Vol. 5, No. 4, April 2024

E-ISSN: 2723-6692

P-ISSN: 2723-6595

http://jiss.publikasiindonesia.id/

Indonesian Journal of Social Science, Vol. 5, No. 4, April 2024 842

The Effect of Viral Marketing and E-Service Quality on Consumer

Buying Interest in Disney+ Hotstar Services

Rama Raihan Syihab, Erlita Ridanasti

Universitas Islam Indonesia, Yogyakarta, Indonesia

Email: bohbohan6@gmail.com, erlita.ridanasti@uii.ac.id

Correspondence: bohbohan6@gmail.com

KEYWORDS

ABSTRACT

Viral Marketing; E-Service

Quality; Consumer

Purchase Interest; Disney+

Hotstar

This research was conducted with the aim of determining the

influence of Viral Marketing and E-Service Quality on Consumer

Purchase Interest in the Disney+ Hotstar Indonesia service. The

population in this study is residents who are users or residents

who know the Disney+ Hotstar Indonesia Video on Demand service

in the Yogyakarta area. This research uses a quantitative approach,

with data collection techniques using questionnaires distributed

online. The sampling technique used purposive sampling with a

sample of 180 respondents. The data analysis used in this research

is multiple linear regression analysis with the Moderated

Regression Analysis (MRA) test which is processed with IBM SPSS

Statistics 26.0 software. The results of this research show that Viral

Marketing has a positive and significant influence on Consumer

Purchase Interest. Meanwhile, E-service Quality has a positive and

significant influence on Business Model Innovation. It was also

found that organizational risk-taking tolerance is a factor in

consumer buying interest. And the Viral Marketing and E-Service

Quality variables together have a positive and significant effect on

Consumer Purchase Interest.

Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)

1. Introduction

Video on Demand (VOD) is a method of delivering media content that enables viewers to watch

videos without being restricted by conventional playback devices or fixed broadcast schedules.

During the 20th century, the dominant mode of media distribution was broadcasting via over-the-air

programming. However, with the advent of internet technology and IPTV in the 1990s, there was a

growing consumer demand for alternative ways to consume content, leading to the emergence of VOD

services accessible on both television and personal computers (Wikipedia, 2022). The concept of VOD

emerged in the media industry and is related to how video content is delivered. Video on Demand

(VOD) is a technology that stores all content that can be accessed at any time that can be paused,

playback, skipped, or even downloaded (Pereira & Tam, 2021).

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Streaming media has gained significant traction as a method for delivering Video on Demand

(VOD). Platforms such as Apple's iTunes and Smart TV applications like Amazon Prime Video offer

options for renting or buying temporary video content. Additionally, there are Internet-based VOD

systems that provide access to bundles of entertainment content rather than just individual titles.

Among the most well-known VOD services are Netflix, Hulu, Disney+, Peacock, HBO Max, and

Paramount+, all of which operate on a subscription basis, requiring users to pay a monthly fee for

access to a library of movies, TV shows, and original series.

In contrast, platforms like YouTube and other internet-based Video on Demand (VOD) systems

employ an advertising-supported approach, offering most of their video content for free while

charging higher subscription fees for premium content access. Additionally, certain airlines offer VOD

as part of their in-flight entertainment, providing passengers with access to content through in-seat

video screens or external portable media players..

As technology develops, a shift from conventional media to digital media has occurred. People

spend more of their time online, including on social media. This opens up new opportunities for

marketers to reach their target market more interactively. Social media platforms like Facebook,

Twitter, Instagram, and others have become very effective places to share information and content.

Content that is unique, entertaining, or controversial has great potential to go viral. People tend to

share content that grabs their attention or triggers certain emotions.

Therefore, the term viral marketing emerged. Viral marketing is a marketing strategy that aims

to create buzz and generate widespread attention for a product, service, or brand through rapid and

exponential content dissemination through word of mouth or online sharing. Viral marketing is one

way of marketing based on the internet by taking advantage of opportunities where consumers often

use social networks in everyday life.

