臺灣博碩士論文加值系統

資訊與科技的發達，智慧型手機在台灣人手一機，平台、裝置和網路不再是阻礙影音播放與即時傳輸的問題，使得網路直播得以普及，經由智慧型手機錄影，行動數據傳輸，直播內容可即時地傳輸到世界的每一角落，相較於過去，觀眾觀看直播的行為有了明顯的不同。創市際©曾在2016年做過調查，看過直播的台灣民眾有40%以上，而知曉網路直播服務的民眾更超過90%，並且還在逐年增加中，因此本研究試圖了解人們為什麼想看直播。
網路直播是一種由直播主發佈的即時影音媒體，因結合互動功能而帶有小型社群的特質，而人們常為娛樂而沉迷在電視、電影或影音部落格中，也會因為崇拜藝人變得盲目且瘋狂，還會因本身對媒體的觀感或期望帶來效益而影響使用媒體的意願，因此本研究提出沉浸、娛樂、社交互動與偶像崇拜四項因素，以問卷調查法收集資料，使用路徑分析法檢定其與態度、知覺價值與觀看意圖間的關係，藉以了解影響觀眾觀看直播的影響因素與途徑。
經由問卷調查，分析313份有效樣本之結果顯示，台灣民眾約有65%透過社群網站觀看直播，觀眾主要因為單純喜歡直播而觀看，而對直播的好感主要來自於直播能讓心情愉快、紓解壓力，其次則是受直播主的魅力所吸引，視性別而略有不同；女性會因欣賞直播主本身而增加對直播的好感，而男性則藉由直播當下與直播主或其他觀眾互動而增加對直播的正面態度。年輕族群較會因沉浸而喜歡直播，而較年長者則不受沉浸所影響。最後，本研究希望能對直播服務的發展略盡心意，也期許對未來探討直播的相關研究有所稗益。

With the rapid development of information technology, everyone has one or more mobile devices in Taiwan. Video real-time transferring from any platform to clients on the internet becomes simple and easy. By using the video recorder on mobile phone, Live-Stream become a popular work and all the contents can be rapidly broadcasted to everywhere in the world. The audiences obviously have different behavior than before. InsightXplorer© had done a marketing survey in 2016, 40% people had ever seen the Live-Stream, more than 90% people know that how to get the service in Taiwan. This study tries to analyze the factors of live stream video audience and actually know what their purpose are.
Live-Stream is a real-time video published by streamers, it combines interaction within a small social group. When people are addicted to TV programs, movies, and video blogs, they will blindly trust the popular leaders and become willing to use the social medias with their own consciousness and personal expectation. This study tries to analyze the factors of live stream video audience. By using the Path Analysis, we can test the relationships among flows, entertainments, social interactions, endorsements, attitudes, perceived values and intentions that we can understand how it influences to Live-Stream audiences.
The result (N=313) shows that about 65% people in Taiwan had ever seen live videos on Social Networking Site. Most of all, the audiences prefer to watch Live-Stream because they can feel relaxed by watching videos. The personal’s charms of streamers is also a important indication, but it shows some different results with gender differences. Female audiences probably like the streamers depend on what are their personal preferences, but males can increase the sense of identity by interacting with broadcaster or other audiences. Young people are flows to watch Live-streams easily, but older people are totally different. Finally, this study wants to contribute the development of Live-Stream service, and I hope it can promote some related issues in the future.

摘要 i
Abstract ii
目錄 iii
表目錄 vi
圖目錄 viii
第一章 緒論 1
1.1 研究背景 1
1.2 研究動機與目的 4
1.3 論文架構 7
1.4 研究流程 8
第二章 文獻探討 10
2.1 網路直播 10
2.1.1 直播的發展 10
2.1.2 直播的特性 11
2.1.3 直播的互動功能 12
2.1.4 直播的商業模式 14
2.1.5 直播的應用與相關研究 16
2.2 使用與滿足理論 19
2.3 沉浸理論 22
2.4 娛樂 25
2.5 社交互動 27
2.6 偶像崇拜 29
2.7 態度 31
2.8 知覺價值 34
第三章 研究方法 37
3.1 研究架構 37
3.2 研究假說 39
3.2.1 沉浸對態度及知覺價值之影響關係 39
3.2.2 娛樂對態度、知覺價值及沉浸之影響關係 40
