現在位置首頁 > 博碩士論文 > 詳目
論文中文名稱:探討學生族使用智慧型手機App與行動電信業者忠誠度之關係 [以論文名稱查詢館藏系統]
論文英文名稱:Exploring the Mobile Telecommunication Companies Loyalty Associated with the Use of Smartphone App within Student Groups [以論文名稱查詢館藏系統]
院校名稱:臺北科技大學
學院名稱:管理學院
系所名稱:管理學院資訊與財金管理EMBA專班
畢業學年度:104
畢業學期:第二學期
出版年度:105
中文姓名:何冠樟
英文姓名:Kuan-Chang Ho
研究生學號:103C23508
學位類別:碩士
語文別:中文
口試日期:2016/05/27
指導教授中文名:吳建文
指導教授英文名:Chien-Wen Wu
口試委員中文名:陳育威;李炯三
口試委員英文名:Yu-Wei Chen;Chiung-San Lee
中文關鍵詞:智慧型手機App、項目集探勘、行動電信、顧客忠誠度
英文關鍵詞:Smartphone App, Itemset mining, Mobile Telecommunication, Loyalty
論文中文摘要: 隨著資通訊科技創新、工商產業活動發達,以及人類追求便捷的生活,行動通信已經成為人與人溝通最重要的管道,而個人行動通訊技術已經由最早的第一代行動通訊系統發展至現在的第四代行動通訊系統,同時手機設備也由功能型手機發展到智慧型手機。
 本研究針對目前較常用的智慧型手機App(包含facebook、LINE、WeChat、skype、Dropbox、Google Drive),結合項目集探勘技術,試圖找出學生族使用智慧型手機App與行動電信業者忠誠度之關係,以期提供剛開台營運的4G行動電信業者,對於新顧客的開發及其行銷策略有進一步的幫助。
 本研究結果發現行動電信業學生族的顧客忠誠度很高,學生族一旦決定使用就會用很久,有35%的學生族使用時間長達5年以上,有93%的學生族每天都會使用行動上網,有75%的學生族能接受的月租資費是在300元~未滿900元之間,有38%的學生族選用智慧型手機品牌比較偏愛Apple,學生族使用ASUS智慧型手機並且每週都搭配facebook App、LINE App、WeChat App、Google Drive App其中一種App使用的顧客忠誠度很高,有95%的學生族每天都會使用LINE App,使用LINE App的學生族中42%有付費的意願。
論文英文摘要:  With the information and communication technology innovation, industrial and commercial progress, and people seek convenient life, the mobile communications have become the most important communication channel between people. The personal mobile communications technology has been developed from the first generation of mobile communication system to the fourth generation of mobile communication system now. The mobile phone devices have been developed from the feature phone to smartphone.
  In this study, we focus on some of popular smartphone Apps, such as facebook, LINE, WeChat, skype, Dropbox and Google Drive, and combine itemset mining technology to figure out the mobile telecommunication companies loyalty associated with the use of smartphone app within student groups. This will help 4G mobile telecommunication companies to develop new customers campaign and marketing strategy.
  The results of this study found that mobile telecommunications within student groups have high customer loyalty. A student once decided to use will become a long term user. 35% of the students use the mobile telecommunication more than five years. 93% of the students use mobile internet every day. 75% of the students can accept a monthly fee between NT$300 to less than NT$900. 38% of the students choose a smartphone would prefer Apple brand. Those students who use ASUS smartphone and one of the following App, such as facebook, LINE, WeChat and Google Drive weekly have high customer loyalty. 95% of the students use LINE App every day. 42% of the LINE App student users are willing to pay for service.
