Analysis of
Zoom Meeting User Behavior Using Technology Acceptance Model Approach
Siti Safaria1*, Ari Rachmad2
Perbanas Institute
Jakarta, South Jakarta, DKI Jakarta, Indonesia1,2
Email: [email protected]1*, [email protected]2
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ABSTRACT |
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Technology Acceptance Model, Perceived Usefulness, Perceived Ease of Use, Attitude Toward Using, Behavioural Intention, Actual Use. |
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This study aims to determine
the level of acceptance of respondents to the Zoom Meeting application in daily use during the
pandemic with the Technology Acceptance Model
(TAM) approach and to determine the behavior of users of
the application related to perceived
usefulness, perceived ease of use,
attitude toward using, and behavioral
intention. Respondents in
this study were taken by random sampling technique. This research is a quantitative descriptive study,
the data analysis tool in this study uses Smart PLS 3.0 Software and uses the Structural
Equation Model (SEM) model. The results
of this study are the level of acceptance of using the Zoom Meeting application for daily needs
is influenced by the ease
of accessing the application and the perceived
benefits of use. In addition, it was found
that there was a significant effect between the PU variables on ATU, PEU on ATU, PU on BI, ATU on BI, and there was
an indirect effect between the PU variables on BI through ATU as an intervening variable. However, the ATU variable cannot mediate the relationship between PEU and BI. |
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INTRODUCTION
The survey, entitled "Unveiling the Tech Revolution:
How Technology Reshapes the Future of Work",
was conducted online through the Populix application.
As many as 77 per cent of people in Indonesia use Zoom. In comparison, Google Workspace is 54 per cent, According to a Populix survey
in April 2023, in an official
statement received Monday, June 19, 2023. Microsoft Teams (30 per cent) and Skype (24 per cent). The survey involved 1,014 male and female Muslim respondents aged 17-55 in
Indonesia. At the corporate
level, Zoom and Google Workspace
are also popular services, with 68 and 49 per cent, respectively. Followed by Microsoft Teams (31 percent), and Google Products (19 percent).
However, as many as 45 per cent of respondents, according to the
survey, also use artificial intelligence-based services to support work,
such as ChatGPT (52 per cent) and Copy.ai (29 per cent). The service is widely used
by people because there are tools for work
(75 per cent), many templates for other
work (53 per cent), and help to
find ideas (44 per cent). Digital services from Zoom, as an application to support online meetings, are the favourite platform preferred by digital service users in Indonesia, following
Google Workspace. Offices, institutions, and campuses also require
these platforms to be used
(26 per cent).
Several supporting applications are needed to support
the implementation of all activities
so that activities
can run even
though they are not directly face-to-face. Many platforms can be used
to organise schools from home,
work from home, and seminars
or conferences, including the Zoom Meeting application
Zoom has a 57.24% share of the
worldwide video conferencing
software market as we head into
2024. The highest Zoom app downloads were recorded in the APAC region in 2020, as most official jobs went
online. In addition, people in this region prefer Zoom over other video conferencing software.
Zoom Meeting is an application
made by Eric Yuan, which has been released since January 2013. This application has many advantages, including the fact that
it can conduct
meetings for up to 100 participants
The data gleaned from the
survey underscores the pressing need
to comprehend the rapid evolution
of technology and its profound
implications for the future of
work. With Zoom emerging as the frontrunner in video conferencing
software and a significant uptake of AI-based services
like ChatGPT and Copy.ai, there's a palpable urgency to grasp user
behavior and preferences in adopting these technologies
Muntianah, Astuti, & Azizah
In a study conducted by Aditya &
Wardhana
Finally, research
conducted by Andriani,
Setyanto, & Nasiri
Given the variations in previous studies' findings, researchers are interested in exploring the behavior
of Zoom Meeting application users using the TAM approach.
This investigation aims to ascertain
respondents' acceptance of the Zoom Meeting
application in daily use, focusing on
perceived usefulness, perceived ease of use, attitude
toward using, and behavioral intention. This endeavor seeks to contribute novel insights into user perceptions
and intentions concerning the Zoom Meeting application.
