Vol-31-2023-Paper-29

Malaysian Journal of Consumer and Family Economics (MAJCAFE) Vol 31 (2023)
https://www.majcafe.com : eISSN : 2948-4189
Factors Influencing Consumers' Attitudes and
Intentions Towards Online Shopping - A Survey of a
Sample of Consumers in Algeria
Nassira Alit1, Driss Mazouzi2
1
Faculty of Economic, Business and Management Sciences, University Abd
El Hamid Mehri-Constantine 2, Algeria
2
Faculty of Economics, Business and Management Sciences, University
Mohamed El Bachir El Ibrahimi of Bordj Bou Arreridj, Algeria
DOI: https://doi.org/10.60016/majcafe.v31.29
Abstract
Continuous technological development has changed consumers' online
purchasing behaviours. In developing countries, online retailers face
challenges as they try to promote e-commerce and convince people to shop
online. To achieve this, these merchants must strive to understand these
behaviours and adapt to them. So, it is appropriate for us as researchers to
study the factors that achieve this. This study aims to identify the factors
affecting Algerian consumers' intention to shop online while considering
attitude as a mediating variable.We conducted a survey in Algeria with 293
individuals. We used the convenience sampling method. We analyzed the
data using structural equation modelling. The study found that privacy,
website design, and attitudes affect people's intentions to shop online. This
study showed the indirect effect of shopping convenience on online purchase
intentions mediated by attitudes.The study also confirmed partial mediating
roles of attitudes of consumers between (shopping convenience, perceived
privacy, website design) and online purchase intention. The study found that
the Time-saving factor does not affect attitudes or intentions to purchase
online.The current study provides retailers and marketers insight into
developing e-business strategies to increase online purchase intentions.
Therefore, online retailers need to understand consumers' intentions and
attitudes toward online shopping, analyze the factors influencing them, and
seek to change these factors to convince consumers and motivate them to
buy.
Keywords: customer attitudes on online buying; online shopping intention;
perceived privacy; shopping convenience; time-saving; web design
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1.0
Introduction
Thanks to modern life's continuous digitalization. Today,
consumers from all around the world are benefiting from Internet
transactions. Due to the rapid increase in Internet access and global
adoption, the number of people making transactions online is rising.
The number of electronic buyers will have reached 2.64 billion by 2023.
They represent 33.3% of the world's population. Currently, the number
of digital buyers has increased by 80 million compared to 2022, which
consists of an increase of 3.1% (OBRELO, 2023).
Considering the Algerian market as a market on which we
conducted the experimental study, we find that its population was
approximately 45.74 million peoples in September 2023 (Worldometer,
2023). Algeria has one of the largest Internet markets in Africa. In 2022,
the country recorded the sixth-largest number of Internet users in
Africa. Their number reached about 27 million in 2022, which means
that more than 60 per cent of the country's population was online.
(Statista, 2023).
The statistics mentioned above may indicate the readiness of
these economies for electronic markets and the excellent potential for
the growth of e-commerce in the country, but, in reality, the Algerian ecommerce market is witnessing relatively limited growth and is still at
the beginning of its journey. In 2022, only 2.8 per cent of the population
in Algeria made a purchase online (Statista, 2023), compared to 33.3
per cent globally. According to trade group GIE Monétique, there were
291 online retailers in Algeria by the end of 2022. Retail e-commerce
sales reached $120 million in 2022(International Trade Administration,
2023).
These numbers require research and investigation, especially
about understanding consumers’ interest in using electronic shopping
in Algeria - as a developing country and a market that appears to be
promising and may develop shortly-. On the other hand, looking at the
academic aspect, we notice that there is momentum in studies that
addressed the behaviour and intention of shopping electronically in the
markets of developed countries, in contrast to studies in developing
countries that received little attention(Bhatti et al., 2022), especially
Algeria, perhaps because it is at the beginning of its journey with
electronic commerce.
Taking into account the importance of e-commerce activities for
the economies of developing countries such as Algeria, as the
prospects for growth through online sales are promising in the future,
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and the relatively new e-commerce among individuals and institutions,
Also taking into account the impact of the Covid-19 pandemic and the
change it has caused on consumer behaviour around the world, and
Algeria is no exception to it (García-Salirrosas et al., 2022). There is a
need to conduct studies that allow these organizations to understand
consumer behaviour toward electronic shopping through a deep
understanding of shopping intentions and attitudes as crucial factors
and direct their efforts toward what is best for them, especially since
there are only a few studies in Algeria that addressed online shopping
intentions.
