The Impact of E-Marketing on Consumer Satisfaction during
Pandemic Time
ALBULENA AVDILI ZEQIRI1, BEHRIJE RAMAJ DESKU2,*, KAROLINA ILIESKA3
1Business Management,
Universitety “Haxhi Zeka”,
REPUBLIC OF KOSOVO
2Faculty of Tourism, Hospitality and Environmental Management,
Universitety “Haxhi Zeka”,
REPUBLIC OF KOSOVO
3Faculty of Economics,
University “St. Kliment Ohridski“,
NORTH MACEDONIA
*Corresponding Author
Abstract: - During the pandemic, E-marketing was of great importance to enterprises in general. Digitized
enterprises or enterprises that have been digitized during the pandemic have managed to develop their work
processes without stalling in their development. At the time when everything stopped working, the companies
that had already digitized processes within their companies were managing to cope with the situation that had
gripped the whole world. The approach of enterprises in the time of the pandemic has greatly influenced the
perception and importance of the digitalization of enterprises in the daily work processes. Communication,
process management, and employee management have been a key factor in not stalling processes, ie in
maintaining the health of employees of those enterprises. As a result of the COVID-19 crisis, the majority of
business executives have ordered their organizations to digitize at least a portion of their operations to
safeguard workers and cater to clients who are experiencing limited mobility. We have all watched what is
undoubtedly going to go down in history as the widespread adoption of digital access to services and remote
work, even though many doubters have not recognized this as a viable prospect. Online ordering and delivery
have become the primary business of grocery businesses. In many nations, the emphasis in schools is entirely
on online education. Plans for "online" supply chains and factories are being actively developed by
manufacturers. Although in some regions the masses have started to reopen and businesses are opening, many
businesses are still considering digitalization and further development of their internal processes as a priority.
Customer satisfaction is one of the greatest assets of any business, including e-business in today's competitive
environment. Several factors can help e-businesses to build a base for their customers. It undoubtedly includes
service and customer satisfaction which can be the determinants of success.
Key-Words: - E-Marketing, Customer satisfaction, Pandemic time, COVID-19, Online orders, Online sales.
Received: July 26, 2023. Revised: February 27, 2024. Accepted: April 23, 2024. Published: May 10, 2024.
1 Introduction
If consumer behavior is compared in different
periods, it can be seen that consumer behavior has
continuously transformed. Various factors have
influenced these transformations, including the
developments that take place in the environment
where we live and act every day. Consumer
behaviors have undergone even greater changes
recently, during the pandemic period, reflecting the
dynamics of life as well as the technological
developments that are being used today. Consumers
make many decisions during the day. Choosing
what to wear is one example of a decision that
requires careful consideration and analysis. What
scent am I going to use? For dinner, what shall I
have?
But there are also many other decisions, which
consumers take on the spot during the purchase of
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DOI: 10.37394/23207.2024.21.97
Albulena Avdili Zeqiri, Behrije Ramaj Desku, Karolina Ilieska
E-ISSN: 2224-2899
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products or services without thinking and analyzing
them. These decisions are made under the influence
of the factors of the situation or the country we are
in, which can be psychological factors or other
factors that can directly affect the purchase decision.
Even though these choices may seem insignificant,
they keep a lot of business professionals up at night
as they attempt to analyze and comprehend
consumer behavior. Understanding the thought
processes that go into consumer decisions allows
businesses to use that knowledge to boost sales
while preventing consumers from making needless
purchases.
The analysis of customer behavior is crucial for
marketers since it provides insight into the factors
that affect consumers' decisions to buy, and what
factors influenced the consumer to buy a certain
product and not another. Businesses can close the
gap in the market and find products that are needed
as well as those that are less needed but still relevant
to the consumer once they understand the behavior
of consumers while making decisions about which
goods or services to purchase.
Businesses can make decisions about how best
to market their goods and services to customers to
maximize their impact by consulting consumer
behavior research.
Reaching out to potential clients and winning
their loyalty to your goods and services requires an
understanding of consumer purchasing behavior.
