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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 魏志平(Chih-Ping Wei) | |
| dc.contributor.author | Ai-Chia Pan | en |
| dc.contributor.author | 潘愛佳 | zh_TW |
| dc.date.accessioned | 2021-06-17T01:20:47Z | - |
| dc.date.available | 2020-08-11 | |
| dc.date.copyright | 2017-08-11 | |
| dc.date.issued | 2017 | |
| dc.date.submitted | 2017-08-10 | |
| dc.identifier.citation | Aaker, D. (1991). Managing Brand Equity. The Free Press, New York, NY.
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/67130 | - |
| dc.description.abstract | 品牌權益(brand equity)泛指企業因為其提供的產品或服務與品牌相聯繫，而能夠比沒有品牌的企業多獲得的市場效益，如品牌忠誠度及溢價銷售。衡量及定期追蹤品牌權益有助於品牌主了解行銷活動的成效，並制定行銷決策與品牌策略。而品牌聯想(brand associations)是品牌權益的關鍵元素，企業在衡量品牌權益時，必須具備擷取並且分析自有品牌聯想網絡的能力。
傳統的品牌權益分析方法通常依靠消費者問卷調查，因此產生諸多限制，例如較高的時間成本、難以招募合適的受訪者，以及無法追蹤突發事件對品牌權益的影響。針對品牌聯想的部分，分析也通常侷限於讓受訪者對品牌的整體印象評分，即使包含了品牌聯想的喜愛度(favorability)、獨特性(uniqueness)及強度(strength)的維度，品牌主也無法確切知道與哪些品牌聯想有連結，進而針對特定的品牌聯想採取行動。 為了解決上述問題，本研究將運用文字分析與情緒分析的技術，提出一個消費者面向的品牌權益預測模型方法。我們透過自動化分析線上產品評論，並判斷具代表性的品牌聯想，進而建構出特定品牌的聯想網絡。我們提出的預測模型以此品牌聯想網絡為基礎，並發展出喜愛度、獨特性以及強度等驅動品牌權益的變因。研究結果發現，以我們提出的方法來處理社群媒體資料，能有效預測品牌權益且篩選出對品牌有代表性的品牌聯想。藉由我們的方法，品牌主也能夠分析品牌的種種聯想是否正面、獨特及強烈，進而更好的掌握品牌的優勢。 | zh_TW |
| dc.description.abstract | Brand equity refers to the incremental value endowed by a brand to a product or service compared to an unbranded counterpart. Firms with higher brand equity enjoy higher customer loyalty and command a price premium. Measuring and monitoring brand equity can help brand owners understand the effectiveness of marketing activity and support their business strategies. Brand associations are critical components of brand equity. To measure brand equity, it is essential for firms to understand their brand associations through extracting brand associations networks.
Traditional measurement of brand equity generally relies on consumer surveys and, thus, incurs several limitations, such as time-consuming, sampling difficulty, and inability to capture the impact of unexpected events on brand equity. The analysis of brand associations tends to be limited to assessment of general brand impressions as well. Brand owners thus have difficulty knowing which associations are linked with the brand and are unable to take actions for particular associations. In response, we apply the text analytics and sentiment analysis techniques to propose a customer-based brand equity (CBBE) prediction model. We automate the process to construct brand association networks for target brands and identify salient brand associations from online product reviews. The brand associations-based variables, including favorability, uniqueness and strength, are acquired from the constructed brand association network. Our proposed method is found to be able to elicit brand associations and predict CBBE effectively. Brand owners can also tell whether an association is favorable, unique and strong to make better use of brand strengths. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T01:20:47Z (GMT). No. of bitstreams: 1 ntu-106-R03749004-1.pdf: 2832698 bytes, checksum: fe63c28519f082f9f58a5e5f5b9e7aa5 (MD5) Previous issue date: 2017 | en |
| dc.description.tableofcontents | 誌謝 i
中文摘要 ii ABSTRACT iii CONTENTS iv LIST OF FIGURES vi LIST OF TABLES vii Chapter 1 Introduction 1 Chapter 2 Literature Review 7 2.1 Customer-based Brand equity 7 2.2 Brand Association Networks 14 Chapter 3 Methodology 17 3.1 Brand association Network Construction 17 3.1.1 Association Extraction 17 3.1.2 Association Grouping & Favorability Identification 19 3.1.3 Association Selection 20 3.1.4 Link Weighting 23 3.2 Customer-based Brand Equity Prediction 24 Chapter 4 Empirical Evaluation 29 4.1 Data 29 4.2 Deep Dive in Association Network Extraction 34 4.3 Evaluation Process of CBBE prediction 37 4.4 Results – Descriptive Statistics 39 4.5 Predictive Evaluation Result 43 4.5.1 Association Selection Methods & Global Threshold Setting 43 4.5.2 Evaluations of Alternatives for Uniqueness Variable 44 4.5.3 Prediction Effectiveness Using Machine Learning Algorithms 45 Chapter 5 Conclusion 47 5.1 Summary 47 5.2 Future works 48 References 51 Appendix A: Scales for Measuring Consumer-based Brand Equity 58 Appendix B: List of Airlines Included in This Study 59 | |
| dc.language.iso | en | |
| dc.subject | 線上評論 | zh_TW |
| dc.subject | 品牌聯想 | zh_TW |
| dc.subject | 文件探勘 | zh_TW |
| dc.subject | 社群媒體分析 | zh_TW |
| dc.subject | 品牌權益 | zh_TW |
| dc.subject | Brand Equity | en |
| dc.subject | Online Product Reviews | en |
| dc.subject | Social Media Analytics | en |
| dc.subject | Text Mining | en |
| dc.subject | Brand Associations | en |
| dc.subject | Social Media | en |
| dc.title | 應用社群媒體分析於品牌權益預測之研究 | zh_TW |
| dc.title | Social Media Analytics for Supporting Customer-based Brand Equity Prediction | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 105-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 吳基逞(Chi-Cheng Wu),盧信銘(Hsin-Min Lu) | |
| dc.subject.keyword | 線上評論,社群媒體分析,文件探勘,品牌聯想,品牌權益, | zh_TW |
| dc.subject.keyword | Social Media,Online Product Reviews,Social Media Analytics,Text Mining,Brand Associations,Brand Equity, | en |
| dc.relation.page | 59 | |
| dc.identifier.doi | 10.6342/NTU201702878 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2017-08-11 | |
| dc.contributor.author-college | 管理學院 | zh_TW |
| dc.contributor.author-dept | 企業管理碩士專班 | zh_TW |
| 顯示於系所單位： | 管理學院企業管理專班(Global MBA) | |
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| ntu-106-1.pdf 未授權公開取用 | 2.77 MB | Adobe PDF |
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