The researchers of this study agree with the literature that has
indicated the need to study the critical factors that can encourage
consumers in developing countries to adopt e-commerce (Bhatti et al.,
2022; García-Salirrosas et al., 2022; Peña-García et al., 2020),
especially in North Africa, and our study fills this gap.
On the other hand, traditional shopping methods have become
insufficient for consumer, who constantly searches for the best and
easiest ways to buy the products they need. Thanks to the use of
technology and the Internet in marketing, many benefits have emerged
for the consumer, such as comparing and searching for products and
their prices easier than traditional shopping, quick access to products
from anywhere in the world, a way to reduce effort, time and cost for
the customer, obtaining the necessary information, many alternatives
for purchase and after-sales amenities(Lakshmi, 2016; Roy & Goel,
2020; Vinh & Ly, 2021; Parajuli et al., 2021).
Despite all the advantages mentioned, online shopping has
problems and obstacles that may prevent the consumer from
completing the purchase process. Consumer reluctance to purchase,
which arises from various problems in online shopping, becomes an
obstacle to the growth of e-commerce. Therefore, the advantages and
disadvantages of online shopping compared to in-store shopping play
a role in attitudes toward this activity and consumer intentions to shop
online (Diaz-Gutierrez et al., 2023).
Purchase intention is one of the most crucial factors that
influence online shopping decisions (Gamage & Jayatilake, 2019). A
better understanding of purchase intention is essential for
understanding consumer behaviour and explaining many marketing
phenomena and problems. Therefore, studies on purchase intention
are of paramount importance for the success of any online retailer and
for improving a company's business (Ho Nguyen et al., 2022; PeñaCopyright © 2018 Malaysian Consumer and Family
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García et al., 2020). It also allows marketers to evaluate the future
growth of online commerce by forecasting online shopping rates.
The current study aims to address the gaps in previous literature
in developing countries by examining the antecedents of intention to
purchase via the Internet in Algeria, namely: ease of shopping, saving
time, website design, and perceived privacy and security. In addition,
attitude is positioned to mediate the relationships between antecedents
and consumer purchase intention.
2.0
Literature Review
2.1
Online Purchase Intention
According to Schiffman et al. (2010), Consumer behaviour
refers to the actions consumers take when they buy, use, evaluate,
search for, and dispose of goods and services that they think will satisfy
their needs. Online shopping behaviour refers to the process of buying
goods and services over the Internet. The process is carried out
through five steps, similar to traditional shopping behaviour (Li &
Zhang, 2002). The consumer senses the need to buy, so he accesses
the Internet with the aim of purchasing and starts searching for
information and all available options. In the end, he purchases the
products that suit his needs. Before making a final purchase,
consumers are exposed to many factors that influence or prevent them
from making a final decision (Kumar & Sobha, 2016).
Academics have used many theoretical models to explain
consumer behaviour in the electronic market(Jadil et al., 2022; Vo et
al., 2022). Among the most important of these models that were
adopted in this study are the Theory of Reasoned Action (TRA)
(Fishbein & Ajzen, 1975) and the Theory of Planned Behavior (TPB)
(Ajzen, 1985).
Online shopping intention refers to buyers' intention to exchange
on shopping websites and is a predictive factor in their shopping
decisions (Dachyar & Banjarnahor, 2017). According to (Peña-García
et al., 2020), online purchase intention refers to the extent to which a
consumer wants to purchase a product from an online retailer. It is
considered an indicator of how well individuals are prepared to perform
a particular behaviour.
Purchase intention describes a consumer's potential and
willingness to make a purchase. Before buying, the buyer has an
emotional decision, which is the willingness or intention to buy, through
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which the consumer's behaviour and future purchases can be
predicted. Therefore, profoundly comprehending the variables
influencing customers' buying intentions will help motivate their
behaviour (Lin & Shen, 2023). According to Ajzen & Fishbein (1977),
cited in (Peña-García et al., 2020), to predict customer behaviour, it is
crucial to understand the attitudes and internal factors that lead to
buying intentions.