Consumer behavior is often influenced by other
factors, such as external factors, for this reason,
businesses must study consumer purchasing patterns
and understand buyer trends. Businesses use
different strategies to encourage consumers to buy,
and this has undoubtedly influenced the change in
consumer behavior. Among the most popular
strategies, the most common ones that businesses
use are: offering different payment options,
purchasing in installments, buying now, paying
later, etc. Consumer behavior, as defined by [1], is
the study of people, groups, and organizations. It
also includes the procedures used to choose, get,
employ, and discard goods and services in addition
to meeting customer demands and mitigating
negative effects on society and the individual. The
cognitive, affective, and physical actions people
take to choose, acquire, and use goods and services
to satisfy their needs and wants are referred to as
consumer purchase behavior. It includes the
purchasing and other consumption-related actions
that participants in the exchange process take part in
[2].Consumer behavior is the culmination of all the
decisions made by human decision-making units
over a period of time involving the acquisition, use,
and disposal of products, services, events,
interactions, people, and ideas. Consumer behavior
encompasses more than just an individual's
purchasing habits. It also covers the utilization of
customer-provided goods, services, events, and
ideas. Consumers also make decisions for other
people when they read books by particular writers,
vote for politicians, and so on [3] .
2 Literature Review
Recognizing e-marketing's broad reach beyond
conventional web-based techniques is essential
when examining how it affects consumer
satisfaction during pandemics. According to [4], is a
broad term that includes a variety of technologies
and communication channels outside of the Internet.
According to [5], Initially, the Web served to
connect computer users to networks to access
content as well as the connection between people to
each other, and today almost every company has its
own Web when offering different information to
clients.
Both the Internet and technological
development play a very large role in influencing
customer satisfaction by enabling communication as
well as the creation and development of
relationships between them.
E-marketing became especially essential to
sustaining customer relationships and satisfaction
during the pandemic when in-person encounters
decreased and online involvement increased. E-
marketing extended beyond websites to include
supply chain management and customer relationship
management through mobile apps, software, and
hardware—all of which existed before the Internet.
Furthermore, non-web internet communication
channels that promote engagement and satisfaction
even in socially isolated periods, such as text
messaging, email, and internet telephony, have
developed as successful marketing platforms.
Also, according to [6], marketing
communication with customers is a key point
because if customer comments are collected and
then carefully analyzed, the company's decision-
making will be correct, and very strong relationships
will be created between them. While, [7],
interactions between companies and customers are
managed by software, to generate high and
continuous profit, companies must first identify
their customers. All this is achieved when the
collected data is analyzed with great care to identify
homogeneous customers.
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[8], affirmed gaining new customers requires
large expenses, including the promotion of products
and services that companies offer, so new customers
are more expensive than existing ones.
The knowledge that attracting new clients is
more expensive than keeping hold of current ones
emphasizes the significance of effective and
customized e-marketing techniques. Businesses can
optimize long-term profitability and minimize
acquisition costs by customizing their marketing
strategies to effectively attract and keep customers
through the analysis of customer behavior data. This
means that to maximize marketing effectiveness and
achieve sustainable growth, a focus on tailored
communication focused retention strategies, and
data-driven decision-making is required.
According to [9], technology alone cannot
create and develop relationships with clients, so also
the staff is another important factor, their
qualification, their commitment to the effective
implementation of E-marketing in such a way that
the loyalty of customers to the company increases.
There are different ways to promote products,
starting from traditional marketing: word of mouth,
then print and television ads.
[10], emphasized today's times, it is impossible
not to mention the era of digitization, where product
advertising is done through marketing channels,
email, and social media marketing.
3 Problem Formulation
The purpose of this research is to fully comprehend
the impact of e-marketing on consumer satisfaction
in the context of pandemics.
Among the specific goals are:
- Analyze the different e-marketing tactics that
companies used during the pandemic.
- Examine the main elements affecting customer
satisfaction in the digital sphere.