According to Paramita, S. (2020, December). Viral Marketing Model Through Digital Content. In

The 2nd Tarumanagara International Conference on the Applications of Social Sciences and

Humanities (TICASH 2020) (pp. 431-434). Atlantis Press. Viral marketing is basically a form of

internet-based word-of-mouth marketing (e-word of mouth marketing) whose promotional function

is networking and designed like a virus spreading from one person to another quickly and widely by

providing special rewards to consumers.

The trust of a consumer or customer in the company is needed, especially in a business that is

carried out with a viral marketing strategy that does not meet each other face to face in transactions.

The company must be able to make a consumer or customer put trust in the company through efforts

to maintain and improve the quality of service to consumers or customers.

High quality can offer added value by serving as a unique incentive for customers to cultivate

enduring and mutually advantageous relationships with the company. (Tjiptono, 2022). This

emotional connection enables the company to gain deep insights into the expectations and individual

requirements of customers, thereby enhancing customer satisfaction. By prioritizing a positive

customer experience, companies can amplify enjoyable interactions while minimizing or eradicating

negative ones. Put simply, service quality can be seen as a gauge of how effectively the service level

meets customer expectations. (Tjiptono, 2022).

Business activities began to shift from conventional patterns to more advanced patterns, one of

which was shopping activities. Shopping activities have begun to shift from offline shopping to online

shopping. Online shopping is a business activity that uses information and communication technology

applications in every transaction. Online shopping is not only used for buying and selling but also for

promotional efforts at large. Consumers do not need to come directly to the store, they only need to

visit the intended site and determine the goods / services they need.

The quality of service provided is also different when compared to the quality of service in

conventional shopping models. In conventional shopping, service quality is measured directly

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through activities between sellers and buyers, while the quality of online or electronic shopping is

measured through services provided by companies through websites or what is often referred to as

e-service quality.

E-service quality refers to the quality of services provided through electronic channels such

as websites, mobile applications, or online platforms. The focus is on the customer's perception of the

total service experience when interacting online with the company or organization. E-service quality

is important to build customer satisfaction, trust, and loyalty in the digital world. By focusing on the

above aspects, companies can deliver a seamless and satisfying online experience that meets or

exceeds customer expectations.

E-service quality, commonly called E-SerQual, was developed to evaluate a service provided

on the internet network. Parasuraman et al. (2005) define e-service quality or electronic service

quality as the extent to which a website is able to facilitate consumer activities, including shopping,

purchasing, and delivery of both products and services efficiently and effectively. Thus, customers

will be more efficient in making transactions in terms of time and cost. Similarly, the availability and

completeness of information and ease of making transactions are also the customer's choice in using

the services of a company.

On the other hand, Walt Disney is a most influential and successful company with business

models for animated and live-action films as well as television shows, theme parks and so on. The

scope and volume of Walt Disney's influence was considerable in similar business environments.

Disney+ Hotstar is an Indian Video on Demand (VoD) service owned by Disney Star and launched in

2015 which is a subsidiary of The Walt Disney Company. Video on Demand (VoD) services such as

Disney+ Hotstar are media delivery systems that allow users to access video without the restrictions

of traditional video playback devices or typical static broadcast schedules. Video on Demand (VoD)

service from Disney+ Hotstar can be used on several devices, such as Android-based Smart TVs,

smartphones, and tablets.

The well-known survey institute Populix (2022) calls video-on-demand (VoD) services a

convenient way to watch a show, ranging from films to other visual series. This is because consumers

do not need to wait for the show schedule to start because consumers can choose their favorite

programs and watch them anytime and anywhere. In terms of consumer usage behavior, Populix

stated that the majority of Indonesians (36 %) open and/or use Video on Demand (VoD) applications

every day, 13% of those surveyed open the application more than 5 times a week, 15 percent of

respondents open Video on Demand (VoD) applications 4-5 times a week, 25 percent of other

respondents use applications 2-3 times a week, 6 percent of users open an app once a week, only 4

percent of respondents use Video on Demand (VoD) services once a month, and only 1 percent of

respondents use Video on Demand (VoD) services once every two weeks. This number is quite

extraordinary because it proves that Video on Demand (VoD) applications are increasingly popular

and become the main choice of Indonesian people when looking for entertainment when tired.

