Factors affecting intention to subscribe SVOD in Vietnam

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VIETNAM

x

NATIONAL

x

UNIVERSITY, HANOI

VIETNAM

x

JAPAN

x

UNIVERSITY

---

LE PHU KHANH

FACTORS AFFECTING INTENTION TO

SUBSCRIBE TO SUBSCRIPTION VIDEO

ON DEMAND SERVICES IN

x

VIETNAM

MASTER’S THESIS

x

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VIETNAM

x

NATIONAL

x

UNIVERSITY, HANOI

VIETNAM

x

JAPAN

x

UNIVERSITY

---

LE PHU KHANH

FACTORS AFFECTING INTENTION TO

SUBSCRIBE TO SUBSCRIPTION VIDEO

ON DEMAND SERVICES IN

x

VIETNAM

MAJOR:

x

BUSINESS ADMINSTRATION

CODE:

x

8340101.01

RESEARCH

x

SUPERVISORS:

Prof. Dr. MOTONARI TANABU

Dr. TRAN HUY PHUONG

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ACKNOWLEDGMENT

First of all, I would like to give my thanks to Prof.Dr. Montonari Tanabu and

Doctor Tran Huy Phuong for helping and give me a lot of valuable advice

during the time I was conducting this master thesis.

Second, I would like to thank Prof. Matsui, Hanh sensei, Hino sensei, Tuan

sensei for giving me comments to improve my thesis on internal defense on

20 May. Moreover, I would like to thank the reviewers, including Prof.

Matsui, Prof.Morita, Hanh sensei. Tuan sensei, Lien sensei for giving me

comments on final defense on 24

June.

In addition, I would like to give many thanks to my family, who has

supported me and motivated me a lot in the time I got difficult in doing the

thesis.

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Table of Content

ACKNOWLEDGMENT
LIST OF TABLES
LIST OF FIGURES

LIST OF ABBREVIATION

CHAPTER 1: INTRODUCTION ... 1

1.1 Research Background ... 1

1.2 Research Objective ... 4

1.3 Research Question ... 4

1.3 Research Subjective and Research Scope ... 4

1.4 Research Contribution ... 4

CHAPTER 2: LITERATURE REVIEW AND HYPOTHESIS 
DEVELOPMENT ... 6

2.1 Review of related definition and previous research ... 6

2.1.1 Definition of OTT platform... 6

2.1.2 Definition of Streaming ... 6

2.1.3 Definition of Video on demand (VOD) ... 7

2.1.4 Definition of Subscription Video on demand (SVOD) ... 8

2.1.5 Related research & research gap ... 9

2.2 Review of the relevant theoretical model of technology adoption: ... 14

2.2.1 Theory of reasoned action (TRA) ... 14

2.2.2 Theory of planned behavior (TPB) ... 15

2.2.3 Technology acceptance model (TAM) ... 15

2.2.4 Unified theory of acceptance and use of technology (UTAUT) ... 16

2.2.5 Reason why the author choosing UTUAT2 as theoretical framework ... 18

2.3 Hypothesis development and conceptual model ... 18

2.3.1. Performance Expectancy ... 19

2.3.2. Effort Expectancy ... 20

2.3.3. Social Influences ... 21

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2.3.5. Price Value ... 22

2.3.6. Facilitating condition ... 23

2.3.7. Consumer Innovativeness ... 23

2.3.8. Media exposure ... 24

2.4 Research conceptual model ... 27

CHAPTER 3: METHODOLOGY ... 28

3.1. Research process ... 28

3.2. Sampling and data collection ... 29

3.3. Sample Population ... 29

3.4. Variable and Measuring Instrument ... 29

3.5. Analysis Method ... 32

3.5.1 Descriptive analysis ... 32

3.5.2 Inferential analysis ... 33

CHAPTER 4: ANALYSIS RESULTS ... 36

4.1 Data Description ... 36

4.2 Reliability analysis ... 38

4.2. Explanatory Factor Analysis ... 38

4.3.1 Explanatory Analysis for independent variable ... 38

4.3.2 Explanatory Analysis for dependent variable... 40

4.3.3 Explanatory Analysis for moderation variable... 40

4.3. Regression Analysis ... 41

4.4. Moderation Analysis... 42

4.5 Hypothesis tested results ... 44

CHAPTER 5: DISCUSSION AND CONCLUSION... 46

5.1. Finding and Discussion ... 46

5.2. Contribution of the thesis ... 50

5.3. Implications for SVOD service providers ... 50

5.4. Limitation and future research direction... 52

REFERENCES ... 54

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APPENDIX 2: Cronbach’s alpha analysis ... 75

APPENDIX 3: Explanatory Analysis ... 80

APPENDIX 4: Pearson Correlation Analysis ... 84

APPENDIX 5: Regression analysis ... 85

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LIST OF TABLES

Table 2.1: Construct's definition ... 19

Table 3.1: Measurement Scale of thesis ... 30

Table 4.1: Cronbach’s alpha for all variable ... 38

Table 4.2: EFA Results for Independent variable ... 39

Table 4.3: EFA Results for Dependent Variable ... 40

Table 4.4: EFA Results for Moderator ... 40

Table 4.5: Results of Pearson Analysis ... 41

Table 4.6: Results of regression analysis ... 41

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LIST OF FIGURES

Figure 2.1: Results study of Cerbeci et al (2019) ... 9

Figure 2.2: Results study of Ramírez-Corre et al (2018) ... 10

Figure 2.3: Research results of Sardanelli et al (2019) ... 11

Figure 2.4: Theory of reasoned action (Fishbein & Ajzen, 1975) ... 14

Figure 2.5: Theory of planned behavior (Ajzen, 1991) ... 15

Figure 2.6: Technology acceptance model (Davis, 1989) ... 16

Figure 2.7: Unified theory of acceptance and use of technology UTAUT 
(Venkatesh et al., 2003) ... 17

Figure 2.8: Unified theory of acceptance and use of technology UTAUT2

(Venkatesh et al., 2012) ... 18

Figure 3.1: Research Model Proposed by Author ... 27

Figure 4.1: Age group of respondences ... 27

Figure 4.2: Descriptive data of current users ... 37

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LIST OF ABBREVIATION

OTT

Over-the-top

SVOD

Subscription Video on demand

TAM

Technology Acceptance Model

TPB

Theory of Planned Behavior

TRA

Theory of Reasoned Action

UTAUT

Unified Theory of acceptance and use

of technology

UTAUT2

Extended Unified Theory of

acceptance and use of technology

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CHAPTER 1: INTRODUCTION

1.1 Research Background

Today, thanks to the advancement of technology, people have changed the way
they consume media (Shim & Kim, 2018). The development of Broadband Internet
paved the way for the multimedia industry to shift from traditional Cable TV to
OTT Streaming (Over-the-top Streaming). OTT is superior to the traditional Cable
TV because of 2 characteristics: mobility and internet (Kim et al., 2016). Thus, OTT
streaming has become the technology preferred by consumers to entertain (Shim et
al., 2018). OTT streaming is well-known for its service called Subscription video on
demand (SVOD).

During 2010, the SVOD market was still in the early stage, with the domination
of Netflix. However, in 2019, there were a lot of big players joining the SVOD
industry, such as Apple, Disney, and WarnerMedia, which pave a new era for the
SVOD market known as the name “Streaming Wars” (Ben, 2019). The predict of
Pwc Global Entertainment and Media Outlook report showed that the size of this
market will be doubling up to $72.8 billion. Other results showed that in 2018,
traditional cable TV firms had less than 3 million users, while SVOD services
revenue increased from 30 billion USD by 2016 to 68 billion USD by 2018 (Yen,
2019).

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level, there still positive evidence showing that this industry has the potential to
grow in Vietnam. By the analysis of Statista.com in 7/2019, there are more than
54% of Vietnamese frequently using the Internet, and these people will increase by
38% in 2023. Also, another figure showed that Vietnam users spend 6-7 hours each

day using the Internet, mainly for entertaining (Statista, 2020). In Vietnam, there are
36 SVOD firms. The foreign firms in this industry are Netflix, Apple TV,.. and the
most famous Vietnamese firms in this industry are ClipTV, FPT play. VTVcab ON,
VTC Now, My K+ NOW,… .The revenue growth of the SVOD industry in
Vietnam is predicted by up to 113% by 2023 (Statista, 2020). Many foreign SVOD
companies are interested in this market. For example, the leader of Netflix – one of
the big firms in the SVOD industry had a meeting with the Head of the Government
Office to make an agreement about entering Vietnam in November 2019 officially
(Luu, 2019). This evidence shows that Vietnam is a potential as well as high
competition for exploit such online entertainment services like SVOD.

For an industry that started to grow like SVOD in Vietnam, since the number of
SVOD users in Vietnam was still limited, the finding of consumer insight and user’s
psychology in subscription intention to SVOD is necessary.

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subscription intention of movie streaming service by using TPB as a based model
(Sardanelli et al., 2019). Although studies about SVOD investigated the
subscription intention from different angles, there still theoretical gaps that needs to
be filled. First, to the best of the author’s knowledge, most studies were looking at
one company (in this case, Netflix) rather than identify factors affecting behavior
intention for a whole industry like SVOD, especially in Vietnam. Second, there is a
lack of research applied UTAUT2 to the domain-specific case like SVOD industries.
Finally, previous studies were focusing on piracy, technology, finance factors.
There was a lack of factors related to mass media as well as factors related to
consumer’s traits to the behavioral intention of SVOD users.

About UTUAT2, this model was the latest one in technology adoption.
Venkatesh et al. (2012) mentioned adding moderator as the way to expand the
theory of UTAUT2. Following Vankatesh’s suggestion, many tried to test the role

of Age, Gender, Personalization,… as a moderator to UTAUT2. But to the best of
the author, there is no research added Media Exposure to UTAUT2 as a moderator.
There is reason to prove that Media Exposure can have a moderating effect. The
fact that consumers made their decision based on the information they gained. The
amount of information from media exposure can affect the cognitive function of a
person (Christakis et al. 2018). According to DeFleur, Melvin, and Everett Dennis
(1998), enough frequency of media exposure could change one person’s behavior
and belief. Because of that, Media Exposure can be treated as a moderator. The
thesis will test the role of Media Exposure whether it has a moderating effect on the
UTAUT2 construct.

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1.2 Research Objective

There is a lack of research applied UTAUT2 to understand consumer’s intention
to subscribe to SVOD. Therefore, this thesis will test UTAUT2 in the SVOD
context as empirical evidence contributes to the SVOD studies.

