Factors that Influence Purchase on Cinema Online Tickets Using Tix-Id
Application, through Buying Interest
JOHN EHJ. FOEH
Faculty of Economics and Business, Bhayangkara Jaya University
Jakarta, INDONESIA
ADLER HAYMANS MANURUNG
Management Doctoral Program, Bhayangkara Jaya University
Jakarta, INDONESIA
FLORENTINA KURNIASARI
Fakultas Ekonomi dan Bisnis, Universitas Multimedia Nusantara
Jakarta, INDONESIA
TIPRI ROSE KARTIKA
Publishing Department, State Polytechnic of Creative Media
Jakarta, INDONESIA
SANDRA YUNITA
Institute Digital Business of Indonesia
Jakarta, INDONESIA
Abstract: - The purpose of this study was to determine the factors that affect directly and indirectly such as
promotion, convenience, and security on the decision to purchase online cinema tickets with the TIX ID
application through consumer buying interest. The data collection technique uses a questionnaire that is
distributed online via the google application form. Data analysis methods include validity, reliability, classical
assumptions, and SEM tests. The number of samples in this study were 200 respondents who had met the
minimum requirements for using SEM (structural equation models). Data processing using SPSS and AMOS.
The results showed that promotion and convenience factors had a significant effect on purchase intention, while
security did not have a significant effect on purchase intention. The results of statistical tests show that there is
no influence of the promotion, convenience, and security variables on purchasing decisions. Furthermore, the
results show that promotion and convenience factors indirectly influence purchasing decisions through
purchase intention.
Key-Words: - Convenience, Security, Purchase Decision, Buying Interest, Promotion.
Received: May 31, 2021. Revised: November 3, 2021. Accepted: December 2, 2021. Published: January 3, 2022.
1 Introduction
The current development of computer,
communication and digitalization technology has
spurred various industrial, production and service
sectors to adopt these developments for the
advancement of a company or organization. These
advances, especially in the field of information
technology and digitalization, have triggered various
sectors such as transportation, health, banking and
various other sectors to adopt them. In today's
modern era, the use of information technology in
financial transactions has become very important.
The development of electronic or digital financial
transactions is very rapid along with the behavior of
people who have limited time and follow trends in
technological developments in their daily lives,
including their rapid impact in the social, economic,
and cultural aspects of society or consumers. This in
turn demands changes and developments in
financial transactions to become more efficient and
modern.
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The development of digital or online transactions
also has an impact on the service industry sector
such as cinemas to keep abreast of advances with
the latest technological developments. One of the
service industry sectors that has recently become the
public spotlight is film and cinema. This industry
has had its ups and downs in its life. After a long
period of being dim and less attractive to the local
community and also due to the influence of the
Covid 19 pandemic, it turns out that in the last 3
years it has revived.
The development of the film industry encourages
the development of the number of competing
cinemas. This means that those cinemas must
actively market their service industries as public
facilities in line with the increasing number of
viewers. In Indonesia today, there are 5 types of
theaters including CGV Blitz, Cinemax, Platinum
Cineplex and the last one is Cinemax 21 Group. The
more types of cinemas that appear, the more
business competition among the cinemas in
question. Cinema entrepreneurs must develop
innovations in the products and services offered by
Cinemax21. Cinemax21 is the largest cinema group
in Indonesia which started its work in the
entertainment industry since 1987. More than 30
years, Cinemax21 is committed to always providing
the best viewing experience for Indonesians through
its marketing activities.
Along with advances in information technology,
Cinemax21 has begun to utilize information
technology to carry out various marketing activities.
Several online movie ticket purchase services are
made based on applications, namely TIX ID, M-
TIX, CGV Cinemas, and Book MyShow. Currently,
one of the applications participating in mobile
commerce that has the leading entertainment service
in Indonesia is the TIX ID application. TIX ID was
launched by PT. Nusantara Elang Sejahtera which
was released on March 21, 2018. TIX ID can
provide a new experience in purchasing cinema
tickets and strive to understand consumer
satisfaction. This application is not a card but an
account in the application that has been provided.
