2. Ain Shams University-
Faulty of Business
DBA -
Academic Year 2020/2021
Supervised by:
Prof. Sayed ElKhouly
Team members:
Naglaa Mohsen Fathalla
Mariam Adel Shawky
Ahmed Abdelfattah Elkholy
Maher Rashed Mohamed
Ayman Al-Sayed Mansi
7. THE IMPACT OF COVID-19
ON THE RETAIL SERVICE QUALITY IN EGYPT
Intro
• The retail environment is changing more rapidly than ever before. It is characterized by intensifying
competition from both domestic and foreign companies.
• The world is facing an extraordinary crisis. The COVID-19 pandemic has sent shockwaves throughout
global communities, dislocated international supply chains and triggered steep selloffs in financial
markets.
• The International Monetary Fund (IMF) published a June 2020 Update to its World Economic Outlook
(WEO), revising its April projections downward. The WEO indicates more significant declines to world
output and trade volumes due to COVID-19 and a slower global economic recovery than initially
predicted.
8. THE IMPACT OF COVID-19
ON THE RETAIL SERVICE QUALITY IN EGYPT
Introduction
(con.)
• Retailers of essential goods such as food, groceries, and healthcare are experiencing increased
demand opportunities for serving consumers at home, while facing challenges of inventory, supply
chain management, delivery, and keeping their facility a safe environment,
• However, retailers of non-essential goods, such as apparel and footwear, are facing a significant drop
in sales and have to adopt new ways to reach and engage customers who are shopping from their
home, just to sustain themselves.
• Technology development is ongoing with an exceptional speed , In this era, retailing has become a
dynamic industry and consumers depending on technology have significantly increased.
9. THE IMPACT OF COVID-19
ON THE RETAIL SERVICE QUALITY IN EGYPT
Introduction
(con.)
• Egypt is one of most diversified economy in the Arab world, and the third largest economy in the
Arab world, its total retail sales amount to US$ 133 billion.
• Egypt retail sector is affected greatly with the COVID-19 pandemic, and faced many noticed shifts and
significant changes.
• Service quality is an essential driver for the success and survival of retailing, so it’ll be essential to
study how it has been affected during this sudden pandemic using three dimensions of retail service
quality (access, reliability, and smart solutions).
11. Literature Review
Challenges
facing Retail
during Covid-19
Dimensions
of
Retail Service
Quality
The importance of
measuring the impact
of COVID-19 on Retail
Service quality
Results from
Previous
Researches
Knowledge
Gap
THE IMPACT OF COVID-19
ON THE RETAIL SERVICE QUALITY IN EGYPT
COVID-19
Pandemic
The Retail industry
in Egypt
The importance
Of
the Retail Sector
Measuring
Retail Service Quality
13. THE IMPACT OF COVID-19
ON THE RETAIL SERVICE QUALITY IN EGYPT
Research
Problem
As mentioned in the literature review, there are many international reports have written
on how the retail sector in general has been affected by the COVID-19 pandemic, but still
only limited numbers of studies in Europe have focused on the impact of COVID-19 on the
retail services quality worldwide. No noticed study was done concerning this specific topic in
the Arab countries. However, a review of retail service quality literature in Egypt indicated
that only one study was done on smart retailing in Egypt, but, there’s no specific study is
published concerning the impact of COVID-19 on the retail services quality in Egypt.
15. RESEARCH QUESTIONS
THE IMPACT OF COVID-19
ON THE RETAIL SERVICE QUALITY IN EGYPT
We can derive from the above-mentioned research problem the following
research questions:
1) Does COVID-19 have impact on retail service quality in Egypt?
2) Which of the three retail service quality dimensions are most affected by the
pandemic?
17. THE IMPACT OF COVID-19
ON THE RETAIL SERVICE QUALITY IN EGYPT
This research aims to:
1) Examine the impact of COVID-19 on retail service quality in Egypt.
