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  • 學位論文

知識分享動機對餐飲評論者網路口碑意圖的影響:應用科技接受模型的擴展架構

The impact of Knowledge Sharing Motivation on Catering Reviewer’s eWOM Intentions: Applied the Extended Architecture of Technology Acceptance Models

指導教授 : 趙仁方 陳秀芬

摘要


網路的快速發展造就了在線知識分享網站和網路口碑(eWOM)的普及化。然而現今台灣餐飲業是個高度競爭的行業,餐飲企業如何獲取顧客的認可,透過網路行銷被視為是Web2.0世代的重要策略。因此,本研究以探討新科技資訊的科技接受模型作為基礎,加入知識分享擴展為研究架構來探討評論者對評論網使用情況和使用態度與網路口碑意圖之間的關係。本研究方法採用便利性抽樣法蒐集研究資料,並使用 SPSS 19 和 Amos 22 作為分析工具進行資料分析。 本研究結果顯示:科技接受模型(TAM)在餐飲評論者對網路口碑意圖有顯著的正向影響;對餐飲評論者的知識分享動機在科技接受模型(TAM)擴展效用也是顯著成立的。但在網站的認知易用性對網站的使用態度路徑則遭到拒絕,這顯示出評論者經過長時間的使用,已熟悉平台操作,不會因為難易度而影響對網站的使用態度。

並列摘要


The rapid development of the Internet has resulted in the popularization of online knowledge sharing sites and eWOM. Nowadays, the catering industry in Taiwan is a highly competitive industry. How catering companies gain the recognition of customers is regarded as an important strategy of Web 2.0 generation through Internet marketing. Therefore, this research explores the technology acceptance model of new scientific and technological information as the foundation, and adds the knowledge sharing as the research framework to explore the relationship between the reviewers' use of comment networks and the use attitude and eWOM intension. The method of this study adopts convenience sampling to collect research data by questionnaire, and uses SPSS 19 and Amos 22 as analysis tools to analyze the data. The result shows that: the Technology Acceptance Model (TAM) has a significant positive impact on eWOM intentions among catering reviewers; the motivation for knowledge sharing among catering reviewers is also clearly established in the expanded use of technology acceptance model (TAM). However, perceived ease of use of the site on the attitudes toward using the site was rejected. This indicates that reviewers have been familiar with platform operations after a long period of use, and does not affect the use of the site due to difficulty.

參考文獻


Kuo, Y. F., & Yen, S. N. (2009). Towards an understanding of the behavioral intention to use 3G mobile value-added services. Computers in Human Behavior, 25(1), 103-110.
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