直播中的關係賭局:觀眾是否甘願冒險?觀眾的風險傾向在不同領導風格直播主與彼此關係建立的調節作用

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直播中的關係賭局:觀眾是否甘願冒險?觀眾的風險傾向在不同領導風格直播主與彼此關係建立的調節作用

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摘要(中)

常常會有很多人好奇為甚麼有人想要花時間去觀看網路直播，但在這個新興時代，網路直播已經成為一個常見的社會現象，直播未來的趨勢可能會逐漸傾向於直播加上垂直行業(例如：教育直播、電商直播等)，或是直播相關顧問團隊也會因此興起，負責規劃直播的生態圈，因此「直播」值得我們更加深入地去探討。
本研究主要探討觀眾的「風險傾向」在直播主不同的「領導風格」下，「直播主與觀眾之間的關係」，本研究參考過去的文獻，並採取實驗法與問卷法來進行研究，以台灣直播主與其觀眾群為研究對象，觀眾在觀看直播時會不會因為個人不同的「風險傾向」，進而去調節「不同領導風格直播主與觀眾的關係」?
當雙方在建立關係時，直播主永遠不會知道這段關係最後會變成如何，這儼然就像是在一個賭局一樣，必須從不確定中去尋找答案。
研究結果顯示在實驗法下，觀眾的「風險傾向」會調節「直播主領導風格與觀眾的情感性關係和混和性關係」而觀眾的「風險傾向」不會調節「直播主領導風格與觀眾的工具性關係；在問卷法下，觀眾的「風險傾向」會調節「服務型領導風格與觀眾的混和性關係」，其餘則不會有調節效果。
本研究採用實驗法與問卷法兩種，希望能夠擴增網路直播相關研究，本研究將直播主與「領導風格」做結合，將人資的領導理論帶進直播的相關研究中，進而去探討其中的關連性，再來就是不同「領導風格」對不同的「直播主與觀眾的關係」確實會有影響，因此本研究所提出的「領導風格」與「直播主與觀眾的關係」的關聯性能夠提供未來直播相關研究基礎，再來就是以社會交換理論中，關係的互惠性來帶出風險傾向，探討觀眾的「風險傾向」在不同「領導風格」對不同的「直播主與觀眾的關係」是否有調節效果，本研究發現觀眾的「風險傾向」或多或少會去影響不同「領導風格」對不同的「直播主與觀眾的關係」，這對未來相關研究議題也提供了實證的基礎。

摘要(英)

There are often many people wondering why some people want to spend time watching live streaming . In this emerging era, live streaming has become a common social phenomenon and the trend of live streaming may gradually turn to live streaming plus vertical industry(For example, live streaming of education, live streaming of Electronic Business , etc.) , or a team of live streaming consultants will rise up and be responsible for planning the live streaming system. Thus, "live streaming" deserves more in-depth discussion.
This research mainly explores the "risk propensity" of the audience under the different "leadership styles" of the live streamer , and "the relationship between the live streamer and the audience". This research refers to the past literature and adopts experimental methods and questionnaires to conduct research. Taking Taiwan′s live streamers and their audiences as the research objects , will risk propensity of the audiences moderate the audience and steamer in different leadership styles?
When building a relationship, the live streamer will never know how this relationship will eventually become. This is like being in a gambling game, and streamer need to find answer under uncertainty.
The results of this research show that under the experimental method, the audience′s "risk propensity" will moderate the " affective relationship and mixed relationship between the different leadership style and the audiences .And the audience′s "risk propensity" will not moderate the instrumental relationship between the different leadership style and the audiences; under the questionnaire method, the audience′s "risk propensity" will moderate the "mixed relationship between servant leadership style and the audiences", and the rest will not have moderating effects.
This research adopts experimental methods and questionnaires, and hopes to expand research about live streaming. This research combines the live streamer with different "leadership styles" to bring the leadership theory of human capital into the relevant research of live streaming, and then explore the relevance of this relationship.
Different "leadership styles" will have an impact on different " relationship between live streamer and audience". Therefore, the "leadership style" and the " relationship between live streamer and audience" proposed by this research is Relevant .It provides the basis for future live streaming research. In addition, the reciprocity of relationships from the social exchange theory brings out the risk propensity, and explores the risk propensity of the audiences moderate the audience and steamer in different leadership styles? This research discovered that the “risk propensity” of the audience will affect the different “leadership styles” and different “relationship between live streamer and audience”, which also provides basic evidence for future research topics.

