政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/70262
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  全文笔数/总笔数 : 113160/144130 (79%)
造访人次 : 50753327      在线人数 : 626
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜寻范围 查询小技巧：
  • 您可在西文检索词汇前后加上"双引号"，以获取较精准的检索结果
  • 若欲以作者姓名搜寻，建议至进阶搜寻限定作者字段，可获得较完整数据
    •  进阶搜寻
    政大機構典藏 > 商學院 > 資訊管理學系 > 學位論文 >  Item 140.119/70262


    请使用永久网址来引用或连结此文件: https://nccur.lib.nccu.edu.tw/handle/140.119/70262


    题名: 企業對線上口碑風暴回應策略之研究
    Company Strategies in Response to Online Firestorm
    作者: 林冠達
    贡献者: 梁定澎
    林冠達
    关键词: 負面口碑
    線上危機管理
    線上口碑風暴
    Negative Word-of-Mouth
    Online Firestorm
    Online Crisis Management
    日期: 2013
    上传时间: 2014-10-01 13:32:28 (UTC+8)
    摘要: 口碑一直以為都是企業行銷的重要利器，而同時也是要害之一，且隨著網路的發達和社群網路的發展，對企業的影響也越來越大。而近幾年在媒體中開始出現一個新名詞，用來形容負面口碑在社群媒體中傳播的現象-線上口碑風暴(Online Firestorm)。
    線上口碑風暴的相關研究相當的稀少，而在許多口碑的相關研究中也未多著墨，但隨著社群媒體的發展，此現象已越來越普遍，因此有研究探討的價值，所以在本研究中將先定義出線上口碑風暴，並以Google搜尋趨勢設計出測量線上口碑風暴的方式，以利將其從負面口碑的傳播分辨出來，並利用這樣的方法找出六個線上口碑風暴的個案來進行研究，配合Coombs的印象修復理論來進一步分析。
    研究結果發現，可以將線上口碑風暴依成因分成「過去不好的服務或產品體驗」、「錯誤的時機情境」和「不適當的聲明或宣傳」，而各類別的最佳回應策略在文中有詳細講述。另外，當企業使用的回應策略越多時，線上口碑風暴持續的時間就可能越久。影響線上口碑風暴的因素有很多，經本研究的討論分析後，發現「負面訊息傳播的平台」、「回應策略的運用」和「企業的規模和性質」為最會影響線上口碑風暴的因素。
    Word-of-Mouth (WOM) has been a major marketing tool to the enterprise, but could also be one of its threats. With the development of the Internet and social networks, the impact of WOM on enterprises is also growing. In recent years, the rapid propagation of negative Word-of-Mouth in social media has gained much attention in media and is named “Online Firestorm.”
    Academic studies about Online Firestorm are rare, and researchers of Word-of-Mouth have not investigated it. Giving the development of social media, this phenomenon has become increasingly common. Therefore it is important for companies to know and better handle it and for researchers to investigate this new issue. In this study, we will define and measure Online Firestorm though Google Trends. We will also collect data from six cases and analyze how different responding strategies may result in different outcomes.
    Research found that Online Firestorm can be categorized into “past bad service or prouduct experience”, “bad timing scenarios” and “inappropriate statements or propaganda” according to the causes of the storm. The best response strategies to all kinds are described in the text. In addition, when used more response strategies, Online Firestorm duration may longer. There are many factors affecting the Online Firestorm, after the discussion and analysis found that "negative information dissemination platform", "the using of response strategies" and "the scale and nature of the enterprises" and as the factors that most likely to affect the Online Firestorm.
    參考文獻: 中文：
    1.吳宜蓁. (2005). 危機傳播 公共關係與語藝觀點的理論與實證 (二版.). 臺北市: 五南.
    2.潘淑滿. (2003). 質性研究: 理論與應用. 臺北市: 心理.
    3.陳向明. (2002). 社會科學質的硏究. 臺北市: 五南.
    英文：
    1.Alavi, M., & Carlson, P. (1992). “A review of MIS research and disciplinary development”, Journal of Management Information Systems, Vol.8,No.4, pp.45–62.
    2.Andrews, K. R. (1951). “Executive training by the case method”, Harvard Business Review, Vol.29,No.5, pp.58–70.
    3.Arndt, J. (1967). “Word of mouth advertising and informal communication”, Advertising Research Foundation,Vol.29,No.3, pp.188–239.
    4.Barton, L. (1993). Crisis in organizations: Managing and communicating in the heat of chaos, College Division: South-Western Publishing Company.