Databooks (2023) states that Disney+ Hotstar is the best-selling paid streaming application in

Indonesia. Its position even surpasses Netflix, Vidio, and HBO GO. Disney+ Hotstar is the best-selling

app with 70% of respondents subscribing. Below Disney+ Hotstar is Netflix; the percentage of

subscribers surveyed is 46%, followed by Vidio at 41%.

Based on the above, the author tried to conduct a research entitled "The Effect of Viral

Marketing and E-Service Quality on Consumer Buying Interest in the Use of Disney+ Hotstar

Indonesia Video On Demand (VoD) Services - Study on Disney+ Hotstar Indonesia Video On Demand

Service Users at the Faculty of Business and Economics UII Yogyakarta.

The purpose of this study is to determine the influence of Viral Marketing on consumer buying

interest in using Disney+Hotstar Indonesia's video-on-demand (VoD) service.

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This research is expected to increase knowledge and insight into the influence of viral

marketing and e-service quality on purchase intentions in the marketing field. The results of this

study are also expected to help as a reference for future research related to viral marketing, e-service

quality, and consumer buying interest.

2. Materials and Methods

This research was conducted with descriptive methods and quantitative approaches. A

quantitative approach is a method of testing data where the information obtained is classified,

compared, and calculated using formulas relevant to the data (Indriantoro & Supomo, 2002) (Rum et

al., 2019). The object raised in this study is Disney+ Hotstar Indonesia. This study was conducted to

identify the relationship between the influence of viral marketing and e-service quality on consumer

buying interest.

The author will evaluate this study, in which this type of research was carried out by

distributing questionnaires. The questionnaires were distributed using social media platforms such

as Instagram, Twitter, Line, and Whatsapp.

The location of the research was carried out in Yogyakarta. The researcher chose this location

because the researcher is currently domiciled in Yogyakarta. On the other hand, Yogyakarta is also

referred to as a student city to make it easier for researchers to find and be interviewed more easily,

especially Yogyakarta, where most of the population is the millennial generation who generally tend

to follow technological changes. According to Databooks (2021), as many as 23.42% of the population

Yogyakarta is a millennial (1981-1996). As many as 22.76% are Generation Z (1997-2012),

22.46% Generation X (1965-1980), and 16.89% are Baby Boomer generation (1946-1964).

This study was conducted by collecting data from 180 respondents through an online survey

created using Google Forms and distributed through social media platforms. Descriptive analysis

showed the characteristics of respondents based on gender, age, occupation, income, and place of

residence. The analysis results indicated that the majority of respondents were aged 17-25 years,

students, with incomes ranging from Rp.1,000,000 to Rp.2,000,000, and from Sleman, Yogyakarta.

The analysis of variables influencing consumer buying interest, namely Viral Marketing, E-

Service Quality, and Consumer Buying Interest, showed high average values, indicating positive

perceptions of respondents towards Disney+ Hotstar's services and marketing. Validity and reliability

tests were conducted using SPSS, with all variables showing valid and reliable values.

3. Result and Discussion

The study was tested with 180 respondents who were successfully collected using an online survey

(questionnaire) created with Google Forms and distributed to social media platforms.

Descriptive Analysis of Respondents

Table 1 Characteristics of Respondents by Sex

Gender

Number of

Respondents

Percentage

Man

104

57,8%

Woman

42,2%

Total

180

100%

Source: Researcher's Processed Data, 2023

Table 1 shows respondent data by gender from 180 respondents. The results of the 180

respondents showed that the number of female respondents was 76 people or as much as 42.2%. While

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the number of respondents who were male was 104 people or as much as 57.8%. Data shows that

men know more about Disney+ services than women.

Table 2 Characteristics of Respondents by Age

Age

Number of

Respondents

Percentage

<17 Years

7,8%

17-25 Years

139

77,2%

26-34 Years

13,9%

35-42 Years

0,6%

>42 Years

0,6%

Total

180

100%

Source: Researcher's Processed Data, 2023

Table 2 shows that the number of respondents with an age range of less than <17 years was

14 respondents or 7.8%. The number of respondents with an age range of 17-25 years was 139

people, or as much as 77.2%. The number of respondents with an age range of 26-34 years was 25

people or 13.9%. The number of respondents with an age range of 35 – 42 years was 1 person or

0.6%. And respondents over the age of 42 years 1 person or 0.6%. This shows that most respondents

in this study were aged 17-25 years.

