探討朋友與專家推薦旅遊景點影響力之研究

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：29

、訪客IP：18.117.192.143

姓名

粘家豪(CHIA-HAO, NIEN) 查詢紙本館藏

畢業系所

企業管理學系

論文名稱

探討朋友與專家推薦旅遊景點影響力之研究
(Investigating the effect of friends and experts when deciding tour destination)

相關論文

★ 在社群網站上作互動推薦及研究使用者行為對其效果之影響	★ 以AHP法探討伺服器品牌大廠的供應商遴選指標的權重決定分析
★ 以AHP法探討智慧型手機產業營運中心區位選擇考量關鍵因素之研究	★ 太陽能光電產業經營績效評估－應用資料包絡分析法
★ 建構國家太陽能電池產業競爭力比較模式之研究	★ 以序列採礦方法探討景氣指標與進出口值的關聯
★ ERP專案成員組合對績效影響之研究	★ 推薦期刊文章至適合學科類別之研究
★ 品牌故事分析與比較-以古早味美食產業為例	★ 以方法目的鏈比較Starbucks與Cama吸引消費者購買因素
★ 探討創意店家創業價值之研究- 以赤峰街、民生社區為例	★ 以領先指標預測企業長短期借款變化之研究
★ 應用層級分析法遴選電競筆記型電腦鍵盤供應商之關鍵因子探討	★ 以互惠及利他行為探討信任關係對知識分享之影響
★ 結合人格特質與海報主色以類神經網路推薦電影之研究	★ 資料視覺化圖表與議題之關聯

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

至系統瀏覽論文 ( 永不開放)

摘要(中)

隨著社群網站（例如Facebook、TripAdvisor等）的崛起，越來越多遊客在網路上分享旅遊經驗及私房景點等資訊。也因為觀光旅遊產業獨有的特性，更突顯了消費者在決策前資訊蒐集的重要性。社群網站提供了消費者一個很好的資訊蒐集管道，但由於社群網站的資訊過度龐大，造成消費者面臨資訊超載的問題。若社群網站能夠幫助消費者節省資訊蒐集的時間，並有效地提高消費者對資訊的信任感，進一步掌握消費者的偏好，將能更有效的提供消費者有興趣的資訊。
過去相關研究將親朋好友與虛擬社群分為兩個主題各別探討他們對於消費者決策的影響力，然而現今社群網站的環境中，已將過去親朋好友與虛擬社群的分類混合在一起，無明確的分類。
因此本研究將探討在社群網站中的朋友（包含現實與虛擬社群的朋友）與專家對消費者決策的影響力，並比較朋友與專家對消費者在選擇旅遊景點的影響力孰輕孰重。更進一步利用親朋好友的意見預測消費者對旅遊景點的偏好。
由研究結果可知，（1）社群網站上的朋友對消費者的影響力較專家的意見強；（2）社群網站上的朋友對消費者產生的影響力，會隨著消費者的關心程度而改變；（3）藉由社群網站上的朋友對旅遊景點的偏好，可以預測消費者對旅遊景點的偏好。

摘要(英)

With the rise of social network, more and more tourists are willing to share their own travel experiences on the Internet. Due to the unique characteristics of tourism, information gathering is very important before tourists decide where the destination is. Social networking site provide a new way for consumers collecting information, but too much information would lead to information overload. If social networking sites could understand what kind of information consumers need, and help consumers to gather useful and trustworthy information quickly. It would provide the right information to consumers in the most effective ways.
In the past, relevant researches focus on the influence of friends and visual group separately, however, in the social network environment, friends and visual group have already combined together and there is no specific classification now. Therefore, this study will investigate the influence of the friends on social networking sites (including real and virtual group) and experts, and then compare the influence between friends and experts. Furthermore, use the decisions of friends to predict the preferences of consumers.
The result shows that: (1) the influence of friends on social networking sites is stronger than experts; (2) the influence of friends on social networking sites is dependent on the EdgeRank; (3) the preferences of friends can predict the preferences of consumers.

關鍵字(中)

★ 社群網路
★ EdgeRank
★ 影響力
★ 旅遊景點

關鍵字(英)

論文目次

摘要 i
ABSTRACT ii
致謝 iii
目錄 iv
圖目錄 vi
表目錄 vii
第一章緒論 1
1-1 研究背景與動機 1
1-2 研究目的 3
1-3 研究架構與流程 4
第二章文獻探討 5
2-1 消費者購買過程之探討 5
2-1-1 消費者決策過程 5
2-1-2 參考群體如何影響決策 5
2-1-3 社會影響（Social Influence） 7
2-2 口碑行銷（Word of Mouth, WoM） 9
2-3 虛擬社群對旅遊規劃的影響 10
2-3-1 觀光服務業特性 10
2-3-2 觀光旅遊社群網站 11
2-3-3 TripAdvisor 12
第三章研究方法 14
3-1 研究假設 14
3-2 研究設計 15
3-2-1 問卷設計 15
3-2-2 研究樣本 17
3-2-3資料收集與分析方法 18
第四章研究資料分析 23
4-1 問卷回收情形 23
4-1-1 回收問卷數統計 23
4-1-2 樣本資料之敘述性統計分析 23
4-2 資料結果分析 26
4-2-1 朋友是否影響受測者決定 26
4-2-2 關心程度越高的朋友對受測者造成的影響越大 28
4-2-3 朋友與專家的影響程度 28
4-3預測受測者對旅遊景點的偏好 29
第五章結論與未來研究建議 33
5-1 研究限制 33
5-2 結論 34
5-2-1 假設驗證 34
5-2-2 預測成效 35
5-3 未來研究建議 36
參考文獻 37
附錄問卷 40

