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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 黃恆獎(Heng-Chiang Huang) | |
| dc.contributor.author | Yu-Yin Chang | en |
| dc.contributor.author | 張毓吟 | zh_TW |
| dc.date.accessioned | 2022-11-23T09:00:20Z | - |
| dc.date.available | 2021-11-05 | |
| dc.date.available | 2022-11-23T09:00:20Z | - |
| dc.date.copyright | 2021-11-05 | |
| dc.date.issued | 2021 | |
| dc.date.submitted | 2021-10-20 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/79432 | - |
| dc.description.abstract | 過去的研究說明擁有成功的全球品牌不僅能擴大公司利益，並有助於承受市場變動風險。然而想要基業長青的全球品牌，不僅需要具備競爭優勢，還要能與時俱進。觀察市場上知名的全球品牌排名年度報告，總有助於提高品牌所屬公司的股票價格，並進而促進績效表現，但由於現有文獻缺乏從歷史觀點來對進行整體研究，因此成功的全球品牌的描述與演變仍然不清楚。本研究採用數據挖掘方法來分析，首先從 Interbrand 於2001 年至 2017 年期間的最佳全球品牌排名列表中，收集的時間序列數據進行研究。再運用親和力傳播聚類算法（AP:affinity propagation clustering algorithm），分析出品牌演化的不同集群，分別為快速上升者、頂尖、穩定、緩長、衰退、暴跌及不一致等。再者，增加了 2018 年至 2020 年的排名與品牌價值，以提供對品牌未來發展的預測可能。 最後，再加上BrnadZ 與Forbes這二種不同品牌排名的資料，使得此項研究的結果更完備並具有重要的營銷意義，該方法的確是能作為數據分析的初步分類，亦可作為後續研究的基礎。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2022-11-23T09:00:20Z (GMT). No. of bitstreams: 1 U0001-1710202101391700.pdf: 4622211 bytes, checksum: 2367a89f7e7ab785628072b594b8f868 (MD5) Previous issue date: 2021 | en |
| dc.description.tableofcontents | "Table of Contents 口試委員會審定書 ……………………………………………………………………………… i 誌謝 ………………………………………………………………………………………………………… ii 摘要 ………………………………………………………………………………………………………… iii Abstract ……………………………………………………………………………………………. iv Table of contents……………………………………………………………….. v List of figures …………………………………………………………………… vii List of tables ……………………………………………………………………. vii 1. Introduction………………………………………………………………….. 1 2. Literature review……………………………………………………………. 5 2.1 Global branding …………………………………………..………… 5 2.2 Brands valuation methods ………………………………… 7 2.3 Global brands ranking related researches…………… 11 3. Methodology …………………………………………………………………………… 13 3.1 Materials and data source …………..………………………….……. 13 3.2 Affinity propagation clustering algorithm ………… 13 3.3 Process ……………………………………………………………………………………………… 17 4. Results …………………………………………………………………………………. 19 4.1 Profile of the best global brands from 2001 to 2017………………………. 19 4.2 Trends of evolution based on the value of the ranking …………………. 21 4.3 Mapping the evolution trend of Interbrand’s rankings from 2018 to 2020 … 36 4.4 Compare the profile of different global brands rankings from 2018 to 2020... 41 4. 5 Compare the different annual brand rankings from 2018 to 2020………………………… 45 5. Discussion and conclusions ………………………………………………………………………… 55 5.1 Research findings and discussion ……………………………………………………………. 55 5.2 Implications and applications ……………………………………………………….. 57 5.3 Limitation future research ….……………………………………………………………………………….. 58 Reference………………………………………………………………………………………………………………………………………………………………… 59 Appendix A. Interbrand’s best global brands from 2001 to 2017, ordered by 2017. 66 Appendix B. The Interbrand’s best global brand ranking data from 2018 to 2020. 72 Appendix C. The BrandZ ranking data from 2018 to 2020. (Order by 2020) …... 77 Appendix D. The Forbes ranking data from 2018 to 2020. (Order by 2020) ….... 81 " | |
| dc.language.iso | en | |
| dc.title | 探索成功全球品牌的演變型態 | zh_TW |
| dc.title | Exploring Patterns of Evolution for Successful Global Brands | en |
| dc.date.schoolyear | 109-2 | |
| dc.description.degree | 博士 | |
| dc.contributor.author-orcid | 0000-0002-8857-0520 | |
| dc.contributor.oralexamcommittee | 陳瑀屏(Hsin-Tsai Liu),江季芸(Chih-Yang Tseng),葛致慧,江宜芳 | |
| dc.subject.keyword | 全球品牌,品牌排名,時間序列數據挖掘,親和力傳播聚類集群分析演算法, | zh_TW |
| dc.subject.keyword | global brand,brand ranking,time-series data mining,affinity propagation clustering algorithm, | en |
| dc.relation.page | 85 | |
| dc.identifier.doi | 10.6342/NTU202103788 | |
| dc.rights.note | 同意授權(全球公開) | |
| dc.date.accepted | 2021-10-20 | |
| dc.contributor.author-college | 管理學院 | zh_TW |
| dc.contributor.author-dept | 國際企業學研究所 | zh_TW |
| 顯示於系所單位： | 國際企業學系 | |
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