3.2.3 社交互動對態度及知覺價值之影響關係 41
3.2.4 偶像崇拜對態度、知覺價值及社交互動之影響關係 42
3.2.5 態度對觀看意圖之影響關係 43
3.2.6 知覺價值對觀看意圖之影響關係 43
3.3 問卷設計 44
3.4 資料分析方法 45
3.4.1 敘述性統計 46
3.4.2 信度分析 46
3.4.3 效度分析 47
3.4.4 因素分析 48
3.4.5 結構方程模型 48
第四章 結果分析與討論 50
4.1 敘述性統計 50
4.2 信度分析 52
4.3 效度分析 53
4.4 模型適配度 56
4.5 研究假說檢定 58
4.6 直接影響、間接影響與總影響 60
4.7 性別差異比較 62
4.7.1 女性樣本分析 63
4.7.2 男性樣本分析 66
4.7.3 性別差異比較結果 69
4.8 年齡差異比較 70
4.8.1 年齡25歲以下樣本分析 71
4.8.2 年齡26歲以上樣本分析 74
4.8.3 年齡差異比較結果 77
4.9 社群網站樣本分析 78
第五章 結論與建議 83
5.1 研究結論 83
5.1.1 沉浸對態度與知覺價值之關係 83
5.1.2 娛樂對態度、知覺價值與沉浸之關係 85
5.1.3 社交互動對態度與知覺價值之關係 85
5.1.4 偶像崇拜對態度、知覺價值與社交互動之關係 87
5.1.5 態度與知覺價值對直播觀看意圖之關係 88
5.1.6 影響觀眾觀看直播意圖的主要影響途徑 89
5.2 管理意涵與研究貢獻 89
5.2.1 學術性管理意涵與研究貢獻 89
5.2.2 實務性管理意涵與研究貢獻 90
5.3 研究限制與未來研究方向 91
參考文獻 93
附錄 正式問卷 112

ETNEWS新閱雲 (民106)。YouTube醒了！推出手機直播，還加入「打賞」功能。取自 http://www.ettoday.net/news/20170208/862518.htm
INSIDE (民105)。新眼球爭奪戰開打，你對「網路直播」知多少？。取自 https://www.inside.com.tw/2016/05/20/broadcasting-live-video-online
SDK.cn (民105)。中國直播為何如此火爆？16個觀察告訴你真相。取自 https://sdk.cn/news/5359
TVBS (民104)。想玩臉書直播？「藍色勾勾」先過3門檻。取自 http://news.tvbs.com.tw/life/615911
Wikipedia (民106)。Google Buzz。取自 https://zh.wikipedia.org/wiki/Google_Buzz
Wikipedia (民106)。Twitch。取自 https://zh.wikipedia.org/wiki/Twitch
Yahoo數位行銷專欄(民105)。2016影音市場趨勢：直播帶動全球影音成長契機。取自 http://yahoo-emarketing.tumblr.com/post/149692242936/yahootv302
Youtube直播頻道 (民106)。就一下下，露臉??。取自 https://www.youtube.com/watch?v=H5AvVkukqZA
中國產業發展研究網 (民106)。2017年中國直播平台行業格局分析。取自 http://www.chinaidr.com/tradenews/2017-03/111167.html
中國產業發展研究網 (民106)。2017年中國直播行業市場規模分析。取自 http://www.chinaidr.com/tradenews/2017-03/111168.html
孔令信 (民105)。318學運帶動的媒體革命-夾腳拖與iPad網路直播模式的反思。傳播研究與實踐，6(1)，229-150。
方雅瑩 (民105)。線上直播演唱會之應用研究(未出版碩士論文)。國立臺灣師範大學，臺北市
王春? (民105)。以使用與滿足理論探討網路遊戲直播平台 Twitch TV 粉絲的持續使用意圖(未出版碩士論文)。南臺科技大學，臺南市。
朱光弘 (民100)。網路直播下的抗爭運動-以野草莓運動為例(未出版碩士論文)。玄奘大學，新竹市。
艾瑞諮詢(民105)。2016年中國移動直播用戶洞察報告。取自 http://report.iresearch.cn/wx/report.aspx?id=2708
何崇瑋 (民105)。人的價值觀對觀看遊戲直播串流動機因素之研究：以Twitch為例(未出版碩士論文)。國立雲林科技大學，雲林縣。
吳迪、何璇 (民99)。微博用戶的使用與滿足訴求。新媒體。取自 http://www.xzbu.com/7/view-2950526.htm
李城忠 (民100)。應用統計學 SPSS & AMOS 範例分析完全手冊 第2版。新北市：新文京開發。
招聘女主播網(民104)。中國互聯網首份網絡主播數據報告。取自 http://www.zpnzb.com/content-9-1522-1.html
林永鑫、黃耀賢、林奎伻、楊濠鴻 (民105)。台灣名人經營粉絲專頁成功因素之研究-以Facebook為例。創新與管理，12(3)，25-46。
洪輝勝 (民99)。探討網站之沉浸經驗、消費者價值與忠誠度關係之研究-以社交網絡服務為例(未出版碩士論文)。朝陽科技大學，臺中市。
胡欣慧、王若帆 (民99)。台灣觀光代言人對觀光客來台旅遊態度及意願之影響。觀光休閒學報，16(2)，117-137。
唐緒軍 (民106)。新媒體藍皮書 中國新媒體發展報告No.8（2017）。中國社會科學院 社會科學文獻出版社。取自 http://www.ssap.com.cn/c/2017-06-23/1056761.shtml
財團法人台灣網路資訊中心 (TWNIC) (民105)。2016年台灣寬頻網路使用調查報告。取自https://www.twnic.net.tw/download/200307/20160922e.pdf
張峻維 (民104)。獎勵對於持續使用行為之分析-以網路影音直播平台為例(未出版碩士論文)。國立臺中科技大學，臺中市。
曹文瑜、林政坤、楊惠貞 (民98)。影響網路直播持續收看意圖相關因素之研究。企業管理學報，81，107-129。
梁定澎 (民101)。資訊管理理論。新北市：前程文化。
速途研究院 (民105)。2017年上半年直播市场用户调研报告。取自 http://www.sootoo.com/content/672233.shtml
陳佑好 (民105)。運動賽事線上直播服務屬性偏好之研究-以聯合分析法探討(未出版碩士論文)。國立體育大學，桃園市。
陳君毅 (民105)。即時串流直播平台Twitch.tv之使用與滿足研究(未出版碩士論文)。國立臺灣師範大學，臺北市。
陳秀娟(譯) （民87）。生命的心流：追求忘我專注的圓融生活。臺北市：天下。
陳俊成 (民105)。線上遊戲與遊戲直播消費行為之研究(未出版碩士論文)。朝陽科技大學，臺中市。
陳威珞 (民101)。Justin TV網路影音直播平台使用行為研究(未出版碩士論文)。國立中正大學，嘉義縣。