METHODS
This research methodology aims to gauge
respondents' receptivity towards integrating the Zoom Meeting application into their daily routines
amidst the pandemic, employing the Technology Acceptance Model
(TAM). It aims to evaluate users'
conduct concerning perceived usefulness, perceived ease of use, attitude
towards usage, and behavioral intention. Participants were chosen through random sampling techniques. The
study adopts a descriptive and quantitative approach, employing Smart PLS 3.0 software for data analysis, utilizing the Structural
Equation Model (SEM)
The effect of Perceived
Usefulness (PU) on Attitude Toward Using (ATU) in Zoom Meeting application users
Perceived Usefulness (PU) is a perception of the
extent to which someone believes
that using a technology will improve their work
performance because of the perceived
benefits
H1: Perceived
Usefulness (PU) has a positive
and significant effect on Attitude
Toward Using (ATU) in Zoom Meeting application users
The effect of Perceived
Ease of Use (PEU) on Attitude Toward
Using (ATU) in Zoom Meeting
application users
User perception of ease
of use is
the user's belief that the
system or technology he uses makes it easier
for him to
do work
H2: Perceived
Ease of Use (PEU) has a positive and significant
effect on
Attitude Toward Using (ATU) in Zoom Meeting application users The effect of Perceived
Usefulness (PU) on Behavioral Intention (BI) in Zoom
Meeting application users
Users of the Zoom Meeting
application who feel the benefits
of the application
to help their
work will form behavioural interests by continuously
using it or even recommending
it to others
as a form of behavioural intention to use. In line
with research from Azhari & Usman (2021), Chen & Aklikokou
H3: Perceived
Usefulness (PU) has a positive
and significant effect on
Behavioral Intention
(BI) Zoom Meeting application
users the influence of Perceived
Ease of Use (PEU) on Behavioral Intention
(BI) in Zoom Meeting Application
Users
Users of the Zoom Meeting
application who find it easy
to use the
Zoom Meeting application in
their daily lives will generate
behavioural interest by continuously using it or
even recommending it to others
as a form of behavioural intention to use. In line
with research from Chen & Aklikokou (2020);
Harryanto et al.
H4: Perceived
Ease of Use (PEU) has a positive and significant
effect on
Behavioral Intention
(BI) in Zoom Meeting application
users The effect of Attitude Toward
Using (ATU) on Behavioral Intention (BI) in Zoom
Meeting application users
Attitude toward using has a significant relationship with behavioral intention in line with the results
of research from Azhari & Usman (2021), Muliati
H5: Attitude Toward Using (ATU) has a positive and significant effect on
Test Indicators
Indicator test or other names
are outer model tests are analyzes carried out to ensure
that the measurement model used is suitable for
measurement because it is valid and
reliable. The indicator test has three measurement criteria: convergent validity, discriminant validity, and composite reliability.
The measurement model for the indicator test
can be seen
in figure 1. next
Figure
1. Hypothesis Test Output Model
Convergent Validity
Variable
indicators are considered
valid if they have a correlation value above 0.70 so that if
there are indicators that have values
below 0.70 they must be discarded
Table 1. Convergent Validity Test Results
|
Indicators |
Perceived Usefulness (X1) |
Perceived Ease of Use (X2) |
Attitude Toward Using (Y1) |
Behavioural Intention (Y2) |
Status |
|
X1.1 |
0.953 |
|
|
|
Valid |
|
X1.2 |
0.951 |
|
|
|
Valid |
|
X1.3 |
0.964 |
|
|
|
Valid |
|
X2.1 |
|
0.970 |
|
|
Valid |
|
X2.2 |
|
0.950 |
|
|
Valid |
|
X2.3 |
|
0.954 |
|
|
Valid |
|
Y1.1 |
|
|
0.964 |
|
Valid |
|
Y1.2 |
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|
0.968 |
|
Valid |
|
Y2.1 |
|
|
|
0.945 |
Valid |
|
Y2.2 |
|
|
|
0.941 |
Valid |
|
Y2.3 |
|
|
|
0.947 |
Valid |
Source: Attached
SmartPLS output
Based
on the results
of the convergent
validity test in table 1. Above, it can be
seen that all indicators of independent and bound variables
in this study have a correlation value above 0.70 so that
they are declared valid and there is
no need for
indicators to be discarded or
deleted.
Discriminant Validity
In contrast to convergent
validity, in this discriminant validity test, research variable indicators are considered valid if they have a construct
correlation value with measurement items greater than
other correlation values
Table
2. Discriminant Validity Test Results
|
Indicators Indicators |
Perceived Usefulness (X1) |
Perceived Ease of Use (X2) |
Attitude toward (Y1) |
Behavioural Intention (Y2) |
Status |
|
X1.1 |
0.953 |
0.849 |
0.796 |
0.842 |
Valid |
|
X1.2 |
0.951 |
0.760 |
0.770 |
0.785 |
Valid |
|
X1.3 |
0.964 |
0.855 |
0.811 |
0.823 |
Valid |
|
X2.1 |
0.844 |
0.970 |
0.865 |
0.885 |
Valid |
|
X2.2 |
0.831 |
0.950 |
0.895 |
0.844 |
Valid |
|
X2.3 |
0.796 |
0.954 |
0.812 |
0.836 |
Valid |
|
Y1.1 |
0.777 |
0.863 |
0.964 |
0.849 |
Valid |
|
Y1.2 |
0.823 |
0.867 |
0.968 |
0.918 |
Valid |
|
Y2.1 |
0.835 |
0.857 |
0.937 |
0.945 |
Valid |
|
Y2.2 |
0.806 |
0.850 |
0.811 |
0.941 |
Valid |
|
Y2.3 |
0.779 |
0.822 |
0.839 |
0.947 |
Valid |
Source: Attached
SmartPLS output
Based
on the results
of the discriminant
validity test in table above, it can
be seen that
all variable indicators in this study have a construct correlation value with measurement items greater than
other correlation values so that
they are declared valid and there is
no need for
indicators to be discarded or
deleted.