The thesis also tests the role of Consumer Innovativeness and moderating effect
of Media exposure to the UTAUT2 model to expand the approach of Media
exposure as moderators and contribute to the theory of UTAUT2.

1.3 Research Question

Based on the research motivation, both theoretical and practical, this study
answers the following question:

1. What are the factors that significantly influence users’ adoption of Subscription
video on demand in Vietnam?

2. Can Media Exposure moderate the relationship between the independent variable
and subscription intention of SVOD in Vietnam?

1.4 Research Subjective and Research Scope

- Research Subjective

The subject of the research will be “Factors affecting intention to subscribe to
SVOD of Vietnamese people who already have acknowledged about this service”.

- Research Scope

The scope of thisxstudyxwillmainly in Hanoi because they have a huge amount

of people in general and have already aware of SVOD service. This study will have
a time range from 2019 to 2020.

1.5.Research Contribution

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The thesis applied UTUAT2 since there is no literature of SVOD applied
UTAUT2 in the SVOD context, especially in Vietnam there has no study related to
subscription video on demand.

The study also confirmed the previous finding of Consumer Innovativeness on
intention behavior in SVOD context.

The study also found the Moderating effect of Mediaxexposurexon

thexrelationshipbetween Hedonic Motivation and Intention Behaviors. The finding

contributed to the UTAUT2 theory because this is the early study that investigates
the moderating role of media exposure to UTAUT2.

- Practical contribution

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CHAPTER

2:

LITERATURE

REVIEW

AND

HYPOTHESIS

DEVELOPMENT

2.1 Review of related definition and previous research

2.1.1 Definition of OTT platform

According to the Ministry of Information and Communication of Vietnam
(MIC, 2019), Over-the-top (OTT) platform is the media service that uses the
internet to transfer content and added values to consumers. OTT platform provides
content directly to the Internet rather than provides under the management of any
Internet Service Provider. Thus, it paves a way for OTT platform users to access
content on many different devices. Another feature of OTT is the recommendation
system that supports users to find content that they needed easily.

There are three types of OTT services. The first one is OTT television,
usually called streaming video. The example for this type are
subscriptionxvideoxonxdemand (SVOD) firms such as Netflix, Amazon Prime,
Hulu, … The second types of OTT are OTT messaging/voice calling services. OTT
messaging/voice calling can be defined as an instant messaging/ voice calling

service provided by the third party as an alternative to traditional SMS. The most
well-known brand for these types is WeChat, Skype, Viber, Zalo,... The final types
of OTT platform types are OTT music, known as music streaming. Examples of
these types are Spotify and YouTube Music (Technavio, 2019). This study will only
be focusing on the first types of OTT, which is video streaming.

2.1.2 Definition of Streaming

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(Austerberry, 2005). In a television broadcast, content is pushed to the user on a
certain schedule.

With streaming, users can choose content, generally through interaction with
the web provider's service. There are three ways to transmit multimedia content,
listed below:

a. Download

Content can be played by users after they have downloaded from the severs.
The multimedia file received will be stored on computer storage media. After
received the multimedia file successfully on the user’s side, the user can
access the content.

b. Progressive Download

Progressive download is defined as the media that can be played a few
seconds after the download process begins. Progressive download is similar
to streaming, but the media in this type still through the process of
downloading, or other terms called pseudo streaming.

c. Streaming

The media can be played directly without going through the download
process. Through this transmission process, parts of the media are received
on the user’s side can be played immediately.

Based on the above definition, it can be concluded that streaming is a method of
transferring content to the user via the web in real-time and can be watched without
having to wait for downloaded.

2.1.3 Definition of Video on demand (VOD)

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Until now, there are many videos on-demand services on the internet which
provide free video content such as Youtube, Vimeo, Dailymotion, and others. Users
of the service can enjoy content videos that have been uploaded by creators from
various fields, such as food, beauty, automotive, music, film, technology, and so on.

Based on the above definition, it can be concluded that the video on demand
is a system for watching video shows in a manner interactive where users can freely
choose the content and be able to control the content.

2.1.4 Definition of Subscription Video on demand (SVOD)

Subscriptionxvideoxonxdemand (SVOD) is defined as a service where users

are charged a subcription fee (generally per month) to be able to choose and enjoy
content freely provided by the SVOD service providers at any time and anywhere as
long as users are connected to the internet (Wayne, 2018). By using OTT
technology, SVOD services can have the ability to help users search for

entertainment content easily with the help of a recommendation system using A.I
and Big Data (Xavier, 2013).

SVOD is also defined as an online entertainment service where users are
charged monthly to access to a streaming library consisting of films, television
shows and other media content (Stastista, 2019a)

In the world such as Netflix, ESPN+, Hulu, and Vietnam such as FPT Play,
K+ Now, Clip TV are some examples of SVOD technology. The number of SVOD
users in the whole world is going up rapidly from around 283 million users a year
by 2018 to 411 million users by 2022. The younger generation is the one who
spends most of the time using SVOD, with users aged 18-24 years spend an average
ofx39 minutesper dayusing SVOD services (Stastista, 2019a)

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the remarkable features of OTT in general as well as SVOD comes from a
recommendation system that helps users find their entertainment content faster.

2.1.5 Related research & research gap

Related Research

Recently, there are a few authors have mentioned about subscription
intention of SVOD. The detail of each research is mention at the following:

Cebeci et al. (2019) were one of the pioneer studies in SVOD with the topic
“Understanding the Intention to Use Netflix: An Extended Technology Acceptance
Model Approach”. UsedxTAMxasxa based theoretical framework on Istanbul
context, the study found out Attitude had a direct effect on the intention to use,
Perceived Usefulness influenced attitudes, support by the moderating effect of

technology anxiety, Knowledge affected both PerceivexEasexofxUse
andxPerceivedxUsefulness, Self-efficacy had a positive effect on
PerceivedxEasexofxUse.

Figure 2.1: Results study of Cerbeci et al (2019)

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Another scholar - Ramírez-Corre with his partners (2018) conducted a topic
name “The acceptance of Netflix: a study using structural equations” to investigate
customer intention of using Netflix in Brazil. The study followed quantitative
analysis using TAM for the hedonic information system suggest by Heijden (2004).
The result found out that Perceived Usefulness, Perceived Ease of Use, Perceived
Enjoyment have a positive relationship with behavior intention, moderating by
Experiences.

Figure 2.2: Results study of Ramírez-Corre et al (2018)

The study has confirmed one of the major findings of Heijden (2004),
augured the importance of two factors about the perception of useful and easy to use,
which came from the TAM model. Ramirez mentioned that under the context of the
hedonic information system, the role of Perceived Enjoyment is more important
than the remaining factors. The limitation of the research is that Ramirez-Corre just
only focusing on four factors: PerceivedxUsefulness, Perceived EasexofxUse,

Perceived Enjoyment, and Experience.

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sample of study still had some limitations while the majority of respondence mostly
from young as 18 to older as 34 age range, which the results tend to represent for
young users.

A qualitative analysis study had been conducted by Dasgupta and Grover
(2019) with the topic “Understanding Adoption Factors Of Over-The-Top Video
Services Among Millennial Consumers in India”. The study found the most
important feature which leads to the adoption of OTT video service is Convenience,
Content, Mobility, Cost. The research did not have a high generalizability level
since it was conducted only in two cities of India. Also, OTT service is a nascent
concept in India, so the finding may not fully understand the insight of consumers
toward OTT video services.

Sardanelli et al (2019) investigated the intention to subscribe to movie
streaming services in Italy from the perspective of illegal downloading using TPB.
The study included variables such as Product Involvement (INV), Subjective Norm
(SN), Frequency of Past Behaviour (FNB), Moral Judgement (MORAL), Perceived
Risk (RISK), Attitude (ATT). The study found out that attitude, frequency of past
behavior, and involvement have an important role in explaining the subscription
intention of movie streaming services.

Figure 2.3: Research results of Sardanelli et al (2019)

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Research Gap

Overall, in terms of SVOD previous study, some factors had been agreed to
have affected intention to subscribe SVOD or video streaming services such as
Perceived Usefulness, Perceived Enjoyment, Perceived Ease of Use, Experience,
Knowledge, Content, Cost, Mobility, Convenience, Attitude, Moral Judgement,
Perceived Risk, Media Option and Social Trend. However, those factors were only
focusing on technology and finance aspects. There is a lack of concern about factors

in the aspect of media promotion and the factors related to consumer trait to the
intention to subscribe to SVOD. Moreover, to the best of the researcher’s
knowledge, there is no research applied UTUAT2 to the context of SVOD.

Therefore, the following study will add Media Exposure to Advertising
SVOD message as media promotion aspect and Consumer Innovativeness as
consumer trait aspect to have a deep understanding of factors affecting the intention
to subscribe to SVOD.

Media exposure to SVOD advertisement as moderator:

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value price of the services. Or in another word, media exposure to SVOD
advertising can strengthenxthexrelationship between the dependent variables and
behavioral intention in UTAUT2.

In academic aspects, Media exposure had been tested in many different
approaches. A. Qader (2011) proved that media exposure can have a direct impact
on behavioral intention. Other scholars also had the same results (Lee, Koo, &
Chung, 2019; Khofanda & Fajarindra Belgiawan, 2018). Some scholars found the
media exposure can have a direct impact on human perception (Li X., 2018; Wang,
Guo, & Shen, 2011). Media exposure in some case can help to influent brand-recall
and purchasing intention (Turley & Shannon, 2000; Sohail & Sana, 2011;
Muhammad & Tanveer, 2015) as well as can be initial preparation for the stage of
the consumer’s decision-making process (Burton et al, 2019). However, recently,
there is a lack of study that tested the moderating role of Media Exposure to the
relationship between human perception and behavioral intention, although some
researchers have suggested this approach. Reynaldo A.Baustista Jr (2017) in the
research of the generic drug, suggested the role of media exposure in strengthening
the relationship between TPB construct and behavioral intention. Another study also

suggested about moderating role of Media Exposure, in this case, Media Exposure
can strengthen the relationship between buying attitude and perception of value (Jan,
Ji, & Yeo, 2019). Therefore, it is a good opportunity to test whether media exposure
can strengthen the relationship between UTAUT2 constructs and behavioral
intention.

Consumer Innovativeness as additional variables related to consumer’s trait.

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explored by previous researchers, some of them were still not been explored
carefully. One of them was Consumer Innovative which proposed by Roger (1983)
in his book called “Diffusion of Innovation”. Some scholars in the domain of
marketing also mentioned this factor (Migley & Downling, 1978; Agarwal &
Prasad, 1988; Flynn & Goldsmith, 1993). Consumer Innovative was defined as “the
willingness of an individual to try out any new information technology.” (Agarwal
& Prasad, 1988). In other words, a person who has open-minded to newness has a
high possibility to accept a technology faster than others as well as more likely to
influent others to adopt new technology (Roger, 1983).