2) Identify which of the three retail service quality dimensions are most affected
by the pandemic.
3) Highlight recommendations concerning how retailers can deal with the COVID-
19 pandemic in the future.
19. THE IMPACT OF COVID-19
ON THE RETAIL SERVICE QUALITY IN EGYPT
RESEARCH HYPOTHESIS
H0: There is no significant impact of COVID-19 on retail service quality in Egypt
H01: There is no significant impact of COVID-19 on Access.
H02: There is no significant impact of COVID-19 on Reliability.
H03: There is no significant impact of COVID-19 on Smart Solutions.
20. Research Model
Challenges
facing Retail
during Covid-19
The importance of
measuring the impact
of COVID-19 on Retail
Service quality
Results from
Previous
Researches
COVID-19 Pandemic
The importance
of the Retail Sector
The research model is designed in the above Figure, with illustration of the
dimensions of each variable, where:
COVID-19 is measured as it is.
Retail Service Quality is measured by 3 dimensions: Access, Reliability, and Smart
Solutions.ail Service Quality
Retail Service Quality
Access
Reliability
Smart Solutions
COVID-19
Fig. 5.1Research Model
Source: By the Student
22. THE IMPACT OF COVID-19
ON THE RETAIL SERVICE QUALITY IN EGYPT
RESEARCH METHODOLOGY
This section presents a description of the methods to be used in this study of
discovering the impact of COVID-19 pandemic on Retail Service Quality in Egypt
(measured by three dimensions: Access, Reliability, and Smart Solutions) using
SPSS program version 25 to ensure that the relevant issues are investigated in a
comprehensive method.
This research has applied quantitative research approach.
23. Target Population: Egyptian Retailers from different types who work in Egypt.
Response rate: Questionnaire was sent to 45 different retailers, only 30
responded. This represents a normal response rate.
Instrument for Data Collection
A survey technique is used based on the use of structured (5- Likert Scale).
questionnaire.
The survey questionnaire consists of 4 pages divided into four parts as follow:
First part: Asks for background information of the respondent (gender - age –
city of operation –educational level - occupation).
Second part: Asks about general information about the respondent (nature of
business – number of employees in your company).
Third part: This part is used to measure the three retail service quality
dimensions as follow:
Group 1: The items for measuring Access are 4 questions.
Group 2: The items for measuring Reliability are 5 questions.
Group 3: The items for measuring Smart Solutions are 6 questions.
Population and
Sampling
Survey
25. A. Reliability Analysis (measure reliability
using Cronbach alpha).
B.Descriptive statistics tool: Analyzing the
sample
C. Analyze data using descriptive statistics
tool: Frequencies
D.Compare means using analysis of
variance: one way ANOVA
E. Compare means using one Sample T-
test
F. Testing the research Hypothesis.
Statistical
Inferences used
are as follows:
26. 1) Reliability Statistics for Access Dimension:
The Cronbach’s Alfa of all questions composing the
Access dimension is 76.5% as shown in the table which
means that the reliability is acceptable for the questions
(Q2 - Q5) of the first dimension and consistence.
27. 2) Reliability Statistics for Reliability Dimension:
The Cronbach’s Alfa of all questions composing the
Reliability dimension reached 61.3% after excluding questions
number 8, 9, &10 as shown in the table, which means that
the reliability is acceptable for the questions (Q6&Q7) and
consistence.
28. 3) Reliability Statistics for Smart Solutions
Dimension:
The Cronbach’s Alfa of all questions composing
“the Smart Solutions” dimension is 76.1%, which
means that the reliability is very good with high
internal consistency for the questions forming this
dimension.
Reliability Statistics
Cronbach's Alpha
Cronbach's Alpha
Based on
Standardized Items N of Items
.761 .736 6
29. 1) 30 surveys are collected from retailers in different business
scopes with different levels of occupations and degree of education
in different cities in Egypt.