論文目次:中文摘要 i
ABSTRACT ii
誌謝 iv
目錄 v
表目錄 vii
圖目錄 viii
第一章 緒論 1
1.1 研究背景與動機 1
1.2 研究目的 2
1.3 研究範圍與方法 2
1.4 研究流程與架構 3
第二章 文獻探討 4
2.1 國內行動電信產業發展概況 4
2.2 智慧型手機與應用程式App定義 5
2.3 顧客忠誠度定義 6
2.4 各式項目集探勘技術介紹及國內外相關研究 8
2.4.1 高頻項目集探勘 8
2.4.2 限制項目集探勘 10
2.4.3 最佳項目集探勘 12
第三章 研究方法 13
3.1 研究步驟 13
3.2 設計問卷 14
3.3 收集資料 14
3.4 項目集探勘分析 15
第四章 研究分析及結果 18
4.1 問卷發放及回收統計分析及結果 18
4.2 敘述性統計分析及結果 18
4.2.1 基本資料統計分析及結果 18
4.2.2 電信使用資料統計分析及結果 22
4.2.3 手機使用資料統計分析及結果 26
4.2.4 facebook App使用資料統計分析及結果 28
4.2.5 LINE App使用資料統計分析分析及結果 30
4.2.6 WeChat App使用資料統計分析及結果 32
4.2.7 skype App使用資料統計分析及結果 33
4.2.8 Dropbox App使用資料統計分析及結果 35
4.2.9 Google Drive App使用資料統計分析及結果 36
4.3 項目集探勘分析及結果 38
4.3.1 基本資料以項目集探勘分析及結果 38
4.3.2 電信使用資料以項目集探勘分析及結果 41
4.3.3 智慧型手機使用資料以項目集探勘分析及結果 43
4.3.4 智慧型手機App使用資料以項目集探勘分析及結果 45
第五章 研究結論與建議 49
5.1 結論 49
5.2 建議 51
5.3 研究限制 52
參考文獻 53
附錄
附錄A 問卷 56
論文參考文獻:丁鴻裕 (2011),消費者行動App使用現況分析,臺北:財團法人資訊工業策進會產業情報研究所(MIC)。
王國壎 (2011),以智慧型手機為核心之智慧生活應用系統開發,碩士論文,國立臺北科技大學機電整合研究所,臺北。
洪玉屏 (2011),熱門手機遊戲之研究-以台灣之Appstore為例,碩士論文,國立臺北科技大學工業工程與管理系,臺北。
徐誠良 (2009),服務品質、轉換成本、顧客滿意度與顧客忠誠度之研究-電信服務業實證,碩士論文,國立臺北科技大學商業自動化與管理研究所,臺北。
陳俊嘉 (2015),群組通訊系統在LTE公眾網路之雲端應用,碩士論文,國立臺北科技大學資訊與財金管理系,臺北。
張永侖 (2011),國內旅遊結合智慧型手機之行動旅遊應用服務模式-以探索台灣為例,碩士論文,國立臺北科技大學工業工程與管理系,臺北。
張琳禎 (2014),品牌真實性與購買意願關係之研究-以智慧型手機品牌為例,博士論文,國立臺北科技大學技術及職業教育研究所,臺北。
葉宗文 (2014),智慧型手機使用者需求之研究,碩士論文,國立臺北科技大學創新設計研究所,臺北。
廖如閔 (2014),手機應用軟體使用者瀏覽行為分群之研究,碩士論文,國立臺北科技大學工業工程與管理系,臺北。
劉明毅 (2011),電信公司執行風險管理機制之事項潛在後果與風險辨識關連研究,碩士論文,國立臺北科技大學商業自動化與管理研究所,臺北。
鄭玉世 (2013),品牌策略、品牌形象、顧客忠誠度與品牌權益之研究 - 以手機產業為例,碩士論文,國立臺北科技大學經營管理系,臺北。
蕭子翔 (2013),服務品質、企業形象與顧客忠誠度之研究- 以中華電信行動電話服務為例,碩士論文,國立高雄應用科技大學資訊管理系,高雄。
Agrawal, R. and Srikant, R. (1994), Fast Algorithms for Mining Association Rules, In: Proceedings of the 20th International Conference on Very Large Data Bases, 487-499.
Agarwal, R. C., Aggarwal, C. C. and Parsad, V. V. V. (2001), A Tree Projection Algorithm for Generation of Frequent Item Sets, Journal of Parallel and Distributed Computing, 61(3), 350-371.
Bonchi, F., Giannotti, F., Mazzanti, A. and Pedreschi, D. (2003a), ExAMiner: optimized level-wise frequent pattern mining with monotone constraints, Proceedings of the Third IEEE International Conference on Data Mining.
Bonchi, F., Giannotti, F., Mazzanti, A. and Pedreschi, D. (2003b), ExAnte: Anticipated Data Reduction in Constrained Pattern Mining, Proceedings of the 7th European Conference on Principles and Practice of Knowledge Discovery in Databases.
Burdick, D., Calimlim, M. and Gehrke, J. (2001), MAFIA: a maximal frequent itemset algorithm for transactional databases, In: Proceedings of the 17th International Conference on Data Engineering, Heidelberg, 443-452.