- Examine the relationships that exist between e-
marketing strategies and consumers' general level
of satisfaction.
- Give companies practical advice on how to
improve customer satisfaction in the context of e-
marketing both during and after the pandemic.
By tackling these goals, the study hopes to
provide insightful information about how e-
marketing is changing and the significant effects it
has on customer satisfaction in the face of the
ongoing worldwide crisis.
3.1 Research Questions
Formulating accurate and targeted research inquiries
is essential when examining how e-marketing
affects customer satisfaction in pandemic situations.
The following research questions relate to the
theme:
Have there been more online orders at the
time of the pandemic?
How satisfied were the businesses with the
online sales orders during the pandemic?
How satisfied were consumers with online
orders during the pandemic?
Do age groups differ in terms of how
satisfied customers are with their online
orders?
Do men and women have different levels of
satisfaction when it comes to internet
orders?
3.1.1 Hypothetical Research Framework
The following research hypotheses, which will be
validated or refuted by this study, can be created
based on the goals and subjects of the paper that
have previously been defined:
Hypothesis
H1- E-Marketing has a positive effect on
consumer satisfaction
H2 E-Marketing has a positive effect on
Businesses
H3- Price has a positive effect on customer
satisfaction
H4 Timely delivery has a positive effect on
consumer satisfaction.
H5Online orders save customers time and money
4 Research Methodology
The survey questionnaire and research questions
that are designed to extract data in the pertinent
fields and the variables needed to fill in the proper
aspects serve as the foundation for this study's
methodology.
This type of primary data collection pertains to
the collection of data by the researcher directly from
the case study. It is a direct representation sample,
meaning that the results are implied from the search
case for the appropriate reason that the interview
model was selected through the representative. The
selection of methods for the data collection is also
based on how the data relates to the research
questions and the research context.
A structured research questionnaire is used in
this study to gather data, which is an instrument that
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Albulena Avdili Zeqiri, Behrije Ramaj Desku, Karolina Ilieska
E-ISSN: 2224-2899
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helps and completes information research. Although
the data collected via the questionnaire will be
quantitative, the data is expected to be qualitative.
Primary data collection was done through a self-
administered physical and online questionnaire,
where different people were selected, of different
ages, on different days, and at different times. In this
survey, the questions posed have multiple answers.
The answers have been at the ranking level, I used
ordinal regression for data analysis, and for
correlation between variables I used Spearman's rho
since more appropriate for ranking. Once the
questionnaire has been in the form 1- very
dissatisfied, 2 dissatisfied, 3 moderately satisfied, 4-
satisfied, and 5- very satisfied. I used ordinal
regression and for correlation between variables I
used Spearman's rho since it is more appropriate for
ranking. The processing of the data collected
through the questionnaire was done using the
Microsoft Excel program and the well-known SPSS.
4.1 Problem Solution
H1- E-Marketing has a positive effect on consumer
satisfaction.
Таble 1. Customer Satisfaction
Freque
ncy
Valid
Percent
Cumulativ
e Percent
Valid
Very
dissatisfied
9
5.0
5.0
Dissatisfied
18
10.0
15.0
Neutral
19
10.6
25.6
Satisfied
117
65.0
90.6
Very satisfied
17
9.4
100.0
Total
180
100.0
In the Table 1 the results show that 9.4% of
customers are very satisfied, 65% are satisfied with
the use of e-marketing, 10.6% of customers are
neutral, 10% of customers are dissatisfied and 5% of
customers are very dissatisfied. We can show that
the overall level of customer satisfaction is 10.0%
not satisfied and 65.0% satisfied. According to the
statistics, there is still an opportunity for
development even though a sizable majority of
customers (65.0%) are satisfied. This is because
10.0% of customers are not satisfied.
The 10.6% neutral category denotes a subset of
customers who are neither content nor unsatisfied
and may offer a chance for enhancement or
additional research into their requirements and
preferences, however, this confirms the hypothesis
of the overall satisfaction of consumers related to e-
marketing. The more advanced e-marketing is, the
higher the level of customer satisfaction is.
