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    題名: 虛擬社群使用者之社群認同度與資訊分享行為關聯性之研究
    其他題名: The study of the relationship between community identify and knowledge sharing behavior of virtual community participants
    作者: 陳金樟;Chen, Jin-Zhang
    貢獻者: 淡江大學教育科技學系碩士班
    何俐安
    關鍵詞: 虛擬社群;社群認同;資訊分享;Virtual Community;community identify;Information Sharing
    日期: 2014
    上傳時間: 2015-05-01 13:42:51 (UTC+8)
    摘要: 現今隨著資訊科技及網路技術不斷的演進,只要能夠連線上網,使用者就可以透過網路迅速的與其他使用者聯繫互相交流資訊,虛擬社群的出現,正好改變了人們有別於以往的相處模式,社群中的成員解決問題的方式可以藉由分享資訊與知識來互相學習。文獻指出,虛擬社群的概念與實體的社群相同,社群成員間會相互支持、分享、交換資訊並獲得社會支持及一定程度的認同與歸屬感,讓使用者願意繼續待在網路團體中。本研究旨在瞭解虛擬社群成員參與虛擬社群之社群認同度與資訊分享行為的關聯性。希望可以藉由探討社群認同與資訊分享行為之間的影響關係,提供虛擬社群經營者在經營上之參考。本研究採問卷調查法,以社群網站Facebook(臉書)之虛擬社群使用者為研究對象(N=494),回收問卷以t-test, one-way ANOVA, Pearson correlation, stepwise regression統計方法進行數據分析。研究獲得的結論有以下幾點:

    一、社群成員間的分享行為是普遍存在。
    二、就個人背景變項所造成的差異程度而言,年齡對社群成員之社群認同有顯著
    的差異性。
    三、就個人背景變項所造成的差異程度而言,不同使用虛擬社群時間對社群成員
    之社群認同有顯著的差異性。
    四、社群成員的社群認同度與其參與資訊分享行為具有顯著相關性。
    五、情感、行為及認知可正向且顯著地預測社群成員分享資訊,其中以認知的預
    測力最大。
    六、虛擬社群facebook的成員會因為個人對其他社群成員或是社群平台的社群
    認同程度不同,而導致資訊分享行為產生改變。
    Nowadays, with the rapid evolution of information and network technology, users can quickly contact with each other over the network to exchange information. Virtual communities have changed the way people interact. Community members learn from each other to solve problems by sharing information and knowledge. Literature indicates that the concept of virtual community is the same as the face-to-face community. Community members often support each other to share and exchange information, and get the sense of identity and belonging to a certain degree, so that Internet users are willing to stay in these groups. This study aims to explore the relationship between community identify and knowledge sharing behavior of virtual community participants in order to make suggestions to the community managers. This is a quantitative research which targets at Facebook users who have had online information exchange experiences. A survey questionnaire was used to collect data (N=494). t-test, one-way ANOVA, Pearson correlation, and stepwise regression were employed for statistical analysis. The findings are:
    1. Sharing behavior is common among community members.
    2. As far as personal factors are concerned, age has
    significant influence on community identify of virtual
    community members.
    3. As far as personal factors are concerned, different time
    using has significant influence on the community
    identify of virtual community members.
    4. Community identify of virtual community members has
    significant influence on the knowledge sharing behavior.
    5. Emotion, behavior and cognition can positively and
    significantly predict community members to share
    information. As a whole, cognition has the maximum of
    predictability.
    6. Virtual community members change their information
    sharing behavior depending on the level of the identity
    to other members or community platforms.
    顯示於類別:[教育科技學系暨研究所] 學位論文

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