On many studies about Consumer Innovativeness, there had been
inconsistent in the results of Consumer Innovativeness to Intention Behaviour.
Some studies proved there was a relationship between these 2 variables (Goldsmith,
2000; Ho & Wu, 2011; Foxall & Bhate, 1991; Paswan & Hirunyawipada, 2006).
However, some showed no relationship between them (Im et al., 2003; Chao et al.,
2012). Therefore, this study will investigate to what extent Consumer
Innovativeness impact Behaviour Intention in the context of SVOD in Vietnam.

2.2 Review of the relevant theoretical model of technology adoption:

2.2.1 Theory of reasoned action (TRA)

This theory explains the behavioral intention byxattitudextowardxbehavior

and subjective norm. The attitudes toward behavior is “the positive or negative of
an individual toward conducting a behavior to the subject” (Fishbein & Ajzen,
1975), and the subjective norm was defined as the feeling of others when we
conducting a behavior.

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The limitation of the Theory of Reason behaviors (TRA) is that this model
assumes a person’s cognitive decided his/her behaviors. Therefore, the theory of
Ajzen cannot explain consumer behaviors if an individual behaves based on his/her
habit or behaves unconsciously. Moreover, Ajzen just considered the relationship
between attitudes and behaviors of an individual itself rather than concerning the
social factors. In the reality, in some cases, social factors do have affect intention
behavior of an individual (Shiau et al., 2012; Rieke et al., 2016)

2.2.2 Theory of planned behavior (TPB)

The theory of plannedxbehavior is an expansion of TRA to enhance the

ability to explain behavior which not under control (Ajzen, 1991). The added
determinant in TRA is Perceived Behavioral Control.

Figure 2.5: Theory of planned behavior (Ajzen, 1991)

According to Aizen (1991): “The Perceived Behavioral control can trigger from
each person’s internal (Ability, Determination...) or external (Time, chance,…)”.

TPB model was considered as more complete than TRA in explaining consumer

behavior.

2.2.3 Technology acceptance model (TAM)

In the studies about technology adoption, some scholars have emphasized the
relationshipxbetweenxattitudexandxintention behavior. Davis (1989) developed TAM

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behavior. TAM was adapted and developed based on the theoretical background of
TRA in constructing relationships among factors to explain human behaviors to
accept and use an Information System (Davis, 1989).

Figure 2.6: Technology acceptance model (Davis, 1989)

TAM explained usersxacceptance through 2 determinants, which were (1)
Perceived Usefulness and (2) Perceived ease of Use. In addition, in TAM, the
perception of a person who using Information technology can be influenced by
environmental factors such as experiences, knowledge, training level, and IT
process. Different from TRA, this theory emphasized the role of the self-making
decision of consumers during the time they consume products.

2.2.4 Unified theory of acceptance and use of technology (UTAUT)

To unify all factors relating to the adoption of technology in the field of
information system, UTAUT was proposed. The intention behaviors can be
explained by 4 key elements in this theory.

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Figure 2.7: Unified theory of acceptance and use of technology UTAUT

(Venkatesh et al., 2003)

UTAUT was used in many studies. There are three kinds of UTAUT
application has been made by scholars. First, some scholars applied UTAUT in
contemporary contexts such as the Internet of Things (IoT) (Sung & Jo, 2018),
Mobile Banking (Yu, 2012). Second, some scholars applied Modified UTAUT2
which added other constructs such as culture (Sriwindono & Yahya, 2012), Risk
(Eneizan et al., 2019). Third, some studies integrated UTAUT with other models
such as Task Technology Fit (TTF) (Zhou et al., 2010). Many studies of UTAUT
showed that different contexts will bring different results. According to Venkatesh
et al (2003) suggestion, there could be another construct that can be added to the
model.

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UTAUT2 has applied the previous construct with 3 new constructs added:
HedonicxMotivation, Price Valuexand Habit.

Figure 2.8: Unified theory of acceptance and use of technology UTAUT2 
(Venkatesh et al., 2012)

2.2.5 Reason why the author choosing UTUAT2 as theoretical framework

In the past, many previous studies applied TAM, TPB, … in explaining
human behavior. Each model has its strength and limitation, the next model tends to
enhance or explained the previous model. As Venkatesh concluded, the UTAUT2 is
the model that inherited almost all of the elements of the previous models (TPB,
TRA, TAM, UTAUT). Therefore, to explain individual consumers' intention to
subscribe to SVOD, UTAUT2 is suitable for this research.

2.3 Hypothesis development and conceptual model

The researchxmodel applies six constructs of UTAUT2. Moreover, because

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Table 2.1: Construct's definition

Construct Definition

Performance expectancy The degree to which using technology will provide
benefits to consumers in performingxcertainxactivities
(Venkatesh et al., 2012)

Effort Expectancy How easy the users can interact with SVOD
(Venkatesh et al., 2012)

Social Influences The extent to which user of SVOD services consider
their behavior associatedxwith otherxpeople’sxbelief
(Venkatesh et al., 2012)

Facilitating condition The extent to which SVOD users believe that with the
availability of stable internet connection and devices
can support using SVOD services (Venkatesh et al.,
2012)

Hedonic Motivation The fun or pleasure derived from using SVOD
(Venkatesh et al., 2012)

Price Value The trade-offxbetween the cost paid for using the

technology and the perceived benefits received
(Venkatesh et al., 2012)

Consumer Innovativeness The tendency of a consumer to buy a new product and
enjoy the uniqueness of the product (Steenkamp et al.,
1999)

Media Exposure Media coverage on SVOD advertising (Reynaldo A.
Bautisca, Jr. et al, 2017)

2.3.1. Performance Expectancy

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20
using technology will provide benefits to consumers in performing certain activities”
(Venkatesh, 2012). Since one of the remarkable features of SVOD and the OTT
platform is film recommendation feature and personalization feature, SVOD can
help users searching movies that they want more quickly compared with previous
media technology.

In previous researches, almost all scholars found a positive relationship
between performance expectancy and behavioral intention. For example, Van der
Heijden (2003) stated that Perceived Usefulness (which similar meaning with
Performance Expectancy) has a positive impact on Information systems which
focuses on entertainment purposes. Performance Expectancy also proved to have a
positive impact on behavioral intention in several studies (Baabdullah, 2018; Cebeci
et al., 2019; Yu & Ting, 2011).

Thus, this research hypothesizes that:

H1: PerformancexExpectancy will have a positive impact on intention to subscribe

to SVOD in Vietnam. 
2.3.2. Effort Expectancy

In UTAUT2, effort expectancy wasxdefinedxasxhowxeasy the users can

operate the system. Davis (1989) foundxthatxanxinformation system which people

think it easier to use is more likely to be adopted. There are many scholars agreed
that effort expectancy can explain the user’s intention. Bautista et al. (2016)
concluded that user’s intention to use social TV system had a high correlation with
how they think that system is easy or not. Lee (2018) also agreed that there is an
impact of online streaming adoption and effort expectancy.

Because of that, it is crucial to examine the role of effort expectancy in the
context of SVOD in Vietnam.

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2.3.3. Social Influences

Social influence is the degree to which an individual is influenced by the
recommendation of other people (Diaz & Loraas, 2010). It is similar to the factor
“subjective norm” defined in TPB by Aijzen (1991)

As in the context of Vietnam, people have a close relationship, and they tend
to live in a closed group society. Therefore, the impact of family and friends can be
considered as important factors to evoke potential users to have curious about
services as well as accept the services.

Social influence has been proved to be significant in many different media
and entertainment contexts. The influence of users’ closest peers will associate with
the intention to use music streaming (Dörr et al., 2013). Leong et al (2013) found
the recommendation of the user’s peer has a positive impact on intention to use
mobile entertainment in Malaysia.

Thus:

H3: Social Influences will have a positive impact on intention to subscribe to SVOD 
in Vietnam.

2.3.4. Hedonic Motivation

Hedonic motivation is defined as “the fun or pleasure derived from using a
technology”, and it hadxbeenxshownxtoxplayxanximportant role in determining
technology acceptance and use behavior (Brown & Venkatesh, 2005). In studies of
information system, results showed that a technology that derives fun and pleasure
to a person will be likely to be accepted (Van der Heijden 2004; Thong et al. 2006).
This statement was also proved in consumer contexts (Brown and Venkatesh 2005;
Childers et al., 2001).

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22
the SVOD services are attractive enough, they may tend to adopt SVOD. Wong
(2014), in the case of mobile-TV, hedonic motivation is one of the most important
factors in choosing mobile-TV. In the hedonic information system context, the role
of Hedonic Information also proved to have an impact on the intention to use a
hedonic information system (Heijden, 2004). Based on this review, the author stated
that:

H4: Hedonic Motivation will have a positive impact on intention to subscribe to

SVOD in Vietnam.

2.3.5. Price Value

An important difference between thexconsumerxusexsetting and the

organizational use setting, when UTAUT2 was developed, is the role of price to the
users’ behavior. The cost and pricing structure may have a significant impact on
consumers’ technology use. Price Value is defined as “thextrade-off between the

cost paid for using thextechnology and the perceived benefits received” (Dodds et

al., 1991). As by Venkatesh et al. (2003), an important difference between the
consumer setting and the organizational setting is that the consumers need to
concern about the cost use while employees do not. The relationship between price
value and subscription intention will be positive if users think that the value of
technology is greaterxthanxthexcostxtheyxhave to pay.

Price value had been proved to have a positive impact on intention to adopt a
technology. For example, Prata, Moraes and Quaresma (2012) found that person
who tends to think the application has a reasonable price will tend to have a high
purchasing intention of mobile application.

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23
high in comparison with the average income of users, it will be a huge barrier for
users to access SVOD. Thus:

H5: Price Valuexwillxhave a positiveximpactxon intention to subscribe to SVOD in

Vietnam.

2.3.6. Facilitating condition

Venkatesh et al. (2003) demonstrated this term as “the beliefs of a person on
the availability of the infrastructure when using technology”. In the context of
SVOD, the term facilitating condition is considered as the extent to which SVOD
users believe that the availability of stable internet connection and devices that can
be accessed to the internet can support them using SVOD services.

The facilitating condition was proved to have a positive impactto behavioral
intention in the study of Internet banking (Emad & Michael, 2009). Support for the
hypothesis is Wong et al. (2014) in the study on the behavioral intention of
mobile-TV.