陳建文、吳紹榮、余姵歆、袁綾 (民104)。Facebook 粉絲專頁對網路持續使用行為意圖之影響：以使用與滿足理論與社會影響觀點。朝陽商管評論，14(S)，19-38。
陳建銘 (民104)。遊戲直播網站忠誠度與持續使用意圖之研究：以Twitch TV為例(未出版碩士論文)。國立東華大學，花蓮縣。
陳竑宇 (民105)。線上遊戲Twitch直播平台之展演行為與社群認同(未出版碩士論文)。國立臺灣藝術大學，新北市。
陳虹吟 (民104)。觀看遊戲線上直播的動機與結果(未出版碩士論文)。輔仁大學，新北市。
陳婷玉、王舜偉 (民95)。愚昧無知或享受參與？---廣播賣藥節目的閱聽人分析。傳播管理研究，5(2)，1-36。
陳慶峰（民90）。從心流理論探討線上遊戲參與者之網路使用行為(未出版碩士論文)。私立南華大學，嘉義縣。
創市際市場研究顧問公司 (民105)。創市際雙週刊 第68期。取自 http://www.ixresearch.com/reports/創市際雙週刊第六十八期-20160801/
創市際市場研究顧問公司 (民105)。創市際雙週刊 第71期。取自 http://www.ixresearch.com/reports/創市際雙週刊第七十一期-20160919/
創市際市場研究顧問公司 (民106)。創市際2017合作專題一：台灣直播市場『台灣網友直播看什麼？』調查。取自 http://www.ixresearch.com/news/news_07_06_17
程宣銘 (民105)。影音直播平台使用者持續使用意圖之研究(未出版碩士論文)。國立清華大學，新竹市。
黃立文 (民87)。網路使用的快感與神迷—遊戲理論與網路瀏覽行為支初探。台灣學術網路一九九八研討會。高雄：中山大學。
黃露葎 (民97)。影音部落格沉浸與惠顧意圖之研究(未出版碩士論文)。國立台北大學，新北市。
新華網 (民104)。愛奇藝1億彈幕”玩兒壞”央視羊年春晚。取自 http://news.xinhuanet.com/ent/2015-02/25/c_127516713.htm
經濟部商業司(民106)。經濟部商業司商工登記資料。取自 http://findbiz.nat.gov.tw/fts/query/QueryBar/queryInit.do
詹蕙華 (民99)。以沉浸理論探討交友網站使用者動機與參與行為關係(未出版碩士論文)。台北科技大學，臺北市。
資策會產業情報研究所(MIC) (民103)。網路直播電視服務發展趨勢分析。取自 http://mic.iii.org.tw/aisp/reports.aspx?id=CDOC20141031011
資策會產業情報研究所(MIC) (民105)。2017年19歲以下網友潛藏巨大消費力量。取自 https://mic.iii.org.tw/IndustryObservations_PressRelease02.aspx?sqno=449
資策會產業情報研究所(MIC) (民106)。【直播大調查系列一】網友最愛Facebook、Youtube、17直播。https://mic.iii.org.tw/IndustryObservations_PressRelease02.aspx?sqno=475

資策會產業情報研究所(MIC) (民106)。【直播大調查系列二】31.3％網友追蹤直播主 15％追蹤者花錢打賞。取自 https://mic.iii.org.tw/IndustryObservations_PressRelease02.aspx?sqno=476
電腦王阿達 (民105)。沒有藍勾勾的照過來 臉書全面開放粉絲團直播功能。取自 https://www.kocpc.com.tw/archives/67667
億邦動力網訊 (民105)。漢子太少！淘寶達人直播男女比例1:24。取自 http://www.ebrun.com/20160725/184195.shtml
劉小紅 (民105)。明星網絡直播的受眾心理及行為研究。新聞研究導刊，7(21)，266-267。
數位時代 (民104)。除了MeerKat! 你應該要知道的台灣直播業5大關鍵。取自 https://www.bnext.com.tw/article/35815/BN-2015-03-31-182345-40
數位時代 (民104)。網路直播超展開，大吸眼球。取自 https://www.bnext.com.tw/article/35911/BN-2015-04-09-153234-36
數位時代 (民104)。藝人黃立成的話題直播App《17》是翻轉世界，還是破壞社會風俗?。取自 https://www.bnext.com.tw/article/37473/BN-2015-09-23-222149-109
數位時代 (民105)。台灣直播平台大點兵。取自 https://www.bnext.com.tw/article/41959/live-platforms-in-taiwan
數位時代 (民106)。直播平台前撲後繼，贏家可能跟你想得不一樣。取自 https://www.bnext.com.tw/article/42897/taiwan-live-streaming-2017
蔡政修 (民105)。Twitch在台灣的接受度與收入流研究(未出版碩士論文)。世新大學，臺北市。
鄭宇君、陳百齡 (民105)。探索線上公眾即時參與網絡化社運-以台灣318運動為例。傳播研究與實踐，6(1)，117-150。
鄭佳興 (民106)。臉書直播主的互動模式與印象管理之研究(未出版碩士論文)。世新大學，臺北市。
鄭賀文 (民105)。影響Twitch實況主持續開台意圖因素之研究：自我決定理論觀點。銘傳大學，臺北市。
穆毅 (民105)。孤獨與狂歡：基于網絡直播用戶的心理和行為分析。新聞研究導刊，7(22)，67-68。
蕭文龍 (民105)。統計分析入門與應用：SPSS中文版+SmartPLS 3(PLS_SEM)。臺北市：碁峰資訊。
頭條財經網(民106)。【互聯網PLUS】Up Live真人騷平台 當紅主播月入七萬。取自 http://hdfin.stheadline.com/owealth_content.php?nid=21171
龍裕鴻 (民105)。我播故我在：網路影音直播主之對話性探討(未出版碩士論文)。國立中山大學，高雄市。
薛璐 (民102)。受眾對名人微博的評論-使用與滿足。中國傳媒科技。取自 http://lunwen.nangxue.com/gongxue/tongxinxue/201310/1382252477.html
蘇冠諺 (民105)。影響體育賽事直播平台持續使用意圖因素之研究(未出版碩士論文)。國立中正大學，嘉義縣。
蘋果日報 (民103)。亞馬遜291億買twitch 搶5千萬玩家商機 氣走Google。取自 http://www.appledaily.com.tw/appledaily/article/headline/20140827/36047736/
蘋果日報 (民106)。各路名人齊聚告別式 送豬哥亮最後一程。取自 http://www.appledaily.com.tw/realtimenews/article/new/20170620/1143007/

