Volume 4, Number 3, March 2023 e-ISSN: 2797-6068 and p-ISSN: 2777-0915
Calvin Prayandi, Imran Pradipta,
Muhammad Rizki, Peri Akbar Manaf
Sekolas Bisnis
Binus, Indonesia
Email: [email protected],
[email protected], [email protected].
|
KEYWORDS Covid-19; shopping; online |
ABSTRACT Online Shopping is the
act of buying products and services through an online store or
e-commerce. The culture of online
shopping in Indonesia began to develop around the 2000s with the introduction
of the internet. One of the benefits obtained by online shopping is that it
makes shopping easier and more practical.
Buyers do not need to spend time and spend on a trip to a physical
store. It has also created a change in one's behavior in shopping. The
purpose of this research is to find out daily needs during the Covid-19
pandemic. This research is a
quantitative study in which a systematic empirical investigation of phenomena
that can be observed using statistical, mathematical, or computational
techniques is carried out. Predefined and highly structured data collection
techniques are a major factor in quantitative research design when associated
with positivis. this study shows what factors
influence buyers' interest in buying a product at Online Groceries during the
pandemic. And from the results of our research shows that one of the accepted
and most significant factors influencing buyers' interest in buying at Online
Groceries is from their Effort Expectancy |
INTRODUCTION
The development of technology certainly has an impact on people's
behavior and life, especially on the lives of the current generation. People
are now familiar with the internet through various devices such as smartphones,
laptops, computers, and others. Human life today is also inseparable from
internet technology, for example, the increasingly massive development of
online shopping has brought changes to the way humans’ shop. Online Shopping is the act of buying products
and services through an online store or e-commerce (Koch, Frommeyer, & Schewe, 2020). The culture of online shopping in Indonesia began to
develop around the 2000s with the introduction of the internet. One of the
benefits obtained by online shopping is that it makes shopping easier and more
practical. Buyers do not need to spend time and spend on a trip to a physical
store. It has also created a change in one's behavior in shopping. Consumer
shopping behavior is a collection of decision-making processes and subsequent
behavior, planned and unplanned, and determined by internal and external
factors (Sharma & Sonwalkar, 2013).
Since February 2020, the world, including Indonesia, has been shocked by
the COVID-19 outbreak which has been declared a pandemic by the World Health
Organization (WHO). As of September 21, 2020, statistics reveal the largest
number of incidents and the highest number of deaths in the United States,
namely 6,660,003 positive cases and 197,442 deaths (Organization, 2019). On the same date, Indonesia reached 248,852 positive
cases and 9,677 deaths. Thus, the case fatality rate (CFR) has reached 4.20%
which is relatively high compared to America which has the highest number of
deaths. As a result, during the COVID-19 pandemic, the government made a policy
of social restrictions and activities in public spaces known as PSBB/ PPKM. One
of the sudden changes imposed by social restrictions and activities is the use
of various higher technologies such as
internet-based services to
communicate , interacting, and working from home (Pandey & Pal, 2020). Consumers are more likely to change their
preferences and behavior patterns such
as switching to online shopping and alternative pickup and delivery options (Dey, Al-Karaghouli, & Muhammad, 2020).
With many people being restricted in their activities due to the COVID-19
protocol policy by staying at home, there is a fairly rapid increase in online
shopping. The results of the PT. Snapcart Digital Indonesia (2020) shows that online
shopping for daily needs ranks first most used by consumers with a percentage
of 76% during quarantine. Due to these changes, consumers face the need to
adopt and use certain technologies practically in a short period of time to
cope with the new reality. The adoption of a technology has become a broad
field of research based on several theoretical foundations. One of the most
widely used and commonly used theories in explaining the use and adoption of
technology is the Unified Theory of Acceptance and Use of Technology (UTAUT).
However, the emergence of new conditions due to the COVID-19 pandemic
has created unique conditions where users do not have time to go through the
usual decision-making process of technology adoption, early use and post-adoption
phase of use (Erjavec & Manfreda, 2022). The transition between different stages occurs more
quickly affected by social restrictions, in which users do not have the same
access to information resources when making decisions (Raza, Qazi, Khan, & Salam, 2020). Therefore, the question arises of how and to what
extent the direct determinant effect of (Venkatesh, Thong, & Xu, 2022) on the decision to
adopt online groceries technology.
