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題名 Big Data應用於網路口碑監測服務之商業模式研究 －以意藍科技為例
Exploring the Business Model of e-WOM Monitoring Services with the Application of Big Data – A Case Study of eLand Tech作者 劉惟成
Liu, Wei Cheng貢獻者 溫肇東
Wen, Chao Tung
劉惟成
Liu, Wei Cheng關鍵詞 海量資料
網路口碑
商業模式
Big Data
e-WOM
business model日期 2013 上傳時間 29-Jul-2014 16:19:08 (UTC+8) 摘要 隨著網路的普及與社群網站的興起，人們的購買行為也跟著改變，從傳統被動地接受企業的產品廣告來決定是否購買，到現在網路社群、網友口碑的力量已經成為人們購買產品或服務主要的參考依據，根據創市際市場研究顧問公司在2012年9月所做的調查發現，大約有53%的消費者會在網路上對商品做評論，且當對商品很滿意時，其上網評論的意願會增加，此調查也發現，網路口碑對於消費者的購買決策具有相當大的影響力，有93%的消費者會上網尋找網路口碑資訊，企業對於網路口碑的影響力實在不可不重視。網路口碑的監測可以提供企業掌握市場上消費者對於產品或服務的反應與評價，但傳統上透過人力搜尋的方式，或自行架設官方討論區的方式來取得網友回饋，都有見樹不見林的窘況，而近年Big Data技術的發展，可以讓企業透過相對低廉的運算成本來進行全面的資料蒐集與分析，提供企業更完整的網路口碑概況，掌握最即時的市場動態。市場上近來也出現導入Big Data技術，提供網路口碑監測服務的第三方公司，而本研究希望探討的是，透過Big Data技術進行網路口碑監測服務的公司，必須擁有何種的核心能力？而這樣的服務到底可以為客戶提供何種價值？最後網路口碑監測服務要如何獲利？本研究藉由個案公司與相關單位的訪談，並輔以獲利世代一書所提出的商業模式九大要素來進行驗證，完整勾勒出網路口碑監測服務的商業模式。本研究最後發現，資訊技術能力是網路口碑監測服務最主要的核心能力，是維持其服務品質的重要基石。不過表面上看來以Big Data來進行網路口碑監測，可以幫助企業在行銷策略上有進一步深入的洞察，但因企業普遍習慣將行銷活動外包給行銷公關公司執行，此網路口碑監測服務對於企業而言，無法完整發揮原先所期待的價值，反而對於行銷公關公司來說，是個可以提升其服務附加價值的工具。最後利用Big Data技術進行分析，並利用雲端的概念提供客戶網路口碑監測服務的應用，具有規模經濟的效果，不過因目前企業限於傳統行銷思維與既有管理制度，要能夠吸引大量企業採用網路口碑監測服務，仍需耗費相當大的資源成本，對客戶進行教育及推廣。
With the popularity of the Internet and the rise of social networking sites, people changed their shopping behaviors. In the past, people passively received advertisements from enterprises and made buying decisions. Today, social network and electronic word of mouth (e-WOM) have become powerful strengths to influence people’s buying decisions. According to the survey of InsightXplorer market consulting corporation in 2012, 53% of customers would make online comments about the products they bought and 93% of customers would search online information before shopping. Obviously, the power of e-WOM is deeply influencing the business.e-WOM monitoring helps corporations to understand the preferences of consumers; but traditionally, enterprises collect online responses of consumers by manual searching operations or building official forum websites. This is found not to be an efficient method. Recently, with the trends of Big Data technology, it benefits enterprises to collect and analyze the complete e-WOM information with lower computing costs. Furthermore, enterprises can handle the real-time market dynamics.There are several enterprises that provide e-WOM monitoring service by using Big Data technology. This thesis is to investigate three questions: 1.) What is the core capability of the enterprises that use Big Data to provide e-WOM monitoring service? 2.) What kinds of value to clients does the e-WOM monitoring service provide with Big Data? 3.) How to make profit with e-WOM monitoring service using Big Data? This thesis describes the business models of e-WOM monitoring service using Big Data through the case study and interviews with the people in related enterprises. The findings are described in below:1. Information technology is the core capability of e-WOM monitoring service by using Big Data technology.2. The enterprises were used to outsource their marketing campaigns to marketing companies. Surprisingly, the e-WOM monitoring service help marketing companies to improve their service values instead of bringing more value to the enterprises3. Using Big Data and cloud computing technology can achieve economies of scale effect, but current enterprises are limited to the traditional marketing concepts and management systems. Attracting more enterprises to adopt e-WOM monitoring service is a big challenge.