Ajzen, I. (1985). From intentions to actions: A theory of planned behavior, In Springer series in social psychology, Kuhl J., & Beckman J. (Eds.). Berlin: Springer, 11-39.
Ajzen, I. (1991). The theory of planned behavior, Organizational Behavior and Human Decision Processes, 50(2), 179-211.
Akman, I., & Mishra, A. (2015). Sector diversity in Green Information Technology practices: Technology Acceptance Model perspective. Computers in Human Behavior, 49, 477-486.
Allameh, S. M., Pool, J. K., Jaberi, A., Salehzadeh, R., & Asadi, H. (2015). Factors influencing sport tourists’ revisit intentions - The role and effect of destination image, perceived quality, perceived value and satisfaction. Asia Pacific Journal of Marketing and Logistics, 27(2), 191-207.
American Psychological Association(APA), American Educational Research Association(AERA), National Council on Measurement in Education(NCME) (1999). Standards for Educational and Psychological Testing. Washington: Author.
Ang, C. S., Talib, M. A., Tan, K. A., Tan, J. P., & Yaacob, S. N. (2015). Understanding computer-mediated communication attributes and life satisfaction from the perspectives of uses and gratifications and self-determination. Computers in Human Behavior, 49, 20-29.
Ayeh, J. K. (2015). Travellers’ acceptance of consumer-generated media: An integrated model of technology acceptance and source credibility theories. Computers in Human Behavior, 48, 173-180.
Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the academy of marketing science, 16(1), 74-94.
Bartsch, A. (2012). Emotional gratification in entertainment experience: Why viewers of movies and television series find it rewarding to experience emotions. Media Psychology, 15(3), 267-302.
Bentler, P. M. (1995). EQS: Structural equations program manual. Encino, CA: Multivariate Software Inc.
Bosshart, L., & Macconi, I. (1998). Defining "entertainment". Communication Research Trends, 18(3), 3-6.
Boyle, E. A., Connolly, T. M., Hainey, T., & Boyle, J. M. (2012). Engagement in digital entertainment games: A systematic review. Computers in Human Behavior, 28(3), 771-780.
Broekhuizen, T., & Hoffmann, A. (2012). Interactivity Perceptions and Online Newspaper Preference. Journal of Interactive Advertising, 12(2), 29-43.
Bründl, S., & Hess, T. (2016). Why Do Users Broadcast? Examining Individual Motives and Social Capital on Social Live Streaming Platforms. Proceeding of the 20th Pacific Asia Conference on Information Systems (PACIS), 332. Chiayi, Taiwan.
Bründl, S., Matt, C., & Hess, T. (2017). Consumer Use Of Social Live Streaming Services: The Influence Of Co-Experience And Effectance On Enjoyment. Proceedings of the 25th European Conference on Information Systems (ECIS), (pp. 1775-1791). Guimarães, Portugal.
Chan, K., Ng, Y. L., & Luk, E. K. (2013). Impact of celebrity endorsement in advertising on brand image among Chinese adolescents. Young Consumers, 14(2), 167-179.
Chang, C. C. (2013). Examining users' intention to continue using social network games: A flow experience perspective. Telematics and Informatics, 30(4), 311-321.