The biggest challenge for online groceries businesses is getting more
consumers to change their minds about buying groceries online
(Singh, Williams, Siahpush, & Mulhollen, 2021). This is because there are risks and uncertainties
that affect the decision-making process and consumer behavior (Pennings, Wansink, & Meulenberg, 2002). Local consumers in Malaysia are skeptical of online
foodstuffs especially regarding perishable goods (Muhammad, Sujak, & Abd Rahman, 2016). This presents a challenge for egroceries
service providers to continue to strive to provide the best quality of service
for consumers.
Consumer behavior is an important
factor that needs to be studied because it relates to purchasing decisions. The
COVID-19 pandemic has created a new reality for consumers around the world. To
overcome this, users of digital technologies have faced the need to adopt and
use certain technologies practically (Erjavec & Manfreda, 2022). Developing an in-depth understanding of the factors
underlying consumer intent in shopping for groceries online has the potential
to lead to the creation of customized services. Of course, this is important to
know, especially with the COVID-19 pandemic which has changed people's habits.
However, the improving situation
with the reduced number of positive cases of COVID-19 in Indonesia has made the
government take a policy of loosening restrictions. This makes activities
gradually return to what they were before the COVID-19 pandemic where shopping
in physical stores can still be carried out optimally without restrictions.
Therefore, the question arises whether the online groceries behavior that has
been formed during the pandemic will be maintained in the midst of this endemic
condition.
Therefore, this research is
important to do in order to gain a thorough understanding of what factors
influence consumers' desire to shop for daily necessities online amid
conditions of easing restrictions due to the COVID-19 pandemic. The results of
this study can also be used by investors / companies as information in
developing technology for shopping applications for daily needs to increase
sales.
RESEARCH METHOD
This research is a quantitative study in which a
systematic empirical investigation of phenomena that can be observed using
statistical, mathematical, or computational techniques is carried out.
Predefined and highly structured data collection techniques are a major factor
in quantitative research design when associated with positivism (Saunders, Lewis, & Thornhill, 2019). The initial step starts from establishing the
problem as an indication of a phenomenon being studied, then determining the
title of the study. Next establishes the hypothesis, as well as obtaining the
concept of variables along with the measurement of the established variables.
In this study, online questionnaires were used to test
research hypotheses that had been created.
The questionnaire consisted of several items that measured various UTAUT
factors, behavioral intentions of online groceries shopping, fear of COVID-19
and other items that were irrelevant to the study. We build measurement items
in our hypothesis model based on existing studies.
The respondents in this study were individuals domiciled in urban areas,
especially Jakarta and its surroundings, who had used online groceries services during the Covid-19 pandemic. The
questionnaire will be made in the form of google
forms links which are then distributed through social media such as whatsapp, line, instagram, and
email for one month. In this study, the questionnaire will be divided into
eight parts, the first part containing data from respondents (gender,
occupation, age, and demographics). Then behavioral questions are also asked such as the frequency of using online groceries services and
applications used.
Then proceed with a set of questions related to the research topic which
will then be answered or responded to by respondents based on their experience
in using online groceries services.
The questions from the questionnaire are based on the variable variables that
the author has chosen including, Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), Facilitating Conditions (FC), Online Groceries Buying Intention
(OGBI), Trustworthiness (TW), and Covid - 19 Fear (CF). Table 1. presents all selected
variables, measurement items, descriptions and reference sources. To maintain
the validity of measurements, we use measurement questions that have already
been validated in the literature; However, we adapted several steps for our
research area, which is online groceries
shopping. All variables are measured on a 5-point Likert scale ranging from 1 (strongly disagree) to 5
(strongly agree). This scale is used to determine how much respondents agree or
disagree with the statements given in the questionnaire.
The sampling technique used is Non
- Probability Sampling with
convenience sampling where non-probability
sampling is a data collection technique where not all samples in the
population have the possibility of being selected. Based on the researcher's
policy in determining the sample elements to be used, the selected sample is
only individuals who are domiciled in Jabodetabek and
have used online groceries services.
While the convenience sampling
technique is a sampling procedure that selects samples from people or units
that are easiest to find/ access.
In determining the sample size,
one of the methods that can be used is the (Roscoe & Blome, 2019). This study will take a minimum of 10 times the
number of variables studied, in this case 6 independent variables and 1
dependent variable. From the Roscoe formula, the minimum number of samples is 70 samples (7x10).