Thus, the study will follow the hypothesis:

H5: Facilitating Condition will have a positive impact on intention to subscribe to 
SVOD in Vietnam

2.3.7. Consumer Innovativeness

Consumer Innovative (CI) is a factor that will be tested in the context of
SVOD in Vietnam. Consumer innovativeness refers to “the degree to which the
individual willing to try out new ideas” (Midgley and Dowling, 1978). Based on
Dabholkar and Bagozzi (2002), personal innovativeness can change individuals’
perceptions of technology. The more innovative a person is, the more he/she will
want to use new technology.

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24
Edumall and Sport channels, Netflix provided an option for consumers to download

the movie on the computer. The variety of services may bring curious to the
Vietnamese users, especially the one who has consumer innovativeness. Therefore,
consumer innovativeness can be a potential factor to explain the intention to
subscribe to SVOD in Vietnam.

In previous research, some scholar has developed and applied to support the
influence of the user’s innovativeness in a different context related to different kind
of technology from purchasing online behavior (Donthu & García, 1999; Goldsmith,
2000), Mobile App Adoption (Sari et al., 2019; Okumus, 2018). Internet of Things
(Sung & Jo, 2018). Subscription Based-Online Service (Ramkumar & Woo, 2018)

With the evidence from the literature, consistent with the fact that SVOD is
an Innovation in Media (Christensen et al., 2015), the author expects that the
subscription intention of SVOD is positively influenced by Consumer
Innovativeness.

H7: Consumer Innovativeness will have a positive impact on intention to subscribe 
to SVOD in Vietnam

2.3.8. Media exposure

In many years, media exposure had shown its important role in changing the
way people think and behave on new services/products. Some scholars showed
media exposure had a direct effect not only on human perception but also on
behavioral intention. Media exposure in this thesis is defined as media coverage for
SVOD advertising. Since a lot of scholars has found media exposure can have a
direct effect to consumer’s perception (Li X., 2018; Wang, Guo, & Shen, 2011) and
direct effect to consumer intention (Lwin et al., 2014; A- Qader & Zainuddin, 2011),
it is possible that media exposure may have a moderating effect between UTAUT2
constructs and consumer intention to subscribe to SVOD as many constructs of

UTAUT2 related to the perception of a person. It is likelyxthat thexmore a person is

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25
toward SVOD, and that change in perception can lead to subscribe intention. Or in
other words, the expectation of performance, easy to use, price value, hedonic, and
facilitating condition will be strengthened under the effect of media exposure.
Hence,

H8: The greater the media exposure to SVOD advertisement, the effect of 
performance expectancy on the subscription intention will be reinforced

H9: The greater the media exposure to SVOD advertisement, the effect of effort 
expectancy on the subscription intention will be reinforced

H10: The greater the media exposure to SVOD advertisement, the effect of social 
influence on the subscription intention will be reinforced

H11: The greater media exposure to SVOD advertisement, the effect of facilitating 
conditions on the subscription intention will be reinforced.

H12: The greater media exposure to SVOD advertisement, the effect of hedonic 
motivation on the subscription intention will be reinforced.

H13: The greater media exposure to SVOD advertisement, the effect of price value 
on the subscription intention will be reinforced.

In the study on diffusion of innovation, Consumer Innovativeness was
widely accepted as the factor affecting the intention to adopt a new product.
However, understand what factors can accelerate the speed rate of adoption among
these types of consumers can help better to expand the knowledge of diffusion

(Roger, 1983). Robertson (1967) claimed that there could be variables that can
switch the rate of adoption. In the field of diffusion research, Media exposure had
been agreed as an importantxdriverxofxinnovation diffusion and has a significant

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26
with consumer innovative trait tend to actively seek for new information and idea
about the product, thus make them easier to be early adopters (Migley & Downling,
1978). Therefore, when these two requirements (the information push of media and
information gained when users actively seeking) are met, an innovative person will
have a large amount of information compared to non-innovative persons, thus
accelerating the adoption speed rate of SVOD product. In another word, the study
proposed a hypothesis:

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2.4 Research conceptual model

The following model is the research model of the thesis proposed by the author:

Figure 2.9: Research Model Proposed by Author

H12

H8 H9 H10 H11 H13 H14

Media Exposure
PerformancexExpectancy

EffortxExpectancy
Social Influences

Facilitating Condition

HedonicxMotivation
PricexValue

Consumer Innovativeness

Subscription Intention
H1

H3
H4

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CHAPTER 3: METHODOLOGY

3.1. Research process

The study will follow the steps shown in the figure below:

Figure 3.1: Research process proposed by author 
Review previous study to

finalize research objective

Identifyxresearch

objective, research
scope, research model

and methodology

Identifyxresearch
population, sample and
scale and measurement
Develop questionnaire
basedxonxpreviousxstudy

Plot test questionnaire

Data collection

Analyze and interpret
the results with SPSS

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3.2. Sampling and data collection

Sample size

The minimum amount of sample required for research is equal to the number of
observable items in the questionnaire multiple by 5 (Hair et al., 2013). This study
will follow this formula for deciding the sample size.

This study has 30 construct items, which means the total sample size is 30 * 5 = 150
in minimum.

3.3. Sample Population

The survey questionnaire has been sent in Google From Online and delivered to
people who acknowledged SVOD services and are user’s SVOD services to give a
better sample to the research objective. To make sure that requirement is met, a
majority of the sample came from the author’s network on Facebook as well as the
questionnaire was delivered to some Movie/ TV show/ Live sport Hobby Group to
make sure it matched with the potential users. Also, the term of SVOD was
explained carefully in the questionnaire. The survey was conducted from 25th March
to 15th April. The author has collected 250 surveys, 38 answers had been eliminated
from data analysis due to 15 respondents answering the same answer, and 23
respondents not aware of SVOD. In another word, there are 212 responses were
valid to process in data analysis.

3.4. Variable and Measuring Instrument

The measures of this research were applied from the previous study and modified to
be suitable for the research object: Subscription Video-on-demand. In which the
questionnaire was based on the UTAUT2 model (Venkatesh et al., 2012). The
questionnaire will follow Likert 5-point scale.

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30
new information technology, I would look for ways to experiment with it” The
questionnaire will follow Likert 5-point scale.

Another construct added name “Media exposure to Advertisement for SVOD” was
adopted by Stroup and Brandstetter (2018). There are 3 items included in this study,
for example: “During the past 30 days when you watch TV, how often do you see
an advertisement for SVOD?”. The questionnaire will follow verbal frequency

5-point scale, ranging from 1 = “Never”, 2 = “Rarely”, 3 = “Sometime”, 4 =
“Frequently”, 5 = “Very Frequently” respectively.

The final construct Behavioural intention is adopted by Venkatesh et al. (2003). The
questionnaire will follow Likert 5-point scale.The pilot test had been conducted
with 20 people who already had a certain knowledge of SVOD and users of SVOD
to check the questionnaire in Vietnamese was confusing or not. After the pilot test,
some items were removed due to the participant’s feedback on confusion meaning.
The final observation elements are presents as follows:

Table 3.1: Measurement Scale of thesis

Factor Code Item Source

Performance
Expectancy

PE1 1. I expect using SVOD improves my
productivity in searching film/TV show.

Venkatesh
et al. (2012)

PE2 2. I expect using SVOD help me searched
film/TV show quickly.

PE3 3. I expect that I can save time using SVOD
service when searching for film/TV
show.

PE4 4. I expect that SVOD service is very useful
to my life in general.

Effort EE1 1. Learningxhowxto use SVOD is easy for

me.

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31
Expectancy EE2 2. I find SVOD easyxtoxuse. et al. (2012)

Davis
(1989)
EE3 3. Itxisxeasyxforxmextoxbecomexskillfulxat

using SVOD

EE4 4. My Interaction with SVOD is clear and
understandable

Social
Influence

SI1 1. Peoplexwhoxare importantxtoxmexthink

thatxIxshouldxusexSVOD.

Venkatesh
et al. (2012)
SI2 2. People whoxinfluence my behavior think

that I should use SVOD.

SI3 3. People whosexopinions that I value prefer

that I use SVOD.
Hedonic

Motivation

HM1 1. UsingxSVODxisxfun. Venkatesh

et al. (2012)
HM2 2. UsingxSVODxisxenjoyable.

HM3 3. UsingxSVODxisxveryxentertaining.

Price Value PV1 1. SVOD is reasonably priced. Venkatesh
et al. (2012)
PV2 2. SVOD is a good value for money.

PV3 3. At the current price, SVOD provide a
good value

Facilitating
condition

FC1 1. I have enough resourced to use SVOD
(Internet/ smart TV / card credit / online
payment method)

Venkatesh
et al. (2012)

FC2 2. I have enough knowledge to use SVOD
FC3 3. SVOD compatible with other technology

I used (Smartphone/ Smart TV / laptop)
FC4 4. I can get help from other if I’m having

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32
Consumer

Innovativeness

CI1 1. If I heardxaboutxaxnewxinformation

technology, Ixwould look for ways to

experiment with it

Agarwal &
Prasad
(1988).
CI2 2. Amongxmyxpeers, xIxamxusuallyxthe first

to try out new information technology
CI3 3. In general, I like to try out new

information technology

Media
exposure to
SVOD

advertisement.

ME1 1. During thexpast 30 days when you watch

TV, howxoftenxdoxyouxsee advertisement

for SVOD?

Stroup &
Brandstetter,
(2018)
ME2 2. During thexpast 30 days, how often do

you see advertisement for SVOD in the
e-newspapers or e-magazines?

ME3 3. Duringxthexpastx30xdays,whenxyou

accessxtoxthe social media, how often do

you see advertisement for SVOD?
Behavioral

Intention

BI1 1. I intend to subscribe SVOD in future Venkatesh

et al (2003)
BI2 2. I predict I would subscribe to SVOD in

future.

BI3 3. I plan to subscribe to SVOD in future.

3.5. Analysis Method

3.5.1 Descriptive analysis

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3.5.2 Inferential analysis

The data collected from the survey will be cleaned first. After that, the author will
use SPSS 20 and Process Macro addon developed by Hayes. The detailed
processing data method showed below:

a. ReliabilityxanalysisxbyxCronbach’sxalpha:

Testing Cronbach’s alpha will make sure the scale is reliable or not. It is vital to
determine Cronbach’s alpha in a study that applied Likert question. The best value
of alpha should be more than 0.9 and the value lower than 0.5 can be considered
inappropriate (Geogre & Mallery, 2010).