Таble 2. Group Statistics
Group Statistics
gender
N
Mean
Std.
Deviatio
n
Std.
Error
Mean
Customer
satisfaction
male
100
5.00
0.000
0.000
fema
le
80
3.38
1.945
.217
Table 2 shows the comparison of female
participants (mean of 3.38), male participants on
average reported higher levels of satisfaction (mean
of 5.00). In comparison to male participants, where
the standard deviation is 0.000, the standard
deviation for female satisfaction scores (1.945)
shows higher variability in satisfaction levels among
female participants. There appears to be some
fluctuation in the sample means from the population
mean, as indicated by the female satisfaction scores'
non-zero standard error of the mean (SEM) of
0.217.
Based on the result of Table 3 nwe reject the
null hypothesis in both Levene's test and the t-test
since their p-values are less than 05.
Consequently, we conclude that the two
independent groups under comparison differ in
terms of consumer satisfaction in a statistically
significant way.
Furthermore, there is a 1.625 mean difference
between the two groups, with a 95% confidence
range that falls between 1.192 and 2.058 when equal
variances are not assumed and between 1.242 and
2.008 when they are.
This implies that there is a difference in the two
groups' average customer satisfaction levels, and the
difference is estimated to lie in the provided
confidence intervals.
In conclusion, the results show that the two
groups' levels of customer satisfaction differ
significantly and that this difference has statistical
significance.
The result presented in Table 4 show that
Consumer satisfaction correlates with benefit and
security payment that is 0.01 level (2-tailed) very
strong correlation between them. Benefit and
security payment have a positive impact on
customer satisfaction.
From this, we can conclude that H1 stands.
H2 E-Marketing has a positive effect on
Businesses
From the parameters of Table 5: (Q9)
correctness in ordering online, (Q10) correctness of
timely delivery,(Q12) extra price, (Q22) easy
processing, (Q30) business satisfaction.
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The only significant variable is easy processing
for a p-value of 0.05.
Таble 3. Independent Samples Test
Independent Samples Test
Levene's Test for
Equality of Variances
t-test for Equality of Means
F
Sig.
t
df
Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
95% Confidence Interval of
the Difference
Lower
Upper
Customer
satisfaction
Equal
variances
assumed
1913.517
.000
8.362
178
.000
1.625
.194
1.242
2.008
Equal
variances
not
assumed
7.474
79.000
.000
1.625
.217
1.192
2.058
Таble 4. Correlations
Good Services
Benefit
Inexpensive
Security
payment system
Spearman's
rho
Good Services
Correlation Coefficient
1.000
.186*
.081
.141
Sig. (2-tailed)
.
.012
.280
.059
N
180
180
180
180
Benefit
Correlation Coefficient
.186*
1.000
-.006
.304**
Sig. (2-tailed)
.012
.
.934
.000
N
180
180
180
180
Inexpensive
Correlation Coefficient
.081
-.006
1.000
.107
Sig. (2-tailed)
.280
.934
.
.154
N
180
180
180
180
Security payment
system
Correlation Coefficient
.141
.304**
.107
1.000
Sig. (2-tailed)
.059
.000
.154
.
N
180
180
180
180
Таble 5. Parameter Estimates
Estimate
Std. Error
Wald
df
Sig.
95% Confidence Interval
Lower Bound
Upper Bound
Threshold
[Q30 = 3.00]
-3.278
1.612
4.133
1
.042
-6.438
-.118
[Q30 = 4.00]
-.470
1.589
.087
1
.767
-3.584
2.644
Location
[Q9=1.00]
-1.039
1.462
.506
1
.477
-3.904
1.825
[Q9=2.00]
-2.944
1.148
6.575
1
.010
-5.195
-.694
[Q9=3.00]
-1.521
.923
2.717
1
.099
-3.330
.288
[Q9=4.00]
-.490
.889
.303
1
.582
-2.232
1.253
[Q9=5.00]
0a
.
.
0
.
.
.