Chang, Y. P. & Zhu, D. H. (2012). The role of perceived social capital and flow experience in building users' continuance intention to social networking sites in China. Computers in Human Behavior, 28(3), 995-1001.
Chen, C. W., Yu, P. H., & Li, Y. J. (2016). Understanding Group-Buying Websites Continuous Use Behavior: A Use and Gratifications Theory Perspective. Journal of Economics and Management,12(2), 177-204.
Cheung, M. F. Y., & To, W. M. (2016). Service co-creation in social media: An extension of the theory of planned behavior. Computers in Human Behavior, 65, 260-266.
Chi, H., Yeh, H. R., & Tsai, Y. C. (2011). The Influences of Perceived Value on Consumer Purchase Intention: The Moderating Effect of Advertising Endorser. Journal of International Management Studies, 6(1), 92-97.
Chiang, H. S. (2013), Continuous usage of social networking sites, The effect of innovation and gratification attributes. Online Information Review, 37(6), 851-871.
Chiua, Y. K. & Lin, C. Y. (2012). The Influence of Spokes-Characters on Consumer Patronage Intention. Asia Pacific Management Review, 17(4), 421-435.
Chu, C. W., & Lu, H. P. (2007). Factors influencing online music purchase intention in Taiwan - An empirical study based on the value-intention framework. Internet Research, 17(2), 139-155.
Cocosila, M., & Igonor, A. (2015). How important is the "social" in social networking? A perceived value empirical investigation. Information Technology & People, 28(2), 366-382.
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297-334.
Csikszentmihalyi M., & LeFevre J. (1989). Optimal experience in work and leisure. Journal of Personality and Social Psychology, 56(5), 815-822.
Csikszentmihalyi, M. (1975). Beyond Boredom and Anxiety: Experiencing Flow in Work and Play, 25th Anniversary Edition. San Franciso: Jossey-Bass Publishers.
Csikszentmihalyi, M., & Csikszentmihalyi, I. (1988). Optimal experience: Psychological Studies of Flow in Consciousness. New York: Cambridge University Press.
Curras-Perez, R., Ruiz-Mafe, C., & Sanz-Blas, S. (2014). Determinants of user behaviour and recommendation in social networks. Industrial Management & Data Systems, 114(9), 1477-1498.
Dhir, A., Pallesen, S., Torsheim, T., & Andreassen C. A. (2016). Do age and gender differences exist in selfie-related behaviours?. Computers in Human Behavior, 63, 549-555.

Dzisah, W. E., & Ocloo, C. E. (2013). Celebrity endorsement and consumer buying behaviour; enhancing the promotion fun ction of marketing in the central business area of accra, the capital city of ghana. 4th Annual International Business Conference, (pp. 254-272). Saint Leo University, Saint Leo, US.
Edge, N. (2013). Evolution of the gaming experience: Live video streaming and the emergence of a new web community. The Elon Journal of Undergraduate Research in Communications, 4(2), 33-39.
Ericsson ConsumerLab (2016). Live Streaming Joins Social Media. Ericsson Mobility Report, Nov 2016. Retrieved from https://www.ericsson.com/assets/local/mobility-report/documents/2016/emr-november-2016-live-streaming-joins-social-media.pdf
Falk, A., Fischbacher, U., & Gachter, S. (2013). Living in two neighborhoods - Social interaction effects in the laboratory. Economic Inquiry, 51(1), 563-578.
Falk, R. F., & Miller, N. B. (1981), A primer for soft modeling. Akron, US: The University of Akron Press.
Fett, A. K., Shergill, S. S., Joyce, D. W., Riedl, A., Strobel, M., Gromann, P. M., & Krabbendam, L. (2012). To trust or not to trust: The dynamics of social interaction in psychosis. Brain, 135(3), 976-984.
Fishbein, M., & Ajzen, I. (1980). Understanding Attitudes and Predicting Social Behavior. Englewood Cliffs, N.J.: Prentice-Hall.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable and measurement error. Journal of Marketing Research, 18(1), 39-50.
George, D., & Mallery, M. (2003). Using SPSS for Windows step by step: a simple guide and reference. Boston: Allyny & Bacon.
Ghani, J. A., & Deshpande, S. P. (1994). Task Characteristics and the Experience of Optimal Flow in Human-Computer Interaction. The Journal of Psychology, 128(4), 381-391.
Gorsuch, R. L. (1983). Factor Analysis (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates.
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2010). Multivariate data analysis 7th Ed. Englewood Cliffs, NJ: Prentice Hall.
Hamari, J., & Sjöblom, M. (2017). What is eSports and why do people watch it?. Internet Research, 27(2), 211-232.
Hamari, J., Shernoff, D. J., Rowe, E., Coller, B., Asbell-Clarke, J., & Edwards, T. (2016). Challenging games help students learn: An empirical study on engagement, flow and immersion in game-based learning. Computers in Human Behavior, 54, 170-179.
Hamilton, W. A., Garretson, O., Kerne, A. (2014). Streaming on Twitch: Fostering Participatory Communities of Play within Live Mixed Media. CHI '14 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 1315-1324). Toronto, Ontario, Canada.