We point out that many factors precede the formation and the
change of attitudes and online purchase intentions. Among these
factors, we cite the advantages and benefits provided by online
shopping, trust, ease of use, security and privacy, saving time, and
website design, which were derived from previous studies, such as
(Comi & Nuzzolo, 2016; Crocco et al., 2013; Naseri et al., 2021;
Schneider & Tezza, 2020; Shergill & Chen, 2005).
As long as the Algerian consumer is at the beginning of his use
of electronic shopping, we believe these factors are very appropriate to
the circumstances in which this consumer lives. His trust in technology
will be low, so we added privacy, perceived security, and the
importance of shopping convenience at this stage. We will also explain
the reasons for choosing the other factors: saving time and designing
the website according to their importance on purchase intention.
Without forgetting the importance of attitudes, which will act as an
intermediary variable between the influencing factors and shopping
intention.
2.2
Consumer Attitudes Toward Online Shopping
Attitudes toward online shopping are defined as the customer's
favourable or unfavourable thoughts about their online shopping
activities(Gamage & Jayatilake, 2019). Attitudes toward behaviour
come not only from evaluating the performance of a particular
behaviour but also from evaluating the expected results of performing
such behaviour, and the level of attitudes toward behaviour can vary
across individuals based on their experience and clients'
characteristics and mindsets (Dinesh, 2021).
Although attitudes generally lead to behaviour, they are
sometimes not synonymous with behaviour. Attitudes reflect either a
positive or an unfavourable evaluation of a particular subject, which
may or may not lead to the behaviour. Accordingly, attitudes may push
individuals toward a specific behaviour or keep them away from it
(Tamilarasi & Angayarkanni, 2016).
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Many studies have confirmed the importance of attitude in
forming purchase intention, such as Lu et al. (2014), Park & Cheon
(2019), and Naseri et al. (2021). So, these attitudes must be studied
and well-identified.
2.3
Shopping Convenience
Forsythe et al. (2006) defined the convenience of shopping as
the ability to shop at any time from various websites without visiting
physical stores, which results in less physical and emotional distress
than traditional shopping.
Convenience relates to ease of use in terms of interaction with
the website and the purchase process, which includes placing an order,
making a payment, and receiving a delivery of products or services.
''Ease of use'' is the consumer's perception that online shopping will
require little effort, affecting consumers' intention to shop online(Perea
y Monsuwe et al., 2004).
Service convenience is a significant element influencing
consumers' adoption of online shopping; therefore, online retailers
must enhance the online convenience aspects of their service offerings
(Saha et al., 2021). The Kim et al. (2004) study found that consumers
are primarily motivated to shop online by convenience.
2.4
Time-Savings
Alreck & Settle (2002) showed that online shopping helps
consumers to save time. According to Nabot et al. (2014), the
interfaces of online purchasing websites should be simple and welldesigned, and the interface should save users' time and help them
quickly search for the product, especially for those with little prior
expertise. Time-Saving is the primary antecedent predicting perceived
value(Escobar-Rodríguez & Bonsón-Fernández, 2017).
Online shopping allows consumers to save time as they do not
need to visit one physical store to another, and they can obtain
information about products and their prices from multiple sources in
minutes. This time-saving feature increases consumers' shopping
satisfaction, thus increasing purchase intention from online stores
(Rashaduzzaman, 2020).
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2.5
Web Design
Some shopping sites retain and attract more online shoppers
than others because they have great designs and are easy to navigate
(Kwaku & Antwi, 2021). Website design is critical in marketing efforts.
A well-designed website not only keeps visitors occupied but also aids
in acquiring new consumers (LAI et al., 2020).
The study of (Saleem et al., 2022) proved that website quality
positively increased consumer online purchase intentions. Naseri et al.,
(2021); Porat et al., (2007) found that web design positively influenced
customer attitudes toward online shopping and their intentions.
2.6
Perceived Privacy and Security
To complete electronic purchasing transactions, many
companies need information about the consumer, but sometimes this
may cause the latter to have privacy concerns, which in turn leads to
reducing trust and enhancing awareness of risks and indirectly affects
consumer behaviour and their willingness to shop electronically (Wang
et al., 2019). Perceived security is a strong determinant of trust
(Escobar-Rodríguez & Bonsón-Fernández, 2017), and trust is also
considered the most crucial factor for social commerce adoption in
developing countries(Paramita, 2023).