Consumers can immediately use the TIX ID
application to make it easier for viewers to buy
cinema tickets without the hassle of queuing and are
free to choose seats anywhere and anytime, as long
as supplies last.
TIX ID also offers many features that can be
accessed easily apart from purchasing cinema
tickets. For this reason, TIX ID provides a digital
wallet for various payment purposes. With this
payment model, it is easier for viewers to directly
make payments online using the balance on the
card. The TIX ID application is also very
aggressively promoting so that through various
innovations and marketing strategies, this
application can attract potential consumers to use it
more. One form of TIX ID promotion is the buy 1
get 1 free pattern every Wednesday. New TIX ID
users are given a 50% discount voucher at certain
times. Through such a marketing pattern, currently
TIX ID has high competitiveness against their
competitors. Thus, factors such as perceived
convenience, safety, buying interest are important
factors that need to be explored further.
On the basis of what has been described
previously, a study is needed on "the direct and
indirect effect of promotion, convenience and
security on the decision to purchase online cinema
tickets using the Tix Id application through purchase
intention".
2 Literature Review
2.1 Consumer Behavior
Consumer behavior, according to Mothersbaugh, et
al. [1], is defined as the activities immediately
engaged in the acquisition, consumption, and
disposal of goods and services, as well as the
decision processes that precede and follow these
acts. Accordingly, consumer behavior is defined as
"all activities, behaviors, and psychological
processes that drive these behaviors before to
buying, when purchasing, using, and spending items
and services after completing the items above, or
while assessing activities" [2]. Meanwhile, Kotler &
Armstrong [3] describes consumer behavior as the
purchasing habits of end consumers, including
individuals and families, who purchase goods for
personal use.
Consumer behavior might be defined as an
individual and household decision-making process
before purchase and behaviors in getting, using,
consuming, and disposing of things based on those
criteria.
2.2 FinTech Definition
The term fintech itself is an abbreviation of the
word financial technology, which means a company
that combines financial services with modern and
innovative technology. Financial Technology,
commonly known as FinTech, is a new financial
service model produced through information
technology innovation, according to Hsueh & Kuo
[4]. Financial Technology (FinTech) is a term that
refers to a mixture of technology and financial
aspects, or it may also refer to financial sector
innovation with a modern twist.
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FinTech companies strive to attract clients by
offering goods and services that are more user-
friendly, efficient, transparent, and automated than
what is already available. Despite the lack of
agreement on the appropriate description of FinTech
and the fact that it is premature to describe a
continuously growing subject, following the various
tries to explain it will provide a thorough
understanding of this modern world. FinTech refers
to businesses or representatives of companies that
integrate financial services with cutting-edge
technology [5]. According to the report, the Fintech
sector may also be separated into many broad
industries based on their distinct business methods.
Fintech may be classified depending on the extent of
engagement in finance, asset management, and
payment, such as mobile payment, using the classic
value-adding analogue to universal banks. In this
context, mobile payment refers to a payment system
that uses a mobile device or smartphone to complete
transactions, including financial instruments such as
cash, debit or credit accounts, and stored account
value (SVA) such as transportation cards, gift cards,
and mobile wallets.
2.3 Promotion
Promotion is an action used to persuade customers
to get familiar with the company's offerings, which
leads to them being satisfied and purchasing the
product [6]. The practice of combining or blending
advertising, personal selling, sales promotion, public
relations, and direct marketing is often associated
with promotion as persuasive communication, and
communication strategies include a habit of mixing
or blending advertising, personal selling, sales
promotion, public relations, and direct marketing
(direct mailing, e-mail, and telemarketing).
The purpose of this definition is the activity used to
communicate information about the product to be
sold to potential consumers. In addition to
communicating information about a product,
promotion is also used as a means to persuade and
influence consumers to consume the product.
