直播成癮？秀場直播使用者持續使用動機研究 - 政大學術集成

全文

(1)國立政治大學國際傳播英語碩士學位學程 International Master’s Program in International Communication Studies College of Communication National Chengchi University. 碩士論文. 治. 立. 政 Master’s Thesis 大. ‧. ‧ 國. 學. 直播成癮？秀場直播使用者持續使用動機研究. y. Nat. io. sit. Why do people watch live streaming？A research on. n. al. er. Viewer’s Intention of Continuous Usage in Taiwan. Ch. engchi. i n U. v. Student：詹冠純 Kuan-Chun Chan Advisor：郭貞 Chen Guo. 中華民國 107 年 6 月 June 2018. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(2) 直播成癮？秀場直播使用者持續使用動機研究 Why do people watch live streaming？A research on Viewer’s Intention of Continuous Usage. 研究生：詹冠純 Kuan-Chun Chan. 政治大指導教授：郭貞 Chen Guo 立. ‧. ‧ 國. 學國立政治大學碩士論文. n. al. er. io. sit. y. Nat. 國際傳播英語碩士學位學程. Ch. engchi. i n U. v. A Thesis Submitted to the International Master Program’s in International Communication Studies National Chengchi University In Partial Fulfilment of the Requirements for the Degree of Master of Arts. 中華民國 107 年 6 月 June 2018. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(3) Abstract The goal of this study is to conduct an investigation on the motivation of user’s continuous intention of using live streaming app in Taiwan. To help current marketing and operation manager in live streaming industry in Taiwan understand more about user intention of continuous usage, this research focus on answering if individual experience and coexperience that audience perceived while interacting with other audiences and. 政治大. broadcaster can affect their continuous usage of live streaming app. In this study, we. 立. found that people will keep on watching live streaming due to entertainment and social. ‧ 國. 學. reasons. Male are more likely to use live streaming app for entertainment and social. ‧. reasons.. sit. y. Nat. n. al. er. io. Keywords: live Streaming, Uses and Gratification, 17Media, Social Connection. Ch. engchi. i n U. v. i. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(4) Table of Contents Abstract ................................................................................................................................. i Table of Contents ................................................................................................................ ii List of Tables ....................................................................................................................... iv List of Figures ...................................................................................................................... v Chapter One – Introduction .............................................................................................. 1 1.1 Research Background and Motivations ................................................................................................... 1. 政治大 1.3 Purpose of the Study ......................................................................................................................................... 3 立. 1.2 Live Stream Platform Research in Taiwan ............................................................................................. 2. ‧ 國. 學. Chapter Two – Literature Review .................................................................................... 4. 2.1 Background of Social Live Streaming Services .................................................................................... 4. ‧. 2.2 Co-experience....................................................................................................................................................... 8 2.3 Technology Acceptance Model ..................................................................................................................... 9. y. Nat. io. sit. 2.4 Uses and Gratification Theory in Live streaming platform .......................................................... 13. n. al. er. Chapter Three – Research Method ................................................................................ 15. Ch. i n U. v. 3.1 Research Design and Measures ................................................................................................................. 15. engchi. 3.2 Data Collection.................................................................................................................................................. 18 3.3 Research Framework and Hypotheses ................................................................................................... 18 3.4 Data Analysis ..................................................................................................................................................... 19. Chapter Four –Analysis and Findings ........................................................................... 21 4.1 Survey administration ................................................................................................................................... 21 4.2 Reliability and Validity .................................................................................................................................. 22 4.3 Model Analysis ................................................................................................................................................... 24. Chapter Five –Discussion................................................................................................. 29 5.1 Overview of Research Finding.................................................................................................................... 29. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(5) 5.2 Intention of Continuous Watching Intention ...................................................................................... 29 5.3 Gender Differences on Live Streaming Platform ............................................................................... 31. Chapter 6 Conclusion and Limitation ........................................................................... 32 6.1 Summary .............................................................................................................................................................. 32 6.2 Research Limitation........................................................................................................................................ 33 6.3 Research Contributions ................................................................................................................................. 34. Reference ............................................................................................................................ 36 Appendix ............................................................................................................................ 39. 立. 政治大. ‧. ‧ 國. 學. n. er. io. sit. y. Nat. al. Ch. engchi. i n U. v. iii. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(6) List of Tables Table 1 Comparison of Tradition TV program and Live Streaming Program ......................... 5 Table 2 Live Streaming Categories ....................................................................................... 7 Table 3 Measurement Items ................................................................................................ 16 Table 4 Demographic Information of Respondent (N = 343) ............................................... 22 Table 5 Reliability and Validity for Constructs .................................................................... 23 Table 6 Rotated Component Matrix .................................................................................... 25 Table 7 Coefficient ............................................................................................................. 26 Table 8 Group Statistics ...................................................................................................... 27. 政治大. Table 9 Independent Sample Tests ...................................................................................... 27 Table 10 Hypothesis support list ......................................................................................... 28. 立. ‧. ‧ 國. 學. n. er. io. sit. y. Nat. al. Ch. engchi. i n U. v. iv. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(7) List of Figures Fig 1 MeerCat ........................................................................................................................ 