The difficulty of protecting privacy and the lack of security of
consumer personal information is one of the most important reasons
consumers avoid online shopping (Jun & Jaafar, 2011). Payment
security is also vital because people are concerned about the security
of their credit cards and personal information (Nabot et al., 2014).
Pereay Monsuwe et al., (2004) explained that low consumer
confidence in online shopping, due to low privacy or misuse of personal
information negatively affects the attitude toward online shopping.
However, higher security and privacy positively affect consumer
confidence and attitudes due to the lower risk of sharing information.
Many studies have emphasized the importance of transaction
security and privacy, which may affect the consumer and his intention
to shop. Among them: (Do et al., 2019; Zhang et al., 2019; and Wang
et al., 2019).
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3.0
Methodology
3.1
Research Framework
Based on the literature on the topic of consumers' attitudes and
intentions toward electronic shopping, the study model can be adopted
in the following form:
Figure 1 : Research Framework
The model was designed based on the previous analysis and
related work such as Dani (2017), Naseri et al. (2021), Schneider &
Tezza (2020), and Li & Zhang (2002). The proposed model included
the following variables: first, the independent variable represented by
the factors (shopping convenience, Time-Saving, Privacy, and website
design). The mediator variable is consumers' attitude toward electronic
shopping, and finally the dependent variable is the intention to
purchase online.
Hypothesis:
H1a: Shopping convenience influences consumer attitudes toward
online purchasing.
H1b: Web design influences consumer attitudes toward online
purchasing.
H1c: Perceived Privacy and security influences consumer attitudes
toward online purchasing.
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H1d: Time-saving influences consumer attitudes toward online
purchasing.
H2a: Shopping convenience influences online shopping intention.
H2b: Web design influences online shopping intention.
H2c: Perceived Privacy influences online shopping intention.
H2d: Time-saving influences online shopping intention
H2e: consumer attitude toward online purchasing affects online
shopping intention.
H3a: Consumer attitude toward online purchasing significantly
mediates the relationship between shopping convenience and
online shopping intention
H3b: Consumer attitude toward online purchasing significantly
mediates the relationship between web design and online
shopping intention
H3c: Consumer attitude toward online purchasing significantly
mediates the relationship between perceived Privacy and online
shopping intention.
H3d: Consumer attitude toward online purchasing significantly
mediates the relationship between time-saving and shopping
intention.
3.2
Research Methods
Based on the type of collected data and its function, this study
involved quantitative research to examine the impact of shopping
convenience, time-saving, perceived Privacy and security, and web
design on consumer attitudes toward online shopping and purchase
intention. A non-random sample was used (convenience sample),
where the questionnaire was distributed electronically, and was filled
out by 293 Algerians. Responses to the questionnaire were analyzed
using Amos version 26, and Table (1) shows the demographic
characteristics of the study sample:
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Table 1 : Characteristics of the Respondents
Gender
Age(in years)
Income
Education level
Male
Female
18-30
31-50
51-70
Above 20000 DZD
20000-40000 DZD
40001-60000 DZD
From 60001DZD and more
Intermediate education
high school education
University level
Frequency (n) Percentage
(%)
211
72,0
82
28,0
179
61,1
111
37,9
3
1,0
53
18,1
107
36,5
76
25,9
57
19,5
7
2,4
23
7,8
263
89,8
Regarding gender, we note from Table 1 that the percentage of
males amounted to (72 %) and the percentage of females (28%). For
the age group, the most significant percentage was for the category
from 18 to 30 years, with a rate of (61.1%), followed by the age group
between 31 and 50 years, with a rate of (37.9%), while the percentage
of the category (between 51 and 70 years) was only 1%. For the
monthly income, the most significant percentage was for the class
(from 20,000 DZD and less than 40,000 DZD) with a rate of (36.5%),
followed by the income category (from 40,001 DZD and less than
60,000 DZD) with a rate of (25.9%), followed by the income category
(more than 60,000 DZD) with a rate of (19.5%). In contrast, the last
class (less than 20,000 DZD) accounted for (18.1%). For the
educational level, the category of individuals with a university level
accounted for the most significant percentage (89.8%), followed by the
high school level (7.8%).