參考文獻 一、 中文文獻Osterwalder, A., & Pigneur, Y. (2012). 獲利世代: 早安財經文化.Rosen, E. (2001). 口碑行銷: 遠流.城田真琴. (2013). 大數據的獲利模式: 經濟新潮社.柯承恩. (2008). 商業模式與文化產業發展在台灣. 經濟前瞻, 118, 104-112. 胡世忠. (2013). 雲端時代的殺手級應用 海量資料分析: 天下雜誌.麥爾荀伯格、庫基耶. (2013). 大數據: 天下文化.資策會. (2013). 2013臺灣消費者科技應用生活型態研究分析報告.廖佩怡. (2006). 實體與網路的口碑之比較：資訊特性觀點之探索性研究. (碩士), 國立臺北科技大學. 蔡政安. (2013). 商業模式初探 餐飲服務業之個案研究. 創業管理研究, 8(4), 1-26. 謝松齡. (2008). 網路商店進行網路口碑管理之研究－以網路化妝品商店為例. (碩士), 政治大學. 鍾采霏. (2013). 智慧型手機應用程式之商業模式分析. (碩士), 政治大學. 二、 英文文獻Afuah, A., & Tucci, C. L. (2000). Internet business models and strategies: Text and cases: McGraw-Hill Higher Education.Amit, R., & Zott, C. (2001). Value creation in e‐business. Strategic management journal, 22(6‐7), 493-520. Applegate, L. M. (2001). Emerging e-business models. Harvard business review, 79-87.Arndt, J. (1967). Role of Product-Related Conversations in the Diffusion of a New Product. Journal of Marketing Research (JMR), 4(3). 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. Benbasat, I., Goldstein, D. K., & Mead, M. (1987). The case research strategy in studies of information systems. MIS quarterly, 11(3). Brown, J. J., & Reingen, P. H. (1987). Social ties and word-of-mouth referral behavior. Journal of Consumer research. Buttle, F. A. (1998). Word of mouth: understanding and managing referral marketing. Journal of strategic marketing, 6(3), 241-254. Chatterjee, P. (2001). Online reviews: do consumers use them? Advances in consumer research, 28(1). Gelb, B. D., Suresh Sundaram. (2002). Adapting to Word of Mouse. Business Horizons, 45(4), 21-25. Hanson, W. A. (2000). Principles of Internet Marketing.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. Johnson, M. (2010). Seizing the white space. Massachusetts: Harvard Business Press. OpenURL. Johnson, M. W., Christensen, C. M., & Kagermann, H. (2008). Reinventing your business model. Harvard business review, 86(12), 57-68. Lindgart, Z., Reeves, M., Stalk, G., & Deimler, M. S. (2009). Business Model Innovation. When the game gets though, change the game, The Boston Consulting Group. Möller, K., Rajala, A., & Svahn, S. (2005). Strategic business nets—their type and management. Journal of Business research, 58(9), 1274-1284. Magretta, J. (2002). Why business models matter. Magretta, J. (2011). Understanding Michael Porter: The essential guide to competition and strategy: Harvard Business Press.Mahadevan, B. (2000). Business Models for Internet-Based E-Commerce: AN ANATOMY. California management review, 42(4). Markides, C. C. (1999). A dynamic view of strategy. Sloan Management Review, 40(3), 55-63. MGI. (2011). Big Data: The next frontier for innovation, competition, and productivity.Osterwalder, A., & Pigneur, Y. (2010). Business model generation: a handbook for visionaries, game changers, and challengers: John Wiley & Sons.Richins, M. L., & Root-Shaffer, T. (1988). The Role of Involvement and Opinion Leadership in Consumer Word-of-Mouth: An Implicit Model Made Explicit. Advances in consumer research, 15(1). Shafer, S. M., Smith, H. J., & Linder, J. C. (2005). The power of business models. Business Horizons, 48(3), 199-207. Sinfield, J. V., Calder, E., McConnell, B., & Colson, S. (2011). How to identify new business models. Timmers, P. (1998). Business models for electronic markets. Electronic markets, 8(2), 3-8. Viscio, A., & Pasternack, B. A. (1996). Toward a new business model. Strategy & Business, 20(2), 125-134. Ward, J. S., & Barker, A. (2013). Undefined By Data: A Survey of Big Data Definitions. arXiv preprint arXiv:1309.5821. Weill, P., & Vitale, M. (2001). Place to space: moving to ebusiness models. Harvard Business School Publishing Corporation, Boston.三、 網路資料創市際. (2012). from http://www.insightxplorer.com/index.html意藍科技. (1999). from http://www.eland.com.tw/維基百科. from zh.wikipedia.org網管人雜誌. (2014). from http://www.netadmin.com.tw/article_content.aspx?sn=1401020004數位時代. (2012). Big Data數字淘金. from http://www.bnext.com.tw/focus/view/cid/103/id/22295/t/1330741007803Gatner. from https://www.gartner.com/it-glossary/big-data/Google. (2013). google.org 流感趨勢. from http://www.google.org/flutrends/intl/zh_tw/about/how.htmli-Buzz網路口碑研究中心. (2010). from http://i-buzzresearchcenter.blogspot.tw/IBM. (2012). from http://www-07.ibm.com/tw/blueview/2012oct/8.htmlIntel. from http://www.intel.comMicrosoft. from http://www.microsoft.com/NIST. from http://bigdatawg.nist.gov/home.phpOpView. (2014). from http://www.opview.com.tw/Oracle. from http://www.oracle.com/index.htmlRappa, M. (2003). Business Models on the Web. from http://digitalenterprise.org/models/models.html 描述 碩士
國立政治大學
科技管理與智慧財產研究所
101359003
102資料來源 http://thesis.lib.nccu.edu.tw/record/#G0101359003 資料類型 thesis dc.contributor.advisor 溫肇東 zh_TW dc.contributor.advisor Wen, Chao Tung en_US dc.contributor.author (Authors) 劉惟成 zh_TW dc.contributor.author (Authors) Liu, Wei Cheng en_US dc.creator (作者) 劉惟成 zh_TW dc.creator (作者) Liu, Wei Cheng en_US dc.date (日期) 2013 en_US dc.date.accessioned 29-Jul-2014 16:19:08 (UTC+8) - dc.date.available 29-Jul-2014 16:19:08 (UTC+8) - dc.date.issued (上傳時間) 29-Jul-2014 16:19:08 (UTC+8) - dc.identifier (Other Identifiers) G0101359003 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/67939 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 科技管理與智慧財產研究所 zh_TW dc.description (描述) 101359003 zh_TW dc.description (描述) 102 zh_TW dc.description.abstract (摘要) 隨著網路的普及與社群網站的興起，人們的購買行為也跟著改變，從傳統被動地接受企業的產品廣告來決定是否購買，到現在網路社群、網友口碑的力量已經成為人們購買產品或服務主要的參考依據，根據創市際市場研究顧問公司在2012年9月所做的調查發現，大約有53%的消費者會在網路上對商品做評論，且當對商品很滿意時，其上網評論的意願會增加，此調查也發現，網路口碑對於消費者的購買決策具有相當大的影響力，有93%的消費者會上網尋找網路口碑資訊，企業對於網路口碑的影響力實在不可不重視。網路口碑的監測可以提供企業掌握市場上消費者對於產品或服務的反應與評價，但傳統上透過人力搜尋的方式，或自行架設官方討論區的方式來取得網友回饋，都有見樹不見林的窘況，而近年Big Data技術的發展，可以讓企業透過相對低廉的運算成本來進行全面的資料蒐集與分析，提供企業更完整的網路口碑概況，掌握最即時的市場動態。市場上近來也出現導入Big Data技術，提供網路口碑監測服務的第三方公司，而本研究希望探討的是，透過Big Data技術進行網路口碑監測服務的公司，必須擁有何種的核心能力？而這樣的服務到底可以為客戶提供何種價值？最後網路口碑監測服務要如何獲利？本研究藉由個案公司與相關單位的訪談，並輔以獲利世代一書所提出的商業模式九大要素來進行驗證，完整勾勒出網路口碑監測服務的商業模式。本研究最後發現，資訊技術能力是網路口碑監測服務最主要的核心能力，是維持其服務品質的重要基石。