After
conducting validity tests (convergent and discriminant validity), it can
be concluded that the four
variables are declared
valid because they have a correlation value above 0.70 and the correlation
value of the construct to
the measurement item is greater than
other correlation values. So that
it can be
continued for composite reliability tests. These results
are summarized in table 3. next:
Table
3. Indicator Validity Test Summary
|
Variable |
Convergent Validity |
Discriminant Validity |
Invalid Indicator |
|
Perceived |
Valid |
Valid |
- |
|
Perceived Ease |
Valid |
Valid |
- |
|
Attitude Toward |
Valid |
Valid |
- |
|
Behavioural |
Valid |
Valid |
- |
Composite Reliability
A
valid research variable can be said
to be reliable
if it has a composite reliability value above 0.70
Table 4. Construct Reliability Test Results
|
Variable |
Loading Factor |
|
Perceived Usefulness (X1) |
0.969 |
|
Perceived Ease of Use (X2) |
0.971 |
|
Attitude Toward Using (Y1) |
0.965 |
|
Behavioural Intention (Y2) |
0.961 |
Source: Attached
SmartPLS output
From
the presentation of the data in the table above,
it can be
concluded that all variables in this study are declared reliable because they have a composite
reliability value above 0.70.
Test Model Fit
The
fit model test was carried out by
looking at the estimated output
results of SmartPLS and comparing
it with SRMR, NFI, Chi-square, and RMS Theta criteria. The following are the results of the
fit model test presented in
table 5.
Table
5. Fit Model Test Results
|
Fit Summary |
Cut Off |
Estimation
Model |
Explanation |
|
SRMR |
Smaller than 0.10 |
0.038 |
Good
Fit |
|
NFI |
Close to 1.0 |
0.855 |
Good
Fit |
|
Chi-square |
χ2Statistics < χ2 Table df=499; Sig=0.05 → χ2=552.074 |
244,503 < 552,074 |
Good
Fit |
|
RMS
Theta |
< 0.12 |
0.285 |
Unfit |
Source: Attached
SmartPLS output
Based
on table 5. above, the SRMR value of 0.038 < 0.10 means that the
indicator covariance residue is smaller
than the cut-off value so
that this goodness of fit measure can be
used to avoid
model specification errors.
The NFI value of 0.855 is close to
the cut-off value of 1.0, so
it can be
said that the design of
this research model is getting a better
fit. Furthermore, the Chi-square value of
244.503 < 552.074 means that
the number of manifest variables
in the PLS path model and the number
of independent variables in the covariance matrix model are sufficient. Finally, the RMS Theta values
are 0.285 > 0.12 so it is said that
the residue from the outer
model is less correlated.
Test the hypothesis
Hypothesis is carried out
to find out
whether the hypothesis that has been formulated is accepted or
rejected. The independent variable is expressed
to have a significant relationship with the dependent
variable if it has a significant value below 0.05 and the t value
is calculated > t table (Ghozali, 2012). The results
of the hypothesis
test of this
research variable are presented in table 6. next:
Table 6. Hypothesis Test Results
|
Hypothesis |
Relationship Direction |
Parameter Coefficient
(Original Sample) |
T Statistics |
P Value |
Status |
|
H1 Perceived Usefulness Affects
Attitude Toward Using |
Positive |
0.225 |
2.107 |
0.036 |
Accepted |
|
H2 Perceived
Ease of Use Affects Attitude Toward Using |
Positive |
0.701 |
6.478 |
0.000 |
Accepted |
|
H3 Perceived Usefulness
affects Behavioral Intention |
Positive |
0.216 |
2.503 |
0.013 |
Accepted |
|
H4 Perceived Ease of Use affects Behavioral Intention |
Positive |
0.241 |
1.798 |
0.073 |
Accepted |
|
H5 Attitude
Toward Using affects B ehavioral Intention |
Positive |
0.520 |
4.579 |
0.000 |
Accepted |
The outcomes of the
hypothesis test provided in Table 7 reveal noteworthy discoveries that can be
drawn. Initially, Perceived Usefulness exerts a positive and statistically
significant impact on Attitude Toward Using among IKPIA Perbanas
students utilizing the Zoom Meeting application. This assertion supports the
Path Coefficient results detailed in table 4.14, where the P-value of 0.036
< 0.05 and the calculated t value of 2.107 > t table 1.9842 signify the
acceptance of Ha and rejection of H0.