2) The category of gender is represented by 80% males and 20%
females.
B. Display of
the sample
using
descriptive
tools
Statistics
Gender Age City Education Occupation NatureOfBusiness
No. of
employees
N Valid 30 30 30 30 30 30 30
Missing
0 0 0 0 0 0 0
30. 3) The category of age consists of 40% between the age of 26-35
years old, and 36.7% are between 36-45 years old, while 20% are
above 46 years old.
4) The cities distributed as follows: 46.7% of the sample are from
Cairo, followed by Delta and upper Egypt with same percentage of
sample size 26.7%.
B. Display of
the sample
using
descriptive
tools
31. 5) Concerning the Education levels: 60% of the sample size is bachelor degree
holders, and 20% represents both post graduates and secondary school
graduates.
6) For occupation: 23.3% of the sample size are store managers, 26.7% are
sales or customer service employees, 13.3% are IT employees, 10% of the
sample for both inventory mangers and marketing mangers, and 16.7% are of
other jobs in the retail business.
B. Display of the
sample using
descriptive tools
32. 7) For the nature of business: according to the sample, 36.7% of retailers in
the sample are working in soap/detergents field, 20% are working in
health/beauty/cosmetics field, 20% represents hyper
markets/supermarkets, and 6.7% of the sample are in the fields of
electronics, jewellery and fashion.
8) The number of employees of retailers in the sample is as follows: 46.7%
are operating with fewer than 25 employees, 26.7% are operating with 25-
50 employees, and 16.7% of the sample operating with more than 100
employees, and 10% represents 51-100 employees.
B. Display of
the sample
using
descriptive
tools
33. Measuring the frequencies for the data in each dimension:
As shown in the above table, the sample size is 30 persons,
the mean for the data in the first Dimension (Access) is 4.03.
And according to the continuous scale, the average of the
sample in the first dimension is: “Agree” that the access to
the products has been impacted by COVID-19.
C. Analyze
data using
Descriptive
statistics tool:
Frequencies
Statistics
D1 D2 D3
N
Valid 30 30 30
Missing 0 0 0
Mean 4.03 4.00 4.06
34. The mean for the data in the second Dimension (Reliability) is “4”.
And according to the continuous scale, it means that average answer
of the sample in the second dimension is also: “Agree” that their
stores performs the services at the promised time and insists on
error-free service during COVID-19.
The mean for the data in the Third Dimension (Smart Solutions) is
“4.06”. And according to the continuous scale, it means that average
answer of the sample in the Third dimension is also: “Agree” that the
smart solutions in their stores have been impacted by COVID-19. in
other words, the average of the sample size have agreed that their
stores have maximized the online services (IOT), developed modern
delivery service beyond lockdown time, adapted less cash policy
during COVID-19, and are expecting to depend more on providing
online services even after the pandemic is over.
C. Analyse
data using
Descriptive
statistics tool:
Frequencies
35. Worth to mention that the most impacted dimension by
COVID-19 by slight difference is the Smart Solutions
measures taken by the retail stores during the pandemic
in terms of enhancing the e-payments solutions,
maximizing the online services and the modern delivery
service beyond lockdown time provided by the retail
stores, also expectation to continue such solutions after
the pandemic.
Therefore, COVID-19 has impacted all of the three
dimensions of the research: Access, Reliability and Smart
solutions, and this impact is equally detected by the
sample with degree of Agree.
C. Analyse
data using
Descriptive
statistics tool:
Frequencies
36. This is used to determine the effect of all dimensions
with each category: Gender / Age / City / Education /
Occupation / Natural of Business and Number of
employees.
The ANOVA is made in order to make generalization for
the sample.
ANOVA table tests the population; if accepted, and
then we can generalize our decision.
The accuracy (significance) is less/equal than 5%.