不過表面上看來以Big Data來進行網路口碑監測，可以幫助企業在行銷策略上有進一步深入的洞察，但因企業普遍習慣將行銷活動外包給行銷公關公司執行，此網路口碑監測服務對於企業而言，無法完整發揮原先所期待的價值，反而對於行銷公關公司來說，是個可以提升其服務附加價值的工具。最後利用Big Data技術進行分析，並利用雲端的概念提供客戶網路口碑監測服務的應用，具有規模經濟的效果，不過因目前企業限於傳統行銷思維與既有管理制度，要能夠吸引大量企業採用網路口碑監測服務，仍需耗費相當大的資源成本，對客戶進行教育及推廣。 zh_TW dc.description.abstract (摘要) With the popularity of the Internet and the rise of social networking sites, people changed their shopping behaviors. In the past, people passively received advertisements from enterprises and made buying decisions. Today, social network and electronic word of mouth (e-WOM) have become powerful strengths to influence people’s buying decisions. According to the survey of InsightXplorer market consulting corporation in 2012, 53% of customers would make online comments about the products they bought and 93% of customers would search online information before shopping. Obviously, the power of e-WOM is deeply influencing the business.e-WOM monitoring helps corporations to understand the preferences of consumers; but traditionally, enterprises collect online responses of consumers by manual searching operations or building official forum websites. This is found not to be an efficient method. Recently, with the trends of Big Data technology, it benefits enterprises to collect and analyze the complete e-WOM information with lower computing costs. Furthermore, enterprises can handle the real-time market dynamics.There are several enterprises that provide e-WOM monitoring service by using Big Data technology. This thesis is to investigate three questions: 1.) What is the core capability of the enterprises that use Big Data to provide e-WOM monitoring service? 2.) What kinds of value to clients does the e-WOM monitoring service provide with Big Data? 3.) How to make profit with e-WOM monitoring service using Big Data? This thesis describes the business models of e-WOM monitoring service using Big Data through the case study and interviews with the people in related enterprises. The findings are described in below:1. Information technology is the core capability of e-WOM monitoring service by using Big Data technology.2. The enterprises were used to outsource their marketing campaigns to marketing companies. Surprisingly, the e-WOM monitoring service help marketing companies to improve their service values instead of bringing more value to the enterprises3. Using Big Data and cloud computing technology can achieve economies of scale effect, but current enterprises are limited to the traditional marketing concepts and management systems. Attracting more enterprises to adopt e-WOM monitoring service is a big challenge. en_US dc.description.tableofcontents 中文摘要 I英文摘要 II誌謝 III目錄 IV圖目錄 VI表目錄 VII第一章 緒論 1第一節 研究動機與背景 1第二節 研究目的與問題 4第三節 研究流程 5第二章 文獻探討 6第一節 Big Data 6第二節 網路口碑 14第三節 商業模式 17第三章 研究設計與方法 25第一節 研究架構 25第二節 研究方法 26第三節 研究對象 26第四節 資料蒐集方式 27第四章 個案研究 30第一節 個案背景介紹 30第二節 OpView社群口碑監測平台 32第三節 相關訪談單位 45第五章 研究發現與討論 54第一節 企業面 55第二節 價值面 59第三節 客戶面 61第四節 財務面 66第五節 其他研究發現 68第六節 問題討論 71第六章 結論與建議 73第一節 研究結論 73第二節 研究貢獻 76第三節 研究限制 77第四節 未來研究方向與建議 77參考文獻 79 zh_TW dc.format.extent 2618658 bytes - dc.format.mimetype application/pdf - dc.language.iso en_US - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0101359003 