[Q10=1.00]
18.038
.000
.
1
.
18.038
18.038
[Q10=2.00]
.900
1.677
.288
1
.592
-2.387
4.186
[Q10=3.00]
-1.125
.615
3.344
1
.067
-2.332
.081
[Q10=4.00]
-.031
.562
.003
1
.956
-1.132
1.070
[Q10=5.00]
0a
.
.
0
.
.
.
[Q12=1.00]
1.102
1.300
.719
1
.397
-1.446
3.651
[Q12=2.00]
2.934
1.525
3.703
1
.054
-.054
5.922
[Q12=3.00]
1.809
1.198
2.278
1
.131
-.540
4.157
[Q12=4.00]
0a
.
.
0
.
.
.
[Q22=1.00]
18.272
3757.195
.000
1
.996
-7345.695
7382.238
[Q22=2.00]
-1.430
.690
4.289
1
.038
-2.782
-.077
[Q22=3.00]
-.563
.669
.707
1
.400
-1.874
.749
[Q22=4.00]
-2.346
.665
12.457
1
.000
-3.649
-1.043
[Q22=5.00]
0a
.
.
0
.
.
.
Link function: Logit.
a. This parameter is set to zero because it is redundant.
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So if easy processing increases per unit,
customer satisfaction decreases by -2.346.
While (Q9) the correctness of ordering online,
(Q10) the correctness of timely delivery, and (Q12)
extra price have no statistical significance. From
this, we can conclude that H2 stands.
H3- Price has a positive effect on customer
satisfaction
(Q11) Has the price of online orders changed
during the pandemic (Q12) Did you pay an extra
price per post for shipping the products (Q17) Price,
(Q19) Free delivery, (Q21) Inexpensive, (Q29)
Customer Satisfaction
From the Table 6, we can see that pricing hurts
consumer satisfaction, which is the opposite of the
hypothesis (H3). More specifically, there is a
tendency for customer satisfaction to decline when
prices rise.
In addition, additional elements that have a big
impact on customer satisfaction levels include
location, free delivery, low-cost options, and
adjustments to online order costs throughout the
pandemic.
These results imply that to improve customer
satisfaction, firms should carefully analyze their
pricing tactics as well as other aspects of their
services since higher prices by themselves might not
always translate into greater satisfaction.
Price and customer satisfaction have a
statistically significant positive link at the 0.05 level
(2-tailed), according to the correlation analysis
shown in Table 7. This implies that there is a
positive correlation between price and consumer
satisfaction. In particular, there is a relatively
significant positive association between pricing and
customer satisfaction, as indicated by Spearman's
rho correlation coefficient of 0.170*.
The third hypothesis (pricing has a positive impact
on customer satisfaction) is supported by a
considerable positive association. According to this
research, consumers believe that more expensive
goods and services provide better value or quality,
which raises customer satisfaction.
As a result, companies stand to gain from
carefully considering how much to charge for their
products to match client preferences and
expectations. This will eventually raise overall
satisfaction levels and encourage client loyalty.
H4 Timely delivery has a positive effect on
consumer satisfaction.
Таble 6. Parameter Estimates
Estimate
Std. Error
Wald
df
Sig.
95% Confidence Interval
Lower Bound
Upper Bound
Threshold
[Q29 = 1.00]
-7.034
1.577
19.903
1
.000
-10.124
-3.944
[Q29 = 2.00]
-5.618
1.549
13.152
1
.000
-8.655
-2.582
[Q29 = 3.00]
-4.795
1.542
9.668
1
.002
-7.817
-1.772
[Q29 = 4.00]
.033
1.475
.001
1
.982
-2.857
2.924
Location
[Q17=3.00]
-2.114
1.157
3.338
1
.068
-4.382
.154
[Q17=4.00]
-1.504
.531
8.024
1
.005
-2.545
-.463
[Q17=5.00]
0a
.
.
0
.
.
.