關鍵字(中)

★ 網路直播
★ 領導風格
★ 關係
★ 風險傾向

關鍵字(英)

論文目次

目錄
摘要 ii
Abstract iv
致謝辭 vi
一、緒論 1
1-1 研究背景 1
1-2 研究目的 3
1-3 預期貢獻 7
二、文獻探討與研究假設 10
2-1 直播主與領導風格 10
2-1-1 直播主 10
2-1-2 魅力型領導 12
2-1-3 威權型領導 15
2-1-4 服務型領導 16
2-2 關係理論 19
2-3 「領導風格」與「觀眾與直播主的關係」 22
2-4 社會交換理論 30
2-5 風險傾向對「領導風格」與「觀眾與直播主的關 31
係」的調節效果 31
三、研究方法 36
3-1 研究對象與樣本發放 36
3-2 影片實驗法設計 36
3-2-1 實驗對象 36
3-2-2 實驗方法 37
3-2-3 魅力型領導(男直播主) 41
3-2-4 威權型領導(男直播主) 43
3-2-5 服務型領導(男直播主) 46
3-2-6 魅力型領導(女直播主) 48
3-2-7 威權型領導(女直播主) 50
3-2-8 服務型領導(女直播主) 53
3-3 實驗問卷設計 55
3-4 實驗問卷假設 56
3-5 問卷法問卷設計 57
3-6 變項衡量方式 58
3-6-1 直播主的領導風格 58
3-6-2 風險傾向 62
3-6-3 觀眾與直播主的關係 63
3-7 控制變數 66
3-8 分析方法 67
3-8-1 敘述統計與相關分析 67
3-8-2 因素分析 67
3-8-3 信度分析 68
3-8-4 效度分析 68
3-8-5 共同方法變異控制 69
3-8-6 變數之組內與組間變異成份分析 69
3-8-7 階層線性模型分析 70
四、資料分析與研究結果 71
4-1 實驗問卷 71
4-1-1 敘述性統計分析 71
4-1-2 相關分析 73
4-1-3 信度分析 76
4-1-4 效度分析的建構 76
4-1-5 實驗問卷結果 78
4-2 一般問卷 86
4-2-1 敘述性統計分析 86
4-2-2 相關分析 89
4-2-3 信度分析 92
4-2-4 效度分析的建構 92
4-2-5 變數之組內與組間變異成份分析 95
4-2-6 共同方法變異分析與因素分析 95
4-3 階層線性模型之假設分析結果 95
4-3-1 關係之虛無模型 96
4-3-2 直播主領導風格與工具性的關係 106
4-3-3 直播主領導風格與情感性的關係 107
4-3-4 直播主領導風格與混和性的關係 109
4-3-4 觀眾的風險傾向對直播主領導風格與工具性關係的 110
調節效果 110
4-3-4 觀眾的風險傾向對直播主領導風格與情感性關係的 112
調節效果 112
4-3-4 觀眾的風險傾向對直播主領導風格與混和性關係的 114
調節效果 114
五、結論與建議 117
5-1 實驗法研究結果 117
5-1-1 直播主領導風格與觀眾間的關係與觀眾的風險傾向對直播 117
主領導風格與觀眾間的關係的調節效果 117
5-2 問卷法研究結果 120
5-2-1 直播主領導風格如何影響與觀眾間的關係 120
5-1-2 觀眾的風險傾向對直播主領導風格與觀眾間的關係 127
的調節效果 127
5-2 研究貢獻 133
5-2-1 研究發現 133
5-2-2 理論貢獻 139
5-3 研究限制與後續建議 142
參考文獻 144
附錄 169
實驗問卷 169
一般問卷 173

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今日新聞網:夯直播/全世界都在瘋開直播　台灣的10大直播平台，取自:
https://www.nownews.com/news/20180712/2787310/
kk news: 2018中國十大直播平台排行榜，取自:
https://kknews.cc/zh-tw/other/arbe88x.html
關鍵評論:不只是拿起手機開始拍—認識直播的五大類別，取自:
https://www.thenewslens.com/article/78434
數位時代:你相信直播是未來嗎? 取自:
https://www.bnext.com.tw/article/41959/live-platforms-in-taiwan
台灣網路中心報告，取自:
https://www.twnic.net.tw/doc/twrp/201812e.pdf
自由時報: YouTube使用行為大調查：7成受訪者天天看，平均花2.5小時，
取自: https://ec.ltn.com.tw/article/breakingnews/2551405
科技新報:17media專訪，取自:
https://technews.tw/2018/12/22/exclusive-interview-with-senior-vice-president-kevin-li-of-17-media/
數位時代: Shopee LIVE正式上線，蝦皮推直播轉型新媒體平台，取自:
https://www.bnext.com.tw/article/52627/shopee-live-launch
TVBS:虛擬直播主，取自: https://news.tvbs.com.tw/world/1049183
Twitch (2017a). Twitch: Social video for gamers. Retrieved from 30.
取自:https://www.twitch.tv/p/about/
Twitch (2017b). Audience. 取自: http://twitchadvertising.tv/audience/
Twitch (2017c). Twitch year in review 2016.
取自:http://www.twitch.tv/year/2016/index.html.
今周刊: 無敵網紅館長：就愛跟觀眾罵來罵去，取自:
https://www.businesstoday.com.tw/article/category/154769/post/201902130020
網路溫度計:Youtuber排行，取自: https://dailyview.tw/top100/topic/36

指導教授

李憶萱

審核日期

2019-7-26

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