Secondly, Perceived
Ease of Use similarly demonstrates a positive and significant direct influence
on Attitude Toward Using among IKPIA Perbanas
students employing the Zoom Meeting application, as indicated in table 7 with P
Value values of 0.000 < 0.05 and calculated t values of 6.478 > 1.9842,
leading to the acceptance of Ha and the rejection of H0.
Thirdly, Perceived
Usefulness also directly and significantly impacts Behavioral
Intention in IKPIA Perbanas students who utilize the
Zoom Meeting application. This is evidenced by P-value values of 0.013 <
0.05 and calculated t values of 2.503 > t table 1.9842, thereby confirming
the acceptance of Ha and the rejection of H0.
However, regarding
Perceived Ease of Use, no direct influence on Behavioral
Intention among IKPIA Perbanas students using the
Zoom Meeting application was observed. This is elucidated in the hypothesis
test results, showing a calculated t value of 1.798 < t table of 1.9842 and
a P-Value value of 0.073 > 0.05, leading to the acceptance of H0 while Ha is
rejected.
Finally, Attitude
Toward Using is shown to positively and significantly affect Behavioral Intention among IKPIA Perbanas
students using the Zoom Meeting application. This is evidenced in Table 7 with
P Value values of 0.000 < 0.05 and a t count of 4.579 > t table 1.9842,
confirming the acceptance of Ha and the rejection of H0.
Path Analysis
Path analysis,
an extension of multiple linear regression, examines causal relationships between variables established by theory. It evaluates
the direct and indirect effects
of variables associated with the independent variable by scrutinizing
coefficient magnitudes. Additionally, it explores whether a mediating variable facilitates the influence of the
independent variable on the dependent
one. The results are typically presented in a Specific Indirect Effects table, where a p-value below 0.05 indicates an indirect influence
from X to Y via the mediating variable,
Z.
Table 7. Test Results Based
on Specific Indirect Effect
|
|
Original Sample (O) |
T Statistics |
P Value |
|
Perceived Usefulness (X1) → Attitude |
0.117 |
1.683 |
0.093 |
|
Toward Using (Y1) → Behavioral Intention |
|
|
|
|
(Y2) |
|
|
|
|
Perceived Ease of Use (X2) → Attitude |
0.365 |
4.359 |
0.000 |
|
Toward Using (Y1) → Behavioral Intention |
|
|
|
|
(Y2) |
|
|
|
Source: Attached
SmartPLS output
Based on the results of
the specific indirect effect test in table 8, it is concluded
that Attitude Toward Using does
not mediate Perceived Usefulness to Behavioral
Intention using the Zoom Meeting application, as evidenced by the P Value
value of 0.093 > 0.05 and the calculated
t value of 1.683 < t table 1.9842, so that Ha is rejected
and H0 is accepted. However, Attitude Toward Using mediates the Perceived Ease
of Use against the Behavioral Intention of using
the Zoom Meeting application, with a P Value value of
0.000 < 0.05 and a calculated
t value of 4.359 > t table 1.9842, so that Ha is accepted
with its mediation effect.
CONCLUSION
This research investigates the impact of Perceived
Usefulness (PU) and Perceived Ease of Use (PEU) on Attitude Toward Using (ATU) and subsequent Behavioral Intention (BI) among users of the
Zoom Meeting application.
The results indicate significant positive effects of both
PU and PEU on ATU, consequently influencing BI. However, a direct relationship between PEU and BI was not observed. Path analysis reveals ATU as a
mediator between PEU and
BI, while no such mediation is observed between
PU and BI through ATU. These findings underscore the significance of users' perceptions regarding the benefits
and ease of use of
the Zoom Meeting app in shaping their attitudes and intentions toward its usage.
Nevertheless, it is important to
acknowledge potential limitations of this study, such as the sample size
or demographic homogeneity, which could affect the
generalizability of the findings. Future research could address these limitations
by employing larger and more
diverse samples or by considering
additional variables that may influence
users' attitudes and intentions toward technology adoption. By doing so, we can
enhance the robustness and applicability of findings, thus providing more comprehensive insights for the development
and marketing strategies of Zoom Meeting and similar
technologies.
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Copyright holder: Siti Safaria, Ari Rachmad (2024) |
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First publication rights: International Journal
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