Table 1 Measurement
Variables and their sources
|
Variable |
Items |
Statement |
Source |
|
Performance Expectancy (PE) |
PE 1 |
I find the online groceries
application useful
in my daily life |
Venkatesh
et al. (2012) |
|
PE 2 |
Using an online groceries app
makes me save me more time on shopping |
||
|
PE 3 |
Using an online groceries\
app makes me more
financially saver |
||
|
PE 4 |
Using an online groceries
app increased my
productivity |
||
|
Effort Expectancy (EE) |
EE 1 |
Groceries online app is easy to use |
|
|
EE 2 |
Using the
online groceries application makes
it easier for me to find the products
I need |
||
|
EE 3 |
Using the
groceries online
application makes it easier
for me to
find out the availability of products |
||
|
EE 4 |
Easy for me to skillfully use the groceries online app |
||
|
Social Influence (SI) |
SI 1 |
My family advised me to use the groceries online application |
|
|
SI 2 |
My closest friends advised me to use the online groceries application |
||
|
SI 3 |
The people I appreciate advise me to use an online groceries app |
||
|
SI 4 |
People I follow on social media advise me to use the groceries online
app |
||
|
Facilitating Conditions (FC) |
FC 1 |
I have equipment, such as a smartphone,
laptop or PC to use the groceries online application |
|
|
FC 2 |
I have the necessary abilities and knowledge to use the groceries
online application |
||
|
FC 3 |
Using an online groceries application is
the same as using any other online shopping application |
||
|
FC 4 |
I can get help from others if I have difficulty in using the groceries
online application |
||
|
Online Groceries Buying Intention (OBGI) |
OGBI 1 |
I intend to use the online groceries application at a later date |
|
|
OGBI 2 |
I will always use the online groceries app |
||
|
OGBI 3 |
I plan to use the groceries online application often |
||
|
OGBI 4 |
How likely is it that
in the next 6 months, you will use the online
groceries application |
||
|
Trustworthiness (TW) |
TW 1 |
I believe that using an online groceries application can replace my habit from offline to online shopping |
(Yousafzai et al.,2003) |
|
TW 2 |
I would believe the online
groceries application if it has good reviews
from its consumers. |
||
|
TW 3 |
I would believe the online
application of groceries if the goods
sold are of
good quality |
||
|
TW 4 |
If the goods
I receive do not have good quality, it can reduce my trust in online groceries
services or applications |
||
|
Covid-19
Fear (CF) |
CF 1 |
The Covid-19 pandemic
has made me worry about getting out of the house |
(Erjavec and Manfreda,
2022) |
|
CF 2 |
The
Covid-19 pandemic
has made me worry about contracting the covid virus |
||
|
CF 3 |
The
Covid-19 pandemic
worries me if there is a large
crowd |
||
|
CF 4 |
The
Covid-19 pandemic
has made me stay at home or indoors
more often |
The sample in
this study was 40 respondents, with the gender of
each respondent consisting of 55% male and 45% female. The age results
of each respondent were dominated by the age of 20-30 years and 45% as private
employees and the domicile of respondents was dominated by the domicile of 45%
of DKI Jakarta and 50% of Tangerang. Most of them have the experience of once
shopping for daily necessities online. The frequency of doing online shopping is dominated
once a month and two to 5 times a month. Most use the GoMart
and Sayur Box applications.
