簡易檢索 / 詳目顯示

研究生: 林裕傑
Lin, Yu-Chieh
論文名稱: 文字探勘技術應用於顧客評論以提升服務品質之研究:以某連鎖健身房品牌為例
Research on Applying Text Mining Techniques to Customer Reviews to Enhance Service Quality: A Case Study of a Chain Fitness Center Brand
指導教授: 周世玉
Chou, Shih-Yu
口試委員: 周世玉
Chou, Shih-Yu
施人英
Shih, Jen-Ying
蔡明志
Tsai, Ming-Chih
口試日期: 2024/05/15
學位類別: 碩士
Master
系所名稱: 管理研究所
Graduate Institute of Management
論文出版年: 2024
畢業學年度: 112
語文別: 中文
論文頁數: 68
中文關鍵詞: 連鎖健身房線上評論文字探勘情感分析
英文關鍵詞: Gym Chains, Online Reviews, Text Prospecting, Sentiment Analysis
研究方法: 文字探勘
DOI URL: http://doi.org/10.6345/NTNU202400866
論文種類: 學術論文
相關次數: 點閱:184下載:9
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報

連鎖健身房的出現為都會區的人們提供便利及多元的運動環境,如今辦理俱樂部會員資格及參與健身房課程,不再是高收入族群的專屬休閒活動,連鎖健身房透過親民的價格,多型態的健身服務,接觸學生、小資族及白領客群,為企業開拓廣大的服務客群。然而,健身房會員與業者消費糾紛卻層出不窮,對雙方而言,損失的不只是金錢與時間精力,也造成消費者對品牌的負面情緒及不信任,長此以往將傷害品牌形象及價值。
隨著網際網路的普及,人們經常通過網路新聞、社群平台,線上影音平台接收資訊與交流,使網路平台累積了大量未經處理的文字與影音資料,本研究對連鎖健身房的線上評論進行文字探勘與情感分析,探詢消費者重視的服務屬性與意見。根據研究結果,健身房會員重視的服務屬性可分為十一類,其中以「會員權益」、「員工可靠性」與「場館管理品質」三類屬性最受會員重視,而情感分析結果則顯示會員對此三屬性的情緒大致為負面。
本研究建議業者落實員工教育訓練,減少業務不以話術誘導消費者購入不合適的課程,以降低消費糾紛次數,並且應落實專業考核督促教練取得合格證照,除了加強員工培訓,維護場館品質上可制定場館使用公約,以加強宣導及場內巡視勸導會員共同維護使用環境,如此可營造更優質的環境氛圍。

The emergence of gym chains has provided people in urban areas with a convenient and diversified sports environment. Nowadays, applying for club membership and participating in gym classes are no longer the exclusive leisure activities of high-income groups, and gym chains have opened up a wide customer base through affordable prices and multi-type fitness services to reach out to students, petty cash-earners and white-collar customers. However, there have been numerous consumer disputes between gym members and gym operators. For both parties, the loss is not only in terms of money, time and energy, but also in terms of consumers' negative sentiment and distrust of the brand, which in the long run will jeopardize the brand's image and value.
With the popularization of the Internet, people often receive information and communicate with each other through online news, social media platforms, and online audio-visual platforms, which have accumulated a large amount of unprocessed textual and audio-visual data. This study conducts a textual exploration and sentiment analysis of the online reviews of gym chains, in order to find out the attributes of the services that are valued by the consumers and the opinions they give to them. According to the results of this study, the service attributes valued by gym members can be categorized into eleven types, among which "members' rights", "staff reliability", and "quality of gym management" are the most valued attributes, and the results of the sentiment analysis show that the members' sentiments towards these three attributes are generally negative.
This study suggests that the industry should implement staff education and training to reduce the number of consumer disputes by reducing the number of salespersons who do not use jargon to induce consumers to purchase inappropriate courses, and should implement professional assessment to urge coaches to obtain qualified licenses. In addition to strengthening staff training, the quality of the venues can be maintained by formulating a convention on the use of the venues to enhance publicity and in-field inspections to persuade members to work together to maintain the use of the environment, which will create a better environmental atmosphere. This will create a better environmental atmosphere.