[Q21=1.00]
2.688
.975
7.594
1
.006
.776
4.600
[Q21=2.00]
-.160
.781
.042
1
.837
-1.692
1.371
[Q21=3.00]
-.260
.634
.167
1
.682
-1.503
.984
[Q21=4.00]
-.116
.388
.090
1
.764
-.876
.644
[Q21=5.00]
0a
.
.
0
.
.
.
[Q19=1.00]
2.568
2.816
.831
1
.362
-2.952
8.087
[Q19=2.00]
2.433
1.174
4.298
1
.038
.133
4.733
[Q19=3.00]
2.257
.801
7.944
1
.005
.688
3.826
[Q19=4.00]
1.295
.499
6.726
1
.010
.316
2.274
[Q19=5.00]
0a
.
.
0
.
.
.
[Q12=1.00]
-6.610
1.526
18.759
1
.000
-9.602
-3.619
[Q12=2.00]
-2.474
1.531
2.611
1
.106
-5.476
.527
[Q12=3.00]
-4.788
1.402
11.667
1
.001
-7.535
-2.041
[Q12=4.00]
0a
.
.
0
.
.
.
[Q11=1.00]
1.914
.933
4.203
1
.040
.084
3.743
[Q11=2.00]
3.280
1.044
9.880
1
.002
1.235
5.326
[Q11=3.00]
1.826
.717
6.490
1
.011
.421
3.231
[Q11=4.00]
.521
.623
.699
1
.403
-.700
1.741
[Q11=5.00]
0a
.
.
0
.
.
.
Link function: Logit.
a. This parameter is set to zero because it is redundant.
WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
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E-ISSN: 2224-2899
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Volume 21, 2024
Таble 7. Correlations
Price
Customer Satisfaction
Spearman's rho
Price
Correlation Coefficient
1.000
.170*
Sig. (2-tailed)
.
.023
N
180
180
Customer Satisfaction
Correlation Coefficient
.170*
1.000
Sig. (2-tailed)
.023
.
N
180
180
*. Correlation is significant at the 0.05 level (2-tailed).
Таble 8. Parameter Estimates
Estimate
Std. Error
Wald
df
Sig.
95% Confidence Interval
Lower Bound
Upper Bound
Threshold
[Q29 =
1.00]
-2.891
.353
67.262
1
.000
-3.582
-2.200
[Q29 =
2.00]
-1.682
.226
55.431
1
.000
-2.125
-1.239
[Q29 =
3.00]
-1.014
.192
27.880
1
.000
-1.391
-.638
[Q29 =
4.00]
2.326
.276
71.268
1
.000
1.786
2.866
Location
[Q31=4]
.219
.345
.403
1
.525
-.457
.896
[Q31=5]
0a
.
.
0
.
.
.
Source: Author
Link function: Logit.
a. This parameter is set to zero because it is redundant.
Таble 9. Parameter Estimates
Estimate
Std. Error
Wald
df
Sig.
95% Confidence Interval
Lower Bound
Upper Bound
Threshold
[Q29 = 1.00]
-2.426
.731
11.024
1
.001
-3.857
-.994
[Q29 = 2.00]
-1.142
.679
2.830
1
.093
-2.473
.189
[Q29 = 3.00]
-.411
.670
.376
1
.540
-1.724
.902
[Q29 = 4.00]
3.681
.770
22.859
1
.000
2.172
5.190
Location
[Q18=1.00]
.970
1.376
.496
1
.481
-1.728
3.667
[Q18=2.00]
.844
.851
.983
1
.321
-.825
2.513
[Q18=3.00]
-.215
.901
.057
1
.811
-1.981
1.551
[Q18=4.00]
.155
.404
.146
1
.702
-.638
.947
[Q18=5.00]
0a
.
.
0
.
.
.
[Q23=1.00]
.988
.698
2.004
1
.157
-.380
2.355
[Q23=2.00]
-.894
.536
2.778
1
.096
-1.945
.157
[Q23=3.00]
.181
.531
.115
1
.734
-.861
1.222
[Q23=4.00]
-.471
.603
.610
1
.435
-1.653
.711
[Q23=5.00]
0a
.