    5.Benoit, W. L. (1995). Accounts, excuses, and apologies: A theory of image restoration strategies, New York:State University of New York Press Albany.
    6.Benoit, W. L. (1997). “Image repair discourse and crisis communication”, Public Relations Review, Vol.23,No.2, pp.177–186.
    7.Berger, J., & Milkman, K. L. (2012). “What Makes Online Content Viral?” Journal of Marketing Research, Vol.49,No.2, pp.192–205.
    8.Blodgett, J. G., Granbois, D. H., & Walters, R. G. (1993).”The effects of perceived justice on complainants’ negative word-of-mouth behavior and repatronage intentions”, Journal of Retailing,Vol.69,No.4, pp.399–428.
    9.Bogdan, R. C., & Biklen, S. K. (1982). Qualitative research for education. , Boston: Allyn and Bacon.
    10.Brown, J., Broderick, A. J., & Lee, N. (2007). “Word of mouth communication within online communities: Conceptualizing the online social network”, Journal of Interactive Marketing, Vol.21, No.3, pp.2–20.
    11.Brown, J. J., & Reingen, P. H. (1987). “Social ties and word-of-mouth referral behavior”, Journal of Consumer Research, Vol.14,No3, pp.350–362.
    12.Buchanan, M. (2003). Nexus: small worlds and the groundbreaking science of networks. New York: W.W. Norton.
    13.Chadwick, B. A., Bahr, H. M., & Albrecht, S. L. (1984). “Social science research methods” http://books.google.com.tw/books?id=j_t9AAAAIAAJ
    14.Chu, S.-C., & Kim, Y. (2011). “Determinants of consumer engagement in electronic word-of-mouth (eWOM) in social networking sites”, International Journal of Advertising, Vol.30,No.1, pp.47–75.
    15.Coombs, T., & Schmidt, L. (2000). “An Empirical Analysis of Image Restoration: Texaco’s Racism Crisis”, Journal of Public Relations Research, Vol.12,No.2, pp.163–178.
    16.Coombs, W. T. (1998). “An analytic framework for crisis situations: Better responses from a better understanding of the situation”, Journal of public relations research, Vol.10,No.3, pp.177-191.
    17.Coombs, W. T. (2014). Ongoing Crisis Communication: Planning, Managing, and Responding. New York: SAGE Publications.
    18.Coombs, W. T., & Holladay, S. J. (2008). “Comparing apology to equivalent crisis response strategies: Clarifying apology’s role and value in crisis communication”, Public Relations Review, Vol.34, No.3, pp.252–257.
    19.Diakopoulos, N., De Choudhury, M., & Naaman, M. (2012).”Finding and Assessing Social Media Information Sources in the Context of Journalism”, Proceedings of the SIGCHI Conference on Human Factors in Computing Systems , pp. 2451–2460.ACM.
    20.Dichter, E. (1966). “How word-of-mouth advertising works”, Harvard Business Review, Vol.44,No.6, pp.147–160.
    21.Gelb, B. D., & Sundaram, S. (2002). “Adapting to “word of mouse”, Business Horizons, Vol.45,No.4, pp.21–25.
    22.Goldsmith, R. E., & Horowitz, D. (2006). “Measuring Motivations for Online Opinion Seeking”, Journal of Interactive Advertising, Vol.6,No.2, pp.2–14.
    23.Gonzalez-Herrero, A., & Pratt, C. B. (1995). “How to manage a crisis before-or whenever-it hits”, Public Relations Quarterly, Vol.40, pp.25.
    24.Gregory, R. P., Rochelle, C. F., & Rochelle, S. G. (2013). “Positive Feedback Trading: Google Trends and Feeder Cattle Futures”, Journal of Applied Business Research , Vol.29, No.5, pp.1325–1332.
    25.Herr, P. M., Kardes, F. R., & Kim, J. (1991). “Effects of word-of-mouth and product-attribute information on persuasion: An accessibility-diagnosticity perspective”, Journal of Consumer Research, Vol.17, No.4, pp.454.
