INTRODUCTION
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,
Despite the success of SVOD in the world, the number of people using this service is still limited in Vietnam According to the figure of Authority of Broadcasting and Electronic Information in 2020, the number of users of the whole SVOD market in Vietnam was 10 million users, which accounts for only 10% market penetration (VTV, 2020) Even the big firm in this industry like Netflix, which has 130 million subscribers in the world (Louis, 2018), is having a low number of users in Vietnam According to ictnew.vn, the number of Netflix subscribers in Vietnam was only 300.000 users, which accounts for just only about 0.31% of the total Vietnamese population (Minh, 2019) Despite the low adoption 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
Recently, the number of studies on SVOD is really limited In previous studies, some key factors had been proved to have an impact on subscription intention The most common factors were perceived usefulness and perceived ease of use (Cebeci et al., 2019; Ramíez-Correa et al., 2017; Sardanelli et al., 2019; Lee et al 2018) For instance, Cebeci et al (2019) using Technology Acceptance Model (TAM), found out that a person who had the perception of usefulness would have the intention to use Netflix in the context of Istanbul, other remaining factors in Cebeci’s study are Perceived Ease of Use, Knowledge and Technology Anxiety In addition, Ramíez-Correa et al (2017) found that a person who had a high enjoyment perception of Netflix would highly have the behavioral intention of using Netflix Some other scholars approached at the angle of movie piracy, which concluded that Moral Judgement and Product Involvement were the two key factors which affecting 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
In conclusion, based on theoretical and practical motivation, the author conducts study names “Factors affecting intention to subscribe to SVOD services in Vietnam” as an MBA thesis topic.
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.
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
The subject of the research will be “Factors affecting intention to subscribe to SVOD of Vietnamese people who already have acknowledged about this service”
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
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
The thesis had proposed several solutions to increase the number of subscribers for SVOD service providers.
Research Contribution
2.1 Review of related definition and previous research
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
According to Oxford Dictionaries, Streaming is a method of sending or receiving data (video and audio material) through the internet in a continuous stream (Oxford University Press, 2019) Streaming is similar to the television broadcast, the only difference is that streaming delivers content through the internet
LITERATURE REVIEW AND HYPOTHESIS
Review of related definition and previous research
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
According to Oxford Dictionaries, Streaming is a method of sending or receiving data (video and audio material) through the internet in a continuous stream (Oxford University Press, 2019) Streaming is similar to the television broadcast, the only difference is that streaming delivers content through the internet
(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)
According to the research of Chen with his collaboration (2014), video on demand (VOD) can be understood as a system that allows users to be able to choose and watch videos that they want regardless of time and place The VOD system can enable users to gain control over the media they watch
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 minutes per day using SVOD services (Stastista, 2019a)
Based on the above definition, it can be concluded that the subscription video on demand is a service provided content such as films, television series, documentaries SVOD service providers require a monthly subscription fee, after paying the fee users can access SVOD’s content anywhere and at any time One of the remarkable features of OTT in general as well as SVOD comes from a recommendation system that helps users find their entertainment content faster
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)
Cerbeci and his team succeeded in building a comprehensive model predicting intention to subscribe to Netflix However, the study still had some limitations First, this study conducted only in Istanbul, so the generalizability of the finding is still a constraint Second, the factors mentioned are mostly looking at the aspect of technology In reality, subscription intention can be affected by other factors such as Price, Perceived Quality,
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)
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
Figure 2.4: Theory of reasoned action (Fishbein & Ajzen, 1975)
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
In the studies about technology adoption, some scholars have emphasized the relationshipxbetweenxattitudexandxintention behavior Davis (1989) developed TAM to explain the behavior of consumers toward a specific technology, which emphasized the relationship between attitudes toward technology and intention 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
In previous studies, there were arguments that there is a similarity between technology acceptance theories Therefore, Venkatesh et al (2003) suggested it would be better if someone can merge them into one unified theory That is the reason UTAUT has been made to support further study related to the acceptance and used of technology
Figure 2.7: Unified theory of acceptance and use of technology UTAUT
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
Almost all studies concluded that 4 elements of UTAUT can predict the behavioral intention and use behavior However, some scholars showed different results Li and Kishore (2006) when researched about Welog social internet system, found that 4 constructs of UTAUT did not have a good result Therefore, due to the advancement of the information system, Venkatesh et al (2012) had extended UTAUT into UTAUT2 UTAUT2 was believed to be more suitable with the context of consumer behaviors than the previous UTAUT (Llamas & Stofega, 2009)
UTAUT2 has applied the previous construct with 3 new constructs added:
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.