Table 2
Validity & Reliability Test
|
Variables |
Questions |
Factor
Loading |
Average
Variance Extracted (AVE) |
Cronbach's
Alpha |
Composite
Reliability |
|
Performance Expectancy (PE) |
I find the online groceries application useful in my daily life |
0.908 |
0.797 |
0.873 |
0.922 |
|
Using an online groceries app
makes me save me more time on shopping |
0.885 |
|
|
|
|
|
Using an online groceries
app increased my
productivity |
0.884 |
|
|
|
|
|
Effort Expectancy (EE) |
Groceries online app
is easy to use |
0.865 |
0.691 |
0.850 |
0.899 |
|
Using the online groceries application makes
it easier for me to find the products
I need |
0.776 |
|
|
|
|
|
Using the groceries online application makes it easier for me to find out the availability of products |
0.826 |
|
|
|
|
|
Functional
Value (FV) |
Easy for me to use groceries online
app |
0.855 |
|
|
|
|
Social Influence (SI) |
My closest friends advised me to use the online groceries application |
0.865 |
0.764 |
0.691 |
0.866 |
|
Reward
(RW) |
People I follow on social media advise
me to use the groceries online app |
0.883 |
|
|
|
|
Facilitating Conditions (FC) |
I have the necessary abilities and
knowledge to use the groceries online application |
0.915 |
0.756 |
0.685 |
0.860 |
|
Using an online groceries application is
the same as using any other online shopping application |
0.821 |
|
|
|
|
|
Online Groceries Buying Intention (OBGI) |
I will always use the online groceries
app |
0.886 |
0.838 |
0.903 |
0.939 |
|
I plan to use the groceries online
application often |
0.933 |
|
|
|
|
|
How likely is it that
in the next 6 months, you will use the online
groceries application |
0.927 |
|
|
|
|
|
Trustworthiness (TW) |
I would believe
the online
groceries application if it has good reviews
from its consumers. |
0.942 |
0.857 |
0.835 |
0.923 |
|
If the goods
I receive do not have good quality, it can reduce my trust in online groceries
services or applications |
0.909 |
|
|
|
|
|
Covid-19
Fear (CF) |
The Covid-19 pandemic
has made me worry about getting out of the house |
0.884 |
0.737 |
0.823 |
0.894 |
|
The Covid-19 pandemic worries me if there
is a large crowd |
0.871 |
|
|
|
|
|
The Covid-19 pandemic has made me stay at home or
indoors more often |
0.820 |
|
|
|
-
Convergent validity test requires that the loading factors
number be greater than or equal to 0.5 (Bagozzi & Yi, 2018),
-
discriminant validity test requires that the variance
number of the average variance extracted (AVE) of each latent variable must be greater
than the number in the correlation
between that latent variable
and other latent variables, as well as for
composite reliability, requires that Cronbach's alpha number be
greater than or equal to 0.7 (Fornell & Larcker, 2021).
Table 3 Hypothesis Testing Results
|
|
Hypothesis |
Path
Coefficients |
t - statistics |
p - values |
Result |
|
H1 |
Performance Expetancy
→ Online Groceries Buying Intention |
0.194 |
0.505 |
0.613 |
Rejected |
|
H2 |
Effort Expetancy
→ Online Groceries Buying Intention |
0.816 |
3.187 |
0.002 |
Accepted |
|
H3 |
Social Influence → Online
Groceries Buying Intention |
-0.506 |
0.698 |
0.090 |
Rejected |
|
H4 |
Facilitating Condition → Online
Groceries Buying Intention |
0.390 |
1.350 |
0.178 |
Rejected |
|
H5 |
Trustworthiness → Online
Groceries Buying Intention |
-0.062 |
0.299 |
0.765 |
Rejected |
|
Covid-19 Fear → Online Groceries
Buying Intention |
0.298 |
1.638 |
0.102 |
Rejected |
In this study, the level of significance used was 5%, using a confidence level of
95%. Therefore, the value of t must reach > 1.96 in order for the hypothesis
to have a significant effect. If the t-value < 1.96 can be interpreted to
mean that the hypothesis has an insignificant effect. Based on the analysis of the results of the
table above,
Hypothesis 2 is acceptable because the t-stat value is greater than
the number
1.96 and the p-value is smaller than the value of 0.5. While the hypothesis of 1,3,4,
5 gets rejection because the p-balue is greater than
the value of 0.05
and the t-stat obtained is smaller than the value of 1.96.
CONCLUSION
Overall, this study shows what factors influence buyers' interest in
buying a product at Online Groceries during the pandemic. And from the results
of our research shows that one of the accepted and most significant factors
influencing buyers' interest in buying at Online Groceries is from their Effort
Expectancy. So that with the existenceof Effort
Expectancy which can provide convenience in the use of the Online Groceries
application to users from the elements of the user interface that is easy to
understand in the application or Its uncomplicated payment system can greatly
influence the users to buy at Online Groceries.
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Copyright Holders:
Calvin Prayandi, Imran Pradipta,
Muhammad Rizki (2023)
First publication
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Devotion -
Journal of Research and Community Service
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