    26.Lancy, D. F. (1993). Qualitative research in education: An introduction to the major traditions. London: Longman Pub Group.
    27.Loewendick, B. A. (1993). “Laying your crisis on the table”, Training & Development, Vol.47, No.11, pp.15–17.
    28.Mangold, W. G., & Faulds, D. J. (2009). “Social media: The new hybrid element of the promotion mix”, Business Horizons, Vol.52,No.4, pp.357–365.
    29.McNaughton, M. (n.d.). “Lessons From the #McDStories Promoted Trend Controversy”, http://therealtimereport.com/2012/01/24/lessons-from-the-mcdstories-promoted-trend-controversy/
    30.McPherson, M., Smith-Lovin, L., & Cook, J. M. (2001). “Birds of a Feather: Homophily in Social Networks”. Annual Review of Sociology, Vol.46,No.1, pp.415–444.
    31.Merriam, S. B. (1998). Qualitative Research and Case Study Applications in Education. San Francisco: JosseyBass Publishers.
    32.Messner, M., & Distaso, M. W. (2008). “The Source Cycle”, Journalism Studies, Vol.9,No.3, pp.447–463.
    33.Murray, K. B. (1991). “A test of services marketing theory: consumer information acquisition activities”, The Journal of Marketing, Vol.55,No.1, pp.10–25.
    34.Myers, S. A., Zhu, C., & Leskovec, J. (2012). “Information Diffusion and External Influence in Networks”, Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining , pp. 33–41. New York: ACM.
    35.Pariser, E. (2011). The Filter Bubble: What The Internet Is Hiding From You. UK: Penguin Books.
    36.Pearson, C. M., & Clair, J. A. (1998). “Reframing Crisis Management”, Academy of Management Review, Vol.23, No.1, pp.59–76.
    37.Pfeffer, J., Zorbach, T., & Carley, K. M. (2014). “Understanding online firestorms: Negative word-of-mouth dynamics in social media networks”, Journal of Marketing Communications, Vol.20, No.1-2, pp.117–128.
    38.Richins, M. L. (1983). “Negative Word-of-Mouth by Dissatisfied Consumers: A Pilot Study”, Journal of Marketing, Vol.47, No.1, pp.68.
    39.Richins, M. L. (1984). “Word of Mouth Communication a Negative Information”, Advances in Consumer Research, Vol.11, No.1, pp.697–702.
    40.Snyder, C. R., Higgins, R. L., & Stucky, R. J. (1983). Excuses: Masquerades in search of grace. New York: Wiley.
    41.Stake, R. E. (1995). The art of case study research. New York: Sage Publications
    42.Sullivan, D. (2006). “Nielsen NetRatings search engine ratings.” http://marketingpedia.com/Marketing-Library/Search/industryNewsSeptA1.pdf
    43.Tkacz, G. (2013). “Predicting Recessions in Real-Time: Mining Google Trends and Electronic Payments Data for Clues.” CD Howe Institute Commentary, No.387.
    44.Trusov, M., Bucklin, R. E., & Pauwels, K. (2009). “Effects of Word-of-Mouth Versus Traditional Marketing: Findings from an Internet Social Networking Site”, Journal of Marketing, Vol.73,No.5, pp90–102.
    45.Ware, B. L., & Linkugel, W. A. (1973). “They spoke in defense of themselves: On the generic criticism of apologia”, Quarterly Journal of Speech, Vol.59, No.3, pp273–283.
    46.Wu, F., & Huberman, B. A. (2007). “Novelty and collective attention. Proceedings of the National Academy of Sciences”, Vol.104, No.45, pp17599–17601.
    47.Yin, R. (2003). Case study research: Design and methods. New York: Sage Publications.
    描述: 碩士
    國立政治大學
    資訊管理研究所
    101356034
    102
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G1013560341
    数据类型: thesis
    显示于类别:[資訊管理學系] 學位論文

    文件中的档案:

    档案 大小格式浏览次数
    034101.pdf2753KbAdobe PDF2348检视/开启


    在政大典藏中所有的数据项都受到原著作权保护.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 回馈