The ideals item for each construct should be at leastxthree. According to Nunnally
and Bernstein (1994), item-total correlations need to be larger than 0.3 to be
accepted.

b. ExploratoryxFactorxAnalysisx–xEFA:

EFA is used to shorten a set of many interdependent observation variables into a
smaller set of variables but more meaningful and most of the information content
still remains the information of the initial set of variables, which ensures mutual
interdependence.

In Exploratory Factor Analysis, there are some requirements need to be satisfied:

 Factor loading > 0.5 (The larger the value, the closer relationship between
observable item and variables)

 KMO value between 0.5 and 1

 Bartlett’sxtestxofxsphericity has Sig < 0.05 (The observed items

arexcorrelatedxwith each other in the population)

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c. Pearson Correlation

The measurement item which meets the evaluation requirement in Cronbach alpha
and EFA willxbextestedxusingxPearsonxCorrelationxanalysis. Pearson. Correlation.

analysiswas conducted between dependent and independent variable to test if there
has multicollinearity between independent variables. The rate of correlation for not
having the multi-collinearity need to be lower than 0.9 (Hair et al., 2013)

d. Regression analysis:

Regression analysis is an analysis method to check the relationship between
dependent variable Y and independent variable X1,X2,…. The outcome is a
regression equation which has a following the function:

Y = + X1 + X2 + ,……+ Xn + ε

Where:

- Y = Score for subscription intention behavior for SVOD
- X1, X2 ,… Xn = Score for the variables of this study’s model
- , , …. = Regression co-efficient of independent variable
- = intercept

- ε = error term

The step of regression analysis is shown below:

- Evaluate the regression equation through R2 and adjusted R2
- Test hypothesis of each constructs’ regression co-efficient.

- Test the hypothesis of normal distribution of residuals: based on the
frequency chart of standardized residuals; see mean value = 0 and standard
deviation = 1.

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e. Moderation analysis

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CHAPTER 4: ANALYSIS RESULTS

4.1 . Data Description

The data below represented for descriptive statistics of the candidate participating in
the survey:

Gender: Among 212 respondents, there are 94 males account for 44% of
respondents, 119 females account for 56% of respondents.

Figure 4.1: Age group of respondents (Source calculation from survey data)

Age: According to the age group by Chart 4.1, the largest percentage of the age
group from 25-30 is 55% of the respondents, followed by a group of 18-24 with
40%. The group of 31-40 has the lowest number account for 5%.

Monthly Income: 34 respondents account for 16% have a salary lower than 5
million VND. 47 respondents account for 22% are 5-10 million VND, 123
respondents respondence account for 58% are 11-20 million VND and 8
respondents have a salary higher than 20 million VND, account for 4%

Occupation: 93 respondents (44%) are students, 88 respondents (41%) are office
staff, 4 respondents (4%) are leader/manager and remain 27 respondents answer
other (13%)

18-24 
40% 
25-30

55%

31-40 
5%

Above 40 
0%

Age

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37
With the question “Are you currently use SVOD”, there are 59% (126 people) have
not currently users, 86 people are currently users account for 41% of respondents.

Figure 4.2: Descriptive data of current users

For the question “How do you know about SVOD?”, 183 known from friend and
Co-worker, 98 known from family, and 48 known via advertisement.

Figure 4.3: Descriptive data of SVOD references channel 
59%

41%

CURRENTS USERS OF SVOD

Not currently user Currently user

86.32%

46.23%

22.64%

0.00%
20.00%
40.00%
60.00%
80.00%
100.00%

Channel

How you know SVOD?

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4.2 . Reliability analysis

Cronbach’sxalphaxwasxused to test the reliability of scales. The acceptable value of

Cronbachxalpha is higher than 0.7. The corrected total correlation of all Items is

satisfied with value > 0.3. The brief analysis represented as follows:

Table 4.1: Cronbach’s alpha for all variable

Variable Number of items Cronbach alpha’s value

PerformancexExpectancy

(PE)

4 0.908

EffortxExpectancy (EE) 4 0.809

SocialxInfluence (SI) 3 0.868

FacilitatingxCondition (FC) 4 0.749

HedonicxMotivation (HM) 3 0.799

PricexValue (PV) 3 0.903

Consumer Innovativeness
(CI)

3 0.869

Behavioral Intention (BI) 3 0.784
Media Exposure (ME) 3 0.793

4.2. Explanatory Factor Analysis

4.3.1 Explanatory Analysis for independent variable

The value of 24 observing items has good Eigenvalue (>1). The 7th factor has the
lowest Eigenvalue at 1.301. The KMO value is valid with value = 0.798 between
0.5 and 1, also the significantxofxBartlett’sxTestxofxSphericity is .000 < 0.05. This

result accepts the validity of data in the explanatory analysis.

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Table 2.2: EFA Results for independent variable 
Rotated Component Matrixa

Component

1 2 3 4 5 6 7

PE4 .879

PE2 .872

PE3 .858

PE1 .822

EE3 .844

EE1 .794

EE2 .754

EE4 .731

PV3 .888

PV2 .854

PV1 .847

CI3 .878

CI1 .867

CI2 .827

SI2 .864

SI3 .859

SI1 .855

FC1 .810

FC3 .780

FC4 .770

FC2 .645

HM2 .821

HM1 .788

HM3 .783

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4.3.2 Explanatory Analysis for dependent variable

Table 4.3: EFA Results for Dependent Variable 
Component Matrixa

Component
1

BI1 .865
BI2 .835
BI3 .808

Behavioral intention scale consists of 3 items, The KMO value is valid with value =
0.694 between 0.5 and 1, also the significantxofxBartlett’sxTestxofxSphericity is .000

< 0.05. This result accepts the validity of data in the explanatory analysis.

Eigenvalue is more than 1 (2.099) with cumulative 69.953% > 50%, explaining
69,953% of behavioral intention.

To sum up, Behavioral intention (BI) scale remain with 3 item BI1, BI2, BI3,
exacted to 1 component – Behavioral intention (BI)

4.3.3 Explanatory Analysis for moderation variable

Table 4.4: EFA Results for Moderator 
Component Matrixa

Component
1
ME3 .852
ME2 .836
ME1 .835

Media exposure scale consists of 3 items, The KMO value is valid with value
= 0.716 between 0.5 and 1, also the significantxofxBartlett’sxTestxofxSphericity

is .000 < 0.05. This result accepts the validity of data in the explanatory analysis.
Eigenvalue is more than 1 (2.186) with cumulative 72.866% > 50%,
explaining 72,866% of behavioral intention.

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4.3. Regression Analysis

Table 4.5: Results of Pearson Analysis

According to Person Correlation table, Effort Expectancy (EE), Social Influence
(SI), Price Value (PV), Hedonic Motivation (HM), Performance Expectancy (PE),
Consumer Innovativeness (CI) have significant relationship with Behavioral
Intention (BI) since the Pearson Correlation is high (0.268; 0.506; 0.574; 0.469;
0.346; 0.451 respectively) and Sig <0.05. Also, the correlation coefficient between
the independent variables is lower than 0.9, therefore there was no multicollinearity
in the regression model. However, we still need to pay attention to multicollinearity
in the next step.

Table 4.6: Results of regression analysis

Variable Path coefficient Sig (1 tailed) VIF

Effort expectancy 0.63 .110 1.161

Social Influence 0.267 .000 1.217

Price Value 0.305 .000 1.370

Hedonic Motivation 0.174 .001 1.351

Performance Expectancy 0.113 .019 1.273

Consumer Innovativeness 0.183 .0005 1.280

Facilitating condition 0.08 .4355 1.017

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42
adjusted R Square = 0.515, which means that 51.5% of the variation of subscription
intention can be explained by the independent variable.

Testing the overall fit of the model by the ANOVA table, the value of sig is .000 <
0.05, therefore, the regression model is suitable with the data set.

All independent variables have VIF <10, which means that there is no
multicollinearity between independent variables.

Table 8 show Facilitating Condition and Effort Expectancy is not having significant
statistics meaning due to the value of significant > 0.05 (FC Sig one-tailed =
0.4355; EE Sig one-tailed = 0.110).

The relationship between dependent and independent variable are shown in the
following

Consumer Innovativeness (CI) (Beta = 0.183 > 0; Sig one-tailed = 0.0005 < 0.05)
hasxsignificant positive relationshipxwithxSubscriptionxIntention

Performance Expectancy (PE) (Beta = 0.113 > 0; Sig one-tailed = 0.019 <0.05)
hasxsignificant positive relationship with Subscription Intention

Social Influence (SI) (Beta = 0.267 > 0; sig one-tailed = 0.000 < 0.05)
hasxsignificant positive xrelationshipxwith Subscription Intention.

Price Value (PV) (Beta = 0.305 > 0; sig one-tailed = 0.000 < 0.05) hasxsignificant

positiverelationshipxwith Subscription Intention

Hedonic Motivation (SI) (Beta = 0.174 > 0; sig one-tailed = 0.001 <0.05)
hasxsignificant positiverelationship with Subscription Intention

4.4. Moderation Analysis

Based on the outcome of regression analysis, the author will test the relationship
between CI and IB, PE and IB, HM and IB, PV and IB, SI and IB because the
remaining has not had any significant to independent variable so there will be no
need for moderation analysis (Hayes, 2018)

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Table 4.7: Moderation analysis by Hayes

Model
Summary

Coefficient Standard
Error

t-value p-value Conclusion
H8

Performance
Expectancy
(PE)

.2754 .0578 4.7614 .000 Reject
because
p-value
= .751 > .05
Media

Exposure
(ME)

-.0148 .0438 -.3371 .7364

PE*ME .1146 0.641 1.7888 .0751

Model
Summary

Coefficient Standard

Error

t-value p-value Conclusion
H10

Social
Influence
(SI)

.3259 .0388 8.4063 .0000 Reject
because
p-value
= .2158
> .05
Media
Exposure
(ME)

.0897 .0446 2.0097 .0458

SI*ME .0585 .0471 1.2414 .2158

Model
Summary

Coefficient Standard
Error

t-value p-value Conclusion
H12

Hedonic
Motivation
(HM)

.4816 .0630 7.6397 .0000 Accept
because
p-value
= .0482
< .05
Media
Exposure
(ME)

-.0259 .0410 -.6303 .5292

HM*ME .1683 .0847 1.9869 .0482

Model
Summary

Coefficient Standard
Error

t-value p-value Conclusion
H13

Price Value
(PV)

.3054 .0302 10.1172 .0000 Reject
because
p-value
= .2408
> .05
Media
Exposure
(ME)

.0439 .0400 1.0957 .2745

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44
Model

Summary

Coefficient Standard
Error

t-value p-value Conclusion
H14

Consumer
Innovativeness
(CI)

.3026 .0417 7.2491 .0000 Reject
because
p-value
= .7489

> .05
Media
Exposure
(ME)

-.0259 .0419 -.6189 .5367

CI*ME .0200 .0624 .3206 .7489

4.5 Hypothesis tested results

The thesis showed that there are five hypotheses are supported to have an impact on
subscription intention, describe as follow:

Hypothesis H1: Performance Expectancyxhas a positive impact on intention to

subscribe to SVOD in Vietnam.