參考文獻

[1]. Kotler, Philip. (2003). Marketing Management, 11th . Pearson Education International.
[2]. Blackwell, Roger D, Miniard, Paul W, & Engel, James F. (2001). Consumer behavior, 9th. Harcourt College Publishers.
[3]. 蔡文輝，(2010)，社會學，修訂六版，三民書局。
[4]. 張春興，(2009)，現代心理學—現代人研究自身問題的科學，重修版，東華書局。
[5]. Asch, S. E. (1951). “Effects of group pressure upon the modification and distortion of judgments.” Groups, Leadership, and Men. S, 222-236.
[6]. Hennig-Thurau, T., Gwinner, K. P., Walsh, G., & Gremler, D. D. (2004). “Electronic word-of-mouth via consumer-opinion platforms: what motivates consumers to articulate themselves on the internet?.” Journal of interactive marketing, 18(1), 38-52.
[7]. Li, F., & Du, T. C. (2011). “Who is talking? An ontology-based opinion leader identification framework for word-of-mouth marketing in online social blogs.” Decision Support Systems, 51(1), 190-197.
[8]. Chatterjee, P. (2001). “Online reviews: do consumers use them?.” Advances in consumer research, 28, 129-133.
[9]. Li, Y. M., Lin, C. H., & Lai, C. Y. (2010). “Identifying influential reviewers for word-of-mouth marketing.” Electronic Commerce Research and Applications,9(4), 294-304.
[10]. Keller, E., & Berry, J. (2003). The influentials: One American in ten tells the other nine how to vote, where to eat, and what to buy. Free Press.
[11]. Smith T, Coyle J R, Lightfoot E, Scott A. (2007). “Reconsidering models of influence: the relationship between consumer social networks and word-of-mouth effectiveness.” Journal of Advertising Research, 47(4), 387.
[12]. Regan, W. J. (1963). “The service revolution.” The Journal of Marketing, 57-62.
[13]. 曹勝雄，(2001)，觀光行銷學，初版，揚智文化。
[14]. Kim, D. Y., Lehto, X. Y., & Morrison, A. M. (2007). “Gender differences in online travel information search: Implications for marketing communications on the internet.” Tourism Management, 28(2), 423-433.
[15]. Bansal, H. S., & Voyer, P. A. (2000). “Word-of-mouth processes within a services purchase decision context.” Journal of service research, 3(2), 166-177.
[16]. Urbany, J. E., Dickson, P. R., & Wilkie, W. L. (1989). “Buyer uncertainty and information search.” Journal of Consumer Research, 208-215.
[17]. Fodness, D., & Murray, B. (1997). “Tourist information search.” Annals of tourism research, 24(3), 503-523.
[18]. Fodness, D., & Murray, B. (1998). “A typology of tourist information search strategies.” Journal of Travel Research, 37(2), 108-119.
[19]. Peterson, R. A., & Merino, M. C. (2003). “Consumer information search behavior and the Internet.” Psychology & Marketing, 20(2), 99-121.
[20]. Yoo, K. H., & Gretzel, U. (2008). “What motivates consumers to write online travel reviews?.” Information Technology & Tourism, 10(4), 283-295.
[21]. TripAdvisor. (2013). About TripAdvisor media group. From http://www.tripadvisor.com/pages/about_us.html
[22]. Murphy, J., & Olaru, D. (2009). “How information foraging styles relate to tourism demographics and behaviours.” Journal of Vacation Marketing, 15(4), 299-309.
[23]. Gretzel, U., & Yoo, K. H. (2008). “Use and impact of online travel reviews.” Information and communication technologies in tourism 2008 (pp. 35-46). Springer Vienna.
[24]. Jin, Y., Bloch, P., & Cameron, G. T. (2002). “A comparative study: does the word-of-mouth communications and opinion leadership model fit epinions on the internet?.” 1st Annual Hawaii International Conference on Social Sciences
[25]. Resnick, P., Kuwabara, K., Zeckhauser, R., & Friedman, E. (2000). “Reputation systems.” Communications of the ACM, 43(12), 45-48.
[26]. Jeacle, I., & Carter, C. (2011). “In TripAdvisor we trust: Rankings, calculative regimes and abstract systems.” Accounting, Organizations and Society, 36(4), 293-309.
[27]. Patel, M. (2011). “How User-Generated Review Websites Impact a Hotel’s RevPar.”
[28]. Ye, Q., Law, R., & Gu, B. (2009). “The impact of online user reviews on hotel room sales.” International Journal of Hospitality Management, 28(1), 180-182.
[29]. Bickart, B., & Schindler, R. M. (2001). “Internet forums as influential sources of consumer information”. Journal of interactive marketing, 15(3), 31-40.
[30]. Kaiser, C., Schlick, S., & Bodendorf, F. (2011). “Warning system for online market research–identifying critical situations in online opinion formation.” Knowledge-Based Systems, 24(6), 824-836.
[31]. 張瑋倫、林憲廷，(2012)，「群體中個體性格相似性之研究」，圖書資訊學研究，6(2)，83-113頁。
[32]. J. Kincaid. (2010). EdgeRank: The secret sauce that makes Facebook’s news feed tick.”TechCrunch. From http://techcrunch.com/2010/04/22/facebook-edgerank/
[33]. Bucher, T. (2012). “Want to be on the top? Algorithmic power and the threat of invisibility on Facebook.” new media & society, 14(7), 1164-1180.
[34]. Gomes, A. K., & da Graca C Pimentel, M. (2011). “Social interactions representation as users behavioral contingencies and evaluation in social networks.” In Semantic Computing (ICSC), 2011 Fifth IEEE International Conference on (pp. 275-278). IEEE.
[35]. Statistics about Facebook Users, (2013). From http://www.checkfacebook.com/

指導教授

許秉瑜

審核日期

2013-6-26

推文