2.4 Convenience
The degree to which computer technology is seen as
reasonably simple to comprehend and utilize is
referred to as convenience or ease of use. This ease
is due to the fact that operational transactions are
completed online. Convenience is the most
important thing that must be considered by
providers or online sellers. This convenience can be
of various levels, depending on the user or the buyer
himself, but of course basically there is a standard of
convenience that is the same level for all users.
Online buyers are usually compared to offline
buyers, what is offered in online buyers usually
must be better than what is offered in offline buyers,
convenience is often one of the attractions. From the
ease of accessing the choice of goods or shipping.
The internet that allows access to stores from
anywhere is one simple example of the convenience
offered by e-commerce providers, prospective
buyers can now access stores from anywhere on a
laptop, PC or mobile device, be it a smartphone or
tablet [7].
According to Ardyanto [8], this convenience
will influence behavior, with the greater a person's
impression of the system's ease of use, the greater
the degree of information technology use.
Manufacturers and businesses typically make it
easier for clients to purchase things by supplying a
product or commodities that they have requested.
How to do online transactions is also connected to
ease or convenience.
2.5 Security
How to prevent or at least detect fraud in an
information-based system when the data has no
physical meaning is known as online transaction
security. Because of the high value of information,
certain people are frequently unable to obtain the
information they want. With so many cases of fraud,
the security factor is also one of the important issues
facing e-commerce users. Fraud cases that occur in
online transactions are certainly worrying for both
sellers and buyers, with the many cases of course
making buyers and sellers more selective when
making transactions through online media [9].
According to Andriyani [10], this condition suggests
that customers will not make purchases until
security assurances are provided because inadequate
security assurances will undoubtedly lead customers
to be concerned, preventing them from making
purchases. When online stores can improve security
and give guarantees to customers, customer trust in
buying rises.
Based on research from Riquelme & Román
[11], security indicators include: data
confidentiality, secure payment methods, terms and
conditions are easy to understand and risks when
making transactions.
2.6 Buying Interest
According to Schiffman & Kanuk [12], buying
interest is a psychological activity that arises from
feelings (affective) and thoughts (cognitive) about a
desired item or service. That interest in purchasing a
product can be interpreted as a happy attitude
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toward an object that motivates people to seek out
these objects by paying money for them. Customer
attitudes about a product shape buying interest,
which stems from consumer faith in the product's
quality. Customer buying interest will decline as
consumer confidence in a product declines. Interest
is defined as a state in which consumers have not
yet performed a particular action that may be
utilized to forecast that behavior or activity.
Consumer buying interest, according to Kotler
& Keller, [6] is a consumer behavior in which
customers have a desire to purchase, utilize,
consume, or even want a product given. Two
elements also impact a person's purchasing interest
in the decision-making process: unexpected events
and attitudes toward others (Respect to Others).
Buying interest indicates a buyer's intent to make a
future purchase.
2.7 Purchase Decision
Purchasing decisions, according to Schiffman &
Kanuk, [12] are the choice of two or more
alternative buy decision choices, implying that one
can make selections if multiple other possibilities
are offered. The process of making a purchase
choice might influence how the buyer made the
decision. Tjiptono [13] says that the purchase
decision is a series of processes that begin with the
consumer recognizing a problem, searching for
information about a specific product or brand, and
evaluating how well each of these alternatives can
solve the problem before making a purchase
decision.
Furthermore, as per Kotler & Keller [6], the
purchasing decision process is a five-stage process
that consumers go through, beginning with problem
recognition, information seeking, evaluating
alternative solutions, purchasing decisions, and
post-purchase behavior long before the purchase.
What customers do has a long-term influence. In
purchasing decisions, there are four factors to
consider appropriateness for requirements,
advantages, accuracy in selecting the goods, and
recurrent purchases.
2.8 Research Framework
In Figure 1, a framework has been formed that
illustrates this research, there are promotion,
convenience, and security variables that affect
purchasing decisions with the buying interest
variable as an intervening variable.