Table 3 Characteristics of Respondents by Occupation

Work

Number of

Respondents

Percentage

Student

46,7%

Self-employed/Entrepreneur

11,7%

Civil Servants

2,8%

SOE Employees

3,9%

Private Employees

23,9%

Not yet employed/looking for

a job

11,7%

Sum

180

100%

Source: Researcher's Processed Data, 2023

Table 3 shows that the number of student respondents was 84 people or 46.7%. The number

of self-employed respondents/entrepreneurs was 20 people, or 11.7%. The number of civil servant

respondents was 5 people or 2.8%. The number of respondents of BUMN employees was 7 people or

3.9%. The number of respondents of private employees was 43 people or 23.9%. The number of

respondents for people who are not yet working/or are looking for work is as many as 21 people or

11.7%. This shows that most respondents in this study are students/students.

Table 3 Characteristics of Respondents by Income

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Income

Number of

Respondents

Percentage

<IDR 1,000,000

12,3%

IDR 1,000,000 – IDR 2,000,000

32,4%

IDR 2,000,000 - IDR 3,000,000

17,9%

IDR 3,000,000 – IDR 4,000,000

11,7%

>Rp.4.000.000

25,7%

Sum

180

100%

Source: Researcher's Processed Data, 2023

Table 3 shows that the number of respondents with an income of <Rp.1,000,000 was 22 people

or 12.3%. The number of respondents with an income of Rp.1,000,000 – Rp.2,000,000 was 58 people

or 32.4%. The number of respondents with an income of Rp.2,000,000 – Rp.3,000,000 was 32 people

or 17.9%. The number of respondents with income of Rp.3,000,000 – Rp.4,000,000 was 21 people or

11.7%. And the number of respondents with an income of >Rp.4,000,000 was 46 people or 22.7%.

This shows that most respondents in this study earn Rp.1,000,000 – Rp.2,000,000.

Table 4 Characteristics of Respondents by Domicile

Domicile

Number of

Respondents

Percentage

Sleman

37,8%

Bantul

13,3%

Kulonprogo

10,6%

Gunung Kidul

Yogyakarta

33,3%

Sum

180

100%

Source: Data processed by researchers, 2023

The results in Table 4 show that the number of respondents from Sleman was 68 people or

37.8%. The number of respondents from Bantul was 24 people, or 13.3%. The number of respondents

from Kulonprogo was 19 people, or 10.6%. The number of respondents from Gunung Kidul was 9

people, or 5%. The number of respondents from Yogyakarta was 60 people, or 2%. This shows that

the domicile of most respondents in this study is from Sleman.

Descriptive Analysis of Variables

Descriptive variables are explanations of the analysis of the results of descriptive analysis of

each research variable. The descriptive results of variables include Viral Marketing, E-Service Quality,

and Consumer Buying Interest. A descriptive scale is needed to analyze each of the research variables

described in Table 5 as follows:

Table 5 Descriptive Scale of Variables

Average Score

Interpretation

1,00 – 1,80

Strongly Disagree

1,81 – 2,60

Disagree

2,61 – 3,40

Nervous

3,41 – 4,20

Agree

4,21 – 5,00

Totally Agree

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Viral Marketing Variable Analysis

Table 6 Descriptive Viral Marketing

Code

Viral Marketing Items

Mean

Category

Description

MBK.1

There is a desire to brand Disney+

Hotstar Indonesia products to others.

4,28

Totally Agree

MBK.2

Disney+ Hotstar Indonesia products

are worth recommending to others.

4,25

Totally Agree

MBK.3

There is interest in subscribing to

Disney+ Hotstar Indonesia.

4,38

Totally Agree

MBK.4

There is interest in resubscribing to

Disney+ Hotstar Indonesia.

4,11

Agree

MBK.5

Disney+ Hotstar subscription fee is

relatively cheap

4,15

Agree

MBK.6

Disney+ Hotstar products deserve to be

a priority choice

4,16

Agree

MBK.7

There is a desire to find more detailed

information about Disney+ Hotstar

Indonesia products.