Hoffman, D. L., & Novak, T. P. (1996). Marketing in Hypermedia Computer-Mediated Environments: Conceptual Foundations. Journal of Marketing, 60(3), 50-68.
Hong, J. C., Lin, P. H., & Hsieh, P. C. (2017). The effect of consumer innovativeness on perceived value and continuance intention to use smartwatch. Computers in Human Behavior, 67, 264-272.
Hsiao, C. H., Chang, J. J., & Tang, K. Y. (2016). Exploring the influential factors in continuance usage of mobile social Apps: Satisfaction, habit, and customer value perspectives. Telematics and Informatics, 33(2), 342-355.
Hsu, C. L. & Lin, J. C. (2016). Effect of perceived value and social influences on mobile app stickiness and in-app purchase intention. Technological Forecasting & Social Change, 108(4), 42-53.
Hsu, C. L., Chang, K. C., & Chen, M. C. (2012). Flow experience and internet shopping behavior: Investigating the moderating effect of consumer characteristics. Systems Research and Behavioral Science, 29(3), 317-332.
Hsu, C. L., Chang, K. C., & Chen, M. C. (2012). The impact of website quality on customer satisfaction and purchase intention: perceived playfulness and perceived flow as mediators. Information Systems and e-Business Management, 10(4), 549-570.
Hsu, M. H., Chang, C. M., Lin, H. C., & Lin, Y. W. (2015). Determinants of continued use of social media: the perspectives of uses and gratifications theory and perceived interactivity. Information Research, 20(2). Retrieved from http://www.informationr.net/ir/20-2/paper671.html#.WW5F_op-Xx4
Hu, M., Zhang, M., & Yu, W. (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.
Huang, L. C., & Shiau, W. L. (2015). Why do people use microblogs? An empirical study of Plurk. Information Technology & People, 28(2), 281-303.
Huang, Y. A., Lin, C., Su, H. J., & Tung, M. L. (2015). I worship, so I download? Idol worship, music purchase and piracy by young consumers in Taiwan. Asia Pacific Journal of Marketing and Logistics, 27(1), 99-12.
Hung, K. (2014). Why Celebrity Sells: A Dual Entertainment Path Model of Brand Endorsement. Journal of Advertising, 43(2), 155-166.
Hung, S. Y., Tsai, J. C., & Chou, S. T. (2016). Decomposing perceived playfulness: A contextual examination of two social networking sites. Information & Management, 53(6), 698-716.
Hung, W. T., Tsang, S. S., & Liu, H. Y. (2010). Website Characteristics and the Impact of User Perceived Value on User Behavior in Web 2.0. Academy of Information and Management Sciences Journal, 13(1), 1-18.
Ilicic, J., & Webster, C. M. (2011). Effects of multiple endorsements and consumer–celebrity attachment on attitude and purchase intention. Australasian Marketing Journal, 19(4), 230-237.
Jaegher H. D., Paolo, E. D., & Gallagher, S. (2010). Can social interaction constitute social cognition?. Trends in Cognitive Sciences, 14(10), 441-447.
Jöreskog, K. G., & Sörbom, D. (1996). LISREL 8: User's reference guide. Scientific Software International. Chicago: Scientific Software International.

Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, 39(1), 31-36.
Katz, E., Blumler, J. G., & Gurevitch, M. (1974). Uses and Gratifications Research. The Public Opinion Quarterly, 37(4), 509-523.
Kaur, P., Dhir, A., Chen, S., & Rajala, R. (2016). Flow in context: Development and validation of the flow experience instrument for social networking. Computers in Human Behavior, 59, 358-367.
Kaytoue, M., Silva, A., Cerf, L., Meira, W., & Raïssi, C. (2012). Watch me playing, i am a professional: A first study on video game live streaming. WWW '12 Companion Proceedings of the 21st International Conference on World Wide Web, (pp. 1181-1188). Lyon, France.
Kezer, M., Sevi, B., Cemalcilar, Z., & Baruh, L. (2016). Age differences in privacy attitudes, literacy and privacy management on Facebook. Cyberpsychology: Journal of Psychosocial Research on Cyberspace, 10(1), article 2.
Khatri, P. (2006). Celebrity endorsement: A strategic promotion perspective. Indian Media Studies Journal, 1(1), 25-37.
Kim, B. (2011). Understanding Antecedents of Continuance Intention in Social-Networking Services. Cyberpsychology, behavior and social networking, 14(4), 199-205.
Kim, E., Lee, J. A., Sung, A., & Choi, S. M. (2016). Predicting selfie-posting behavior on social networking sites: An extension of theory of planned behavior. Computers in Human Behavior, 62, 116-123.
Kim, H., & Niehm, L. S. (2009). The Impact of Website Quality on Information Quality, Value, and Loyalty Intentions in Apparel Retailing. Journal of Interactive Marketing, 23(3), 221-233.
Kim, J., & Song, H. (2016). Celebrity's self-disclosure on Twitter and parasocial relationships: A mediating role of social presence. Computers in Human Behavior, 62, 570-577.

Kim, S., & Yoo, S. J. (2016). Age and Gender Differences in Social Networking: Effects on South Korean Students in Higher Education, In Social Networking and Education, Issa, T., Isaias, P., & Kommers, P. (Eds.). Switzerland: Springer, 69-82.
