The Impact of the Pandemic Covid-19 on the Digitalization of Trade in
Developing Countries
GERTI DAJÇI1, MATEUS HABILI2
1Department of Economics,
Albanian University,
Street Blvd Zogu I 1001, Tirana,
ALBANIA
2Department Management and Marketing,
Tirana Business University College,
Street of Kavaja Tiranë 1023,
ALBANIA
Abstract: - E-commerce is a new form of commerce where the consumer buys products and services from the
comfort of where he is. The Covid-19 pandemic forces consumers to buy products online due to the inability to go
out. Consumers have more used E-commerce in developed countries than in developing countries; several factors
cause this. In developing countries, the COVID-19 pandemic brought the digitalization of trade by encouraging the
number of online purchases. In developed countries, it also brought digitization because it encouraged the purchase
of products that were not considered before to be bought online or that have yet to be bought online. The purpose
of the study is to highlight the role and impact that the pandemic had on the digitization of trade in developing
countries and, more specifically, in Albania. The primary data of the study are from a sample of 610 respondents.
Some of the study's conclusions are the frequency of online product purchases affects the consumer's satisfaction
with online purchases, the repurchase of online products after the pandemic shows the level of satisfaction that the
consumer receives from online purchases that force him to return.
Key-Words: - E-commerce, COVID-19, digitalization, trade, developing countries, technology, transition
economies.
Received: June 7, 2023. Revised: March 12, 2024. Accepted: April 1, 2024. Published: April 25, 2024.
1 Introduction
E-commerce is the conduct of sales in digital form
through the Internet. E-commerce is an indicator that
increases the possibility of business development.
Also, E-commerce affects the economic growth of a
country, [1], [2]. In 2018-2019, the most developed
economies in the world had an impact of e-commerce
with 11% of and 4% of GDP for the whole world, [3].
Based on the rate (CAGR) for e-commerce retail sales
in the first countries, there are seven developing
countries; this is based on the projection for the period
2023 to 2027, an element that shows that E-commerce
has a more significant impact on the economy of a
developing country than for a developed country, [4].
E-commerce is selling through telecommunications,
[5]. E-commerce is the exchange of values by
applying information and communication technology,
[6], but it also involves doing business from the
Internet or digitizing products and services through
the Internet, [7]. E-commerce has created relationships
between consumers, businesses, and governments, [8],
[9]. The most frequent monetary transactions are
between B2B, where the most frequent are
communication, electronic procurement, and
electronic supply chain management, [10]. The other
most widespread form of e-commerce is (B2C), where
the business sells to the end consumer, where the most
popular businesses are Amazon and Alibaba. Besides
the advantage that B2B has over B2C, retail trade has
had rapid growth, [9], but there is also another form of
electronic commerce, such as (C2C), where
consumers sell from each other through online
platforms.
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2 Literature Review
2.1 E-commerce and Digitalization of Trade
E-commerce has made transactions more comfortable
for the consumer and has influenced the increase in
trade efficiency. The Internet has an impact on
international trade, [11]. The Internet has
revolutionized trade worldwide, mainly in exports,
[12], [13]. The Internet has had the effect of
increasing accessibility and creating relationships
between buyers and sellers. The Internet has an impact
on the economic growth of a developing country. E-
commerce allows businesses to expand quickly and
with little operational cost, [14]. E-commerce
increases productivity and can reduce costs, [15]. E-
commerce is a development that has changed how
businesses are done worldwide, [16]. E-commerce
combines sales between individuals, companies, and
governments, [17].
2.2 E-commerce in Pandemic
Based on the World Bank, the countries with the most
significant impact of the pandemic with a negative
effect on the volume of sales are: Albania (87.4
percent), Georgia (87.2 percent), Republic of Moldova
(90 percent), North Macedonia (76.9 percent), the
decline occurred compared to a year ago where the
average decline was recorded for Albania with 51.6%,
for Georgia, 47.1%, for the Republic of Moldova with
57.1% percent and 43.0% for North Macedonia, [16].