4,37

Totally Agree

MBK.8

There is a desire always to update

information about Disney+ Hotstar

Indonesia products to others.

4,47

Totally Agree

Average of overall variable items

4,27

Judging from Table 8, it can be seen that of the 180 respondents taken as a sample, most of

the respondents gave a very agreeable assessment of the question of consumer buying interest

variables. The highest ranking is on "There is a desire to always update information about the product

Disney+ Hotstar Indonesia to others.". The lowest rating is on "There is interest in resubscribing

Disney+ Hotstar Indonesia.”. Overall, respondents gave a high assessment of the variable consumer

buying interest. This shows that consumer buying interest has a good value in the sample in the

Yogyakarta area.

Research Instrument Test

In this study, measurements were carried out by testing the validity and reliability of each

variable, namely Viral Marketing, E-Service Quality, and consumer buying interest. Testing the

validity and reliability of these variables was carried out with the help of the SPSS program with a

total of 180 respondents.

Validity Test

The validity test is based on indicator analysis, which involves correlating each indicator score

with a variable score or the total score of all question indicators. In this study, the number of research

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samples was obtained as many as 180 respondents, then obtained a value (dF) = 180-2 for a

confidence level of 95% (α = 5%) so that the r table was obtained at 0.1463. As well as testing this

validity help the SPSS Statistic 26 application. The questionnaire can be said to be valid if the

calculated r value is greater than the table r or if the significance level is less than 0.05. The results of

the validity test can be seen in Table 9 below:

Table 9 Validity Test Results

Variable

Indicators

R-count

Information

Viral Marketing

VM.1

0,660

Valid

VM.2

0,636

Valid

VM.3

0,704

Valid

VM.4

0,557

Valid

VM.5

0,748

Valid

VM.5

0,707

Valid

VM.7

0,695

Valid

VM.8

0,643

Valid

VM.9

0,733

Valid

VM.10

0,682

Valid

E-Service Quality

ESQ.1

0,633

Valid

ESQ.2

0,612

Valid

ESQ.3

0,645

Valid

ESQ.4

0,648

Valid

ESQ.5

0,634

Valid

ESQ.6

0,590

Valid

ESQ.7

0,633

Valid

ESQ.8

0,633

Valid

ESQ.9

0,762

Valid

ESQ.10

0,648

Valid

ESQ.11

0,661

Valid

ESQ.12

0,623

Valid

Consumer Buying

Interest

MBK.1

0,687

Valid

MBK.2

0,625

Valid

MBK.3

0,776

Valid

MBK.4

0,686

Valid

MBK.5

0,783

Valid

MBK.6

0,723

Valid

MBK.7

0,679

Valid

MBK.8

0,648

Valid

Source: Data processed by researchers, 2023

Reliability Test

Reliability testing, according to Ghozali (2018), is the stability, reliability, and consistency of

a series of measurements. In this study, reliability tests used SPSS 26 software. The following are the

results of the reliability test calculations presented in Table 10:

Table 11 Reliability Test Results

Variable

Cronbach's Alpha

Information

Viral Marketing

0,864

Reliable

E-Service Quality

0,869

Reliable

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Consumer Buying

Interest

0,851

Reliable

Source: Researcher's Processed Data, 2023

A questionnaire is considered reliable if respondents' responses to the statement are

consistent over time (Ghozali, 2011). This measure of reliability uses the so-called Cronbach alpha.

Cronbach's alpha is a coefficient that indicates how well items in a set correlate with each other

(Sekaran & Bougie, 2016). A variable is said to be reliable if the result > 0.60 = reliable and the result <

0.60 = unreliable (Ghozali, 2011).

The results of the reliability test showed that all variables had an Alpha coefficient of > 0.60.

That way, it can be concluded that all the points of research variables are reliable and can be used as

variable research instruments.