3.3
Questionnaire Design
We adapted the survey instrument in our study based on
previous related work. We measured the variables: shopping
convenience, time saving, and web design through Dani (2017).
However, we measured perceived privacy and security through Dani
(2017) and Kim et al. (2008) scale items. We measured consumer
attitude toward online shopping by adapting the items of Nguyen et al.
(2019) scale. While online purchase intention was measured using
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three items from Kim et al. (2008). Each measurement indicator for all
variables was scored on a 5-point Likert scale, ranging from 1(strongly
disagree) to 5(strongly agree). Table 2 lists the items used in our
research.
4.0
Research Findings and Discussion
Confirmatory factor analysis (CFA) was first used to evaluate the
constructs and to check the validity of the measurement model. The
hypotheses were then tested using a structural model. Structural
Equation Modeling (SEM) was applied to validate the research model
and hypotheses. According to Hair et al., (2010), the SEM report (the
measurement and the structural models) should ensure an good fit to
the data, which may be measured using various commonly used
goodness-of-fit indices.
4.1
Measurement Model
Firstly, Cronbach's Alpha was utilized to evaluate the reliability
of the survey instrument in this study. Table 2 reports Cronbach’s Alpha
values for convenience, time-saving, perceived Privacy and security,
web design, attitudes, and intentions to purchase online. The results
confirmed that all Cronbach's Alpha values exceeded 0.70, which
indicates a good level of internal consistency (Cortina, 1993).
Table 2 : Items Measuring the Reliability of the Survey Instrument
Mean
Shopping convenience
− I can purchase things at any moment. Online shopping
is available 24 hours a day
− Online shopping gives me more options to choose from
− When buying online, it is convenient to select and
compare products.
Time-saving
− Product evaluation and selection during online shopping
takes less time
− Online shopping does not waste time
Perceived Privacy and security
− Online shopping provides security and Privacy
− I like online shopping from a trustworthy website
− I feel safe while shopping online
4,09
4,12
Cronbach’
s Alpha
0,758
4,14
4,01
3,74
3,76
3,72
3,94
3,82
4,20
3,94
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0,726
0,745
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Mean
Web design
− When purchasing online, I prefer to do so from a site
that offers security, ease of browsing, and ordering
convenience.
− Website design helps me search for and choose the
right product while shopping online
− I prefer to purchase from a website that delivers
accurate information.
− I believe that getting used to the website before the
actual purchase order reduces the risks of online
shopping
Attitude
− Using online shopping sites is a good idea that allows
me to purchase products that are not available around
me
− I like the idea of using the Internet to purchase the
goods I need
− Buying goods from websites is a wise idea
Intention
− I expect that I will use the websites regularly to
purchase more goods in the future
− I wish to purchase via the Internet goods soon
− I intend to recommend to my friends to shop online.
3,98
3,76
Cronbach’
s Alpha
0,816
3,94
4,08
4,00
4,02
4,02
0,878
4,07
3,98
4,02
4,04
0,897
4,06
3,98
In this study, AMOS 26 was used to do a confirmatory factor
analysis (CFA). The fit indices indicated a good fit to the data
(χ2=266,970, p=0,000, χ2/df=2,225; GFI=0,912; CFI=0,947;
RMSEA=0,065). The Composite Reliability (CR) and Average Variance
Extracted (AVE) were used to assess convergent and discriminant
validity. As shown in Table 3, all CRs are above 0,7(ranging from 0,742
to 0,897), and all AVE values (ranging from 0,528 to 0,745) are more
than 0,5 (Hair et al., 2014). The results of this analysis allowed us to
establish the reliability and convergent validity of each conceptual
framework construct.
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Table 3 : Convergent Validity and Discriminant Validity
Attit
Conv
Time
Priv
Desi
Inte
CR
0,878
0,769
0,742
0,795
0,827
0,897
AVE
0,706
0,528
0,595
0,564
0,546
0,745
MSV
0,642
0,371
0,284
0,440
0,396
0,642
MaxR(H)
0,879
0,782
0,802
0,799
0,841
0,905
Attit
0,840
0,609
0,361
0,643
0,629
0,801
Conv
Time
Priv
Desi
Inte
0,726
0,486
0,582
0,545
0,568
0,771
0,533 0,751
0,386 0,500 0,739
0,357 0,663 0,586 0,863
CR: Construct Reliability; AVE: Average Variance Extracted; MSV: Maximum Shared
Variance
Construct discriminant validity was assessed using AVE,
maximum shared variance (MSV), and construct squared correlation
coefficients. As shown in Table 3, the AVE values were more than the
MSV values, and the square root of the AVE for each construct (The
square root of AVE is indicated by the bold value shown in the diagonal
of Table 3) was greater than its estimated correlation coefficients with
constructs. All of these findings revealed that all of the constructs had
appropriate discriminant validity.