Chang, T., Lee, J. and Chen, R. (2008), The Effects of Customer Value on Loyalty and Profits in a Dynamic Competitive Market, Computational Economics, 32(3), 317.
Cheung, Y. L. and Fu, A. W. (2002), FP-tree Approach for Mining N-most Interesting Itemsets, Proceedings of the SPIE Conference on Data Mining.
Fornell, C. (1992), A National Customer Satisfaction Barometer: The Swedish Experience, Journal of Marketing, 56(1), 6-21.
Fu, A. W., Kwong, R. W. and Tang, J. (2000), Mining N-most Interesting Itemsets, Proceedings of International Symposium on Methodologies for Intelligent Systems, 59-67.
Gouda, K. and Zaki, M. J. (2001), Efficiently mining maximal frequent itemsets, In: Proceedings of IEEE International Conference on Data Mining, San Jose, 163-170.
Griffin, J. (1995), “Customer loyalty : how to earn it, how to keep it”, Lexington Book, New York.
Gronholdt, L., Martensen, A., and Kristensen, K. (2000), The relationship between Customer Satisfaction and Loyalty: Cross Industry differences, Total Quality Management, 11(4), 509-514.
Heskett, J. L., Jones, T. O., Loveman, G. W., Sasser, W. E. and Schlesinger, L. A. (1994), Putting the service-profit chain to work, Harvard Business Review, 72(2), 164-172.
Hong, S. C. and Goo, Y. J. (2004), A Causal Model of Customer Loyalty in Professional Service Firms: An Empirical Study, International Journal of Management, 21(4), 531-540.
Ng, R. T., Lakshmanan, L. V. S., Pang, A. and Han, J. (1998), Exploratory Mining and Pruning Optimizations of Constrained Associations Rules, Proceedings of the 1998 ACM SIGMOD International Conference on Management of Data.
Oliver, R. L. (1997), Satisfaction: a behavioral perspective on the consumer, McGraw Hill, New York.
Parasuraman, A., Zeithaml, V. A. and Berry, L. L. (1994), Improving Service Quality in America: Lessons Learned, Academy of Management Executive, 8(2), 32-52.
Park, J. S., Chen, M. S. and Yu, P. S. (1997), Using a hash-based method with transaction trimming for mining association rules, IEEE Transactions on Knowledge and Data Engineering, 9(5), 813-825.
Prayag G. and Ryan C. (2012), “Antecedents of Tourists' Loyalty to Mauritius: The Role and Influence of Destination Image, Place Attachment, Personal Involvement, and Satisfaction”, Journal of Travel Research, 51(3), 342-356.
Rauyruen, P. and Miller, K. E. (2007), Relationship Quality as a Predictor of B2B Customer Loyalty, Journal of Business Research, 60(1), 21-31.
Reichheld, F. F. and Sasser, W. E. (1990), Zero defections: quality comes to services, Harvard Business Review, 68(5), 105-111.
Reynolds, F. D., Darden, W. R. and Martin, W. S.(1974), Developing an Image of the Store-Loyal Customer, Journal of Retailing, 50(4), 73-84.
Savasere, A., Omiecinski, E. and Navathe, S. (1995), An Efficient Algorithm for Mining Association Rules in Large Databases, In: Proceedings of the 21st International Conference on Very Large Data Bases, 432-444.
Selnes, F. (1993), “An examination of the Effect of Product Performance on Brand Reputation, Satisfaction and Loyalty”, European Journal of Marketing, 27(1), 19-35.
Stum, D. L. and Thiry, A. (1991), Building customer loyalty, Training and Development, 45(4), 34-36.
Uncles, M. D., Dowling, G. R. and Hammond, K. (2003), Customer loyalty and customer loyalty programs, Journal of Consumer Marketing, 20(4), 294- 316.
Wu, C. (2002a), The Problem of Mining the Most Profitable Frequent Itemset, Proceedings of the 4th International Conference on Electronic Commerce, in CD-ROM.
Wu, C. (2002b), On Mining the Longest Frequent Itemset, Proceedings of the 17th International Conference on Computers and Their Applications, 122-125.
Wu, C. (2003), Exactly Mining the Longest Frequent Itemset, Proceedings of the 2003 International Conference on Technology and Management, Taipei, Taiwan, in CD-ROM.
Zou, Q., Chu, W. W. and Lu, B. (2002), SmartMiner: a depth first algorithm guided by tail information for mining maximal frequent itemsets, In: Proceedings of IEEE International Conference on Data Mining, 570-577.
論文全文使用權限:不同意授權