Classical Assumption Test

Normality Test

The normality test is used to determine whether the residual or residual variables in the

regression model are normally distributed. Kolmogorov-Smirnov statistical test analysis was used for

this test. The t-test and f-test are known to assume that the residue follows the corresponding

distribution. If this point of view is violated, the statistical test is considered invalid. The normality

test is performed to find out whether in the regression model, the dependent variable and the

independent variable are normally distributed or not. This step is carried out by looking at the

distribution of residual distribution and by conducting statistical tests of Kolmogorov Smirnov. If the

significance value is greater than 0.05 then it can be concluded that normally distributed data and

regression models can be used.

The picture of the distribution of residual distribution is as follows:

Figure 2.0

Residual Distribution of Normality Test

The figure shows that the distribution of residual distribution spreads around the line

following a diagonal line. This means that the regression model is normally distributed. While

statistical tests Kolmogorov Smirnov, the following figures are obtained:

Table 12 Normality Test Results

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One-Sample Kolmogorov-Smirnov Test

Unstandardized

Residuals

180

Normal

Parametersa,b

Mean

0E-7

Std. Deviation

3.47617972

Most Extreme

Differences

Absolute

.101

Positive

.096

Negative

-.101

Kolmogorov-Smirnov Z

1.351

Asymp. Sig. (2-tailed)

.052

a. Test distribution is Normal.

b. Calculated from data.

Source: Data processed by researchers, 2023

Multicollinearity Test

In the Multicollinearity Test, a good regression model is if there is no correlation between

independent variables or, in other words, the correlation is 1 or close to 1. In addition, it can also be

seen from the value Tolerance and Inflation Factor (VIF). Value Inflation Factor (VIF) should be less

than 10 and for value Tolerance more than 0.1 (Priyastama, 2017). From the research data obtained

the following results:

Table 13 Multicollinearity Test Results

Coefficientsa

Type

Unstandardized

Coefficients

Standar

dized

Coefficie

nts

Sig.

Collinearity

Statistics

Std.

Error

Beta

Tolera

nce

VIF

(Constant)

-.827

3.288

-.251

.802

VM_X1

.267

.077

.280

3.485

.001

.517

1.934

ESQ_X2

.423

.082

.414

5.166

.000

.517

1.934

a. Dependent Variable: MBK_Y

Source: Data processed by researchers, 2023

The data shows that the Tolerance value is 0.517 and 0.517 where the number is more than

0.1. While the Inflation Factor (VIF) figures are at 1.934 and 1.934, where the numbers are less than

10. Thus it can be said that the variables in the study did not occur multicollinearity.

Heteroscedasticity Test

This heteroscedasticity test is performed in a regression model to find out whether the

residual observation is not the same as other observations fixed. This is called homoscedasticity, and

when different, it is called heteroscedasticity. A good regression model is one with constant

observation, homoscedasticity, or no heteroscedasticity. The test method is the Glejser test. From

Table 14, it can be concluded that the significance value is> 0.05. In this case, regression does not have

heteroscedasticity, so the heteroscedasticity test is fulfilled. The results of the heteroscedasticity test

are presented in the following table:

Table 14 Heteroscedasticity Test Results

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Variable

Sig.

Conclusion

Viral Marketing

0,222

No heteroscedasticity

occurs

E-Service Quality

0,833

No heteroscedasticity

occurs

Source: Data processed by researchers, 2023

Test the hypothesis

Significant Test T (Test T)

H1: Viral Marketing has a positive and significant effect on Consumer Buying Interest in using

Disney+Hotstar Indonesia video-on-demand (VoD) services.

The criterion used is that if the sigifikansi value (Sig) < 0.05, then the independent variable

(X1) partially affects the dependent variable (Y).

Table 15 T-Test Results

Coefficients

Type

Unstandardize

d Coefficients

Standardize

Coefficients

Sig.

Collinearity

Statistics

Std.

Error

Beta

Tolerance

VIF

(Constan

-.827

3.288

-.251

.80

VM_X1

.267

.077

.280

3.485

.00

.517

1.9

ESQ_X2

.423

.082

.414

5.166

.00

.517

1.9

a. Dependent Variable: MBK_Y

Source: Data processed by researchers, 2023

When viewed from the table above, it appears that the level of significance (Sig) of the variable

Viral Marketing (VM_X1) is 0.001. The number is below 0.05, which means the variable independent

(X) Viral Marketing (VM_X1) partially has a significant effect on the dependent variable (Dependent),

namely Consumer Buying Interest (MBK_Y).

