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    政大典藏 > College of Commerce > MBA Program > Theses >  Item 140.119/136731


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    Title: 探討文字探勘於商業策略優化之應用 - 以戶外婚宴會館產業為例
    Exploring the Application of Text Mining in Optimizing Business Strategy : A Case Study of Outdoor Wedding Banquet Industry
    Authors: 簡廷軒
    Chien, Ting-Hsuan
    Contributors: 羅明琇
    簡廷軒
    Chien, Ting-Hsuan
    Keywords: 文字探勘
    網路爬蟲
    主題分析
    詞頻分析
    婚宴會館
    戶外婚禮
    Text Mining
    Web Crawler
    Topic Model Analysis
    Word Frequency Analysis
    Wedding Hall
    Outdoor Wedding
    Date: 2021
    Issue Date: 2021-08-04 16:38:03 (UTC+8)
    Abstract: 近幾年結婚的風潮改變，結婚年齡增加、結婚率下降，造成整個結婚產業有很大的變動，整體市場的需求變少，並且近年來新人對於結婚的觀念轉變，多追求客製化與精緻路線，歐式戶外婚禮的風氣逐漸興盛，許多傳統的飯店業者因此加入戰局，因此原先就以戶外婚禮為主打的業者，必須更加了解消費者的需求，強化自身的服務與品牌定位，才能因應市場的衝擊。
    本研究採用Python程式語言撰寫網路爬蟲並建立LDA主題模型，以Google Map評論與結婚吧討論區的評論與貼文作為資料集，並以台北與桃園地區代表性的戶外婚宴會館業者作為對象，透過詞頻與主題模型，從競爭者與消費者兩個角度進行分析。
    從競爭者的角度來看，評論者最在意的內容大致可以分為服務、環境與餐點，而不同的角色（新人、賓客）對此會有不同在意的點。並且以網路評論而言，賓客相較於真正做出購買決策的新人來說，數量差距很大，也更有影響力；因此除了要顧及新人的考量因素以外，也須讓賓客感到滿意，才能提升評論的星數。
    從消費者的角度來看，本研究發現婚紗挑選與攝影為消費者投入程度較高的兩個主題，而本研究最為在意的婚禮場地主題則投入程度一般，顯示時代潮流造成新人意識的改變，可能多還是體現在婚紗與攝影上，因此也建議婚宴會館業者也可以採取異業結盟的方式，與同產業中互補的廠商進行合作。
    In recent years, the trend of marriage has changed. The marriage age has increased and the marriage rate has decreased. This has caused great changes in the entire marriage industry. The overall market demand has decreased and turn into exquisite and customized. European style outdoor weddings are gradually prospering, and many traditional hotels have joined the battle. Therefore, those who originally focused on outdoor weddings must better understand the needs of consumers and strengthen their service and brand positioning in order to respond to the impact of the market.
    This research uses Python as the programming language to write a web crawler and build an LDA topic model. It uses comments and posts in Google Map and Marry Bar as a data set, and uses representative outdoor wedding banquet operators in Taipei and Taoyuan as the target. Through word frequency and topic model, analysis is carried out from the perspectives of competitors and consumers.
    From a competitor’s point of view, the content that reviewers care most about can be roughly divided into service, environment, and meals, and different roles like prospective couples or guests will have different concerns. And in terms of online reviews, compared with prospective couples who actually make purchase decisions, there is a big gap in the number of guests, and they are also more influential. Therefore, in addition to considering the prospective couples, the guests must also be satisfied in order to increase the number of stars in the review.
    From the perspective of consumers, this study finds that wedding dress selection and photography are two topics that consumers have a high degree of attention, while the topic of the wedding venue that this study cares most has an average degree of attention, which shows that the trend of the times has caused a change in the thoughts of prospective couples. It may still be reflected in wedding dresses and photography. Therefore, it is also recommended that wedding banquet operators can also adopt cross-industry alliances and cooperate with complementary players in the same industry.
    Reference: 一、 中文部分
    1. 江明晏（2020）。後疫情時代，飯店業揭婚宴4大趨勢。經濟日報。取自：https://money.udn.com/money/story/5612/5118889
    2. 李杰恩（2020）。價格與線上評論對新產品擴散之影響－以Amazon網站為例。未出版碩士論文，中國文化大學國際企業管理學系，台北市。
    3. 卓怡君（2008）。台灣結婚消費發展趨向。臺灣經濟研究月刊，31卷12期，P37-44。
    4. 林庭安（2019）。一年少10000對新人結婚！為何婚宴場館仍一直開、業者搶著進入？。經理人。取自：
    https://www.managertoday.com.tw/articles/view/57079
    5. 林瑞麟(2009)。網路社群創新行銷之研究-以婚宴產業為例。未出版碩士論文，淡江大學企業管理學系碩士在職專班，新北市。
    6. 高宗郁（2019）。以線上消費者評論呈現形式與電子商務網站內容探討消費者之購買意圖。未出版碩士論文，國立中央大學資訊管理學系，桃園市。
    7. 張金印 (2010)。大台北都會區消費者對婚禮企劃服務認知之研究。未出版碩士論文，經國管理暨健康學院健康產業管理研究所，基隆市。
    8. 莊士萱（2021）。應用文字探勘技術探索臺灣天梯型旅遊體驗之研究。未出版碩士論文，國防大學資訊管理學系，桃園縣。
    9. 莊淑惠、林鴻南、吳政霈(2014) 。線上產品評論對消費者購買意圖之影響：認知需求與產品知識調節效果之探討。管理評論，33(4)。
    10. 陳庭暄 (2010) 。 客制化婚宴新人滿意度之研究: 體驗觀點。未出版碩士論文，國立高雄餐旅學院，高雄市。
    11. 黃俊堯、柳秉佑(2016)。消費者線上口碑與評論研究：國內外相關文獻回顧與討論，臺大管理論叢，26卷3期：215-256。
    12. 經濟部商業司(2009)：結婚產業研究暨整合拓展計畫。台北：經濟部商業司。
    13. 葉晉嘉（2013）。微型創意產業的服務接觸與行銷－以婚禮顧問業為例。行銷評論，10卷4期，P381-408。
    14. 羅凱揚、蘇宇暉（2018）。讓心動顧客即刻下單的關鍵-線上評論分析。上網日期110年5月15日，檢自：https://medium.com/marketingdatascience/讓心動顧客即刻下單的關鍵-線上評論分析-online-review-analytics-ae5c33e8eb43