Fig. 1: Research Framework
2.9 Hypothesis
The hypothesis might be stated as follows, based on
the framework and theory presented in the literature
study:
H_1 : It is assumed that promotion affects the
interest in buying online cinema tickets using
the TIX ID application
H_2: It is assumed that convenience affects the
interest in buying online cinema tickets using
the TIX ID application
H_3: It is suspected that security affects the interest
in buying online cinema tickets using the TIX
ID application
H_4: It is assumed that promotions have an effect
on online ticket purchase decisions for cinemas
using the TIX ID application
H_5: It is assumed that convenience affects the
decision to purchase online cinema tickets
using the TIX ID application
H_6: It is assumed that security affects the decision
to purchase online cinema tickets using the
TIX ID application
H_7: It is assumed the decision to purchase online
cinema tickets using the TIX ID application is
thought to be influenced by buying interest
3 Research Methods
This research was held in the Bogor Regency area,
with respondents chosen based on having purchased
movie tickets using the TIX ID app. The time of this
research was from May to June 2020. In this study,
to obtain primary data, a questionnaire was
distributed online using google form. This method
was used because it was still in the state of the
Covid Pandemic 19. Thus the data were obtained
from respondents' answers which were arranged
ordinal based on a Likert scale of 1 - 5, with a
statement order strongly agree = 5, agree = 4,
neutral = 3, disagree = 2 , and strongly disagree = 1.
The population of this research is
respondents who have purchased cinema tickets
through the TIX ID application. It is assumed that
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these respondents have the same tendency to
purchase cinema tickets on the TIX ID application.
The number of samples in this study amounted to
200 people. This meets Ferdinand criterion [14] for
calculating sample size, which stipulates that a
sample size of larger than 30 and fewer than 500 is
sufficient for all investigations. Furthermore, SEM
analysis necessitates good samples ranging from
100 to 200 samples.
3.1 Operational Definition of a Variable
Table 1 shows the operational definitions of the
variables in the study as well as their measurement
techniques.
Table 1. Operational Definition of Variables
Variable
Definition
Indicator
Promoti
on (X1)
The company's
activities
aimed at
communicatin
g the product's
benefits and
persuading
customers
1. Advertising
2. Sales promotion
3. Personal selling
4. Public relations
5. Direct
marketing
Easy
(X2)
The
confidence of
application or
website users
can be used
without
problems and
without
problems
Clear and easy
to understand
(uncomplicated
application)
It doesn't take
much effort to
interact easy to
use system
Flexible (the
application can
be used at any
time)
Easy to operate
(the application
is easy to
operate accord-
ingly needs)
Security
(X3)
Security is a
sense of
security felt by
consumers
when making
transactions
online without
feeling danger
or be fooled
confidentiality
of data
safe payment
methods
risks when
making
transactions
clear provisions
Buying
Interest
(Y1)
In a consuming
attitude, buying
interest is one
of the
component
behaviors. The
respondent's
Transaction
interest
Referential
interest
Interest
preferences
tendency to act
before the
purchasing
choice is
implemented is
known as
purchase
intention.
Explorative
interest
Buyi
ng
Deci
sion
(Y2)
Is a process
carried out by
consumers in
determining a
decision to
make a
transaction
on line
Consumer needs
Has benefits
Accuracy in buying
products
Repeat purchase
Likert
Scale
1-5
3.2 Data Analysis Method
The data analysis approach employed in this
study was structural equation modelling (SEM),
which was preceded by many research instruments
testing such as validity and reliability tests, as well
as traditional assumption tests such as normality,
multicollinearity, and heteroscedasticity tests [14].
3.3 Stages of Modeling and Structural Equation
Analysis
The Structural Equation Modeling (SEM) approach
is a development of route analysis and multiple
regression, both forms of multivariate analysis,
according to Ferdinand [15]. The step diagram for
the structural equation model approach follows the
following seven main steps:
Relation of theoretical models
Development of path diagrams or
flowcharts built on constructs to show
causality relationships
Convert path diagrams into equations
Determine the input matrix and estimate the
proposed model, estimated model
coefficients and evaluate the criteria for
goodness of fit.