.
0
.
.
.
[Q22=1.00]
3.545
.781
20.616
1
.000
2.015
5.076
[Q22=2.00]
.090
.605
.022
1
.881
-1.095
1.275
[Q22=3.00]
1.421
.517
7.567
1
.006
.409
2.434
[Q22=4.00]
.102
.553
.034
1
.853
-.982
1.187
[Q22=5.00]
0a
.
.
0
.
.
.
a. This parameter is set to zero because it is redundant.
The result presented in Table 8 (Q29) Customer
Satisfaction, (Q31)Time delivery.
According to the data analysis, at the traditional
p-value threshold of 0.05, the parameter estimate for
timely delivery (Q31) exhibits statistical
significance. This suggests that customer
satisfaction levels are highly influenced by the
delivery schedule. Thus, it offers compelling
evidence in favor of hypothesis H4, which contends
that prompt delivery enhances consumer
satisfaction.
The statistical relevance of timely delivery
emphasizes how crucial it is in influencing the
opinions and experiences of customers. Consumers
frequently connect professionalism, dependability,
and general contentment with a service or product
WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2024.21.97
Albulena Avdili Zeqiri, Behrije Ramaj Desku, Karolina Ilieska
E-ISSN: 2224-2899
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with prompt delivery. Consequently, companies that
place a high priority on timely delivery stand a
better chance of increasing customer satisfaction
and retaining loyal consumers.
H5 Online orders save customers time and
money.
The results presented in Table 9 show the
impact of various factors on customer satisfaction.
These factors include 'Saving time' (Q18), 'Easy
processing' (Q22), 'Easy fund transfer' (Q23), and
'Customer Satisfaction' (Q29).
Saving time and money is perceived as having a
large positive impact, as indicated by the estimate
for Q22=1.00, which is 3.545.
At the point of 0.05, the p-value for this
estimate is 0.000, demonstrating statistical
significance.
Customers may believe that placing an online
order saves them time and money when they find
the process simple, according to the statistical
significance of "Easy processing" (Q22).
This result is in line with general expectations
because simple, streamlined procedures are
frequently linked to efficacy and cost-effectiveness.
The strong positive impact suggests that
customers' perceptions of time and money savings
may be improved by making it easier to complete
online orders.
Customers can save time and money by placing
orders online, as evidenced by the statistically
significant parameter estimate, which supports
hypothesis H5.
Research questions:
Have there been more online orders at the
time of the pandemic?
Businesses claimed that there was an increase in
online sales during the pandemic of up to 50%.
How satisfied were the businesses with the
online sales orders during the pandemic?
Businesses are very satisfied with online orders at
the time of the pandemic, they have shown an
increase in online sales. From their answers, 55.6%
are very satisfied, 14.4 satisfied, and 30% neutral.
How satisfied were consumers with online
orders during the pandemic?
Consumers responded that they were very satisfied
with online shopping during the pandemic time
because they saved time and money. After all,
usually orders came with free delivery.
Their answers were thus: Very satisfied 9.4%,
satisfied 65%, neutral 10.6%, dissatisfied 10% and
very dissatisfied 5%.
Is there a difference between the ages and the
level of consumer satisfaction with online
orders?
The percentage of satisfaction with online orders by
age is thus divided by 6.7% of the most dissatisfied
customers. Most of the customers are aged over 60
(16.67%) and 41 to 50 years (11.11%).
Dissatisfaction was 17.2% of whom most over 60
(75%) and 51 to 60 (33.30%). From the total we
have noted that the majority of the respondents
52.8% said that they are generally satisfied with the
online orders, most of them 71.42% are aged 21 to
30 olds, 63.8% are between the ages of 31 and 40,
and 55.56% are between the ages of 41 and 50. Of
the 180 surveyed customers, 18.3% of them were
satisfied with the online orders, 33.33% were under
20, 22.22% were from 41 to 50 years, 19.10% were
aged 51-60, 18.2 % were aged from 31 to 40 years,
14.28% age from 21 and 30 years of age and
customers over 60 years old 8.33%. The last 5% of
the surveyed customers were very satisfied with the
online orders, most of which belong to the age of 20
years 33.33% and 31-40 years old 5.5%. From this
analysis, we can say that there are major differences
between the ages in terms of satisfaction with online
orders.