D. Compare
means using
analysis of
variance:
one way
ANOVA
37. According to the above analysis, there is no significance difference
between results obtained from males and females, which means that
the sample have been impacted equally by the covid-19 in terms of the
three dimensions access, reliability and smart solutions as all the results
of different levels of gender with the three dimensions as shown are
more than 0.05 (5%).
D. one way
ANOVA:
analysis of
variance by
Gender
ANOVA
Sum of
Squares
df Mean Square F Sig.
D1
Between
Groups
.001 1 .001 .001 .972
Within Groups 11.591 28 .414
Total 11.592 29
D2
Between
Groups
.052 1 .052 .147 .705
Within Groups 9.948 28 .355
Total 10.000 29
D3
Between
Groups
.208 1 .208 .650 .427
Within Groups 8.977 28 .321
Total 9.185 29
38. According to the above analysis, there is no significance difference
between results obtained from the different categories of age, which
means that the sample with different age groups have been impacted
equally by the covid-19 in terms of the three dimensions access,
reliability and smart solutions as all the results of different levels of
age with the three dimensions as shown are more than 0.05 (5%).
D. one way
ANOVA:
analysis of
variance by
Age
ANOVA
Sum of
Squares
df Mean
Square
F Sig.
D1
Between
Groups
.507 3 .169 .397 .756
Within Groups 11.084 26 .426
Total 11.592 29
D2
Between
Groups
.697 3 .232 .649 .591
Within Groups 9.303 26 .358
Total 10.000 29
D3
Between
Groups
.243 3 .081 .235 .871
Within Groups 8.943 26 .344
Total 9.185 29
39. According to the above table analysis there is no significance
difference between the results obtained from Cairo, Delta, Upper
Egypt or other cities, which means that all cites have been impacted
equally by the covid-19 in terms of the three dimensions access,
reliability and smart solutions as all the results of different cities with
the three dimensions as shown are more than 0.05 (5%).
D. one way
ANOVA:
analysis of
variance by
City
Multiple Comparisons
LSD
Dependent Variable (I) City (J) City
Mean Difference (I-
J) Std. Error Sig.
D1 Cairo Delta .165 .288 .571
Upper Egypt -.022 .288 .939
Delta Cairo -.165 .288 .571
Upper Egypt -.188 .325 .569
Upper Egypt Cairo .022 .288 .939
Delta .188 .325 .569
D2 Cairo Delta .000 .270 1.000
Upper Egypt .000 .270 1.000
Delta Cairo .000 .270 1.000
Upper Egypt .000 .304 1.000
Upper Egypt Cairo .000 .270 1.000
Delta .000 .304 1.000
D3 Cairo Delta -.063 .255 .808
Upper Egypt .167 .255 .519
Delta Cairo .063 .255 .808
Upper Egypt .229 .288 .433
Upper Egypt Cairo -.167 .255 .519
Delta -.229 .288 .433
40. According to the above analysis, there is no significance difference
between the results obtained from post graduate holders, bachelor
degree holders, and secondary school graduates, which means that all
level of education have been impacted equally by the covid-19 in terms
of the three dimensions access, reliability and smart solutions as all the
results of different levels of education with the three dimensions as
shown are more than 0.05 (5%).
D. one way
ANOVA:
analysis of
variance by
Education
Multiple Comparisons
LSD
Dependent Variable (I) Education (J) Education
Mean Difference
(I-J)
Std. Error Sig.
D1
Postgraduate
Bachelor degree -.250 .304 .418
Secondary School -.042 .372 .912
Bachelor degree
Postgraduate .250 .304 .418
Secondary School .208 .304 .499
Secondary School
Postgraduate .042 .372 .912
Bachelor degree -.208 .304 .499
D2
Postgraduate
Bachelor degree -.333 .267 .223
Secondary School -.667 .327 .051
Bachelor degree
Postgraduate .333 .267 .223
Secondary School -.333 .267 .223
Secondary School
Postgraduate .667 .327 .051
Bachelor degree .333 .267 .223
D3
Postgraduate
Bachelor degree .046 .275 .867
Secondary School .000 .336 1.000
Bachelor degree
Postgraduate -.046 .275 .867
Secondary School -.046 .275 .867
Secondary School
Postgraduate .000 .336 1.000
Bachelor degree .046 .275 .867
41. D. one way
ANOVA:
analysis of
variance by
Occupation
ANOVA
Sum of
Squares
df Mean Square F Sig.