Kim, Y. H., Kim, D. J., & Wachter, K. (2013). A study of mobile user engagement (MoEN): Engagement motivations, perceived value, satisfaction, and continued engagement intention. Decision Support Systems, 56(35), 361-370.
Lee, M. R., Yen, D. C., & Hsiao, C. Y. (2014). Understanding the perceived community value of Facebook users. Computers in Human Behavior, 35, 350–358.
Lemay, D. J., Doleck, T., & Bazelais, P. (2017). “Passion and concern for privacy” as factors affecting snapchat use: A situated perspective on technology acceptance. Computers in Human Behavior, 75, 264-271.
Li, H., Liu, Y., Xu, X., Heikkilä, J., & van der Heijden, H. (2015). Modeling hedonic is continuance through the uses and gratifications theory: An empirical study in online games. Computers in Human Behavior, 48, 261-272.
Lin, C. A., & Kim, T. (2016). Predicting user response to sponsored advertising on social media via the technology acceptance model. Computers in Human Behavior, 64, 710-718.
Lu, Y., Zhou, T., & Wang, B. (2009). Exploring Chinese users’ acceptance of instant messaging using the theory of planned behavior, the technology acceptance model, and the flow theory. Computers in Human Behavior, 25(1), 29-39.
Lunney, A., Cunningham, N. R., & Eastin, M. S. (2016). Wearable fitness technology: A structural investigation into acceptance and perceived fitness outcomes. Computers in Human Behavior, 65, 114-120.
Luo, M. M., & Remus, W. (2014). Uses and gratifications and acceptance of Web-based information services: An integrated model. Computers in Human Behavior, 38, 281-295.
Luqman, A., Cao, X., Ali, A., Masood, A., Yu, L. (2017). Empirical investigation of Facebook discontinues usage intentions based on SOR paradigm. Computers in Human Behavior, 70, 544-555.
McQuail, D. (2010). Mass communication theory: an introduction (pp. 420-430). Los Angeles, CA: SAGE.
Mouakket, S. (2015). Factors influencing continuance intention to use social network sites: The Facebook case. Computers in Human Behavior, 53, 102-110.
Mouakket, S. (2017). The role of personality traits in motivating users' continuance intention towards Facebook: Gender differences. Journal of High Technology Management Research, In Press, Corrected Proof, 1-17.
Mulaik, S. A., James, L. R., Van Alstine, J., Bennet, N., Lind, S., & Stilwell, C. D. (1989), Evaluation of Goodness-of-Fit Indices for Structural Equation Models, Psychological Bulletin, 105(3), 430-445.
Nascimento, G., Ribeiro, M., Cerf, L., Cesário, N., Kaytoue, M., Raïssi, C., Vasconcelos, T., & Meira W. (2014). Modeling and analyzing the video game Live-Streaming community. Web Congress (LA-WEB), 2014 9th Latin American. Ouro Preto, Brazil.
Nelson, O., Tunji, O., & Gloria A. (2012). The dysfunctional and functional effect of celebrity endorsement on brand patronage. Online Journal of Communication and Media Technologies, 2(2), 141-152.
Novak, T. P., Hoffman, D, L., & Yung, Y. F. (2000). Measuring the Customer Experience in Online Environments: A Structural Modeling Approach. Marketing Science, 1(19), 22-42.
Novak, T. P., Hoffman, D. L. & Yung, Y. F. (1998). Modeling the Structure of the Flow Experience Among Web Users. Marketing Science and the Internet Mini- Conference. MIT, Cambridge, MA, US.
Nunnally, J. C. (1978). Psychometric Theory. New York: McGraw Hill.
Nyaseda, C. (2010). The Effectiveness of Celebrity Endorsed Advertising: A Kenyan Perspective. Graduate Faculty of the Marshall Goldsmith School of Management Alliant International University.
Ohanian, R. (1991). The Impact of Celebrity spokespersons’ Perceived Image on Consumers’ Intention to purchase. Journal of Advertising Research, 31(1), 46-53.
Oztekin, C., Teksöz, G., Pamuk, S., Sahin, E., & Kilic, D. S. (2017). Gender perspective on the factors predicting recycling behavior: Implications from the theory of planned behavior. Waste Management, 62, 290-302.
Phua, J., Jin, S. V., & Kim, J. J. (2017). Uses and gratifications of social networking sites for bridging and bonding social capital: A comparison of Facebook, Twitter, Instagram, and Snapchat. Computers in Human Behavior, 72, 115-122.
Punyanunt-Carter, N. M., Cruz, J. J. D, L., & Wrench, J. S. (2017). Investigating the relationships among college students' satisfaction, addiction, needs, communication apprehension, motives, and uses & gratifications with Snapchat. Computers in Human Behavior, 75, 870-875.
Reinecke, L., Vorderer, P., & Knop, K. (2014). Entertainment 2.0? the role of intrinsic and extrinsic need satisfaction for the enjoyment of facebook use. Journal of Communication, 64(3), 417-438.
Rosengren, K. E. (1974). Uses and gratification: A paradigm outlined, In Blumler , J. G., Katz, E. (Eds.)., The Uses of Mass Communications: Current Perspectives on Gratifications Research, Beverly Hills: Sage, 269-286.