5 Fig 2 Technology Acceptance Model ................................................................................... 12 Fig 3 Proposed Research Model ........................................................................................... 19 Fig 4 Results of Proposed Model ......................................................................................... 28. 立. 政治大. ‧. ‧ 國. 學. n. er. io. sit. y. Nat. al. Ch. engchi. i n U. v. v. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(8) Chapter One – Introduction 1.1 Research Background and Motivations In recent ten years, online social community has changed the landscape of traditional media, shifting the way how people consuming information. Nowadays, Internet has several attractive features when it comes to online self-presentation. People tend to be. 政治大 tradition media which serve 立audience as passive receiving information without processing more active than ever regarding information seeking and processing. Compared to. ‧ 國. 學. and consuming (Esrock & Leichty, 1998).. New media tend to serve their audience as respective person as they can receive. ‧. information and interpret with their own consideration and mindset. Web 2.0 enable. y. Nat. io. sit. people present themselves in online community on their own will, sharing personal. al. er. thoughts, ideas and talents. This kind of community, which rely on user-generated content. n. v i n C hYouTube, or Facebook (UGC) includes video platform (Bründl & Hess, 2016). Live engchi U. streaming now enable users and audience broadcast publicly live audio and video streams along with a shared chatroom (Hamilton, Garretson, & Kerne, 2014) .Take Twitch for example, with a single free account, the audience can communicate with the broadcaster easily. The interactive communication is open in streams (Hamilton et al., 2014). This kind of online social networks have become a part of the lives of audience, serving to satisfy the desire to communicate with other audiences in streams (Chang & Chuang, 2011).. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(9) 1.2 Live Stream Platform Research in Taiwan Live streaming activity has witnessed its prosperity since the availability of diverse platforms(Hu, Zhang, & Wang, 2017) . Actually, from technology prospective the live streaming platforms have presented more than a decade. However, it is not until the popularity of mobile phone and 4G internet that the social live streaming platform can gain increased intention. With the well-known cases such as Twitch, a social live streaming platform focusing on online gaming category which acquired by Amazon for the sum of $970 million (Bründl & Hess, 2016). Besides, Twitch has identified a. 治政大more than one million gamer have promising niche e-sport market. Every month in 2013, 立 ‧ 國. 學. broadcasted and more than 40 millions of people have watched these gaming Twitch channels (Pires & Simon, 2015).. ‧. Due to the new trend of online social community, other markets start to pay attention. sit. y. Nat. to this emerging opportunity and social trend. In Taiwan, although the most used Internet. n. al. er. io. application is still webpage searching and surfing, being a part of online virtual. i n U. v. community has become one of the major activity (Chang & Chuang, 2011).. Ch. engchi. Prior research has examined the motivational factors which influence the watching intention or using attention in live streaming field (Bründl & Hess, 2016; Payne, Keith, Schuetzler, & Giboney, 2017; Pires & Simon, 2015). While live streaming platform research is gradually increased, motivations for live streaming users in Taiwan has not been quantitatively examined. With the emerging market for live streaming like Taiwan, it is necessary to know what motivates people in Taiwan become so addicted to live streaming app. I assume that, due to the different culture and user behavior between countries, motivational factors will differ. 2. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(10) 1.3 Purpose of the Study The goal of this study is to conduct an investigation on the motivation of user’s continuous intention of using live streaming app in Taiwan. In this research, I will adopt research variables proposed by Hu et al., (2017) which is built by the basis of Social identity theory. Besides, I will also combine TAM (Technology Acceptance Model) which is proposed by Davis(1989) and U&G theory to make this research more comprehensive. The research focuses on the biggest live streaming app in Taiwan named 17Media. To. 政治大 help current marketing and operation manager in live streaming industry in Taiwan 立. ‧ 國. 學. understand more about user intention of continuous usage, this research focus on answering if individual experience and co-experience that audience perceived while. ‧. interacting with other audiences and broadcaster can affect their continuous usage of live. Nat. sit. y. streaming app. Marketers in live streaming platform in Taiwan has tried several ways to. n. al. er. io. increase the user retention in live streaming app. This research can be useful when they have to allocate marketing resources.. Ch. engchi. i n U. v. For these objectives to be achieved, the article is structured as follows. The first section deals with the theoretical foundations for the development of the research. After which research methodology is presented, with full details of the participants in the research, and of a thorough descriptions of the adoption model from previous research. Finally, results are discussed and conclusion are drawn.. 3. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(11) Chapter Two – Literature Review. 2.1 Background of Social Live Streaming Services This study examines the factors that influence people’s continuous watching intention by combining co-experience with TAM (Technology Acceptance Model). The following chapter constitutes the introduction of the condition of Live Streaming Service in Taiwan and summarizes the previous literature about the theory of Technology. 政治大. Acceptance model and conceptualization of co-experience. Moreover, I will explain main. 立. construct of the research in this chapter.. ‧ 國. 學. On January 2009, the well-known social networking application Twitch has reached. ‧. more than 175 million active users. Meanwhile, every minute, more than ten hours of. sit. y. Nat. user-generated content were uploaded to the video sharing platform YouTube(Kaplan &. io. al. er. Haenlein, 2010). This number presents the powerful networking ability of social media.. v. n. The concept of social media refers to “ a group of Internet-based applications which build. Ch. engchi. i n U. on the ideological and technological foundations of Web2.0, and enable people to create exchange of user-generated content.(Bründl, Matt, Hess, & Christian, 2017). Live streaming platform perceive the characteristics of social media but develop novel type of it which is, “where user broadcast as well as live video content and features for synchronous international facilitate sociability (Bründl et al., 2017). At the SXSW Festival in Texas in March, 2015, an app named MeerKat quickly become famous because of Twitter. According to CNN report, MeerKat users exceeded. 4. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(12) 10,000, 75% of users came from United States. However, when Twitter launched its own live broadcast service, Meerat immediately fell.. Fig 1 MeerCat. 政治大. 立. ‧. ‧ 國. 學. Nat. sit. y. The differences between live streaming and traditional TV program lie on the “real- time. n. al. er. io. interactions as Table 1 shown.. Ch. engchi. i n U. v. Table 1 Comparison of Tradition TV program and Live Streaming Program Traditional TV program. Live streaming program. Characteristic. One-way. Real Time Interaction. Target Audience. 35+ years old. 25-35 years old. Content. Mostly sports, concerts and UGC. (User. generated. news. The PGC (Professional content). is higher. It’s. generated content) is higher common. to. see. talent. and the production fee of shows. program is higher Revenue. Advertising. Virtual gift. 5. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(13) Generally, live streaming platform can be categorized in to two types. First, general live streaming services, without any thematic limitation such as talent show or live sharing. Second, specific content sharing such as gaming, sports and art sharing. In Taiwan, according to the research of Institute for Information Industry, watching on live streaming platform has become one of the most important media usage behavior. In the survey, 78.4% of the participants visit live streaming platform or website by using mobile phone or computer. Amount the three months active users for all kinds of live streaming. 政治大. services, most users are watching on livestreaming platform by using mobile phone.. 立. Due the emerging research on live streaming platform(Dickey, 2007; Venkatesh,. ‧ 國. 學. 2000),some researchers have conducted research from technological prospective(Dickey,. ‧. 2007). Yet few research has combined the technological with the social psychological. sit. y. Nat. prospective. Ever since 2015, Taiwan has been regarded as new market for live streaming. io. al. er. platform. At present, there are more than five categories of live streaming content such. n. as news, sports, game facts, entertainment, music, presentations, and talent show on. Ch. engchi. i n U. v. Taiwan’s live streaming platform. In addition to news and sports events which are produced by professional TV stations, most live streaming content are produced by live streaming platform users like 17Media or Live House.in.. 6. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(14) Table 2 Live Streaming Categories. Platform. Content. YouTube. News, Sports , Gaming , Music. Twitch. Gaming. RC. Talent show. 17Media. Talent show. Lang live. Talent show. Up live. Talent show. MeMe live. Talent show. 政治大. Source: thenewslens (https://www.thenewslens.com/article/78434). 立. ‧ 國. 學. In Taiwan, live streaming has become one of the most important social behavior.. ‧. The biggest live streaming app 17Media predicts the whole Pan-Entertainment industry. sit. y. Nat. will welcome the generation of “Web 3.0” in 2018. Moreover, 17Media will continue. io. al. er. expand actively its global reach including Korea, Japan, Singapore and Malaysia. Due to. v. n. its founder Jeffrey Huang, 17Media have claimed itself the biggest live streaming. Ch. engchi. i n U. platform in Taiwan. With more than 7000 contracted streamers and more than 1.3 million accumulated watching hours per year, 17 Media indeed has been creating a glorious record for live streaming industry in Taiwan. Therefore, this research will collect samples from 17 Media via in-app helper.. 7. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(15) 2.2 Co-experience Previous research reveals that human experience is not just individualistic but includes social context and social interactions(Lim, Cha, Park, Lee, & Kim, 2012). That is to say, people tend to exist and live in the world context is because all the social activities they conduct in relationship which are created by social interactions. Some researchers even further claim the importance of perceiving human interactions as the formation of a shared experience with others(Lim et al., 2012). In fact, the idea of social. 政治大. interactions and shared experiences can be supported through social shared cognition. 立. theory which refers to the idea that the sharing experience through social interactions with. ‧ 國. 學. others in certainly the main point people can make decisions and how they exist in social. ‧. society. (Brewer, 1991; Cannon-Bowers, Salas, & Converse, 1993; Fussell & Krauss,. sit. y. Nat. 1991; Hardin & Higgins, 1995; Ickes & Gonzalez, 1994; Klimoski & Mohammed, 1994;. io. al. er. Resnick, Levine, & Teasley, 1991; Rommetveit & Blakar, 1979; Thompson & Fine, 1999).. n. Firstly proposed by Battarbee (2004), co-experience is defined as the user. Ch. engchi. i n U. v. experience can be shaped by experience which be shared and co-created in social interaction where participants share their moods, feeling and affections regarding to their own experience of consuming information(Battarbee, 2004). The concept of coexperience pay attention to the sharing experience between participants of a technology, product or service by taking all their consumption experience into consideration. That is to say, this concept highlights the sharing knowledge in virtual or physical presence can be of much importance of individuals’ experience (Battarbee, 2003). Lim et al. (2012) firstly proposed the conceptualization and operationalization for the concept of co-. 8. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(16) experience. According to the research, there are three dimensions when it comes to coexperience which are participation, cognitive communion, and resonant contagion(Lim et al., 2012). Base on the research, participation refers to a perception of partly contribute to the context that all users share the experience together. On the other hand, cognitive communion represents the perception that a user shares the same cognitive level with others in the context of their communication. Resonant contagion is somehow the extent to which a user’s behavior can have influence on the others(Hu et al., 2017). With the. 治政大 in social media is actually knowledge about this conceptualization, co-experience 立 ‧ 國. 學. reflected by its sub-dimension of participation, cognitive communion, and resonant contagion (Battarbee, 2004; Lim et al., 2012). Base on this concept, co-experience can. ‧. also be applied to live streaming platform which interactions are important element in. n. al 2.3 Technology Acceptance Model Ch. engchi. er. io. sit. y. Nat. live streaming platforms.. i n U. v. Proposed by Davis (1986), the Technology Acceptance Model has been applied to several research. The Technology Acceptance Model (TAM) (Davis, 2017) is the most widely applied model of user acceptance and usage. TAM was adapted from the Theory of Reasoned Action (TRA)(Ajzen & Fishbein, 1975). This dominant paradigm posits that user acceptance can be explained by two beliefs：perceived usefulness and perceived ease of use(van der Heijden, 2004). Perceived ease of use is defined as "the degree to which a person believes that using a particular system would be free of effort"(Davis,. 9. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(17) 2017).Perceived usefulness is defined as "the degree to which a person believes that using a particular system would enhance his or her job performance”(Davis, 2017). The technology acceptance model(TAM) has been widely studied in IS research as an explanation of the use of information systems across IS types and nations(Information, 2017). Moreover, TAM has attracted a growing body of research such as user-oriented interactive computer system. Started with e-mail and graphic(Davis, 2017), TAM has been applied to several field such as social media for exploring the individuals’ acceptance and use of social medium(Ngai, Moon, Lam, Chin, & Tao, 2015), online. 治政 banking(Zandhessami & Geranmayeh, 2014),online 大 games usage(Hsu & Lu, 2004). 立 ‧ 國. 學. Further implication make adjustment to this model, researcher found out that. hedonic variant as an important variable in social media field such as live streaming. ‧. platform(van der Heijden, 2004). Van der Heijden’s (2004) hedonic variant of the TAM. sit. y. Nat. derives from the original theory’s parsimony and strong generalizability, while. n. al. er. io. incorporating the hedonic aspects that are essential to cover consumers’ affordances in. i n U. v. live streaming platform research. From original concept of TAM includes three. Ch. engchi. theoretical constructs to predict and explain actual use behavior: perceived usefulness, perceived ease of use, and behavioral intention(Davis, 2017). The hedonic variant of the TAM expands the model by the construct perceived enjoyment, which is considered to be the dominant predictor over perceived usefulness in the context of hedonic IS. As the conceptualization of intrinsic motivation, enjoyment has received considerable research attention in recent year which can be defined as the degree to which performing an activity is perceived as providing pleasure and joy in its own ways (Ngai et al., 2015).. 10. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(18) TAM (Technology Acceptance Model) does explain what motivate people to actual use a new technology. However, in this research I want to include other components in order to provide a broader view and better understanding of IT adoption. Davis et al. adapted the motivation perspective and added perceived enjoyment and explained IT acceptance from both extrinsic and intrinsic motivational perspectives would be a suitable example of further adoption (Lee, Cheung, & Chen, 2005). Compared to the other variables, perceived enjoyment can further indicate why people want to watch on live streaming platform.. 立. 政治大. ‧ 國. 學. Motivation theories argue that motivation formulates the mechanism of human behavior and action(Zhang, Zhao, & Tan, 2008). When people are not triggered, they will. ‧. feel no inspiration to act. Indeed, motivation theory can be divided into two ideas. sit. y. Nat. according to the different reasons or goals to act: Intrinsic motivation and extrinsic. n. al. er. io. motivation in terms of reasons or goals or perform an action (Venkatesh, 2000).. i n U. v. Extrinsic motivation is that, people always perform actual action by intriguing by. Ch. engchi. something apart from its own sake, such as a reward or recognition(Information, 2017).The reason why they choose to use any technology like Facebook, Instagram or online learning platform is mainly because of rational calculation for benefits(Fagan, Neill, & Wooldridge, 2008). On the other hand, intrinsic motivation refers to the fact of doing something for its own sake. For example, playing online game itself is interesting, engaging to someone who chose to spend time on it. The decision to use technology is partly determined by intrinsic motivation.. 11. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(19) Derived from the definition of intrinsic and extrinsic motivation, user behavior is almost driven by its perceived value and benefits. Therefore, proposed by Davis(1989), TAM(Technology Acceptance Model) describes perceive usefulness (PU) refers to “ the degree to which a person believes that using a particular system would enhance his or her performance”. Furthermore, Davis et al. also proclaim that perceived usefulness in the technology acceptance model is an example of extrinsic motivation. For live streaming platform, it indeed perceived the characteristics that people can get benefits such as getting new knowledge while listen to broadcasters’ sharing(Zhang et al., 2008).. 治政大 is triggered by the feeling of As for intrinsic motivational perspective, user behavior 立 ‧ 國. 學. enjoyment, pleasure and fun. Perceived enjoyment is defined as “the extent to which the. activity of using the technology is perceived to be enjoyable”. On the basis of this. ‧. definition, perceived enjoyment is a form of intrinsic motivation. For live streaming,. n. al. Ch. engchi. er. io. entertainment programs on live streaming platform.. sit. y. Nat. people usually use it for entertainment since there are tons of talent show and. i n U. v. Fig 2 Technology Acceptance Model. 12. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(20) 2.4 Uses and Gratification Theory in Live streaming platform U&G theory is based on a set of assumptions that audience can process and consume information actively with precise goals held in their own minds (Sangwan, 2005). First proposed by Katz (1959) and then developed based on the concepts of social and psychological need (Köprülü, Helvaci, & Turhan, 2016). This theory mainly explains that audience have different gratification needs when they choose to use different kinds of media. Uses and gratification theory claims that audience are lead by their own needs and. 政治大 while use and gratification theory focus on the need to consider what people do with 立 motivations. Tradition mass media theory emphasize that effect of media is powerful. ‧ 國. 學. media (Rubin, 2002; Ruggiero, 2000; Parker and Plank, 2000; O’Donohoe, 1994; Katz, 1959).This theory has been applied to many mass media and social media research field.. ‧. For example, the context of radio (Herzog, 1944; Cantril and Allport, 1935); newspapers &. Allport,. 1935);. television. (Cantril. y. (Cantril. &. Allport,. sit. magazines. Nat. and. n. al. er. io. 1935).Furthermore, in recent years, a variety of researchers have applied this theory to. i n U. v. new media field such as Internet and mobile phones(Cantril & Allport, 1935)Previous. Ch. engchi. studies in social and psychological field have indicated five categories of use and gratification needs that lead audience to use mass media (Katz, E,. Blumler, J.G., & Gurevitch, 1973; Sangwan, 2005). These needs and motivations includes functions of cognitive, affective, social integrative, personal integrative, and tension release (Katz, E,. Blumler, J.G., & Gurevitch, 1973). In this theory, cognitive needs indicated that people using mass media to acquire information and knowledge for having a better understanding of new things. Affective needs indicate that audience use mass media for pleasurable, aesthetic, and emotional experience. Social-integrative needs indicate that 13. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(21) people use mass media for social reasons. For example, they often use social media to remain contact with their friends, family, and colleague. Personal- integrative needs indicate that people use mass media for the desire to make themselves more confident and trustworthy. For example, some people will utilize social media to build personal brand to reach potential business partners. Tension-release needs indicate that people use mass media for hedonic value in the area of consumer consumption. Previous research divided motivation into two dimensions: Utilitarian and hedonic value (Katz, E,. Blumler, J.G., & Gurevitch, 1973) . In social media field, information is one of the most important. 治政大 People no longer go to news dimensions (Katz, E,. Blumler, J.G., & Gurevitch, 1973) 立 ‧ 國. 學. website for daily news. On contrary, they get information from their social network such. as Twitter, Facebook, and other social network websites (Hirschman & Holbrook,. ‧. 2016).In live streaming field, social relationship can be also the most important factors to. sit. y. Nat. the reasons why people use live streaming services. Previous study states that people. n. al. er. io. participate in activities on social networks because of the desire to be recognized.. i n U. v. Furthermore, this kind of desire can be recognized as self-presentation. (Tufekci, 2008).. Ch. engchi. After conducting literature review, I divided these variables into four main dimensions: entertainment,loneliness,past time, and sociability to make it more simple and clear.. 14. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(22) Chapter Three – Research Method 3.1 Research Design and Measures Based on the theoretical components of U&G theory, this research develops a research model as shown in Figure 1. In this paper, the proposed model will be utilized to explain the continuous watching intention in terms of individual motivations. On the other hand, co-experience variables will be use to account for the sociability. In total, seven variables and four dimensions were included in this research.. 政治大 The study was designed to answer the proposed framework and hypothesis. I will 立. ‧ 國. 學. conduct an online survey in 17 live streaming app by sending out the online survey. through in-app message helper. The sample includes all wide range of users in 17 app. I. ‧. will apply prior study to this study and use items which suit research question. To be more. sit. y. Nat. specific, three dimensions of co-experience were measure from Lim et al (2012). As for. n. al. er. io. continuous watching intention items were adapted from Kang, Hong and Lee’s (2009). i n U. v. research. All these measures are followed the five-point Likert response format (1=”not. Ch. engchi. agree at all” to 5=”absolutely agree”). Additionally, each variable was labeled and abbreviated as follows: Participation (PA), Cognitive Communion (CC), Resonant Contagion (RC), Perceived Enjoyment (PE), Perceived Ease of Use (PEOU), Perceived of Usefulness (PU), Continuous Watching intention(CWI). Moreover, as shown in Table 3, we can see I divided these variables into four dimension : entertainment, sociability, loneliness, and past time. Furthermore, to ensure the validity, I invited about 20 potential live streaming app users to check the wording and suitability of this questionnaire. All advices from the pre-test were taken into consideration in this research. 15. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(23) Table 3 Measurement Items Construct. Variable. Sociability. Item. Source. Participation. PA1: When using [SLSS], I feel I. Lim et. (PA). am interacting as a group of users.. al., 2012. PA2: When using [SLSS], I feel I am a part of the channel community. PA3: When using [SLSS], I feel I am participating with the users in the chat. Cognitive. CC1: When using [SLSS], I feel I. 治 Communion政share similar thoughts with the 大 (CC) users in the chat. 立. Lim et al., 2012. ‧ 國. 學. CC2: When using [SLSS], I feel my information is shared with the users in the chat.. ‧. CC3: When using [SLSS], I feel I. al. n. Contagion. Ch. (RC). RC1: When using [SLSS], my. er. io. Resonant. y. users.. sit. Nat. share the same perspective as the. behavior is influenced by the users. v ni. Lim et al., 2012. in the chat. U en h i using [SLSS], my g cWhen RC2: behavior influences the users in the chat. RC3: When using [SLSS], the users in the chat agree upon similar opinions.. 16. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(24) Table 4 Measurement Items (Cont.) Construct. Variable. Entertainment. Item. Relaxation. Source. RX1: Watching SLSS allows me to unwind. Smock et al. 2011. RX2: Watching SLSS relaxes me RX3: Watching SLSS is a pleasant rest Escapism. ES1: Using SLSS, I can forget about school, work, or other things. Smock et al. 2011. ES2: Using SLSS, I can get away from the rest of my family or others. Using SLSS, I can get away 治政ES3: from the rest of大 my family or others.. 立. ES4: Using SLSS, I can get away. ‧ 國. Companionship. ‧. alone.. Smock et al. 2011. else to talk or be with.. y. CP2: I use SLSS when there’s no one. Nat. CP3: Using SLSS makes me feel less. n. al. lonely.. sit. io Past time. CP1: Using SLSS, I don’t have to be. er. Loneliness. 學. from what I’m doing.. C h something I do.U n i engchi. Distraction. v. DS1: Using SLSS is a habit, just. Smock et al. 2011. DS2: When I have nothing better to do, I use SLSS DS3: Using SLSS passes the time away, particularly when I’m bored. DS4: Using SLSS gives me something to do to occupy my time.. 17. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(25) 3.2 Data Collection The biggest live streaming platform 17Media was chosen as representative of talent show dominated platform in this study. Invitation were sent to users in 17Medai with incentives which it’s possible to get free movie tickets if they finish this questionnaire. Besides, I will also ask some of popular streamers to send the questionnaires. Participants were asked to fill their unique user name in 17Media to prevent them from over-filling the questionnaire. Questionnaires are developed to test the proposed hypothesis. In order. 政治大. to avoid duplicate answers, this survey will only include effective responses.. 立. ‧ 國. 學. 3.3 Research Framework and Hypotheses. To sum up, based on the literature review, this study proposes following hypotheses:. ‧ y. Nat. er. io. sit. H1: Entertainment is positively related to continuous watching intention H2: Loneliness is positively related to continuous watching intention. al. n. v i n C hto continuous watching H3: Past time is positively related e n g c h i U intention. H4: Sociability is positively related to continuous watching intention. 18. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(26) 立. 政治大. Nat. io. sit. y. 3.4 Data Analysis. ‧. ‧ 國. 學 Fig 3 Proposed Research Model. n. al. er. Based on the literature review, I adapted items from previous research. A two-step. Ch. i n U. v. approach was employed to analyze the data. First, confirmatory factor analysis would be. engchi. used to verify the validity and estimate the competence of the measurement model. Second, I will use regression analysis to test the relationship among constructs. In order to research data to be of value and of use, I conduct pre-test to assure the data is reliable and valid. Reliability refers to the repeatability of findings. On the other hand, validity refers to the credibility of the research. Moreover, the goal to conduct a pre-test is to prevent the questionnaire items from misunderstanding. This pretest is sending during March 26, 2018 to March 28, 2018. I collected 20 questionnaires in total. 19. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(27) and ask five classmates to see if there was any misunderstanding of questionnaire sentence. All questions are checked and edited accordingly. Moreover, according previous research indicates that male have more positive attitude toward computers than female(Durndell & Haag, 2002). Research in computermediated technology shows that male are more likely to be heavy users than women especially when it comes to computer video game(Durndell & Haag, 2002). Other research indicates that males are more likely to adopt e-commerce and e-learning than female(Durndell & Haag, 2002). In this research, I want to further investigate if these. 治政大 I conduct an independent research results can apply to live streaming industry. Therefore, 立 ‧. ‧ 國. 學. samples T test to see if there would be a difference between male and female.. n. er. io. sit. y. Nat. al. Ch. engchi. i n U. v. 20. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(28) Chapter Four –Analysis and Findings 4.1 Survey administration We collected the data using online questionnaire tool Surveycake from May 21th to May 28th. A total of 343 questionnaires were collected via 17Media in-app tool. Participants completed the survey for the chances to get two free movie tickets. The final sample of 343 respondents we use already excluded the incomplete samples. The sample comprised 61.3% males and 38.2% females, and the participants’s ages mainly from. 政治大. 18-35, participants who age under 18 accounts for 0.6%, 46.5% of participants aged from. 立. 18-25, 39% of participants aged from 26-35. As for marriage status, 59.4% of participants. ‧ 國. 學. are single and 26.4% of participants are in a relationship. This result indicated the. ‧. majority of participants are single and age between 26-35. For the location. sit. y. Nat. allocation,58.1% of participants are from northern Taiwan,24.3% of participants are from. io. al. er. central Taiwan, 11.7% of participants are from southern Taiwan.The demographic. n. statistics are given in Table 4.. Ch. engchi. i n U. v. 21. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(29) Table 5 Demographic Information of Respondent (N = 343) Measure. Items. Count. %. Gender. Male. 212. 61.3%. Female. 131. 37.9%. Under 18. 2. .6%. 18-25. 160. 46.5%. 26-35. 134. 39%. 36-45. 22. 6.4%. 26 治政 Single 大205. 7.6% 59.2%. 91. 26.3%. married. 48. 13.9%. North. 198. Central. 83. South. 40. Others. 20. Age. Above 46. Location. ‧. Nat. 58.1% 24.3% 11.7% 5.9%. io. n. al. married. C. hengchi 4.2 Reliability and Validity. sit. Youth gender: 1 = male, 2 = female. marital status: 1 = single, 2 = in a relationship, 3=. er. a. 學. ‧ 國. 立In a relationship. y. Marriage Status. i n U. v. In this research, I assessed the reliability and validity from previous research. The. basic research criteria I adapted is as follow : (1) composite reliability (C.R) and Cronbach’s Alpha should be above 0.7 for reliability test ; (2) all factor loadings should exceed 0.6. The following tests of full sample (N=346) are shown in Table 5.. 22. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(30) Table 6 Reliability and Validity for Constructs Construct. Items. Factor Loading. Cronbach’ α. Entertainment. RX1. 0.756. 0.854. RX2. 0.737. RX3. 0.637. ES1. 0.748. ES2. 0.755. ES3. 0.744. CP1. DS1. 0.597. 0.863. DS2. 0.709. DS3. 0.765. DS4. 0.763. PA1. 0.778. PA2. 0.778. PA3. 0.715. y. ‧ 國 io. n. al. 0.797. ‧. Nat. Sociability. CP2. 學. Past time. 0.932. CC1. CCC2 hengchi. iv n U0.804 0.729. CC3. 0.686. RC1. 0.609. RC2. 0.734. RC3. 0.667. 0.874. sit. 立. 0.802 治政 CP2 0.830 大. er. Loneliness. 0.882. 0.834. 0.805. 23. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(31) 4.3 Model Analysis In this research data analysis was performed using regression analysis to test whether the variables we proposed have positive relationship with continuous watching intention. Therefore, in this research, I first conducted a confirmatory factor analysis to determine the dimensions, and then the regression analysis was presented. Before testing the proposed hypothesis, this research need to evaluate whether the scales can reach satisfactory levels of reliability and validity. After conducting a confirmatory factor analysis, I clarified four main components and based on theory review renamed as:. 治政大 are shown in table5. Afterward, Entertainment, loneliness, past time, and sociability which 立 ‧ 國. 學. I tested the Cronbach’s α and individual item reliability the make sure each item to reach the research criteria. As shown in Table 5 all values of Cronbach’s α are above 0.7 which. ‧. indicate the scale had reached our research criteria and had high reliability. In addition, I. sit. y. Nat. conducted an individual item-reliability test to see if each item was significant. After. n. al. er. io. conducting factor analysis, we can see the items I selected as shown in Table 5, the factor. i n U. v. loading in each construct exceeded the correlation between the construct and the others. Ch. engchi. except items for perceived of enjoyment. The items for perceived of enjoyment should be included in Entertainment construct. However, for these items, the factor loadings are under 0.6. Besides, the factor loading for ES1 is also below 0.6. Therefore, we decided to excluded these four items as shown in Table 6.. 24. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(32) Table 7 Rotated Component Matrix Research Variables. Component 1. 2. RX1. .756. RX2. .737. RX2. .637. ES1. .748. ES2. .755. ES3. .744. CP1 CP2. 立. CP3. 3. 政治.802 大 .830 .797. ‧ 國. 學. DS1. .597. DS2. .709 .765. ‧. DS3 DS4. CC1 CC2. y. sit er. al. n. PA3. io. PA2. .763. Nat. PA1. 4. Ch. engchi U. v ni. .778 .788 .715 .729 .804. CC3. .686. RC1. .609. RC2. .734. RC3. .667. PE1. .548. PE2. .569. PE3. .597. 25. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(33) Table 8 Coefficient Construct. Standardized. t. Sig. Coefficients Beta Entertainment. .254. 4.174. .000***. Loneliness. -.024. -.431. .667. Past time. .195. 3.407. .001**. Sociability. .312. 5.136. .000***. *p < .05.. **p < .01.. ***p < .001. In this research, I detected several potential factors which may affect user ’ s continuous watching intention on live streaming platforms. The results indicated that. 政治大 sociability, past time and entertainment usage are strongly related to continuous watching 立. ‧ 國. 學. intention on live streaming platforms. However, in this research I also found out that loneliness might not be the important factors for people who decide to keep on watching. ‧. live streaming shows.. Nat. sit. y. In Table 7 shows the results of proposed model for the full sample. As shown we. n. al. er. io. can see that Entertainment, Past time, and Sociability were found to be positively. i n U. v. associated with continuous watching intention (𝛽=0.254, t = 4.174 ; 𝛽 = 0.195, t = 3.407 ;. Ch. engchi. 𝛽 = 0.312, t =5.136) ,which supported H1, H3, H4. However, loneliness was found to be not positively associated with continuous watching intention (𝛽 = -0.024, t = -0.024). As for gender differences, I conducted independent samples T test. As shown in Table 9, we can see for sociability, male are more likely to watch live streaming for social reasons ( t = 3.948,p < 0.001).. 26. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(34) Table 9 Group Statistics Construct. Gender. Mean. Std. Deviation. Entertainment. Male. 3.80. 0.719. Female. 3.60. 0.729. Male. 3.64. 0.996. Female. 3.34. 0.980. Male. 3.52. 0.817. Female. 3.31. 0.838. Loneliness Past time Sociability. Male Female. 0.116. 0.734. 2.701. 0.223. 0.637. 2.273. 0.002. 3.948. io. al. n. Ch. *p < .05.. 340. 0.014*. y. 2.470. Sig.(2-tailed). 340. 0.007**. 341. 0.24. 229. 0.0001***. sit. 0.551. df. er. 0.356. 9.987. t. ‧. Entertainment. Sociability. Sig. Nat. F. Past time. 0.999. Table 10 Independent Sample Tests. Construct. Loneliness. 0.792. 學. ‧ 國. 立. 3.68 政治 3.28 大. v ni. < .01. ***p < .001 e **p ngchi U. 27. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(35) Table 11 Hypothesis support list Hypothesis. Result. H1 : Entertainment is positively related to continuous watching intention. Supported. H2: Loneliness is positively related to continuous watching intention. Not Supported. H3 : Past time is positively related to continuous watching intention. Supported. H4 : Sociability is positively related to continuous watching intention. Supported. 政治大. Fig 4 Results of Proposed Model. 立. ‧. ‧ 國. 學. n. er. io. sit. y. Nat. al. Ch. engchi. i n U. v. 28. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(36) Chapter Five –Discussion 5.1 Overview of Research Finding In this research, I detected several potential factors which may affect user ’ s continuous watching intention on live streaming platforms. The results indicated that sociability, past time and entertainment usage are strongly related to continuous watching intention on live streaming platforms. However, in this research I also found out that. 政治大. loneliness might not be the important factors for people who decide to keep on watching. 立. live streaming shows which is a fruitful insights since most marketers in Taiwan thought. ‧ 國. 學. that the reasons why people want to use live streaming platform is because they need. ‧. someone to be accompanied with.. sit. y. Nat. n. al. er. io. 5.2 Intention of Continuous Watching Intention. i n U. v. The results of this proposed model show that factors in each constructs which may. Ch. engchi. be associated with continuous watching intention. The main dimension in this research are entertainment, loneliness, past time, and sociability. I separately test each factor in the dimension and fist conducted the factor analysis to see if the result supported my proposed model. In the result, I found not that most my proposed hypothesis were supported. However, loneliness does not which was surprised to me. In my previous working experience in live streaming industry, most marker will use “ loneliness “ as the key insights to attract new user since they believe that people who watch on live streaming platform are lonely and need companion. There are two possible explanation: First, 29. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(37) people will refuse to admit that they are lonely and need someone to be with. Second, people are more likely to regard live streaming platform as a tool to pass time and use it just for fun. As for sociability, in this research, I found out that sociability has significant impacts on continuous watching intention. It is an important factors for people’s intention on continuous watching intention since virtual community is a reason for people decide to keep on following broadcasters. From my previous experience, we spend time on creating an online community by giving some incentives. For example, if broadcasters are willing to hold offline events they can get some gifts. Besides, all broadcasters were. 治政 told that they need to create their own Line group to大 keep on reinforce their social ties 立 ‧ 國. 學. with their fans. Therefore, with regard to sociability, mutual communication is important between broadcasters and their fans. Either marketer in live streaming industry or. ‧. broadcasters themselves should make the users feel like they are actually be part of a. sit. y. Nat. community. For entertainment and past time, we can know people need something to. n. al. er. io. relax, the characteristics of live streaming can be the best choice for them. For live. i n U. v. streaming users, they don’t have to reveal themselves online but still they can make some. Ch. engchi. new friends and spend whatever time they want to watch on live streaming programs. Moreover, living in a fast-paced society, people tend to find somewhere to escape from the overwhelming pressure. Live streaming seems to be the best choice for them. With the traits of anonymity and interactive interaction, people can find a place to relax with competing with others.. 30. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(38) 5.3 Gender Differences on Live Streaming Platform The results of independent samples t test show that male are more likely to use live streaming platform for social reason. The possible reason for these results is the demographic background for live streaming platforms focusing on talent shows. Around 80% of broadcasters are female. Therefore, it’s reasonable that male users are more likely to use live streaming platforms for social reason. For female, live streaming still have different types of programs for them to choose from, however, the motivation for them. 治政大 for use are more likely to be entertainment. 立. ‧. ‧ 國. 學. n. er. io. sit. y. Nat. al. Ch. engchi. i n U. v. 31. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(39) Chapter 6 Conclusion and Limitation. 6.1 Summary The purpose of this study was to explore the user intention and motivation on watching live streaming platform in Taiwan since live streaming platforms have changed how people behave and also how people interact with social media. More and more marketing directors and manager recognize live streaming as an emerging new social. 政治大 In this research, I 立 applied U&G theory to live streaming platform. Besides, I. media for them to utilize in near future.. ‧ 國. 學. combined co-experience concept from social-psychological perspective with technology acceptance theory. The main findings are summarized and discussed in the results. ‧. analysis. First of all, I discussed what motivate people to watch on live streaming. y. Nat. io. sit. platforms. Second, I discussed what are the main reason people are willing to follow their. er. favorite broadcasters. For the first question, I prove that participation, cognitive. al. n. v i n C hrelaxation, companionship, communion, resonant contagion, and distraction directly have engchi U. influence on watching intention which indicated all marketer can utilize these insights to conduct some marketing plans. Hence, we can know that the more people perceive these feelings, the more people are willing to keep on watching live streaming platforms. For the second question, I want to categorize the main reason why people want to keep on watching live streaming platform. For this question, I conduct factor analysis to separate the main components of variables. I separately investigate these variables based on literature reviews and found that there are four components for keeping on watching live streaming platforms : Sociability, loneliness, entertainment, and past time. In this research, 32. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(40) I found out that sociability, entertainment, and past time are the main reasons which motivate people on watching live streaming platform. However, I also found that loneliness is not the main reason why people want to watch live streaming. This insight can be utilized by most marketers in Taiwan since the advertising which they are using now is focusing on “loneliness”. For people enjoy watching live streaming, they pay more attention on social community. Besides, I also found that “past time” is also one of the most important factors. Therefore, based on this insight, marketing director in Taiwan can improve and design different ways of marketing to reach their potential heavy. 治政大 ever “ as their advertising users. For example, they can use “best past time activity 立 ‧ 國. 學. slogan insights when they are going to launch a new marketing campaign.. On the other hand, as the sociability become the most important factor, we can suggest. ‧. marketers to focus on off-line campaign to reinforce the online community. For most live. sit. y. Nat. streaming platforms in Taiwan, they focus on the “ broadcaster-only” campaigns. As. n. al. er. io. a managerial implication, marketers should base on this insight to conduct a. i n U. v. comprehensive marketing plan including both online and offline campaign to reinforce. Ch. engchi. the community tie in live streaming platforms.. 6.2 Research Limitation Still, several limitations exist in this research. First, the data collection process might be limited to just one platform. This research was conducted in Taiwan and offer questionnaire via 17media’s in app tool. Therefore, future studies are suggested to include more live streaming in Taiwan such as lang live, MeMe, Liveme, etc. Furthermore, cross-cultural analysis is also encouraged to conduct a more comprehensive research on 33. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(41) live streaming platform. Second, in this research I focus on only talent show genre. However, there are more popular live streaming categories in this field such as gaming and sports. Future study is suggested to include more categories in live streaming field to compare difference between them. More details about different content influence should be conducted in future study. Third, in this research we mainly conduct a research on the watching intention. However, factors that motivate people to watch and spend money would be different. Current study hasn’t cover all motivation of spending. Thereby, further study is suggested to conduct a research on the factors which affect user’s. 治政 spending intention. Finally, regarding the proposed 大 research framework, future studies 立 ‧ 國. 學. can explore more additional moderator and control variable such as gender, age, and education to develop a more complete model of live streaming platform. Besides, future. ‧. research are suggest to add group interviews to further understand to mindset of live. n. al. er. io. sit. y. Nat. streaming users.. Ch 6.3 Research Contributions e. ngchi. i n U. v. This study contributes to extent study on mobile live streaming research in following aspects. First, live streaming nowadays gain more and more attention whilst still hasn‘t received enough attention in academic filed. This study is the first research on live streaming app in Taiwan. Furthermore, not only apply the use and gratification theory into live streaming field but also combine social-psychological theory into this research. More and more marketing department in live streaming industry in Taiwan want to know more about their audience. Before conducting this research, they can only get data from. 34. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(42) their data base and didn’t know how to utilize them the do better analysis. This research provide them with a direction to better understand their users. To further investigate users on live streaming app, we collect usage data to know whether different motivation will result in different usage type. By applying U&G theory to live streaming app in Taiwan, we can know the reason why people in Taiwan enjoy live streaming app so much. We thought that people might use live streaming app as a escapism. However, we found out that in live streaming platform the social community is more important in live streaming context.. 立. 政治大. ‧. ‧ 國. 學. n. er. io. sit. y. Nat. al. Ch. engchi. i n U. v. 35. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(43) Reference Ajzen, I., & Fishbein, M. (1975). Belief, Attitude, Intention and Behaviour: An Introduction. to. Theory. and. Research,. (July),. 480.. Retrieved. from. http://people.umass.edu/aizen/f&a1975.html Battarbee, K. (2003). Defining co-experience. Proceedings of the 2003 International Conference on Designing Pleasurable Products and Interfaces - DPPI ’03, 109. https://doi.org/10.1145/782896.782923 Battarbee, K. (2004). Co-Experience - Understanding User Experiences in Social Interaction.. Art. and. Design.. Retrieved. from. 政治大. http://www.informaworld.com/index/926563995.pdf. Bründl, S., & Hess, T. (2016). Why Do Users Broadcast ? Examining Individual Motives. 立. and Social Capital on Social Live Streaming Platforms. PACIS 2016 Proceedings,. ‧ 國. 學. (January), Paper 332.. Cantril, H., & Allport, G. W. (1935). The psychology of radio. The psychology of radio.. ‧. Oxford, England: Harper.. Chang, H. H., & Chuang, S. S. (2011). Social capital and individual motivations on. y. Nat. knowledge sharing: Participant involvement as a moderator. Information and. sit. Management, 48(1), 9–18. https://doi.org/10.1016/j.im.2010.11.001. al. n. 13(3), 319–340.. er. io. Davis. (2017). Perceived Usefulness , Perceived Ease of Use , and User Acceptance of, Dickey, M. D. (2007).. i n C Game h design and learning: eng chi U A. v. conjectural analysis of how. massively multiple online role-playing games (MMORPGs) foster intrinsic motivation. Educational. Technology. Research. and. Development,. 