4.2
Structural Model with Path Coefficients
The formulated hypotheses were tested using a structural
model. As shown in Figure2, and all fit indicators suggested an
appropriate model:(χ2=0,000; p=0,000; GFI=1,000; CFI=1,000;
TLI=1,024, RMSEA=0,000).
Figure 2 : Structural Model with Path Coefficients
Table 4 summarizes the results of testing the relationships
among the different variables using the structural model.
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From Table 4, all paths were significant leading from shopping
convenience, perceived Privacy, and website design toward attitudes
(p<0.001). Hence, the results support H1a, H1b, and H1c. all paths
were significant leading from perceived Privacy, website design, and
attitude toward purchase intention (p<0.001). Hence, the results
support H2b, H2c, and H2e
Table 4 : Summary of the Structural Model Path Coefficients
Hypotheses
Findings
H1a
supported
H1b
H1c
H1d
H2a
H2b
H2c
H2d
H2e
β:Path
S.E t-Value p-Value
coefficient
s
Convenience ---> Attitude
0,250
0,057 4,399 <0,001
Design_websit ---> Attitude
e
Privacy
---> Attitude
time_saving ---> Attitude
Convenience --->
Design_websit --->
e
Privacy
--->
time_saving --->
Attitude
--->
0,320
0,048
6,642
<0,001
supported
0,314
-0,018
0,056
0,039
5,606
-0,450
<0,001
0,652
supported
Not supported
intention
intention
0,062
0,133
0,052
0,045
1,201
2,929
0,230
<0,001
Not supported
supported
intention
intention
intention
0,216
0,000
0,484
0,052
0,035
0,051
4,169
0,011
9,448
<0,001
0,991
<0,001
supported
Not supported
supported
On the other hand, the path coefficients were insignificant from
time-saving to attitudes (p>0.05). Hence, the finding does not support
H1d. The path coefficients were also insignificant from time-saving and
shopping convenience to purchase intention (p > 0.05). Hence, the
result does not support H2a and H2d.
4.3
Mediation Test
Using structural equation modelling, the direct and indirect
effects of constructs on each other can be measured. Table 5
summarizes the mediation results and presents the direct, indirect, and
total effects of attitudes toward online shopping and consequently
accepts or rejects the hypotheses H3a, H3b, H3c, and H3e.
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Table 5 : Summary of Direct and Indirect Effects
Time_Saving Convenience
Total effect
attitude
Intention
-0,018
-0,008
0,250
0,183
Web
Design
0,320
0,288
Privacy Attitude
0,314
0,368
0,484
Direct effect
attitude
Intention
-0,018
0,000
0,250
0,062
0,320
0,133
0,314
0,216
0,484
Indirect effect
VAF
Intention
-0,009
/
0,121
66,1%
0,155
53,8%
0,152
41,3%
0,000
Total effect and Variance Accounted For (VAF) can be used to
test the strength of the mediator. The VAF value represents the indirect
effect's beta coefficient concerning the overall impact. A VAF value
greater than 80% denotes complete mediation, between 20% and 80%
denotes partial mediation, and a value lower than 20% denotes no
mediation (Hair et al., 2014).
Since saving time did not have a significant effect on attitudes,
H3d was not supported, meaning consumers' attitudes toward online
purchasing do not mediate the relationship between saving time and
intention to shop online.
The results in Table 5 show that H3a was supported since the
value of VAF ranges between 20% and 80%, stating that attitude plays
a role as a partial mediator, and this mediator can explain 66.1% of the
effect of shopping convenience on shopping intention.