D1
Between Groups 1.978 5 .396 .988 .446
Within Groups 9.613 24 .401
Total 11.592 29
D2
Between Groups 2.465 5 .493 1.570 .206
Within Groups 7.535 24 .314
Total 10.000 29
D3
Between Groups 1.878 5 .376 1.233 .324
Within Groups 7.307 24 .304
Total 9.185 29
According to the above analysis, there is no significance difference
between results obtained from different occupations, which means that the
sample have been impacted equally by the covid-19 in terms of the three
dimensions access, reliability and smart solutions as all the results of
different levels of gender with the three dimensions as shown are more than
0.05 (5%).
42. According to the above table analysis, there is no significance
difference between the results obtained from different business
types except for the third dimension, which means that all
business types have been impacted equally by the covid-19 in
terms of access and reliability, but for smart solutions there is a
significance difference between the results obtained from
different business types as all the results as shown less than 0.05
(5%).
D. one way
ANOVA:
analysis of
variance by
nature of
Business
ANOVA
Sum of
Squares df Mean Square F Sig.
D1 Between Groups 1.974 6 .329 .787 .589
Within Groups 9.617 23 .418
Total 11.592 29
D2 Between Groups 1.572 6 .262 .715 .641
Within Groups 8.428 23 .366
Total 10.000 29
D3 Between Groups 6.692 6 1.115 10.291 .000
Within Groups 2.493 23 .108
Total 9.185 29
43. ANOVA
Sum of
Squares
df Mean Square F Sig.
D1
Between
Groups
1.005 3 .335 .823 .493
Within Groups 10.587 26 .407
Total 11.592 29
D2
Between
Groups
2.896 3 .965 3.534 .029
Within Groups 7.104 26 .273
Total 10.000 29
D3
Between
Groups
1.667 3 .556 1.921 .151
Within Groups 7.519 26 .289
Total 9.185 29
D. one way
ANOVA:
analysis of
variance by
No. of
Employees
According to the above table analysis, there is no significance difference
between the results obtained from retailers with different number of
employees, except for the second dimension, which means that all
retailers with different numbers of employees, have been impacted
equally by the covid-19 in terms of access and smart solutions, but for
reliability, there is a significance difference between the results
obtained from different company size with respect of no. of employees
where, the results as shown less than 0.05 (5%).
44. E. Compare means using
one Sample T-test
One-Sample Statistics
N Mean Std. Deviation Std. Error Mean
D1 30 4.03 .632 .115
D2 30 4.00 .587 .107
D3 30 4.06 .563 .103
One-Sample Test
Test Value = 1
t df Sig. (2-tailed) Mean
Difference
95% Confidence
Interval of the
Difference
Lower Upper
D1 26.279 29 .000 3.033 2.80 3.27
D2 27.982 29 .000 3.000 2.78 3.22
D3 29.738 29 .000 3.056 2.85 3.27
45. From all of the above tests, we can reach the following
Hypotheses Test results to state whether there is impact of
COVID-19 on each of the three dimensions used to measure the
Retail service quality in Egypt.
H0: There is no significant impact of COVID-19 on retail service
quality in Egypt. Testing this using the relevant questions, and
descriptive analysis tools showed a significant impact of COVID-
19 on retail service quality in Egypt. So, we reject the
null hypothesis.
H01: There is no significant impact of COVID-19 on Access.