Hypothesis development and conceptual model
The researchxmodel applies six constructs of UTAUT2 Moreover, because the sample of the study is mainly new potential users, the factor Habit will not be mention Consumers need to have rich experiences in using SVOD to generate habit
Because the context of this study was focused mainly on potential consumers, so the role of habit may hard to examine (Venkatesh et al., 2012) Along with six constructs of UTAUT2, the author also integrates the role of Consumer Innovativeness and the Moderating role of Media Exposure
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
Performance expectancy is defined as “the degree to an individual believes that the technology can support him/her to accomplish a certain task” (Davis et al., 1992; Shin, 2009) This factor is similar to Perceived Usefulness in TAM In UTAUT2, Performance expectancy can be understood as “the degree to which 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: Performance x Expectancy will have a positive impact on intention to subscribe to SVOD in Vietnam
In UTAUT2, effort expectancy was x defined x asxhow x easy 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
H2: Effort Expectancy will have a positive impact on intention to subscribe to SVOD in Vietnam
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 (Dửrr 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
H3: Social Influences will have a positive impact on intention to subscribe to SVOD in Vietnam
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;
As SVOD is a service focus heavily on entertainment value rather than utilitarian value, the role of hedonic motivation can be considered as one of the important factors explaining consumer intention to subscribe If the consumers feel 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
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 “the x trade-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
It is seen that there is still a lot of free option and the illegal option as an alternative for SVOD in the context of Vietnam Therefore, price value is needed to be mention in the context of SVOD as users need to pay axsubscriptionxfeexinxorderxto access the content inside SVOD If the price is too high in comparison with the average income of users, it will be a huge barrier for users to access SVOD Thus:
H5: Price Value x will x have a positive x impact x on intention to subscribe to SVOD in Vietnam
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
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
Hedonic x Motivation Price x Value Consumer Innovativeness
METHODOLOGY
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
Identify x research population, sample and scale and measurement
Develop questionnaire based x on x previous x study
Analyze and interpret the results with SPSS
Sampling and data collection
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.
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 25 th March to 15 th 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.
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
The adding variable – Consumer Innovativeness was applied from a previous study of Agarwal & Prasad (1988) An example of one of the items is “If I heard about 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
PE1 1 I expect using SVOD improves my productivity in searching film/TV show
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
Expectancy EE2 2 I find SVOD easyxtoxuse et al (2012)
EE4 4 My Interaction with SVOD is clear and understandable
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
HM1 1 UsingxSVODxisxfun Venkatesh et al (2012) HM2 2 UsingxSVODxisxenjoyable
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)
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 trouble using SVOD
CI1 1 If I heardxaboutxaxnewxinformation technology, Ixwould look for ways to experiment with it
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?
(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?
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.
Analysis Method
The demographic data of the respondence will be presented in tables and charts
The classification criteria will be as follows: Gender, Age, Job, Salaries, Sources of awareness.
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 Reliability x analysis x by x Cronbach’s x alpha:
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 Exploratory x Factor x Analysis x – x EFA:
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)
Bartlett’s x testxofxsphericity has Sig < 0.05 (The observed items arexcorrelatedxwith each other in the population)
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 X 1 ,X 2 ,… The outcome is a regression equation which has a following the function:
- Y = Score for subscription intention behavior for SVOD
- X 1 , X 2 ,… X n = Score for the variables of this study’s model
- , , … = Regression co-efficient of independent variable
- ε = error term The step of regression analysis is shown below:
- Evaluate the regression equation through R 2 and adjusted R 2
- 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
- Test if there have multicollinearity by checking VIF value If the VIF value of one construct < 2, there has not any multicollinearity and we do not need to remove the variable and vice versa e Moderation analysis
Moderation analysis is to check whether the moderate variable can regulate the relationship between the independent variable and the dependent variable or not
The moderate variable can strengthen or weaken the relationship between dependent and independent variable (Hayes, 2013)
ANALYSIS RESULTS
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%)
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
Not currently user Currently user
Friend and Co-worker Family Advertisement
Reliability analysis
Cronbach’s x alphaxwasxused 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
Explanatory Factor Analysis
4.3.1 Explanatory Analysis for independent variable
The value of 24 observing items has good Eigenvalue (>1) The 7 th 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’s x TestxofxSphericity is 000 < 0.05 This result accepts the validity of data in the explanatory analysis
The value of Total Cumulative is 75.073% > 50%, showing that the 7 factors can explain 75.073% of data variation
Table 2.2: EFA Results for independent variable
All factor loadings are larger than 0.5 To sum up, the table shows that 24 measuring items are group into 7 independent variables
4.3.2 Explanatory Analysis for dependent variable
Table 4.3: EFA Results for Dependent Variable
Behavioral intention scale consists of 3 items, The KMO value is valid with value 0.694 between 0.5 and 1, also the significantxofxBartlett’s x TestxofxSphericity 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
Media exposure scale consists of 3 items, The KMO value is valid with value
= 0.716 between 0.5 and 1, also the significantxofxBartlett’s x TestxofxSphericity 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
To sum up, Media exposure (ME) scale remains with 3 item ME1, ME2, ME3, exacted to 1 component – Media exposure (ME).
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; Sig one-tailed = 0.0005 < 0.05) hasxsignificant positive relationshipxwithxSubscriptionxIntention
Performance Expectancy (PE) (Beta = 0.113 > 0; Sig one-tailed = 0.019 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