The following are some of the most widely used
suitability indexes and cut-off values:
Degree of Freedom (DF) or degrees of
freedom (DB) must be positive, which
indicates the model is not underidentified.
CMIN / DF generally ranges from ≤ 2.0-3.0
as an indicator to measure the suitability of
the model.
Chi-square value at the probability level ρ ≥
0.05 or ρ ≥ 0.1 is expected to be low. The
tested model is considered good or
satisfactory if the chi-square value is
smaller than the table value.
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RMSEA (Root Mean Square Error of
Approximation) index is used to adjust for
the chi-square in a large sample, indicating
the model's appropriateness. RMSEA ≤ 0.08
is a requirement so that the model shows a
close fit of the model.
GFI (Goodness of Fit = R2 in regression)
and AGFI (adjusted R2) are size ranges that
take into account the weighted proportion of
variance in a sample convariant matrix.
They range from 0 (poor fit) to 1 (perfect
fit). GFI and AGFI values ≥ 0.90 indicate
good fit, if between 0.80 ≤ GFI and AGFI ≤
0.90 it indicates marginal fit (moderate).
TLI (Tucker Lewis Index) is an incremental
fit alternative that compares a tested model
to a baseline model. Acceptance 0.95 is
recommended as a reference value for
model acceptance.
The CFI (Comparative Fit Index) is an
index whose magnitude is unaffected by
sample size, making it ideal for determining
a model's level of acceptance. The expected
value is ≥ 0.94
Model interpretation and modification.
Table 2 contains detailed descriptions of the
goodness of fit model and the model adequacy
criteria.
Table 2. Goodness of Fit Model Index
4 Results and Discussion
4.1 Instrument test results
To find out whether the questions tested are valid or
not, it can be seen from the Item-total statistics table
for each item (questions in the questionnaire) in the
Corrected Item-total Correlation column. The
variables of each question are used to conduct this
test. The Corrected Item-Total Correlation value
exceeds the r table value, indicating valid question
items. The validity test results show that all
correlation values (r count) are greater than or equal
to the value of r table or are declared valid, as
shown in Table 3. In Table 3, it consists of column 1
(variable name), column 2 (indicator code), column
3 Correlation calculated value), column 4 (r table
value 5%) and column 5 (information). When the
value of column 3 is greater than column 4, it is
stated that the indicator is valid. The test results in
Table 3 show that all indicators used are valid
Table 3. Result of Validity Test
(1)
Variable
(2)
Indicat
or Code
(3)
Correlation
(r
calculated)
(4)
Value
ofrtab
(N=30
𝜶=5%
(5)
Information
PM1
0,720
0,361
Valid
PM2
0,692
0,361
Valid
Promotion
PM3
0,749
0,361
Valid
PM4
0,708
0,361
Valid
PM5
0,756
0,361
Valid
KMD1
0,828
0,361
Valid
KMD2
0,868
0,361
Valid
Easy
KMD3
0,831
0,361
Valid
KMD4
0,771
0,361
Valid
KMD5
0,785
0,361
Valid
KMN1
0,776
0,361
Valid
Security
KMN2
0,806
0,361
Valid
KMN3
0,659
0,361
Valid
KMN4
0,722
0,361
Valid
MB1
0,847
0,361
Valid
Buying
Interest
MB2
0,831
0,361
Valid
MB3
0,867
0,361
Valid
MB4
0,796
0,361
Valid
KP1
0,756
0,361
Valid
Buying
KP2
0,825
0,361
Valid
Goodness of Fit
Index
Cut-off Value
Chi-Square (
χ
2
)
Small expected
Degree of Freedom (df)
Positive
Significance Probability
(P-Value)
≥ 0.05
RMSEA
≤ 0.08
GFI
≥ 0.90
AGFI
≥ 0.90
CMIN/DF
≤ 2.00
TLI
≥ 0.95
CFI
≥ 0.94
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Decision
KP3
0,848
0,361
Valid
KP4
0,800
0,361
Valid
Source: Processed Primary Data, 2020
Furthermore, the reliability test uses the Cronbach's
Alpha formula. The results of the reliability test
show that the variables of promotion, convenience,
security, purchase intention, and purchase decision
have a Cronbach's Alpha value greater than 0.60 so
that all questions from the questionnaires that have
been distributed are declared reliable or reliable.