en_US dc.subject (關鍵詞) 海量資料 zh_TW dc.subject (關鍵詞) 網路口碑 zh_TW dc.subject (關鍵詞) 商業模式 zh_TW dc.subject (關鍵詞) Big Data en_US dc.subject (關鍵詞) e-WOM en_US dc.subject (關鍵詞) business model en_US dc.title (題名) Big Data應用於網路口碑監測服務之商業模式研究 －以意藍科技為例 zh_TW dc.title (題名) Exploring the Business Model of e-WOM Monitoring Services with the Application of Big Data – A Case Study of eLand Tech en_US dc.type (資料類型) thesis en dc.relation.reference (參考文獻) 一、 中文文獻Osterwalder, A., & Pigneur, Y. (2012). 獲利世代: 早安財經文化.Rosen, E. (2001). 口碑行銷: 遠流.城田真琴. (2013). 大數據的獲利模式: 經濟新潮社.柯承恩. (2008). 商業模式與文化產業發展在台灣. 經濟前瞻, 118, 104-112. 胡世忠. (2013). 雲端時代的殺手級應用 海量資料分析: 天下雜誌.麥爾荀伯格、庫基耶. (2013). 大數據: 天下文化.資策會. (2013). 2013臺灣消費者科技應用生活型態研究分析報告.廖佩怡. (2006). 實體與網路的口碑之比較：資訊特性觀點之探索性研究. (碩士), 國立臺北科技大學. 蔡政安. (2013). 商業模式初探 餐飲服務業之個案研究. 創業管理研究, 8(4), 1-26. 謝松齡. (2008). 網路商店進行網路口碑管理之研究－以網路化妝品商店為例. (碩士), 政治大學. 鍾采霏. (2013). 智慧型手機應用程式之商業模式分析. (碩士), 政治大學. 二、 英文文獻Afuah, A., & Tucci, C. L. (2000). Internet business models and strategies: Text and cases: McGraw-Hill Higher Education.Amit, R., & Zott, C. (2001). Value creation in e‐business. Strategic management journal, 22(6‐7), 493-520. Applegate, L. M. (2001). Emerging e-business models. Harvard business review, 79-87.Arndt, J. (1967). Role of Product-Related Conversations in the Diffusion of a New Product. Journal of Marketing Research (JMR), 4(3). 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. Benbasat, I., Goldstein, D. K., & Mead, M. (1987). The case research strategy in studies of information systems. MIS quarterly, 11(3). Brown, J. J., & Reingen, P. H. (1987). Social ties and word-of-mouth referral behavior. Journal of Consumer research. Buttle, F. A. (1998). Word of mouth: understanding and managing referral marketing. Journal of strategic marketing, 6(3), 241-254. Chatterjee, P. (2001). Online reviews: do consumers use them? Advances in consumer research, 28(1). Gelb, B. D., Suresh Sundaram. (2002). Adapting to Word of Mouse. Business Horizons, 45(4), 21-25. Hanson, W. A. (2000). Principles of Internet Marketing.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. Johnson, M. (2010). Seizing the white space. Massachusetts: Harvard Business Press. OpenURL. Johnson, M. W., Christensen, C. M., & Kagermann, H. (2008). Reinventing your business model. Harvard business review, 86(12), 57-68. Lindgart, Z., Reeves, M., Stalk, G., & Deimler, M. S. (2009). Business Model Innovation. When the game gets though, change the game, The Boston Consulting Group. Möller, K., Rajala, A., & Svahn, S. (2005). Strategic business nets—their type and management. Journal of Business research, 58(9), 1274-1284. Magretta, J. (2002). Why business models matter. Magretta, J. (2011). Understanding Michael Porter: The essential guide to competition and strategy: Harvard Business Press.Mahadevan, B. (2000). Business Models for Internet-Based E-Commerce: AN ANATOMY. California management review, 42(4). Markides, C. C. (1999). A dynamic view of strategy. Sloan Management Review, 40(3), 55-63. MGI. (2011). Big Data: The next frontier for innovation, competition, and productivity.Osterwalder, A., & Pigneur, Y. (2010). 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