Table 1. E-readiness in the Transition Economies of
the UNECE source: UNECE, based on UNCTAD
B2C Index 2019 and UNCTAD B2C Index 2020
Country
Rank, 2019
Rank, 2020
Albania
75
86
Armenia
78
84
Azerbaijan
62
65
Belarus
37
35
Georgia
50
47
Kazakhstan
57
60
Kyrgyzstan
111
97
Republic of Moldova
54
53
Montenegro
77
78
North Macedonia
51
52
Russian Federation
40
41
Serbia
45
43
Tajikistan
129
121
Turkey
53
57
Ukraine
52
51
Uzbekistan
93
107
For 2020, the impact of the pandemic on
companies was 36.6% in Georgia, 39.5% in the
Republic of Moldova, 24.3% in North Macedonia, and
18.1% in Albania, [18].
2.3 Factors Affecting the Digitalization of
Trade
Technology has impacted society as a whole on a
global level but has increased commerce's speed,
security, and efficiency. E-commerce has developed
the trade process from the exchange of consumer
products and information between the customer and
the organization, [19]. The ecosystem of commerce
around the world has changed, [20]. M-commerce is
about selling over the phone, a convenient way to buy
products and receive services. This also constitutes a
transformation of doing business, [21]. Through E-
commerce, services such as various payments,
financial services, sales, and purchase of various
products, etc., are performed. Despite this
transformation, the sale of products will combine M-
E-commerce and E-commerce. However, the
application of M-commerce also needs help because it
combines three elements: money, technology, and
consumers, [22].
Fig. 1: Implementation of Paperless Trade-Related
Measures in the UNECE Region, 2021 UNECE
Regional Report on Digital and Sustainable Trade
Facilitation, 2021
The Figure 1 shows M-Commerce in 2021. The
increase in the number of smartphones has led to the
growth of M-commerce. E-commerce is predicted to
have an upward trend based on two strong points:
convenience and personalization of buying products.
This forecast with an upward trend is closely related
to the increase in the number of smartphones; the
more the number of smartphones increases, the more
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Volume 21, 2024
it increases (M-commerce). However, the so-called
"Social Commerce," where e-commerce is integrated
with social media, has also made consumers buy
products from social media. It should be emphasized
that the application of AI in e-commerce will increase
the efficiency and variety of services in E-commerce,
improving the consumer experience. Some innovative
services where AI has been applied in e-commerce are
personalized recommendations through algorithms,
chatbots, and voice assistants; consumers through
social media receive much information and
recommendations for products and services, and social
media influences the consumer's purchase decision,
[23]. Artificial intelligence (AI) will significantly
influence the revolution in E-commerce. However,
artificial intelligence will also influence the marketing
process because the efficiency of targeting consumers
will increase, and the demand will be better matched
to the offer. It will Bhardwaj customer service is
further improved, [24]. Another form of E-commerce
is multi-channel sales, where there is a mix between
offline and online channels where there is a mix of
contact points, such as physical stores, applications,
and websites, [25].
2.4 E-commerce in Albania
In 2020, the figure of 113 million USD is reached for
E-commerce in Albania, while the projection in 5
years is that it will reach the figure of 192 million
USD with an annual increase of 11.2%. Where the
number of e-commerce users is expected to be 1
million. E-commerce users have an increase of 36.6%
more users; in 5 years, this driver is expected to be
40.8%. Most of the payments in Albania are made
with cash, which makes it much more challenging to
measure purchases in E-commerce, where it is
calculated that 8% of consumers have credit cards.