4.2 Classical Assumption Test Results
Using SPSS version 22 software, traditional
assumption testing includes normality,
multicollinearity, and heteroscedasticity tests. The
results show that the data is normally distributed in
the first test. Furthermore, the values obtained from
the multi collinearity test results show that between
the independent variables there is no multi
collinearity problem. And finally, the third test also
shows that there is no heteroscedasticity problem in
the model used.
4.3 Structural Analysis and Modeling in
Research
SEM (structural equation modelling) is a cross-
sectional, linear, and broad statistical modelling
technique. Factor analysis, path analysis, and
regression are among the techniques used in this
SEM. According to Ferdinand [14], SEM analysis
generally uses several statistical test tools to test the
acceptance of a research model. The measurement
between the degree of suitability between the
hypothesized models and the data presented in this
study uses several fit indexes, namely; Chi-Square,
Root Mean Square error of Approximation
(RMSEA), Goodness of Fit Index (GFI), Adjust
Goodness of Fit Index (AGFI), Minimum Sample
Discrepancy Function Comparative Fit Index (CFI).
The results obtained showed that the model was
not fit. The action that needs to be done is to modify
the model by adding or removing connections /
links, adding variables, reducing variables. Model
modification can be done by looking at the resulting
Modification Indices. Modification indices offer
numerous suggestions for adding links or
connections to improve the model's fit by lowering
the chi-square value.. Therefore, the PM1, PM3,
KMD1, KMD4, KMD5, KMN2, KMN4, MB4, and
KP1 indicators must be removed to meet the
Goodness of Fit Index value. From each index
obtained, the results of the removal of the
Modification Index make the GOF value very fit
and are presented in Table 4 below.
Table 4. Comparison of the Goodness of Fit Index
with the Research Model Test Results
Source: Processed Primary Data, 2020
The results of SEM testing with the help of the
AMOS version 22.0 program in Table 4 show that
the main model of this study has a χ2 Chi-Square
value of 62.008, which is smaller than the limit of a
significant level of 0.05 (5%) with a model
significance probability value of 0.240. The test
results on other indices such as GFI (0.943), AGFI
(0.906), TLI (0.9880), CFI (0.992), RMSEA
(0.030), provide information indicating that all
variables in the model are well accepted.
From the results of the Goodness of Fit test
summarized in Table 4, it is proven that the model is
fit with the existing data, therefore, hypothesis
testing can be done. Hypothesis testing is done by
looking at the C.R (Critical Ratio) value found in
the AMOS output table regarding regression
weights which is shown in Table 5. below:
Table 5. Regression Weights: (Group Number 1 –
Default model)
Estimate
S.E.
C.R.
P
Label
MB
<---
PM
,537
,113
4,758
***
par_11
MB
<---
KMD
,355
,113
3,137
,002
par_12
MB
<---
KMN
-,070
,257
-,273
,785
par_18
KP
<---
MB
1,019
,312
3,265
,001
par_10
KP
<---
PM
,019
,215
,089
,929
par_13
KP
<---
KMD
,115
,171
,677
,499
par_14
Goodness
of Fit
Cut of Value
Model
Test
Results
Criteria
Chi-square
(
χ
2
)
≤
73,31
62,008
Good
Probability
≥
0,05
0,240
Good
RMSEA
≤
0,08
0,030
Good
GFI
≥
0,90
0,943
Good
AGFI
≥
0,90
0,906
Good
CMIN/DF
≤
2,00
1,127
Good
TLI
≥
0,95
0,988
Good
CFI
≥0,94
0,992
Good
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Volume 18, 2022
KP
<---
KMN
-,195
,293
-,666
,505
par_15
PM2
<---
PM
,624
,106
5,899
***
par_1
KMD3
<---
KMD
,983
,111
8,826
***
par_2
KMD2
<---
KMD
1,000
KMN3
<---
KMN
1,000
KMN1
<---
KMN
1,759
,679
2,592
,010
par_3
MB1
<---
MB
1,000
MB2
<---
MB
1,128
,101
11,204
***
par_7
MB3
<---
MB
1,087
,107
10,193
***
par_8
KP2
<---
KP
,874
,095
9,247
***
par_9
KP3
<---
KP
1,000
PM4
<---
PM
,615
,093
6,586
***
par_16
KP4
<---
KP
,919
,088
10,445
***
par_17
PM5
<---
PM
1,000
Table 5 provides information relating to the
estimated significance of the influence parameters
between the variables contained in the research
which has been hypothesized. Through the table in
question, it can be seen that Promotion (PM) affects
Purchase Interest (MB) very significantly with an
estimated value of 0.537 with a probability of 0.00.
