使用OTT影音平台的關鍵因素與行為模式－以YouTube為例

A STUDY OF OTT PLATFORM USERS' INTENTION-THE CASE OF YOUTUBE

10.6338/JDA.202010_15(5).0002

賴禹心(Yu-Xin, Lai)；鄭宇庭(Yu-Ting Cheng)；蘇志雄(Chih-Hsiung Su)

YouTube ； 線上影音社群平台 ； OTT影音平台 ； 科技接受模式 ； YouTube ； Online audiovisual community platform ； OTT audiovisual platform ； technology acceptance model

Journal of Data Analysis

15卷5期（2020 / 10 / 01）

21 - 43

繁體中文

隨著行動網路蓬勃發展，行動影音世代來臨，網路影音已成為人們吸收資訊及休閒娛樂的重要管道，人們只要擁有手機，便能在任何時間及地點選擇想觀看的影音內容。線上影音社群平台YouTube因為擁有多元豐富的影音內容，吸引台灣使用者平均每週觀看YouTube達14.6小時。本研究以科技接受模式為理論基礎，探究影響使用者採用YouTube線上影音社群平台的關鍵因素為何，由探討「平台功能」、「可得性」、「個人設計」、「溝通互動」及「分享互動」與「知覺有用性」、「內容與平台態度」、「社群互動態度」、「行為意圖」之關聯性。本研究所採用的資料為張伯謙（2019）探索使用新興媒體平台的關鍵影響因素與行為模式（E10606）之調查數據，篩選出最常使用YouTube的165個樣本進行細部分析。採用SPSS 22.0和AMOS 26.0進行敘述統計分析、成對樣本T檢定、單因子相依變異數分析、測量模式分析及結構模式分析。由實證結果可知影響YouTube影音社群平台使用者的行為意圖有四個顯著因素，依照各自的影響效果排序為溝通互動、平台功能、個人設計及分享互動。

With the vigorous development of mobile networks and the advent of mobile audio and video generations, online audio and video has become an important channel for people to absorb information and entertainment. As long as people have mobile phones, they can choose the audio and video content they want to watch at any time and place. The online video and audio community platform YouTube has attracted Taiwanese users to watch YouTube for an average of 14.6 hours per week because of its diverse and rich video and audio content. This study takes the technology acceptance model as the theoretical basis and explores the key factors that affect users' adoption of YouTube's online audio-visual community platform. It explores ＂platform functions＂, ＂availability＂, ＂personal design＂, ＂ communication and interaction＂ and ＂The relationship between＂ sharing interaction＂ and ＂perceived usefulness＂, ＂content and platform attitude＂, ＂community interaction attitude＂ and ＂behavior intention＂. The data used in this research is the survey data of Zhang Boqian (2019) exploring the key influencing factors and behavior patterns (E10606) of using emerging media platforms, and the 165 samples most commonly used by YouTube were screened for detailed analysis. SPSS 22.0 and AMOS 26.0 were used for descriptive statistical analysis, paired sample T test, single factor dependent variance analysis, measurement mode analysis and structural mode analysis. From the empirical results, we can see that there are four significant factors that affect the behavioral intentions of users of the YouTube video and audio community platform, which are ranked as communication interaction, platform function, personal design and sharing interaction according to their respective impact effects.

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