Something that is also related to the culture of not
using cards in everyday transactions. Payment by card
is an essential element for conducting trade through E-
commerce. Although the Albanian consumer uses
credit cards sparingly, he uses telephone and prepaid
payments. At the same time, digital wallets are a
method that is not used by the Albanian consumer or
is used in a meager percentage. Albanian consumers
use prepaid cards more because they offer safe and
fast payments. Another form applied by the Albanian
consumer is Mobiano, which deals with mobile phone
payments, and more specifically, payments by the
Albanian consumer are by credit card-20%, prepaid
card-30%, via phone 35%, by transfers banking-10%,
with Ewallet-5%. In Albania, it is estimated that there
will be about 1.4 million users on social media by
2020, and the most significant part uses smartphones
to log into social media, [26]. The most popular social
media is Facebook, which can reach up to 1 million
individuals, while the social media that comes after
Facebook is Instagram, with 870 thousand if it is used
to communicate with target individuals.
In contrast, if used as a means of communication
to target individuals, Twitter reaches 91 thousand
consumers, [27]. Another element that has a high
impact on e-commerce is logistics. In Albania,
logistics has a low level; the infrastructure also causes
this because Albania is classified as a hilly-
mountainous country to the extent of 75%, an element
that affects the speed of transport and the quality of
service. The railway lines need to be functional and
can be very slow at best, [28]. E-commerce in Albania
is at a low level, but the COVID-19 pandemic
increased the number of online purchases. However,
the level of mistrust is high from the consumer, which
makes the Albanian consumers visit physical stores as
much as possible. Electronic payments are at a low
level, but this market is expected to grow by 11.9%
for the years 2022-2027. It should be emphasized that
e-commerce in Albania, after the e-commerce
pandemic, has had an expansion. This element has
made many businesses see this aspect as an
opportunity to adapt to consumer demand. Also, the
Albanian government, through legislation, has given
E-commerce support to companies that offer products
within Albania, [29].
3 Methodology
3.1 Research Questions
This paper aims to give answers to the following
research questions:
1. How much does the frequency of purchases affect
customer satisfaction from online shopping?
2. Does repurchasing online products after the
pandemic affect customer satisfaction from online
shopping?
3. Buying thoughtless products during the pandemic
affects consumer satisfaction.
4. How much does online product repurchasing
affect customer satisfaction?
5. How much does the purchase of thoughtless
products affect the consumer?
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3.2 Research Method
The type of study is quantitative. The Method applied
in the study is the survey, and the questionnaire was
applied as a research instrument. The sample is
probabilistically random, where each element has the
same choice. The sample consists of 295 respondents,
where the population in the city of Tirana consists of
925,268 individuals on January 1, 2023, [30], with a
margin of error of 5% and a confidence level of 95%,
for the sample to be statistically representative there
should be 385 individuals. In the study, 610
respondents.
3.3 Data Analysis
The study was built based on the linearity of research
instruments, such as research questions, methodology,
and analysis, that serve the study's purpose. Based on
the type of descriptive study and quantitative approach
in the analysis, reliability analysis was applied to
measure the stability of the questionnaire; with
Cronbach's Alpha test, multiple regression was
applied to measure the influence the variables have on
each other.
3.4 Research Limitations
The study's limitations consist of failing to study all
the factors affecting a country's trade. The study did
not consider the factors that influence consumer
behavior in E-commerce. In the study, the
macroeconomic variables that can affect trade directly
and indirectly should have been considered.
4 Data Analysis and Research Findings
Table 1. Reliability analysis
Cronbach's
Alpha
Cronbach's
Alpha Based on
Standardized
Items
N of Items
.903
.557
15
Based on the Table 1 the questionnaire is reliable
to be applied in the study because, based on
Cronbach's Alpha test, the reliability coefficient is 0.9.
This result makes the questionnaire valuable for the
study and, subsequently, for other analysis phases. It
also shows that the survey can measure 90% of the
purpose of the study.
Table 2. KMO Test
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.
.700
Bartlett's Test of
Sphericity
Approx. Chi-Square
30.800
df
3
Sig.
.000
Based on Table 2 the KMO test measures the
suitability of the variables taken in the study and is
based on the KMO coefficient of 0.7 and the sig value
that is less than 5%. The variables taken in the study
are suitable for analysis based on multiple regression.