Do men and women have different levels of
satisfaction when it comes to internet orders?
The difference between the satisfaction of men and
women with online orders, with 5% of men and 5%
of women saying they are very satisfied with online
orders and 8% of men said they are very dissatisfied
with online orders and 5% of women have also been
dissatisfied with online orders. In general, customers
said they were on average satisfied with online
orders, of which 57% were males and 47.5% were
females. So from this, we see that men are more
satisfied with online orders.
5 Conclusions
Through the results achieved in this paper, we have
managed to bring important conclusions that can
serve as a source of information for further studies
or as suggestions for businesses and consumers in
the use of E-Marketing.
From the surveys, we understand that most of
the customers who were users of online shopping at
the time of the pandemic were satisfied with the
WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2024.21.97
Albulena Avdili Zeqiri, Behrije Ramaj Desku, Karolina Ilieska
E-ISSN: 2224-2899
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Volume 21, 2024
accuracy, ease, and correctness of the businesses
that provided these online sales.
Even though before the pandemic time a
majority of consumers had been reluctant to order
online for many reasons. From consumer responses,
we found that the most common products in online
orders during the pandemic were food, clothing, and
technology.
Through this research, we realized that the trust
in consumers in online ordering is greater than
before the time of the pandemic because it was a
dose of distrust thinking that most businesses that
operate online are fake or do not exist at all, and
their purpose the only one is consumer fraud.
5.1 Recommendations for Future Research
From the research we concluded that every
business must have E-Marketing to function
regardless of the circumstances we may be in, as
was the case with the Pandemic.
Businesses need to invest more to gain the trust
of consumers.
The online ordering process should be very
easy to use by consumers regardless of their age
and level of education.
To create other forms of information for
consumers who do not use social networks
(information portals, Facebook, Instagram, etc.)
Stress the value of localizing and culturally
sensitive e-marketing methods to the specific
cultural quirks and preferences of your target
audience. Assist companies in making
investments in consumer-friendly localized
language, visuals, and content. To effectively
engage with the target audience and improve
customer satisfaction, emphasize how important
it is to understand local cultures, festivals, and
traditions.
Urge companies to focus on mobile
optimization when it comes to their e-marketing
initiatives, such as creating mobile-friendly
content, flexible websites, and focused mobile
advertising.
It is recommended that companies look to
enhance their e-commerce platforms by adding
features like safe payment methods, expedited
checkout procedures, and customized product
suggestions. To keep ahead of the competition
and satisfy consumers' changing needs, we
propose investigating new e-commerce trends
like voice and social commerce.
In a market where competition is fierce,
emphasize the value of developing solid
customer relationships. To efficiently track
customer contacts, obtain feedback, and
personalize communications, firms should be
encouraged to invest in strong Customer
Relationship Management systems. Suggest the
use of email marketing campaigns, customer
feedback systems, and loyalty programs to
improve customer satisfaction, build rapport,
and promote repeat business.
Encourage companies to place a high priority on
protecting consumer data by adhering to
applicable laws, putting strong cybersecurity
measures in place, and following open data
handling procedures. Stress how crucial it is to
earn customers' trust by protecting their data and
honoring their need for privacy.
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DOI: 10.37394/23207.2024.21.97
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E-ISSN: 2224-2899
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Contribution of Individual Authors to the
Creation of a Scientific Article (Ghostwriting
Policy)
The authors equally contributed in the present
research, at all stages from the formulation of the
problem to the final findings and solution.
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 conflicts of interest to declare.
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
https://creativecommons.org/licenses/by/4.0/deed.en
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DOI: 10.37394/23207.2024.21.97
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E-ISSN: 2224-2899
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