In addition, according to Sujarweni Sujarweni (2014), if t counts > t table, then the independent

variable (X1) affects the dependent variable (Y).

So, the t table is seen at 0.025; 177, if seen in the table, points to 1.973. If consulted with the

table above, it can be seen that t calculates the variable Viral Marketing (VM_X1) 3.485 is greater than

1.973. Thus, the independent variable (X) Viral Marketing (VM_X1) partially has a positive and

significant effect on the dependent variable, namely Consumer Buying Interest (MBK_Y).

H2: E-Service Quality (ESQ has a positive and significant effect on Consumer Buying Interest

in using services Video on Demand (VoD) Disney+Hotstar Indonesia.

When viewed from the table above, it appears that the significance level (Sig) of the E-Service

Quality (ESQ_X2) variable is 0.00. This number is below 0.05, which means that the independent

variable E-Service Quality (ESQ_X2) partially has a significant effect on the dependent variable, namely

Consumer Buying Interest (MBK_Y).

Table 16 T-Test Results

Coefficientsa

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Type

Unstandardized

Coefficients

Standard

ized

Coefficie

nts

Sig.

Collinearity

Statistics

Std.

Error

Beta

Tolera

nce

VIF

(Constan

-.827

3.288

-.251

.802

VM_X1

.267

.077

.280

3.485

.001

.517

1.934

ESQ_X2

.423

.082

.414

5.166

.000

.517

1.934

a. Dependent Variable: MBK_Y

Source: Data processed by researchers, 2023

In addition, according to Sujarweni (2014), if t counts > t table, then the variable independent

(X) effect on variables Dependent (Y).

So t table is seen at 0.025; 177, if seen in the table points to 1.973. If consulted with the table above,

it can be seen that the calculation t for the E-Service Quality (ESQ_X2) variable is 5.166. greater than

1,973. Thus, the independent variable E-Service Quality (ESQ_X2) partially has a positive and

significant effect on the dependent variable, namely Consumer Buying Interest (MBK_Y).

Significant Test F (Test F)

H3: Viral Marketing and E-Service Quality together affect Consumer Buying Interest in using

the service Video on Demand (VoD) Disney+Hotstar New Zealand

The Simultaneous Regression Coefficient Test (Test F) is carried out with the criterion if the

significance value (Sig) < 0.05, then the independent variable (X) simultaneously or together affects

the dependent variable (Y). From the results of processing research data, the following picture is

obtained:

Table 17 F Test Results

ANOVA

Type

Sum of

Squares

Mean

Square

Sig.

Regres

sion

1508.573

754.287

61.

724

.000

Residu

als

2163.005

12.220

Total

3671.578

a. Dependent Variable: MBK_Y

Source: Data processed by researchers, 2023

From the table above, it can be seen that the Significance value is 0.00, which means it is less

than 0.05. If calculated by the formula F table where if F calculate > F table, then the variable

independent (X) effect on variables Dependent (Y).

So, the F table is seen at number 2, 180, with the result pointing at the number 19, 49. If you

consult the table above, it can be seen that F count points to the number 61.724. When connected

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Indonesian Journal of Social Science, Vol. 5, No. 4, April 2024 856

with F table, it appears that 61.724 > 19.49. Thus, it can be concluded that the Viral Marketing Variable

(VM_X1) and the E-Service Quality Variable (ESQ_X2) simultaneously or together have a positive and

significant effect on the Consumer Buying Interest Variable (MBK_Y).

Results of the Coefficient of Determination

The coefficient of determination test is needed to determine the ability of the independent

variable or independent in explaining a bound variable or Dependent.

Table 18 Results of the Coefficient of Determination

Model Summaryb

Type

Square

Adjusted R

Square

Std. Error of

the Estimate

.641a

.411

.404

3.496

a. Predictors: (Constant), ESQ_X2, VM_X1

Source: Data processed by researchers, 2023

From the table mentioned above, it can be seen the coefficient of determination, namely in the

column Adjusted R Square. In the column Adjusted R Square, There is a number of 0.404, which means

that the coefficient of determination is 40.4%. The figure 40.4% means that the ability of the

independent variable or independent to explain a bound variable or Dependent is 40.4%. Thus, there

are still about 59.6% which is another factor that affects the dependent variable or Dependent.