Table 3. Total Variance
Total Variance Explained
Compo
nent
Initial Eigenvalues
Extraction Sums of
Squared Loadings
Total
% of
Varianc
e
Cumulati
ve %
Total
% of
Varianc
e
Cumulat
ive %
1
1.181
39.372
39.372
1.181
39.372
39.372
2
.994
33.126
52.498
3
4
.825
.723
27.502
26.7501
8.130
100.000
Table 4. Component Matrix
Component Matrix
Component
2
How often do you buy products
online?
-.762
If yes, how satisfied are you
with the online service during
the pandemic?
.663
How likely are you to continue
shopping online after the
pandemic?
During the pandemic, have you
bought products you did not
think you would buy online?
.554
Table 5. Regression model
Model Summary
Model
R
R Square
Adjusted R
Square
Std. Error of
the Estimate
Durbin-
Watson
1
.654a
.684
.062
1.19904
.592
Based on Table 3, Table 4 and Table 5 on the
regression analysis, it was found that the independent
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variables measure 68% of the dependent variable. The
value of R2 measures the equation's significance,
indicating that the equation is suitable for prediction.
Y= β0+ β1 * x1+ β2 * x2+ β3 * x3
Customer satisfaction from Ecommerce=4.258-0.228x
frequency of online shopping - 0.021 x online shopping
after the pandemic + 0.31 x online purchase of unthinkable
products
Table 6. ANOVA TEST
ANOVAa
Model
Sum of
Squares
df
Mean
Square
F
Sig.
1
Regression
33.567
2
16.783
11.674
.000
b
Residual
1381.631
961
1.438
Total
1415.198
963
Hypothesis 1: The variables that were not taken into
the study impact the satisfaction of online shopping.
Based on Table 6, the value is less than 5%, which
shows that hypothesis 1 is accepted and that the
factors that should have been taken into the study have
much influence on the satisfaction the consumer gets
from online shopping.
Hypothesis 2: The frequency of online shopping has
an impact on the satisfaction of online shopping.
Based on Table 6, the sig value is less than 5%, which
shows that hypothesis 2 is accepted and that the
frequency of online purchases greatly influences the
satisfaction the consumer gains from online purchases.
Hypothesis 3: Post-pandemic online repurchase has
an impact on shopping satisfaction.
Based on Table 6, the sig value is less than 5%, which
shows that hypothesis 3 is accepted and that
repurchasing online products after the pandemic
impacts the satisfaction that the consumer gains from
online shopping.
Hypothesis 4: The purchase of unthinkable products
has an impact on the satisfaction of the purchase.
Based on Table 6, the value of sig is less than 5%,
which shows that hypothesis 4 is accepted and that
buying products online impacts the satisfaction that
the consumer gets from online shopping.
Hypothesis 5: The frequency of online shopping
harms the satisfaction that consumers get from online
shopping.
Hypothesis 6 is accepted since the sig value is less
than 5%. The impact measure is 22.8%, which shows
that if all variables are zero with 1% of the frequency
of online purchases, consumer satisfaction from online
purchases will decrease by 22.8%, so an increase in
the number of online purchases will increase
consumer dissatisfaction with online purchases. The
increase in the number of online purchases will lead to
an increase in dissatisfaction, which indicates that the
quality of the service as a whole decreases. It should
be emphasized that buying products online is a
process and not just a factor.
Hypothesis 6: Online repurchasing after the pandemic
negatively affects the satisfaction that consumers get
from online shopping.
Repurchases of online products after the pandemic
negatively affect consumers' satisfaction with online
shopping. Hypothesis 6 is accepted since the sig value
is less than 5%. The impact measure is 2.1%, which
shows that if all variables are zero with a 1% increase
in online repurchases after the pandemic, consumer
satisfaction from online purchases will decrease by
2.1%, so an increase in the number of online
repurchases will increase the dissatisfaction of
consumer towards online shopping, which shows that
consumers have not received the same level of
satisfaction with online shopping as during the
pandemic. The increase in online repurchases will lead
to an increase in dissatisfaction, which shows that the
same quality of service has yet to be received. This
element relates to the companies' service or the
increase in the consumer's expectations for online
purchases.
