由於Web2.0網路服務在不同的技術支援之下，為使用者帶來許多創新的應用服務，提供了各類型的資訊互動與分享的環境。而使用者在網路上的角色也從單向的資訊接受轉變為社群建構與內容編輯的生產者與消費者等多重角色。這種結合參與和互動的概念，儼然改變了過去使用者對於網路中的資訊使用行為與習慣。而Web2.0最著名的代表平台即是維基百科(Wikipedia)，是以使用者可以自行在該平台上瀏覽或者是編修百科全書條目，結合了虛擬社群與知識分享的概念。除了虛擬社群上的知識管理之外，知識分享亦被視為公司組織成功的關鍵，如何讓知識在組織內分享與擴散，並發揮其最大效用，將成為最重要的議題。本研究將透過主成分分析(Principal component analysis, PCA)，將準則依其屬性加以分類成獨立成份，再運用網路層級分析法(Analytic Network Process, ANP)與VIKOR模式來建立知識分享平台使用者滿意度指標(USI)，之後透過需求落差與關聯結構圖以找出平台改善方向，並藉此來建構出知識分享平台服務發展策略。

Web2.0 represents a new mode of sharing and connecting with others online, providing a variety of platformsto interact and exchange ideas. In the past, the websites are built for users to downloading or postingon their needs. This way, the relationship between website developer and viewers is unidirectional. On theother hand, Web2.0 provides with more possibilities for information suppliers and viewers to link. For example, users evolved from viewing Encyclopedia Britannica unilaterally to editing Wikipedia jointly. Wikipediais also one of the most representative Web2.0 platforms, where users could edit and browse the entries.Apart from its importance in promoting knowledge sharing, knowledge management has also been seen as akey to success. How to effectively make knowledge be shared and spread within a virtual or real communitywould become one of the most important issues nowadays. This study would like to find out the users’ needsand their motivation to share, and proposes a suitable development strategies and operation models to onlineplatforms and forums in the future. This study would select aspects/criteria for users to evaluate the motivationand factors affecting knowledge sharing, and then find out aspects/criteria what need to improve based onthe Decision Making Trial and Evaluation Laboratory (DEMATEL). Furthermore, the Principal componentAnalysis (PCA) is applied to categorize criteria based on their properties, the Analytic network process (ANP)is used to determine the weights of components, and the VIKOR is adopted to evaluate the user satisfactoryindex.