第一章 緒論 1 第一節 研究背景 1 第二節 研究動機 3 第三節 研究目的 3 第二章 文獻探討 4 第一節 連鎖健身房 4 第二節 服務品質 5 第三節 線上評論 5 第四節 文本情感分析 10 第三章 研究方法 18 第一節 研究流程 18 第二節 資料來源 19 第三節 原始資料處理 20 第四章 研究分析與結果 22 第一節 文本預處理 22 第二節 特徵詞聚類 26 第三節 情感分析 33 第四節 情感分析結果 35 第五章 結論與建議 54 第一節 研究結論 54 第二節 管理意涵 55 第三節 研究限制 57 參考文獻 58 中文參考文獻 58 英文參考文獻 61 附錄 66 附錄一 自定義詞彙表 66 附錄二 健身房會員重視構面 67

中華民國有氧體能運動協會 (2000)。台灣健身房 (體適能中心) 設施及管理之研究。行政院體育委員會。
王瓊霞、黃彥翔 (2020)。健身房產業對國民健康的影響及貢獻。國民體育季刊,49(3),4-8。
李城忠、曾浚吉、張婉貞 (2019)。健身會館體驗行銷、品牌形象與專業知能對顧客滿意度之影響。管理資訊計算,8(1),34-44。
李程豐 (2012)。以社會網路為中介變項探討員工授權賦能、組織承諾及團體效能之關聯性─以某連鎖運動健身俱樂部為例〔未出版之碩士論文〕。朝陽科技大學。
宗成慶、夏睿、張家俊 (2019)。文本數據挖掘。清華大學出版社。
林坤賢、蔡俊明 (2019)。基於深度學習的自然語言處理中預訓練 Word2Vec 模型的研究。國教新知,66(1),16-31。
林金賢、顏素娟、徐曉頡 (2021)。結合文字探勘與量化工具從線上留言挖掘旅館業者的競爭優勢。資訊管理學報,28(3),337-360
邱建章 (2020)。臺灣健身產業的經營型態與趨勢發展 (1953-2020)。國民體育季刊,49(3),9-15。
周秩年、黃怡姍(2022),運動服務業發展趨勢(2022 年),擷取自https://www.twtrend.com/trend-detail/sports-activities-2022/。
凃育婷 (2020)。基於順序遷移學習開發繁體中文情感分析工具〔未出版之碩士論文〕。國立台灣大學。
倪家珍、王笠言、林孟彥 (2020)。住宿業訂房平台線上評論之比較性分析-以Agoda與Airbnb為例。觀光休閒學報,26(3),259-282。
翁崇雄 (1998)。期望服務與服務績效影響服務品質評量之研究。臺大管理論叢,9(1),153-176。
國家發展委員會 (2021)。108年數位發展調查報告。國家發展委員會。
教育部體育署 (2021)。健身房空間應用及設計規劃參考手冊。教育部體育署。
教育部體育署 (2022)。運動現況調查。教育部體育署。
陳世榮(2015)。社會科學研究中的文字探勘應用:以文意為基礎的文件分類及其問題。人文及社會科學集刊,27(4),683-718。
陳克健、陳正佳、林隆基 (1986)。中文語句分析的研究─斷詞與夠詞。中央研究院資訊科學研究所技術報告 (未出版)。
陳俊良 (2019)。台灣健身房的文化轉型:結構詮釋學的分析〔未出版之碩士論文〕。國立台灣大學。
陶治中、簡睿志(2016)。三元決策理論應用於社群媒體挖掘之情感分析-以UBER在臺營運話題為例。運輸計劃季刊,45(4),301-330。
黃致豪、范智明、林高正(2014)。運動俱樂部顧客期望之研究-以大台北地區為例。休閒產業管理學刊,7 (1),23-39。
黃心宜(2014)。基於影響力分析之意見單元評價的研究〔未出版之碩士論文〕。淡江大學。
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 (3),215-256。
楊惠淳(2011)。以主客觀分析與相互資訊檢索探討情感分析之準確度-以電影評論為例〔未出版之碩士論文〕。國立臺北科技大學。
葉乃菁、王玳琪、張嘉珍、吳騏、賴志遠(2009)。建構創新政策研究工具文字探勘之應用簡介。國研科技,(22),17-20。
劉金岭、錢升華 (2021)。文本數據挖掘與Python應用。清華大學出版社。
葉嘵月、陳志一(2006)。國立臺灣大學綜合體育館健身中心設施器材佈置顧客滿意度調查研究。運動教練科學,(7),39-50。
蕭惠如 (2017)。應用文字探勘於資訊管理領域研究趨勢〔未出版之碩士論文〕。銘傳大學。
謝吉隆、楊苾淳(2018)。從「應變自然」到「社會應變」:以文字探勘方法檢視國內風災新聞的報導演變。教育資料與圖書館學,55(3),285-318。
謝麗星、周明、孫茂松 (2012)。基於層次結構的多策略中微博情感分析和特徵抽取。中文信息學報,26 (1),73-83。
鍾易瑋、鄭志富(2023)。臺北地區網球俱樂部會員知覺服務品質與顧客滿意度關係之研究。淡江體育學刊,(26),65-90。
簡之文 (2012)。部落格文章情感分析之研究〔未出版之碩士論文〕。淡江大學。
Aggarwal, R., Gopal, R., Gupta, A., & Singh, H. (2012). Putting money where the mouths are: The relation between venture financing and electronic word-of-mouth. Information Systems Research, 23(3-part-2), 976-992.
Amblee, N., & Bui, T. (2011). Harnessing the influence of social proof in online shopping: The effect of electronic word of mouth on sales of digital microproducts. International journal of electronic commerce, 16(2), 91-114.
Anderson, M., & Magruder, J. (2012). Learning from the crowd: Regression discontinuity estimates of the effects of an online review database. The Economic Journal, 122(563), 957-989.
Archak, N., Ghose, A., & Ipeirotis, P. G. (2011). Deriving the pricing power of product features by mining consumer reviews. Management science, 57(8), 1485-1509.
Cao, Q., Duan, W., & Gan, Q. (2011). Exploring determinants of voting for the “helpfulness” of online user reviews: A text mining approach. Decision Support Systems, 50(2), 511-521.
Chau, M., & Xu, J. (2012). Business intelligence in blogs: Understanding consumer interactions and communities. MIS quarterly, 1189-1216.
Clemons, E. K., Gao, G. G., & Hitt, L. M. (2006). When online reviews meet hyperdifferentiation: A study of the craft beer industry. Journal of management information systems, 23(2), 149-171.
Cormode, G., & Krishnamurthy, B. (2008). Key differences between Web 1.0 and Web 2.0. First Monday.