The results also show that H3b was supported since the value
of VAF ranges between 20% and 80%, stating that attitude plays a role
as a partial mediator. This mediator can explain 53.8% of the effect of
web design on shopping intention. Finally, H3c was supported since
the value of VAF ranges between 20% and 80%, stating that attitude
plays a role as a partial mediator. This mediator can explain 41.3% of
the effect of perceived privacy on shopping intention. The following
figure summarizes the previous factors influencing the intention and
attitude toward online shopping.
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Figure 3 : Testing SEM for Factors Affecting Online Shopping Intention
5.0
Discussion and Implications
This study showed that shopping convenience has a positive
effect on attitude and the indirect impact of shopping convenience on
online purchase intentions via attitude toward online purchasing. This
finding is consistent with several previous researches such as Naseri
et al., (2021); Delafrooz et al.(2009), Kim et al.(2004), Rashaduzzaman
(2020), Tanadi et al.(2015); THAO & HAI (2016); and Kim et al.,(2004),
which showed that shopping convenience has the most substantial
effect on respondents' purchase intention. According to Tanadi et al.
(2015), shopping convenience, including time, effort, and stress, was a
significant motivating factor influencing the intention to shop online. A
study by Thao & Hai (2016) also showed that perceived benefits
positively impact women's intention to shop apparel online. In contrast,
shopping convenience has the most substantial effect on respondents'
intentions.
The results of the study (Schultz & Izquierdo-Yusta, 2011)
proved the critical role of Internet Convenience on the intention to use
the Internet to purchase. The results of the study (Jiang et al., 2013)
also suggest that The greater the convenience perceived in searching,
transactions, possession, and post-purchase, the greater the possibility
of repurchasing and recommendation by the customer, hence the
online shopping convenience is positively related to behavioural
intentions. Kakar & Kakar (2020) also showed that convenience
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dimensions significantly impact intention for both in-store and online
shopping.
Therefore, the consumer's ability to purchase desired products
quickly, the possibility of making a comparison between different
products through online shopping sites, the availability of a wide range
of products, and obtaining sufficient information using simple clicks and
with less effort and time, all of these factors affect his intention to buy
in a positive way. This prompts retailers to pay attention to the ease of
shopping and make more efforts to make online shopping easy and
provide more advantages and facilities that motivate the consumer to
shop online.
Contrary to the assumption of the study researchers - based on
reality and based on previous studies - that time-saving has a positive
impact on the intention to shop, the results of the research did not
support the hypothesis and proved that saving time did not affect either
the intention to shop or the attitude. These results are inconsistent with
those found by Alreck & Settle (2002) and (Escobar-Rodríguez &
Bonsón-Fernández, 2017); the latter found that time-saving is a critical
antecedent that predicts perceived value and the last effects online
fashion purchase intention. However, they are consistent with those
found by Rashaduzzaman (2020).
Saving time does not affect shopping intention because of the
long time to receive the ordered products, especially since Algeria is a
developing country, which may cause obstacles during payment and
delivery. This finding associated with time-saving requires further
investigation.
The third result of this study was that the effect of website design
on purchase intention was positive and significant. This finding is
consistent with several related works, such as those of Haryeni (2021),
Porat et al.(2007), Nguyen et al.(2019), and Naseri et al. (2021).
The success of e-commerce businesses depends to some
extent on their ability to attract customers and encourage them to shop
through their websites. One of the ways to achieve this in developing
countries is to have a good website design that attracts consumers, is
easy, and helps keep visitors browsing the site for a long time (Kwaku
& Antwi, 2021). The study of (Saleem et al., 2022) proved that website
quality positively increased consumer online purchase intentions. In
another study conducted by Khialani (2018), the results demonstrated
that each of the components of website design had a statistically
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significant effect on online trust, and the latter mediated the impact of
website design factors on purchase intention.
Haryeni & Hirma's (2022) research showed that the design and
layout of the online website significantly affect the consumer's attitude
toward online shopping. Dinesh (2021) discovered that the perceived
image of a website is related to various elements, the most important
of which is the website's design, and has an important impact on the
online store's attitude. Naseri et al. (2021) and Porat et al. (2007) found
that web design positively influenced customer attitudes toward online
shopping and their intentions.