Hypothesis 7: Buying mindless products online
positively affects the satisfaction consumers get from
online shopping.
Hypothesis 7 is accepted since the sig value is less
than 5%. The impact measure is 31%, which shows
that if all the variables are zero with a 1% increase in
purchases of unthinkable products, it will increase
consumer satisfaction from online purchases by 31%,
i.e., an increase in the number of unthinkable products
purchased online will increase consumer satisfaction
with online shopping, which shows that buying a
specific category of products, especially those that a
consumer did not think he could get online, gave him
a certain level of satisfaction. The pandemic has
forced consumers to buy products they did not think
they could buy online, influencing the transfer of
online purchases for a specific category of products. It
has influenced the digitalization of trade.
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5 Conclusions
Many variables besides those taken in the study have
much influence on consumers to buy online, this fact
guides studies in the E-Commerce field to analyze
other variables that were not taken into the study
because they significantly affect the satisfaction that
the consumer benefits from shopping online. The
frequency of online purchases has a significant impact
on customer satisfaction, the more the frequency of
purchases increases, the more the risk that the
customer will be dissatisfied with the quality of the
service because the very characteristic of the service is
that it cannot be provided equally to all customers, it
should be noted that the service combines
interpersonal communication because, in the case of
machines, the service is standard. Customer
dissatisfaction brings a negative word of mouth for
online shopping, an element that would demotivate
online shopping; it should be noted that the increase in
online shopping can necessarily affect the quality of
the service, and if it does not affect it then it will turn
into a positive service and will make the consumer
make a positive word of mouth element that would
influence the increase of online purchases by
consumers. Regarding online repurchasing after the
pandemic, it affects satisfaction in online shopping, an
element that shows that individuals who bought online
during the pandemic had a certain level of satisfaction
that they would return to buy online again, an element
that shows that the pandemic has affected
digitalization of trade because it has encouraged
consumers to buy online, and this has influenced their
approach to buying online. The pandemic has also
influenced the purchase of products they did not think
of buying online; this shows that the pandemic has
influenced the promotion of online purchases for
products that the consumer has been skeptical about
buying for many reasons. Based on the study, the
pandemic with the ban on movement that it brought
encouraged many individuals to buy online, so during
this period, E-commerce has been a forced choice
rather than a desire.
A limitation of the study is that only some factors
affecting online shopping have been studied. Also,
there is no measuring indicator to record whether
consumers who have shopped online during the
pandemic continue to shop online. Future studies in
this field should be oriented towards the identification
of the indicators that are the most important in the step
of the consumer in developing countries in the use of
E-commerce platforms, it should also be researched in
the description of the consumer in developing
countries taking into consider the macro and micro
economic factors of the country where the study takes
place.
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WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2024.21.86
Gerti Dajçi, Mateus Habili
E-ISSN: 2224-2899
1046
Volume 21, 2024
Contribution of Individual Authors to the Creation
of a Scientific Article (Ghostwriting Policy)
Ph.D. Gerti Dajçi conceptualized the article,
interpreted the data, and revised them critically for
crucial scientific content, principal findings, and
recommendations.
Msc. Mateus Habili designed and performed the
statistical analysis collected the data and
contributed data analysis tools; he was also
accountable for all aspects of the work in ensuring
that questions related to the accuracy and integrity
of any part of the work were appropriately
investigated and resolved.
Sources of Funding for Research Presented in a
Scientific Article or Scientific Article Itself
No funding was received for conducting this study.
Conflict of Interest
The authors have no conflict of interest to declare that
is relevant to the content of this article.
Creative Commons Attribution License 4.0
(Attribution 4.0 International, CC BY 4.0)
This article is published under the terms of the
Creative Commons Attribution License 4.0
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US
WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2024.21.86
Gerti Dajçi, Mateus Habili
E-ISSN: 2224-2899
1047
Volume 21, 2024