Furthermore, Ease (KMD) also has a significant
effect on buying interest (MB) with an estimated
value of 0.355 and a probability of 0.002.
Meanwhile, Security (KMN) does not affect
Purchase Interest (MB). From Table 5, it is also
known that Purchase Interest affects Purchase
Decision (KP) very significantly with an estimated
value of 1.019 and a probability value of 0.001.
Furthermore, still in Table 5 it can be seen that
each Promotion (PM), Ease (KMD), and Security
(KMN) variable does not directly affect the
Purchase Decision (KP) with a small estimated
value and a probability value that is far above the
tolerance limit of 0.05. The results of the subsequent
calculations in Table 5 show the effect of each
indicator from each of each variable which is not
essentially the main objective of the study in this
study. One of the main reasons is that each indicator
can have different effects according to the product,
or according to the location of the study or related to
consumer behavior.
A detailed description of the research model
based on the theory as well as the data that has been
obtained which is then presented in the form of a
research model in Figure 2. Based on the findings
obtained, it can be concluded that the research
model is adequate and fits the Goodness of Fit Index
requirements. All hypothesis testing using SEM
were conducted to prove the effect of promotion,
convenience, and security on purchase intention and
purchase decision. (see Figure 2).
Fig. 2: Result of Structural Equation Model
Source: Processed Primary Data, 2020
4.4 The Effect of Promotion (X1), Convenience
(X2) and Security (X3) on Purchase
Intention (Y1)
In further studies and for statistical convenience, the
variable symbols use a common and standard
notation. The first hypothesis testing was conducted
to prove the effect of promotion, convenience and
safety on purchase intention. The results of the tests
suggest that:
With a coefficient of 0.54, a significance level
of 5%, and a Critical Ratio (CR) value of 4.758
with a value of t count, ≥ 1.65, the promotion
directly influences buying interest.
Convenience has a direct effect on buying
interest of 0.35, with a significance level of 5%
and a Critical Ratio (CR) value of 3.137 with a
value of t count, ≥ 1.65.
Security has no direct effect on purchase
intention of -0.070, with a significance level of
5% and the Critical Ratio (CR) value of -0.273
with a value of t count, namely ≤ 1.65. As a
result, the hypothesis is rejected, and the
security variable has a coefficient value of -
0.195, indicating that it has no meaningful
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2022.18.2
John Ehj. Foeh, Adler Haymans Manurung,
Florentina Kurniasari, Tipri Rose Kartika,
Sandra Yunita
E-ISSN: 2224-3496
17
Volume 18, 2022
influence on purchase intention. This is
reinforced by the respondents' uncertainty
regarding risks such as data leakage, the risk of
conducting online transactions, and unclear
provisions.
The results of this study also show that the effect of
the promotion variable is greater than the ease and
security of the buying interest variable. This means
that promotions greatly affect buying interest,
because with promotions it is easier to influence
consumer interest in using the TIX ID application.