We justify the importance of the impact of website design on the
intention by the fact that the consumer in electronic shopping is far from
the merchant and the product and that most of his dealings will be with
the website; this is what makes website design, according to our belief,
the most important thing in convincing the consumer, a factor that
cannot be overlooked and may have significant effects. Therefore,
electronic retailers must pay attention to website design and employ all
means to make the shopping site attract many visitors, retain them for
a long time, urge them not to change the website, and, most
importantly, motivate and persuade them to buy.
The fourth result of this study was that the effect of perceived
privacy and security on purchase intention was positive and significant.
This finding is consistent with Do et al. (2019) and Zhang et al. (2019),
who showed that perceived transaction security positively correlates
with online purchase intention and intention to use mobile payment.
Wang et al. (2019) also proved that consumers’ personal privacy
concerns affect consumers’ purchase intention in mobile commerce.
(Naseri et al., 2021) also concluded that trust and privacy security
positively influence consumers' attitudes and intentions.
We justify the importance of perceived privacy and security in
shopping intentions because individuals in Algeria, a developing
country, consider electronic technology for commercial transactions
fraught with risks, especially since they are beginning their experience
with electronic commerce. Therefore, retailers in this country must
raise individuals' confidence in electronic shopping by increasing
possible methods to maintain their privacy and information security.
According to the results of this study, the attitude toward
purchasing was the most influential factor on purchase intention among
the previous elements. This finding is consistent with those of Park &
Cheon, (2019) who indicated that brand attitude influences purchase
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intent, where the purchase is not necessarily the action that follows
purchase intention. This is known as the gap between intentions and
actual behaviour, and this gap is attributed to consumer attitudes.
Therefore, the study of consumer intent is seen as an acceptable tool
for assessing consumers' attitudes when making a purchase(Naseri et
al., 2021)
Understanding consumer attitudes helps predict the online
shopping rate and their behaviours and intentions. Lu et al. (2014)
showed that when an online influencer makes a favourable
recommendation, the purchase intention increases, which results in a
positive impression of the product and positive attitudes toward it. Since
- according to the results of the study - attitude has the most substantial
influence on shopping intention, it is necessary to harness various
marketing efforts to enhance the user's positive attitudes through
continuous improvement in the factors that influence him because it will
positively affect the intention to shop online.
6.0
Conclusion and Recommendations
The current challenge facing retailers - especially in developing
countries such as Algeria - is how to deal with technology that is leading
to significant changes in the business world, and among the results of
these changes is a change in purchasing behaviours among
consumers over the Internet. This, in turn, may affect the performance
of online retailers, necessitating the need to understand these
behaviours and take appropriate marketing strategies.
This research developed a framework for improving our
comprehension of consumers' online buying intentions. The results
revealed three key factors influencing consumers' online purchase
intention: perceived privacy, ease of use, and website design.
Additionally, these factors significantly improve the attitudes of
consumers and the purchase intentions of the latter. So, such factors
are the primary influencing aspects of online shopping in Algeria.
However, the study's findings have noticed the insignificant
effect of the "time-saving" factor on attitude and online purchase
intention. The study also confirmed the partial mediating roles of
consumers' attitudes toward online shopping (shopping convenience,
perceived privacy, and website design) and purchase intention.
The study also confirmed that shopping convenience is
important when individuals shop process, as it gives them greater ease
and more options. The study's results confirmed the importance of
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privacy and security, as individuals prefer to buy from trustworthy
websites that provide safety and ensure privacy. The website's design
helps individuals in online shopping, as they like sites that enable them
to search for products easily, choose the appropriate product, and
provide accurate and helpful information.
Therefore, online retailers must pay attention to the element of
ease of shopping and provide more advantages and facilities that
motivate the consumer to shop online, as well as pay attention to
designing their websites and making them easy to use, simple, and
convenient, and the necessity of providing a design that encourages
consumers to shop online. Retailers in this country must also raise
individuals' confidence in online shopping by using various methods to
maintain their privacy and the security of their information.
Finally, Marketers need to know consumer behaviour toward
online shopping. So, it is crucial to identify the factors that affect his
attitudes toward online shopping and his intention to reach a purchase
decision. While these findings provide important insights into online
shopping intention in a developing country, we acknowledge some
limitations. Convenience sampling limits the generalizability of the
results to the entire population of Algeria. Undoubtedly, additional
factors impact online purchase intention, but they were not examined
in this study. Future research must consider other variables that affect
customers' e-shopping intention, such as online shopping experience
and innovation.
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