Scheibe, K., Fietkiewicz, K. J., & Stock, W. G. (2016). Information Behavior on Social Live Streaming Services. Journal of Information Science Theory and Practice, 4(2), 6-20.
Shafiq, R., Raza, I., & Zia-ur-Rehman, M. (2011). Analysis of the factors affecting customers’ purchase intention: The mediating role of perceived value. African Journal of Business Management, 5(26), 10577-10585.
Shen, K., & Khalifa, M. (2010). Facebook Usage Among Arabic College Students: Preliminary Findings on Gender Differences. International Journal of e-Business Management, 4(1), 53-65.
Shi, N., Lee, M. K., Cheung, C. M., & Chen, H. (2010). The Continuance of Online Social Networks: How to Keep People Using Facebook?. Proceedings of the 43rd Hawaii International Conference on System Sciences - 2010. Honolulu, HI, USA.

Sjöblom, M., & Hamari, J. (2017). Why do people watch others play video games? An empirical study on the motivations of Twitch users. Computers in Human Behavior, 75, 985-996.
Soltani, I., & Gharbi, J. E. (2008). Determinants and Consequences of the Website Perceived Value. Journal of Internet Banking and Commerce, 13(1), 1-13.
Su, Y. S., Chiang, W. L., Lee, J. C., & Chang, H. C. (2016). The effect of flow experience on player loyalty in mobile game application. Computers in Human Behavior, 63, 240-248.
Tariq, J., Sajjad, A., Usman, A., & Amjad, A. (2017). The role of intentions in facebook usage among educated youth in Pakistan: An extension of the theory of planned behavior. Computers in Human Behavior, 74, 188-195.
Thorburn, E. D. (2014). Social Media, Subjectivity, and Surveillance: Moving on From Occupy, the Rise of Live Streaming Video. Communication and Critical/Cultural Studies, 11(1), 52-63.
Tucker, L. R., & Lewis, C. (1973). A reliability coefficient for maximum likelihood factor analysis. Psychometrika, 38(1), 1-10.
Van Noort, G., Voorveld, H. A. M. & Van Reijmersdal, E. A. (2012). Interactivity in Brand Web Sites: Cognitive, Affective, and Behavioral Responses Explained by Consumers' Online Flow Experience. Journal of Interactive Marketing, 26(4), 223-234.
Van Schaik, P., Martin, S. & Vallance, M. (2012). Measuring flow experience in an immersive virtual environment for collaborative learning. Journal of Computer Assisted Learning, 28(4), 350-365
Vorderer, P., Klimmt, C., & Ritterfeld, U. (2004). Enjoyment: At the heart of media entertainment. Communication Theory, 14(4), 388-408.
Vosmeer, M., Ferri, G., Schouten, B., & Rank, S. (2016). Changing Roles in Gaming: Twitch and new gaming audiences. Proceedings of 1st International Joint Conference of DiGRA and FDG. Dundee, Scotland, UK.
Wang, C. C., Chen, C. T., Yang, S. C., & Farn, C. K. (2009). Pirate or Buy? The Moderating Effect of Idolatry. Journal of Business Ethics, 90(1), 81-93.
Wang, K. (2015). Determinants of mobile value-added service continuance: The mediating role of service experience. Information & Management, 52(3), 261-274.
Wang, S. W., Kao, G. H., & Ngamsiriudom, W. (2017). Consumers' attitude of endorser credibility, brand and intention with respect to celebrity endorsement of the airline sector. Journal of Air Transport Management, 60(2), 10-17.
Webster, J., Trevino, L. K., & Ryan, L. (1993). The Dimensionality and correlates of flow in human-computer interaction. Computers in Human Behavior, 9(4), 411-426.
Wei, K. K., & Wu, Y. L. (2013). Measuring the impact of celebrity endorsement on consumer behavioural intentions: a study of Malaysian consumers. International Journal of Sports Marketing & Sponsorship, 14(3), 2-22.
Wei, P. S., & Lu, H. P. (2014). Why do people play mobile social games? An examination of network externalities and of uses and gratifications. Internet Research, 24(3), 313-331.
Wirth, W., Hofer, M., & Schramm, H. (2012). Beyond pleasure: exploring the eudaimonic entertainment experience. Human Communication Research, 38(4), 406-428
Wu, B., & Chen, X. (2017). Continuance intention to use MOOCs: Integrating the technology acceptance model (TAM) and task technology fit (TTF) model. Computers in Human Behavior, 67, 221-232.
Wu, H. L. (2009). An Integrated Framework of SNS Users’ Motivations. Proceedings of the Fifteenth Americas Conference on Information Systems (AMCIS). San Francisco, California.
Yu, J., Zo, H., Choi, M. K., & Ciganek, A. P. (2013). User acceptance of location-based social networking services - An extended perspective of perceived value. Online Information Review, 37(5), 711-730.


Zhang, C. B., Li, Y. N., Wu, B., Li, D. J. (2017). How WeChat can retain users: Roles of network externalities, social interaction ties, and perceived values in building continuance intention. Computers in Human Behavior, 69, 284-293.
Zhou, T., & Lu, Y. (2011). Examining mobile instant messaging user loyalty from the perspectives of network externalities and flow experience. Computers in Human Behavior, 27(2), 883-889.