4.5 The Effect of Promotion (X1), Convenience
(X2) and Security (X3) on Purchasing
Decisions (Y2)
The second hypothesis is tested to see if promotion,
convenience, and security impact purchase
decisions. The hypothesis testing findings reveal
that:
The promotion had no direct influence on
purchase decisions with a value of 0.019, a
significance level of 5%, and a Critical Ratio
(CR) of 0.089 with a t count of 1.65. Because
the respondents are primarily young
individuals who have never had a fixed salary,
the hypothesis is rejected. The promotion
variable has no significant influence on
purchase decisions, with a coefficient value of
0.191. Thus the increase or decrease in prices
offered through promotions by TIX ID does
not affect purchasing decisions.
Convenience has no direct effect on purchasing
decisions of 0.115, with a significance level of
5% and a Critical Ratio (CR) value of 0.677
with a value of t count ≤ 1.65. The
Convenience of use of the TIX ID application
does not really affect the decision to buy
cinema tickets, since application users who are
generally students and young people have
sufficient time and money to spend.
Security has no direct effect on purchasing
decisions with a coefficient value of -0.195, at
a significance level of 5% and a Critical Ratio
(CR) value of -0.666 with a value of t count, ≤
1.65. As a result, the hypothesis is rejected.
The security variable does not influence
purchase decisions since the security element
of utilizing TIX ID still does not guarantee the
risk factors from the transactions conducted.
Thus it can be concluded that the factors of
promotion, convenience and security do not have a
direct effect on purchasing decisions.
4.6 Effect of Purchase Intention (Y1) on
Purchasing Decisions (Y2)
The third hypothesis test demonstrates and proves
the impact of the purchasing interest variable on
purchase choices. At the 5% significance level, the
findings of testing the third hypothesis reveal that
buying interest directly influences purchase
decisions by 1.019. With a critical ratio (CR) of
3.265 with a value of t count ≥ 1.65. This leads to
the conclusion that purchasing intention has a
substantial beneficial impact on purchasing
decisions. The results showed that the higher the
buying interest, the higher the decision to buy.
Conversely, the lower the buying interest, the lower
the purchasing decisions by consumers.
5 Conclusion, Suggestion and
Implication for Future Research
In general, it can be concluded from this research
that promotion and convenience factors have a
significant and direct influence on consumer buying
interest. It should also be noted that the effect of the
promotion variable is greater than the convenience
variable. It is also well established that promotions,
convenience, and security have no direct or
meaningful impact on purchase decisions. The
study's findings suggest that promotion and
convenience variables indirectly impact purchase
decisions through customer purchasing desire.
The conclusion above is related to the use of
the TIX ID application in relation to the need to buy
cinema tickets online, but it may be different if the
same research model is applied to other purposes of
use. For this reason, it is recommended to conduct
similar research for other purposes such as
shopping, paying for parking and so on. The
security factor that does not have an influence on
buying interest can be caused by consumers still
thinking about the risks that may occur so that the
TIX ID seller still needs to explain about the
guarantee against the risks that may occur.
Consumers are quite critical of the new things they
experience but need sufficient time to decide to
adopt the new innovation.
In connection with this problem, it is
necessary to conduct other research related to
buying interest and purchasing decisions related to
the educational background and age of consumers,
knowledge of the internet and its applications, how
fast consumers are in adopting new innovations and
also compared with the responses of consumers who
have experience using TIX. ID, especially in terms
of security and risks that have been faced.
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2022.18.2
John Ehj. Foeh, Adler Haymans Manurung,
Florentina Kurniasari, Tipri Rose Kartika,
Sandra Yunita
E-ISSN: 2224-3496
18
Volume 18, 2022
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(Attribution 4.0 International, CC BY 4.0)
This article is published under the terms of the
Creative Commons Attribution License 4.0
https://creativecommons.org/licenses/by/4.0/deed.en
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WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2022.18.2
John Ehj. Foeh, Adler Haymans Manurung,
Florentina Kurniasari, Tipri Rose Kartika,
Sandra Yunita
E-ISSN: 2224-3496
19
Volume 18, 2022