The regression result of Performance Expectancy was significant, which means that
hypothesis H1 is accepted.

Hypothesis H2: EffortxExpectancyxhasxpositiveimpactxon intention to subscribe to

SVOD in Vietnam.

The regression result of Effort Expectancy was insignificant, which means that
hypothesis H2 is rejected.

Hypothesis H3: Social Influences has axpositive impact on intention to subscribe to

SVOD in Vietnam.

The regression result of Social Influence was significant, which means that
hypothesis H3 is accepted.

Hypothesis H4: Facilitating Condition has a positive impact on intention to

subscribe to SVOD in Vietnam.

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Hypothesis H5: HedonicxMotivation hasxa positive impactxon intention to subscribe

to SVOD in Vietnam.

The regression result of Hedonic Motivation was significant, which means that
hypothesis H5 is accepted.

Hypothesis H6: Price Value has a positive impact on intention to subscribe to

SVOD in Vietnam.

The regression result of Price Value was significant, which means that hypothesis
H6 is accepted.

Hypothesis H7: Consumer Innovative has a positive impact on intention to

subscribe to SVOD in Vietnam.

The regression result of Consumer Innovativeness was significant, which means

that hypothesis H7 is accepted.

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CHAPTER 5: DISCUSSION AND CONCLUSION

5.1. Finding and Discussion

The thesis based on UTUAT2 proposed by Venkatesh et al. (2012). It also
incorporates consumer innovativeness as an additional variable and Media Exposure
as a moderator to check the role of both variables in the context of SVOD.

With 212 samples, the results of the thesis have verified as well as argued
some factors listed in the following:

First, Price Value have positive impact on intention to subscribe to SVOD.
This result is consistent with other results related to technology adoption
(Munnukka, 2008; Venkatesh et al., 2012). In the research of mobile internet,
Venkatesh mentioned that the concept of cost and benefit usually go along together
in any consumer contexts. The result of the thesis showed that in SVOD industry,
consumers tend to have a high price sensitivity level. This because the consumers
have a lot of free alternative options such as illegal free websites, or some of the
providers of AVOD such as YouTube.

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47
providers in Vietnam (FPT Play, ClipTV,.) also spend 2-3% of their revenues to
produce original content. Or in another example of Vietnam SVOD’s firm, My K+
NOW instead of producing original content, they take advantage of licensed many
different sports video/ film as exclusive content of these services.

Social Influences also found to have a positive impact on intention to
subscribe to SVOD. The references from friends and family are important factors
affecting purchase intention in most research (Ajzen, 1991; Venkatesh et al., 2012).
This result was understandable in terms of consumer behavior psychology. Vietnam
is the society that has a higher level of collectivism rather than individualism
according to Hofstede’s cultural dimension theory (Ana et al, 2007). Therefore,
Marketing Word of Mouth still has its role in the context of Vietnam since the voice
from family and friend is an important aspect which can enhance the behavior
intention.

The hypothesis between Consumer Innovative trait and Intention Behavior
also accepted in this study. This supports the results of Goldsmith (2000), Ho & Wu
(2011), Foxall & Bhate (1991), Paswan & Hirunyawipada (2006). Besides, Vietnam
is a country with a young population. The young people usually have a high level of
innovativeness. Currently, with the effort of listening to consumers, the multimedia
industry has changed a lot to satisfy the curiosity of innovative people, from adding
the downloading feature to the personalization feature.

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48
Effort expectancy is a factor that does not have an impact on intention to
subscribe to SVOD. This construct was also shown in another research that it did
not have any impact on behavior intention (Singh & Matsui, 2017). This can be
explained because the sample of this study is mainly young people from 18 to 30,
therefore they already have a certain knowledge of using this type of technology,
which leads to the fact that they do not care much about whether the technology has
easy to use or not. In addition, the Facilitating Condition showed no effect on
behavioral intention, some studies had already proved that this construct is not
inconsistent (Dörr et al. 2013, Wagner and Hess 2013). Because the sample mainly
adopted in the urban area (in this case, Hanoi) where the internet facility is good
and each people have at least one device that can be connected to the internet, the

facilitating condition is not a big problem.

Media Exposure was found to have strengthened the
relationshipxbetweenxHedonic Motivationxand Subscription Intention. The results

suggest that the frequency of media exposure will stimulate the perception of
enjoyment of SVOD toward consumers.

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49
advertising types of SVOD recently in Vietnam heavily tend to be Emotional, which
focusing on showing SVOD provider’s appealing contents rather than deeply
representing its feature. For instance, some providers (e.g. Netflix) use its
advertising budget to promote its trendy content as an indirect way to attract
consumers to have a positive perception of their SVOD service. Finally, some
features of SVOD (e.g. Recommendation,..) need to be trial used to change the
perception of the potential consumer as advertising cannot express fully its idea to
change consumer’s mind.

Compared with the research of Reynaldo et al (2017)

Recently, studies of the moderating role of Media Exposure is not many.
There is the only research of Reynaldo (2017) tried to investigate whether Media
Exposure can strengthen the relationship between TPB construct and behavioral
intention. The results of the study showed that Media Exposure did not strengthen
the relationship between TPB constructs (Subjective norm, Perceived Behavioural
Control, and Attitudes) and behavioral intention. However, this thesis showed that
Media Exposure can enhance the relationship between Hedonic Motivation and
Behavioural Intention. The difference in results can be explained because of
different contexts. The study of Reynaldo et al (2017) investigated a product
(generic drug), while SVOD is an entertainment service. People may need more

time to trust an advertisement for the generic drug because using that drug can be
risky, since it may affect health. In contrast, using SVOD provided no risk because
it just an entertainment service, so people will easier to trust advertisements for
SVOD service. Another explained for the differences in 2 study could be due to the
difference in culture, demographic and types of respondents, therefore there needs a
further study which applied in a different region to have a clear answer.

The effect of COVID-19

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50
SVOD and enjoy its content at home seems to be an interesting way to entertain at
that time. A recent study of Neilsen showed that in 500 Vietnamese, 60% of
respondents said that they had changed their way of entertain during COVID-19
(Nielsen Corporation, 2020). Note that during social distancing, all movie theatres
(one of the direct competitors of SVOD) had to be closed. Because of that, people
who usually go to the movie theater have no choice but to choose SVOD as an
alternative. Second, there was an increase in the time of using the internet during
COVID-19. Because people spend more time on the internet, they will have more
exposure to advertising. In consequence, the perceptions toward SVOD can be
easily affected.

5.2. Contribution of the thesis

Currently, the SVOD industry in Vietnam and the world was in the emerging
stage. By using the latest technology acceptance model, the thesis provides an early
framework for SVOD providers in finding factors affecting SVOD subscription
intention in Vietnam. The thesis also contributed two major findings to the literature.

First, since previous studies of SVOD mainly explained subscription
intention by using TAM or TPB, this study provides early empirical evidence

applying UTAUT2 to SVOD context to enrich the knowledge of the UTAUT2
model as well as studies of SVOD.

Second, the thesis found Media Exposure can strengthen Hedonic Motivation
and Behavioral Intention. This study is early research which adds Media exposure
as the moderating variable to the UTAUT2 model. Further research can try to test
media exposure as a moderating variable in different contexts.

5.3. Implications for SVOD service providers

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Price Value: The SVOD service providers need to have an appropriate

pricing strategy to attract consumers to purchase their products. One of the
strategies they could think about is Profile Package. Currently, an SVOD account
can share up to four small accounts (known as Profile Package) at the same time.
Because it is cheaper when purchasing Profile Package, people tend to buy it from
the one who already has an account instead of buying an account from SVOD
providers. Therefore, SVOD providers can make an official group on social media
to gather people who have a demand to buy the Profile package of SVOD. By doing
so, providers of SVOD can gain a win-win situation: The consumers can acquire
and experiences SVOD at a reasonable price as well as SVOD providers can gain
more users, which is very important since the early stage of innovation is to attract
as many potential loyal users as possible before the market reaching a mature stage.

Hedonic Motivation: The result of the study showed that people will have

the intention to subscribe if they think SVOD service interesting. Therefore, SVOD
service providers should generate more content options to meet consumer’s tastes.

Besides, according to the recent research of Q&Me – a local market research
company, one of the factors which trigger the consumers to sign up for SVOD
services is Content features their favorite celebrities, so when producing original
content SVOD providers can think about inviting suitable celebrities for acting in
SVOD service provider’s movie. (Q&Me, 2020). Moreover, SVOD publisher
should provide other option which brings added value to consumers such as film
review article with comment or virtual reality film, …

Social Influence: Because thesis results showed the recommendation of

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52
content. This method has already done by Netflix with the campaign promoting its
movie Money Heist, Itaewon Class,…

Performance Expectancy: This factor has a small impact on subscription

intention compared to other factors in the thesis. However, it still has its role since
the recommendation feature of SVOD is one of the features that make this service
unique compared with another illegal movie watching website. The service
providers need to enhance the recommendation/personalization algorithm in order
to make these features become a unique selling point for their services.

Consumer Innovativeness: To increase the intention of SVOD service,

SVOD providers need to introduce the service to this group of consumers. As a
result, when individuals with innovative trait have already experienced the service,
the information of SVOD service can spread quickly through word of mouth from
this person. According to Agarwal and Prasad (1988), the person who has consumer
innovative trait can change the perception of users who hesitate to change, so the
rate of SVOD adoption will be increased if there is enough people have innovative

trait satisfy with SVOD services. SVOD services providers could find this type of
consumer in the group fan of new products/ technology reviewers/streamers, which
consists of people who are curious about new products.

Media Exposure: The results study shows that advertisements still an

important part of the business activity of SVOD services providers. Although ads
cannot transfer into sales in the short-term, the result proves that it can enhance the
perception of consumers. SVOD needs to invest more in Media Advertising since it
was a good tool to gain awareness as well as attracting a consumer to have intention
toward SVOD services.

5.4. Limitation and future research direction

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53
- The research had investigated 212 samples, still a small sample size in terms
of the quantitative analysis. Moreover, almost all sample are young people in
Hanoi, which mean that the representative is not quite. The sample is not
enough to generalize the current situation in Vietnam fully. Further study
needs to conduct on a different sample with more representative. Moreover,
there may be some problems related to the common method bias which
partly lead to some unwanted results.