55(3),. 253–273.. https://doi.org/10.1007/s11423-006-9004-7 Durndell, A., & Haag, Z. (2002). Computer self efficacy, computer anxiety, attitudes towards the Internet and reported experience with the Internet, by gender, in an East European. sample.. Computers. in. Human. Behavior,. 18(5),. 521–535.. https://doi.org/10.1016/S0747-5632(02)00006-7 Esrock, S. L., & Leichty, G. B. (1998). Social responsibility and corporate web pages: Self-presentation or agenda-setting? Public Relations Review, 24(3), 305–319. https://doi.org/10.1016/S0363-8111(99)80142-8. 36. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(44) Fagan, M. H., Neill, S., & Wooldridge, B. R. (2008). EXPLORING THE INTENTION TO USE COMPUTERS : AN EMPIRICAL INVESTIGATION OF THE ROLE OE INTRINSIC MOTIVATION , EXTRINSIC MOTIVATION , AND PERCEIVED EASE OE USE University of Texas at Tyler University of Washington - Tacoma University of Texas at Tyler. Journal of Computer Information Systems, 4417(Spring), 31–37. https://doi.org/10.1080/08874417.2008.11646019 Hamilton, W. A., Garretson, O., & Kerne, A. (2014). Streaming on twitch: fostering participatory communities of play within live mixed media. Proceedings of the SIGCHI Conference. on. Human. Factors. in. Computing. Systems,. 1315–1324.. https://doi.org/10.1145/2556288.2557048 Hirschman, E. C., & Holbrook, M. B. (2016). Consumption : Hedonic Concepts ,. Journal. 政治大. of Marketing, 46(3), 92–101. https://doi.org/10.2307/1251707 Hsu, C. L., & Lu, H. P. (2004). Why do people play on-line games? An extended TAM. 立. with social influences and flow experience. Information and Management, 41(7), 853–. ‧ 國. 學. 868. https://doi.org/10.1016/j.im.2003.08.014. Hu, M., Zhang, M., & Wang, Y. (2017). Why do audiences choose to keep watching on live video streaming platforms? An explanation of dual identification framework.. ‧. Computers in Human Behavior, 75, 594–606. https://doi.org/10.1016/j.chb.2017.06.006. y. Nat. Information, M. (2017). Acceptance Model Gender Differences in Use of E-Mail : An. sit. Extension to the Technology Acceptance Model1, 21(4), 389–400.. er. io. Katz, E,. Blumler, J.G., & Gurevitch, M. (1973). American Association for Public. al. n. v i n C hSource : The PublicUOpinion Quarterly , Vol . 37 , No . Blumler and Michael Gurevitch engchi Opinion Research Uses and Gratifications Research Author ( s ): Elihu Katz , Jay G . 4 ( Winter , 1973-1974 ), pp . 509-523 Published by. Public Opinion Quarterly, 37(4), 509–523. Köprülü, O., Helvaci, İ., & Turhan, M. (2016). Role of Social Media on Purchasing Behavior of Consumers Through Digital Marketing. European Journal of Business and Social Sciences, 5(05), 21–29. Retrieved from http://www.ejbss.com/recent.aspx-/ Lee, M. K. O., Cheung, C. M. K., & Chen, Z. (2005). Acceptance of Internet-based learning medium: The role of extrinsic and intrinsic motivation. Information and Management, 42(8), 1095–1104. https://doi.org/10.1016/j.im.2003.10.007 Lim, S., Cha, S. Y., Park, C., Lee, I., & Kim, J. (2012). Getting closer and experiencing together: Antecedents and consequences of psychological distance in social media-. 37. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(45) enhanced real-time streaming video. Computers in Human Behavior, 28(4), 1365–1378. https://doi.org/10.1016/j.chb.2012.02.022 Ngai, E. W. T., Moon, K. K., Lam, S. S., Chin, E. S. K., & Tao, S. S. C. (2015). Social media models, technologies, and applications. Industrial Management & Data Systems, 115(5), 769–802. https://doi.org/10.1108/IMDS-03-2015-0075 Payne, K., Keith, M. J., Schuetzler, R. M., & Giboney, J. S. (2017). Examining the learning effects of live streaming video game instruction over Twitch. Computers in Human Behavior, 77, 95–109. https://doi.org/10.1016/j.chb.2017.08.029 Pires, K., & Simon, G. (2015). YouTube Live and Twitch : A Tour of User-Generated Live. Streaming. Systems.. MMSys. DataSet,. 1–6.. https://doi.org/10.1145/2713168.2713195. 政治大. Sangwan, S. (2005). Virtual Community Success: A Uses and Gratifications Perspective. Proceedings of the 38th Annual Hawaii International Conference on System Sciences,. 立. 00(C), 193c–193c. https://doi.org/10.1109/HICSS.2005.673. ‧ 國. 學. Tufekci, Z. (2008). Can You See Me Now? Audience and Disclosure Regulation in Online Social Network Sites. Bulletin of Science, Technology & Society, 28(1), 20–36. https://doi.org/10.1177/0270467607311484. ‧. van der Heijden, H. (2004). User Acceptance of Hedonic Systems. MIS Quarterly, 28(4),. y. Nat. 695–704.. sit. Venkatesh, V. (2000). Determinants of Perceived Ease of Use : Integrating Control ,. n. al. er. io. Intrinsic Motivation , Acceptance Model. Information System Research, 11(4), 342–365.. iv n Science U Letters,. Zandhessami, H., & Geranmayeh, P. (2014). Determinants of user acceptance of internet. Ch. banking: An empirical study. Management. engchi. 4(7), 1369–1374.. https://doi.org/10.5267/j.msl.2014.6.035. Zhang, S., Zhao, J., & Tan, W. (2008). Extending TAM for Online Learning Systems: An Intrinsic Motivation Perspective. Tsinghua Science and Technology, 13(3), 312–317. https://doi.org/10.1016/S1007-0214(08)70050-6. 38. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(46) Appendix 使用者者對於直播觀看行為調查表親愛的寶寶：您好，此份問卷主要探討直播平台使用者的持續使用動機。只需您撥出約5分鐘的時間做填寫。感謝您的協助，你所回答的每一個問題都將僅作為研究所用，以妥善保護您的個人基本資料。請安心填寫。. 第一部分：直播個人經驗. 學. ‧ 國. 立. 政治大我看直播是因為……. ‧. 請依據下列敘述依據同意程度勾選。. n. al. er. io. sit. y. Nat. 同意程度. 編. 題目. Ch. 非常. i n U. 不同. 意. engchi. 號. 不同. v. 普通. 同意. 非常同意. 意 1 2 3. 讓我感覺比較輕鬆讓我很放鬆直播是很好的休閒活動. 1. 2. 3. 4. 5. 1. 2. 3. 4. 5. 1. 2. 3. 4. 5. 39. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(47) 4. 直播讓我暫時忘卻工作、學業. 1. 2. 3. 4. 5. 1. 2. 3. 4. 5. 和其他的壓力 5. 讓我暫時遠離家庭或其他人帶來的壓力. 6. 直播讓我暫時遠離壓力或責任. 1. 2. 3. 4. 5. 7. 可以讓我短暫逃避我現在該完. 1. 2. 3. 4. 5. 政治大. 立. 成的事. 1. 2. 3. 學. 4. 5. 9. 可以讓我在沒有人陪伴的時候. 1. 2. 3. 4. 5. 1. 2. 3. 4. 5. 3. 4. 5. ‧ 國. 讓我可以不用一個人. y. Nat. 讓我覺得沒有這麼寂寞. n. al. Ch. v ni. e n g c1h i U2. 11. 看直播是一種習慣. 12. 如果不知道做什麼的時候，我. er. io. sit. 可以有人作伴 10. ‧. 8. 1. 2. 3. 4. 5. 會看直播 13. 在我無聊時，可以用來殺時間. 1. 2. 3. 4. 5. 14. 讓我在零碎的時間，有事情可. 1. 2. 3. 4. 5. 以做. 40. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(48) 第二部分：直播使用行為調查同意程度編號. 題目. 非常. 不同. 不同. 意. 普通. 同意. 非常同意. 意 1. 1 2 政治大. 在使用直播時，我認為我有. 立. 3. 4. 5. 4. 5. 4. 5. 4. 5. 在使用直播時，我認為我是這 1. 學. 2. ‧ 國. 跟其他用戶互動。 2. 3. ‧. 個直播大家庭其中的一份子。. n. al. 1. 2. 3. er. io. 在使用直播時，我覺得好像. sit. y. Nat. 3. Ch. 跟直播裡面的觀眾一同參與. engchi. i n U. v. 一件事。 4. 使用直播時，我覺得我跟大. 1. 2. 3. 多數直播用戶有差不多的想法。. 41. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(49) 使用直播時，我覺得我的想. 1. 2. 3. 4. 5. 1. 2. 3. 4. 5. 1. 2. 3. 4. 5. 學. 5. 4. 5. 4. 5. 法是跟可以跟大家分享的。 6. 使用直播時，我覺得我看事情的角度跟大家差不多. 7. 我認為在看直播時，我的行為會被直播中其他用戶影. 立. 8. ‧ 國. 響。. 政治大. 我認為在看直播時，我的行. 1. 2. 1. 2. 3. io. 會有差不多的想法. n. al. 10. Ch. y. 3. er. 我認為觀看相似直播的用戶. sit. Nat. 9. ‧. 為會影響直播中其他用戶。. e n g c1h i. 我覺得在使用直播的過程可. i n U. v. 2. 3. 4. 5. 1. 2. 3. 4. 5. 1. 2. 3. 4. 5. 以讓我獲得樂趣 11. 我覺得使用直播可以讓我感到開心. 12. 我覺得我會繼續關注我喜愛的主播. 42. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(50) 13. 我會繼續關注我喜愛主播的. 1. 2. 3. 4. 5. 1. 2. 3. 4. 5. 直播，暫時不會有其他選擇我覺得我不會繼續關注我喜愛的主播了. 第三部分：基本資料調查. 立. 政治大 1. 性別 (必填). 學. □ 男. ‧ 國 io. sit. ‧. □ 國中以下. Nat. 2. 請問您的教育程度？ (必填). y. □ 女. □ 國中 □ 高中. n. al. Ch. □ 大學. er. 14. i n U. v. e□n研究所以上 gchi. 3. 請問您的年齡？ (必填) □ 15 歲以下 □ 16─25 歲 □ 26─35 歲 □ 36─45 歲 □ 46 歲以上 4. 請問您的職業？（會再細分） □ 學生. 43. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(51) □ 資訊業 □ 軍公教 □ 服務業 □ 金融保險 □ 其他 5. 請問您的居住地區？ (必填) □ 北部 □ 中部 □ 南部 □ 東部. 學. ‧ 國. 立. 離島政 □治大 □ 其他. 6. 請問您觀看直播的頻率？ (必填) □ 每週少於 1 次. ‧. □ 每週 1─2 次. y. Nat. □ 每週 3─4 次. n. al. Ch. engchi. er. io. □ 每天. sit. □ 每週 5─6 次. i n U. v. 7. 請問您觀看打賞（送禮）的頻率？ (必填) □ 從不 □ 每週少於 1 次 □ 每週 1─2 次 □ 每週 3─4 次 □ 每週 5─6 次 □ 每天. 8. 請問您觀看打賞（送禮）的每月平均花費金額？ (選填) □ 從不送禮 44. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(52) □ 少於台幣 500 □ 台幣 500-1500 間 □ 台幣 1500-4500 間 □ 台幣 4500-15000 間 □ 台幣 15000 以上. 9. 請問您每月可支配收入約為？____________元（月收入百分比） 10. 請問您時常觀看直播的類型為？ □ 才藝（歌唱、舞蹈、脫口秀等）. 學. ‧ 國. 立. 政治大 □ 聊天談心 □ 星座命理. Nat. y. ‧. □ 遊戲電玩. n. □ 搞笑趣聞. Ch. e n□ g科技3C chi. er. io. al. sit. □ 寵物. i n U. v. □ 保養美妝 □ 運動健身. 問卷到此結束，謝謝寶寶的配合與協助，抽獎結果將會於_______直接寄信至得獎者信箱，再麻煩寶寶們注意信箱收件喔！. 45. DOI:10.6814/THE.NCCU.IMICS.011.2018.F05.

(53)