    二、 英文部分
    1. Allahyari, M., Pouriyeh, S., Assefi, M., Safaei, S., Trippe, E. D., Gutierrez, J. B., & Kochut, K. (2017). Text summarization techniques: a brief survey. arXiv preprint arXiv:1707.02268.
    2. Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. the Journal of machine Learning research, 3, 993-1022.
    3. Chen, K. J., & Liu, S. H. (1992). Word identification for Mandarin Chinese sentences. In COLING 1992 Volume 1: The 15th International Conference on Computational Linguistics.
    4. Christos Faloutsos and Douglas W Oard. 1998. A survey of information retrieval and filtering methods. Technical Report.
    5. Desai, K., Devulapalli, V., Agrawal, S., Kathiria, P., & Patel, A. (2017). Web Crawler: Review of Different Types of Web Crawler, Its Issues, Applications and Research Opportunities. International Journal of Advanced Research in Computer Science, 8(3).
    6. Goldberg, Y. (2017). Neural network methods for natural language processing. Synthesis lectures on human language technologies, 10(1), 1-309.
    7. Grishman, R. (2019). Twenty-five years of information extraction. Natural Language Engineering, 25(6), 677-692.
    8. Kobayashi, V. B., Mol, S. T., Berkers, H. A., Kismihók, G., & Den Hartog, D. N. (2018). Text mining in organizational research. Organizational research methods, 21(3), 733-765.
    9. Li, G. C., Liu, K. Y., & Zhang, Y. K. (1988). Identifying Chinese Word and Processing Different Meaning Structures. Journal of Chinese Information Processing, 2, 45-53.
    10. Mitchell, T. M. (1997). Machine learning. 1997. Burr Ridge, IL: McGraw Hill 45.
    11. Saxena, A., Prasad, M., Gupta, A., Bharill, N., Patel, O. P., Tiwari, A., ... & Lin, C. T. (2017). A review of clustering techniques and developments. Neurocomputing, 267, 664-681.Steyvers, M., & Griffiths, T. (2007). Probabilistic topic models. Handbook of latent semantic analysis, 427(7), 424-440.
    12. Zhai, C., & Massung, S. (2016). Text data management and analysis: a practical introduction to information retrieval and text mining. Association for Computing Machinery and Morgan & Claypool.
    Description: 碩士
    國立政治大學
    企業管理研究所(MBA學位學程)
    108363081
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0108363081
    Data Type: thesis
    DOI: 10.6814/NCCU202100667
    Appears in Collections:[MBA Program] Theses

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