- The study has found an interactive approach of Media Exposure to SVOD
advertisement to the relationship between Hedonic Motivation and
Subscription Intention. However, future studies need to investigate deeply
which types of advertisements have an impact on this phenomenon. Also,
some other media such as E-Word-of-mouth need to be concerned to have a
better result of the moderating effect of Media Exposure. Moreover, different
settings and contexts need to be tested since media exposure to advertising

can be different in other settings.

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APPENDIX 1: Questionnaire

Vietnamese Version

XinxchàoxAnh, xChị!

TôixtênxlàxLê Phú Khánh, họcxviênxcaoxhọcxngànhxQuảnxtrịxkinhxdoanh của

Đại học Việt Nhật – Đại học Quốc gia Hà Nội.
TôixđangxthựcxhiệnxđềxtàixnghiênxcứuxvềxCácxnhân tốxảnhxhưởngxđếnxýxđịnh đăng

kí sử dụng dịch vụ truyền hình trực tuyến trả phí củaxkhách hàngxcáxnhânxtạixViệt

Nam. Đểxhồnxthànhxđềxtài, xtơixrất mong nhận được sự quan tâm giúp đỡ của Anh

(Chị) trong việc tham gia trả lời bản câu hỏi này. Tất cảxnhữngxthôngxtin màxAnh

(Chị) cung cấp trong bản câu hỏi, chúng tơi chỉ sử dụng cho mục đích nghiên cứu
của đề tài.

Dịch vụ thuê bao video theo nhu cầu hay cịn gọi là dịch vụ truyền hình trực tuyến 
trả phí (Subcription Video-on-demand) là dịch vụ cung cấp kho nội dung bản quyền 
giải trí đến người dùng.

Khách hàng sẽ phải đăng kí trả phí theo hình thức thuê bao từng tháng, 
sauxkhixđăngxkí dịchxvụ, kháchxhàng có thể tiếp cận những bộ phim/ chương trình

truyền hình đặc sắc trong nước và quốc tế cùng với các tính năng ưu việt khi sử 
dụng dịch vụ: Xem truyền hình nội dung khơng giới hạn với chất lượng 4K, Ultra 
HD; khơng quảng cáo; có thể xem phim trên bất cứ thiết bị nào có kết nối internet 
(Smart TV, Android TV, Smartphone, Tablet,..) ở bất cứ thời gian và địa điểm nào. 
Tìm kiếm phim dễ dàng với tính năng cá nhân hóa,..

Hiện nay tại Việt Nam, các nhà cung cấp dịch vụ này là Netflix, CLIPTV, My K+ 
NOW, gói VIP của những dịch vụ như FPT PLAY VIP, Zing VIP,..

Anh/Chị từng nghe/ biết đến dịch vụxtruyền hình trực tuyến trảxphí (Netflix, FPT

Play VIP, CLIPTV, My K+ NOW,..) chưa?

□ Đã nghe qua (Tiếp tục khảo sát)
□ Chưa nghe qua (Dừng khảo sát)

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66
Xin vui lòng cho biết ý kiến của Anh (Chị) với mỗi câu hỏi dưới đây :

1. Giớixtính:

 Nam  Nữ
2. Nhóm tuổi:

 Dưới 18 - 24  Từ 25 – 30  Từ 31 – 40  Trên 40
3. Nghềxnghiệpxhiệnxtại :

 Học sinh/ sinh viên  Nhân viên văn phòng
 Doanh nhân/ lãnh đạo/ quản lý  Khác

4. Mức lương hiện tại của Anh (Chị):

 Dưới 5 triệu  Từ 5 – 10 triệu
 Từ 11 – 20 triệu  Từ 20 triệu trở lên

5. Anh/chị có đang sử dụngxdịchxvụxtruyềnxhìnhxtrựcxtuyến trả phí (Netflix, FPT

Play VIP, CLIPTV, My K+ NOW..) khơng :

□ Có
□ Khơng

6. Anh/chị biết đến dịch vụ truyền hình trực tuyến trả phí qua kênh thông tin nào 
(có thể chọn nhiều hơn 1 đáp án) :

□ Bạn bè

□ Người thân gia đình

□ Quảng cáo trên các phương tiện truyền thông

PHẦN B : CÁC NHÂN TỐ ẢNH HƢỞNG ĐẾN DỊCH VỤ TRUYỀN

HÌNH TRỰC TUYẾN

Xin vui lòng cho biết ý kiến của các Anh (Chị) về mức độ đồng ý với từng câu nhận
định dưới đây

1 2 3 4 5

Hồn tồn
khơng đồng ý

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Nhóm A : Cảm nhận sự hữu ích Mức độ đồng ý

1. Sửxdụngxdịchxvụxtruyềnxhìnhxtrựcxtuyến trả phí có thể giúp

tơi tìm kiếm phim/chươngxtrìnhxtruyền hình hiệu quả

1 2 3 4 5

2. Sửxdụngxdịchxvụxtruyềnxhìnhxtrựcxtuyến trả phí có thể giúp

tơi tìmxkiếmxnhữngxbộxphim/chươngxtrìnhxtruyền hình một

cách nhanh chóng

1 2 3 4 5

3. Sửxdụngxdịchxvụxtruyềnxhìnhxtrựcxtuyếnxtrảxphíxcóxthể

giúpxtơi tiếtxkiệmxthờixgianxtìmxkiếmxnhữngxbộxphim/

chươngxtrình truyềnxhình.

1 2 3 4 5

4. Tơi nghĩ nhìn chung dịch vụ truyền hình trực tuyến trả phí rất
hữu íchxchoxcuộcxsống của tơi

1 2 3 4 5

Nhóm B : Cảm nhận dễ sử dụng Mức độ đồng ý

5. Học cách sửxdụngxdịchxvụxtruyềnxhìnhxtrựcxtuyến trả phí khá

dễ dàng 1 2 3 4 5
6. Tơi cảm thấy dịchxvụxtruyềnxhình trực tuyến trả phí dễ sử

dụng 1 2 3 4 5

7. Tơi có thể sửxdụng thành thạo dịchxvụ truyền hình trực tuyến

trả phí mộtxcáchxdễxdàng

1 2 3 4 5

8. Các chức năng của dịch vụ truyền hình trực tuyến trả phí đơn

giản và dễ hiểu 1 2 3 4 5

Nhóm C : Ảnh hưởng xã hội Mức độ đồng ý

9. Nhữngxngườixquanxtrọngxvớixtơi (giaxđình, bạnxbè,…)

choxrằng

tơixnênxsửxdụngxdịchxvụxtruyềnxhìnhxtrựcxtuyếnxtrảxphí

1 2 3 4 5

10. Nhữngxngườixảnhxhưởngxđếnxhànhxvixcủaxtôi (sếp, giáo

viên,…)

choxrằngxtơixnênxsửxdụngxdịchxvụxtruyềnxhìnhxtrựcxtuyến trả

phí

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68
11. Nói chung, những người tơi quen khun tơi nên sử dụng

dịch vụ truyền hình trực tuyến trả phí 1 2 3 4 5

Nhóm D : Cảm nhận sự thích thú Mức độ đồng ý

12. Tơixcảmxthấyxsửxdụngxdịchxvụ truyền hình trực tuyến trả phí

rất vui 1 2 3 4 5
13. Tôi cảm thấy sửxdụngxdịch vụ truyền hình trựcxtuyếnxtrả phí

hấp dẫn 1 2 3 4 5
14. Tơi cảm thấy sử dụngxdịch vụ truyền hình trực tuyến trả phi

rất giải trí 1 2 3 4 5

Nhóm E : Giá trị giá cả Mức độ đồng ý

15. Dịch vụ truyềnxhình trực tuyến trả phí có mức giá hợp lý 1 2 3 4 5

16. Sử dụngxdịch vụ truyền hình trựcxtuyếntrả phí rất đáng đồng

tiền 1 2 3 4 5

17. Dịchxvụxtruyềnxhình trực tuyến trả phi mang lại nhiều giá trị

hơn so với chixphí bỏ ra.

1 2 3 4 5

Nhóm F : Điều kiện vật chất Mức độ đồng ý

18. Tơi nghĩ tơi có đủ nguồn lực cần thiết đểxsửxdụngxdịch vụ

truyền hình trực tuyến trả phí (đường truyền mạng, thiết bị
xem phim, thẻ thanh toán,.. )

1 2 3 4 5

19. Tơi nghĩ tơi có đủ kiến thức cần thiết để sử
dụngxdịchxvụxtruyền hình trực tuyến trả phí

1 2 3 4 5

20. Nhìn chung các dịch vụxtruyền hình trực tuyến trả phí có thể

tươngxthích với tất cácxthiết bị tơi có (Smartphone, laptop,

Android TV,..)

1 2 3 4 5

21. Tơixcó thểxnhận được sự trợ giúp của người khác nếu như có

vấn đề trong việc sử dụngxdịch vụxtruyền hìnhxtrực tuyến trả

phí.

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Nhóm G : Tính đổi mới Mức độ đồng ý

22. Nếu tôi nghe về sản phẩm/dịch vụxcơngxnghệxmới, tơi sẽ tìm

cách để trải nghiệm nó 1 2 3 4 5
23. Trong số bạn bè, tôixthườngxlàxngườixđầu tiên thử nghiệm

cácxsản phẩm/dịch vụ công nghệ mới ra mắt

1 2 3 4 5

24. Nhìn chung tơi thích thú với việc thử dùng các
sảnxphẩm/dịchxvụ công nghệ mới

1 2 3 4 5

Nhóm H : Ýxđịnhxsửxdụng Mức độ đồng ý

25. Tơi có ý định đăng kíxdịch vụ truyền hình trực tuyến trả phí

trong thời gian tới 1 2 3 4 5
26. Tơi nghĩ rằng mình sẽ đăng kí dịchxvụxtruyềnxhìnhxtrực tuyến

trả phí trong thời gian tới 1 2 3 4 5
27. Tơi có kế hoạch đăng kí dịch vụ truyềnxhìnhxtrựcxtuyến trả

phí trongxthờixgianxtới

1 2 3 4 5

PHẦN C : Ý KIẾN VỀ PHƢƠNG TIỆN TRUYỀN THƠNG

Xinxvuixlịngxchoxbiếtxýxkiếnxcủa Anh/chị dưới đây

1 2 3 4 5

Không bao giờ Hiếm khi Thỉnh thoảng Thường xuyên Rất thường
xuyên

Nhóm K: Tiếp xúc với phương tiện truyền thông Tần suất

1. Trong 30 ngày qua khi xem TV, bao lâu thì bạn thấy
quảng cáo về dịch vụ truyền hình trực tuyến trả phí trên
TV ?

1 2 3 4 5

2. Trong 30 ngày qua, bao lâu thì bạn thấy quảng cáo về dịch

vụ truyền hình trực tuyến trả phí trên báo và tạp chí mạng
?