Testing this using the relevant questions, and descriptive
analysis tools showed a significant impact of COVID-19 on
Access in retail service quality in Egypt. So, we reject the
null hypothesis.
F. Testing
Hypotheses:
46. H02: There is no significant impact of COVID-19 on Reliability.
Testing this using the relevant questions, and descriptive
analysis tools showed a significant impact of COVID-19 on
Reliability in retail service quality in Egypt. So, we reject
the null hypothesis.
H03: There is no significant impact of COVID-19 on Smart
Solutions, testing this using the relevant questions, and
descriptive analysis tools showed a significant impact of COVID-
19 on Smart Solutions in retail service quality in Egypt. So,
we reject the null hypothesis.
F. Testing
Hypotheses:
47. The study shows that there is impact of COVID-19 on each
of the three dimensions.
And according to the descriptive analysis of the data
collected, the degree of impact of COVID-19 on each
dimension is “grade 4 “which is interpreted as “Agree”
according to the continuous scale measure, and this
impact is equally sensed among the sample despite there
are different age, education levels, gender, and cities of
operation, except for the nature of business on Smart
solutions and No. of employees for reliability.
Conclusion
49. Recommendations
This study recommends that:
Retailers will need to forecast the potential demand, and be
ready to have enough goods at a store level, under all the
different scenarios they face in order to fulfill their customer
needs.
Retailers should shift to sourcing locally in order to avoid
any shortage in products because of any new sudden shocks
like they faced during COVID-19 shutdown. This will also
make the businesses feel secure especially with regards to
cleanliness and safety practices.
Retailers should diversify their sources and transport
contractors in order to avoid suspension of products.
50. Recommendations
This in turn will require changes in the logistics in Egypt, there
should be an emphasis on more local shipping and movements.
Also, there will be more demand for trains and trucks, which
may put a deeper load on Egyptian transportation system. This
is thus calling for changes in the way we can optimize freight
movement to ensure logistical resources are being used most
efficiently so that retailers can be more reliable by affording
their products to their customers at reasonable prices and be
fast in their delivery.
Retailers should take into consideration that the consumers’
demands have changed: people want fast, low cost, and at their
door right when they want it. This means speed and cost need to
be balanced and optimized. And affordable prices are optimized
too.
Despite of any situation, retailers should be keen to deliver their
products with same features and error-free as shown in their
websites in order to be reliable with the consumers if they want
to gain their confidence for long term relations.
51. Recommendations
Artificial Intelligence and the Internet of Things are the best
smart solutions to ensure that resources are used most
effectively to get high quality goods, delivered on time, and
with as little expenditure as possible.
In order to rapidly match the trend towards digitalization,
the retailers should be agile and rapidly develop and innovate
their strategies and organizational processes, so that they can
survive the changes that environment imposes upon them.
Retailers should start to implement automation throughout
the supply chain. In turn, they should also prepare to begin
training their employees to the new transition.
52. Recommendations
Retailers should improve their digital channels, so that they
can increase their connection with their customers online.
They should rethink their customer experience and find ways
to deliver on customer preferences and needs through digital
channels. So, they should diversify their sales channels.
Safety First: Retailers should think “safe retailing” by
outlining the steps they are taking to keep employees and
customers safe.
Retailers should enhance e-payments deals and transactions.
53. As the retailers should expand their online services,
they should hire more IT and digital marketing
personnel for fast transition towards digitalization.
Retailers is recommended to increase the number of
“SMART stores”, where products and services are
characterized with hybridization between new
technologies and traditional retail features.
Huge financial investments are required to adopt
IOT, so it’s better for retailers to start cooperating
with each other for this sake.
Recommendations
54. The coming future will sure be completely
different in the field of retailing. We will
emerge in a very different world compared to
the one before the pandemic. The old rules
will no longer be applied. Sustainable and
effective retail service quality will be the main
driver to ensure long-term survival, so, it
should be the main goal.
Recommendations
