behavior in online shopping. Heliyon. 5(10). p.e02690.

Shahmohammadi, S. and et.al., 2020. Comparative greenhouse gas footprinting of online versus
traditional shopping for fast-moving consumer goods: A stochastic approach. Environmental
science & technology. 54(6). pp.3499-3509.
Tzeng, S.Y. and et.al., 2021. Factors affecting customer satisfaction on online shopping
holiday. Marketing Intelligence & Planning.
Online
Dalgleish, R., 2020. How the Covid 19 Pandemic has Accelerated the Shift to Online Spending.
[Online]. Available through: < https://blog.ons.gov.uk/2020/09/18/how-the-covid-19-
pandemic-has-accelerated-the-shift-to-online-spending/>