</div>
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70
3. Trong 30 ngày qua khi bạn truy cập mạng xã hội, bao lâu

thì bạn thấy quảng cáo về dịch vụ truyền hình trực tuyến
trả phí?

1 2 3 4 5

Xin chân thành cám ơn sự giúp đỡ của Quý Anh (Chị).

English Version

My name is Le Phu Khanh, MBA students at Vietnam Japan University.
Now I am conducting research topic name Factor affecting intention to subscribe

SVOD in Vietnam. Hope I can gain support from you guy to finish the questionnaire.

All of your information will be using only for research purposes. Thank you so
much !

SVOD is a service that provides unlimited entertainment content. To using service,
users need to register per month (subscribe) to access service. Some of the
remarkable feature of SVOD was : Watching content anytime, anywhere with video
quality up to 4K, no advertisement, can watching in any devices which have an
internet connection, find entertainment content easily with personalization/ content

recommendation feature,..

In Vietnam, some of the famous SVOD services are Netflix, ClipTV, My K+
NOW,.. as well as premium version of some services such as FPT Play VIP, Zing
VIP,…

Have you heard about SVOD (Netflix, FPT Play VIP, CLIPTV, My K+ NOW,..) ? 
□ Yes (Continues the survey)

□ No (End the survey)

PART A : BASIC INFORMATION

Please choose information which suitable with you :
1. Gender:

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71
 From 18 - 24  From 25 – 30  From 31 – 40  Above 40
3. Current Job :

 Student  Officers staff
 Entrepreneur/ leader/ manager  Other

4. Salary

 Below 5 million  From 5 – 10 million
 From 11 – 20 million  Above 20 million

5.Are you currently use SVOD:
□ Yes

□ No

6. From which channel you know about SVOD (you can choose more than 1
answer):

□ Friend & Colleague
□ Family

□ Media Advertisement

PART B : RESPONDENCE OPINION

From what extent you agreed/ disagree with this opinion ?

1 2 3 4 5

Totally
disagree

Disagree Neutral Agreed Totally agreed

Group A: Performance Expectancy

Degree of

agree

1. I expect using SVOD improves my productivity in

searching film/ TV show

1 2 3 4 5

2. I expect using SVOD help me searched film/ TV show

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72
3. I expect that I can save time using SVOD service when

searching for film/ TV show.

1 2 3 4 5

4. I expect that SVOD service isxveryxusefulxtoxmyxlife in

general.

1 2 3 4 5

Group B: Effort Expectancy

Degree of

agree

5. Learning how to use SVOD is easy for me.

1 2 3 4 5

6. I find SVODxeasyxtoxuse.

1 2 3 4 5

7. It is easy for me to become skillful at using SVOD

1 2 3 4 5

8. My Interaction with SVOD is clear and understandable

1 2 3 4 5

Group C: Social Influences

Degree of

agree

9. Peoplexwhoxareximportantxtoxmexthinkxthat I should use

SVOD.

1 2 3 4 5

10. PeoplexwhoxinfluencexmyxbehaviorxthinkxthatxI should use

SVOD.

1 2 3 4 5

11. People whose opinions that I value prefer that I use

SVOD.

1 2 3 4 5

Group D : Hedonic Motivation

Degree of

agree

12. Using SVOD is fun.

1 2 3 4 5

13. Using SVOD is enjoyable.

1 2 3 4 5

14. Using SVOD is very entertaining.

1 2 3 4 5

Group E : Price Value

Degree of

agree

15. SVOD is reasonably priced.

1 2 3 4 5

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Group F: Facilitating Condition

Degree of

agree

18. I have enough resourced to use SVOD (Internet/ smart TV

/ card credit / online payment method)

1 2 3 4 5

19. I have enough knowledge to use SVOD

1 2 3 4 5

20. SVOD compatible with other technology I used

(Smartphone/ Smart TV / laptop)

1 2 3 4 5

21. I can get help from other if I’m having trouble using

SVOD

1 2 3 4 5

Group G: Consumer Innovativeness

Degree of

agree

22. IfxIxheardxaboutxaxnewxinformationxtechnology,

Ixwouldxlook for ways to experiment with it.

1 2 3 4 5

23. Amongxmyxpeers, Ixamxusuallyxthexfirstxtoxtry out new

information technology.

1 2 3 4 5

24. In general, I like to try out new information technology.

1 2 3 4 5

Group H: Subscription Intention

Degree of

agree

25. I intend to subscribe SVOD in future

1 2 3 4 5

26.

I

predict I would subscribe SVOD in future

1 2 3 4 5

27. I plan to subscribe SVOD in future.

1 2 3 4 5

PART C : MEDIA OPTION

Please chose your opinion regarding this opinion:

1 2 3 4 5

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Group K: Media Exposure Degree of 
Frequency

4. Duringxthexpastx30xdaysxwhenxyouxwatchxTV,

howxoftenxdo you see advertisement for SVOD?

1 2 3 4 5

5. Duringxthexpastx30xdays, howxoftenxdoxyou see

advertisement for SVOD in the newspapers or
e-magazines?

1 2 3 4 5

6. Duringxthexpastx30 days, whenxyouxaccessxto the social

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APPENDIX 2: Cronbach’s alpha analysis

Performance Expectancy

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Social Influence

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Facilitating Condition

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Consumer Innovativeness

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APPENDIX 3: Explanatory Analysis

EFA for Independent Variable

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .789
Bartlett's Test of Sphericity Approx. Chi-Square 2809.456

df 276

Sig. .000

Total Variance Explained

Compon
ent

Initial Eigenvalues

Extraction Sums of Squared
Loadings

Rotation Sums of Squared
Loadings

Total

% of
Variance

Cumulativ

e % Total

% of
Variance

Cumulativ

e % Total

% of
Variance

Cumulativ
e %
1 5.925 24.689 24.689 5.925 24.689 24.689 3.176 13.235 13.235
2 2.840 11.832 36.520 2.840 11.832 36.520 2.616 10.899 24.134
3 2.273 9.470 45.990 2.273 9.470 45.990 2.550 10.623 34.757
4 2.019 8.413 54.403 2.019 8.413 54.403 2.417 10.069 44.827
5 1.787 7.447 61.851 1.787 7.447 61.851 2.409 10.038 54.865
6 1.489 6.203 68.054 1.489 6.203 68.054 2.321 9.669 64.534
7 1.301 5.421 73.475 1.301 5.421 73.475 2.146 8.941 73.475

8 .768 3.200 76.675

9 .728 3.032 79.707

10 .573 2.386 82.093

11 .541 2.255 84.348

12 .499 2.081 86.429

13 .434 1.808 88.237

14 .396 1.650 89.887

15 .367 1.530 91.417

16 .363 1.511 92.927

17 .333 1.388 94.315

18 .303 1.263 95.579

19 .263 1.098 96.676

20 .236 .985 97.661

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22 .183 .764 99.278

23 .098 .408 99.686

24 .075 .314 100.000

Extraction Method: Principal Component Analysis.

Rotated Component Matrixa

Component

1 2 3 4 5 6 7

PE4 .879

PE2 .872

PE3 .858

PE1 .822

EE3 .844

EE1 .794

EE2 .754

EE4 .731

PV3 .888

PV2 .854

PV1 .847

CI3 .878

CI1 .867

CI2 .827

SI2 .864

SI3 .859

SI1 .855

FC1 .810

FC3 .780

FC4 .770

FC2 .645

HM2 .821

HM1 .788

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Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 6 iterations.

EFA for Dependent Variable

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .694
Bartlett's Test of Sphericity Approx. Chi-Square 182.770

df 3

Sig. .000

Total Variance Explained

Component

Initial Eigenvalues Extraction Sums of Squared Loadings

Total % of Variance Cumulative % Total % of Variance Cumulative %

1 2.099 69.953 69.953 2.099 69.953 69.953

2 .516 17.197 87.151

3 .385 12.849 100.000

Extraction Method: Principal Component Analysis.

Component Matrixa

Component
1

BI1 .865

BI2 .835

BI3 .808

Extraction Method:
Principal Component
Analysis.

a. 1 components
extracted.

EFA for Moderator

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .708
Bartlett's Test of Sphericity Approx. Chi-Square 187.969

df 3

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Total Variance Explained

Component

Initial Eigenvalues Extraction Sums of Squared Loadings
Total % of Variance Cumulative % Total % of Variance Cumulative %

1 2.123 70.769 70.769 2.123 70.769 70.769

2 .461 15.357 86.126

3 .416 13.874 100.000

Extraction Method: Principal Component Analysis.

Component Matrixa

Component
1

ME3 .852

ME2 .836

ME1 .835

Extraction Method:
Principal Component
Analysis.

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APPENDIX 5: Regression analysis

Model Summaryb

Model R R Square

Adjusted R
Square

Std. Error of the

Estimate Durbin-Watson

1 .729a .531 .515 .36605 1.866

a. Predictors: (Constant), Facilitating_Condition, Social_Influence, Effort_Expectancy,
Consumer_Innovative, Performance_Expectancy, Hedonic_Motivation, Price_Value
b. Dependent Variable: Behaviour_Intention

ANOVAa

Model Sum of Squares df Mean Square F Sig.

1 Regression 30.968 7 4.424 33.017 .000b

Residual 27.335 204 .134

Total 58.303 211

a. Dependent Variable: Behaviour_Intention

b. Predictors: (Constant), Facilitating_Condition, Social_Influence, Effort_Expectancy,
Consumer_Innovative, Performance_Expectancy, Hedonic_Motivation, Price_Value

Coefficientsa
Model
Unstandardized
Coefficients
Standardized
Coefficients

t Sig.

Collinearity
Statistics

B Std. Error Beta

Toleranc

e VIF

1 (Constant) 1.292 .303 4.263 .000

Effort_Expectancy .060 .049 .063 1.229 .220 .862 1.161

Social_Influence .166 .033 .267 5.049 .000 .822 1.217

Price_Value .161 .030 .305 5.437 .000 .730 1.370

Hedonic_Motivation .181 .058 .174 3.128 .002 .740 1.351
Performance_Expecta

ncy .098 .047 .113 2.086 .038 .786 1.273