Discussion of Results

If the regression equation is consulted with the results of research data processing as

mentioned in the table below:

Table 19 Regression Equation Results

Coefficients

Type

Unstandardized

Coefficients

Standard

ized

Coefficie

nts

Sig.

Collinearity

Statistics

Std.

Error

Beta

Toleranc

VIF

(Constant)

-.827

3.288

-.251

.802

VM_X1

.267

.077

.280

3.485

.001

.517

1.934

ESQ_X2

.423

.082

.414

5.166

.000

.517

1.934

a. Dependent Variable: MBK_Y

Source: Researcher's Processed Data. 2023

Then the regression equation becomes:

Y = -0.827 + 0.267X1 + 0.423X2 + e

The regression equation means that:

1. If there is no change in the Viral Marketing variable (X1) and E-Service Quality variable (X2),

there will be -0.827 units in Consumer Purchase Intent for Disney+Hotstar Indonesia users. It

also illustrates the importance of activities related to Viral Marketing and E-Service Quality for

Disney+Hotstar Indonesia companies so that Consumer Buying Interest is always well

maintained.

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Indonesian Journal of Social Science, Vol. 5, No. 4, April 2024 857

2. If the Viral Marketing variable (X1) increases by 1% and the E-Service Quality variable (X2) is

zero. The constant is also zero, then the Viral Marketing variable (X1) will contribute positively

by 0.267 units to the Consumer Buying Interest variable of Disney+Hotstar Indonesia users.

This is in line with research conducted by Furqon (2020), which shows that Viral Marketing has

a significant effect on purchasing decisions. In addition, research conducted by Sembiring &

Ananda (2019) and research conducted by Dima et al. (2020) also show that there is a significant

impact of viral marketing on consumer purchase intentions.

In theory, this is in line with what Hendrayati & Pamungkas (2020) conveyed, which states that Viral

Marketing is something that has been created by the company itself to promote its products, in

the hope that people who see the campaign will be impressed so that they will convey the

message to their friends and family.

3. Furthermore, if the E-Service Quality (X2) variable increases by 1% and Viral Marketing (X1) is

zero and the constant is also zero, then the E-Service Quality (X2) variable will contribute

positively by 0.423 units to the Consumer Buying Interest variable of Disney+Hotstar Indonesia

users.

If you look at the results of multiple regression tests simultaneously where it turns out that the

Viral Marketing Variable (VM_X1) and the E-Service Quality Variable (ESQ_X2) simultaneously or

together have a positive and significant effect on the Consumer Buying Interest Variable (MBK_Y)

with a coefficient of determination of 0.404, it means the ability of the independent or

independent variable to explain the dependent variable is 40.4%. Thus, there are still about

59.6%, which is another factor that affects the dependent variable.

Thus, the Disney+Hotstar Indonesia company still needs to find other factors that influence

consumer purchase intentions on Disney+Hotstar Indonesia products so that the company has higher

competitiveness. Other factors beyond Viral Marketing and E-Service Quality which amounted to

59.6% are a challenge for future researchers to conduct further research.

4. Conclusion

Based on the analysis and discussion of the influence of Viral Marketing and E-Service Quality

on Consumer Buying Interest in using Disney+Hotstar Indonesia's video-on-demand (VoD) service,

several conclusions emerge. Firstly, it is evident that Viral Marketing significantly impacts Consumer

Buying Interest in utilizing Disney+Hotstar Indonesia's VoD service. Secondly, E-Service Quality also

plays a crucial role in influencing Consumer Buying Interest in the same service. Moreover, when

considering both Viral Marketing and E-Service Quality together, they jointly exert a considerable

influence on Consumer Buying Interest in utilizing Disney+Hotstar Indonesia's VoD services. These

findings underscore the importance of effective marketing strategies and high-quality service

provision in driving consumer interest and engagement with VoD platforms like Disney+Hotstar

Indonesia.

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