Cui, G., Lui, H. K., & Guo, X. (2012). The effect of online consumer reviews on new product sales. International Journal of Electronic Commerce, 17(1), 39-58.
Dave, K., Lawrence, S., & Pennock, D. M. (2003, May). Mining the peanut gallery: Opinion extraction and semantic classification of product reviews. In Proceedings of the 12th international conference on World Wide Web (pp. 519-528).
Dhar, V., & Chang, E. A. (2009). Does chatter matter? The impact of user-generated content on music sales. Journal of Interactive marketing, 23(4), 300-307.
Felbermayr, A., & Nanopoulos, A. (2016). The role of emotions for the perceived usefulness in online customer reviews. Journal of Interactive Marketing, 36(1), 60-76.
Feng, J., & Papatla, P. (2011). Advertising: stimulant or suppressant of online word of mouth?. Journal of Interactive Marketing, 25(2), 75-84.
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.
Hutto, C., & Gilbert, E. (2014, May). Vader: A parsimonious rule-based model for sentiment analysis of social media text. In Proceedings of the international AAAI conference on web and social media (Vol. 8, No. 1, pp. 216-225).
Sparck Jones, K. (1972). A statistical interpretation of term specificity and its application in retrieval. Journal of documentation, 28(1), 11-21.
Kharde, V., & Sonawane, P. (2016). Sentiment analysis of twitter data: a survey of techniques. arXiv preprint arXiv:1601.06971.
Kim, D., & Kim, S. Y. (1995). QUESC: An instrument for assessing the service quality of sport centers in Korea. Journal of sport management, 9(2), 208-220.
Kohavi, R., & Provost, F. (1998). Machine Learning. Glossary of Terms. Volume, 30, 2-3.
Lam, E. T., Zhang, J. J., & Jensen, B. E. (2005). Service Quality Assessment Scale (SQAS): An instrument for evaluating service quality of health-fitness clubs. Measurement in physical education and exercise science, 9(2), 79-111.
Larson, B. V., & Steinman, R. B. (2009). Driving NFL fan satisfaction and return intentions with concession service quality. Services Marketing Quarterly, 30(4), 418-428.
Ludwig, S., De Ruyter, K., Friedman, M., Brüggen, E. C., Wetzels, M., & Pfann, G. (2013). More than words: The influence of affective content and linguistic style matches in online reviews on conversion rates. Journal of marketing, 77(1), 87-103.
Moe, W. W., & Schweidel, D. A. (2012). Online product opinions: Incidence, evaluation, and evolution. Marketing Science, 31(3), 372-386.
Moe, W. W., & Trusov, M. (2011). The value of social dynamics in online product ratings forums. Journal of marketing research, 48(3), 444-456.
Mostafa, M. M. (2013). More than words: Social networks’ text mining for consumer brand sentiments. Expert systems with applications, 40(10), 4241-4251.
Nelson, P. (1970). Information and consumer behavior. Journal of political economy, 78(2), 311-329.
Oliver, R. L. (1999). Whence consumer loyalty?. Journal of marketing, 63(4_suppl1), 33-44.
O'reilly, T. (2009). What is web 2.0. " O'Reilly Media, Inc.".
Pan, Y., & Zhang, J. Q. (2011). Born unequal: a study of the helpfulness of user-generated product reviews. Journal of retailing, 87(4), 598-612.
Pang, B., & Lee, L. (2008). Opinion mining and sentiment analysis. Foundations and Trends® in information retrieval, 2(1–2), 1-135.
Pang, B., & Lee, L. (2004). A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts. arXiv preprint cs/0409058.
Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1985). A conceptual model of service quality and its implications for future research. Journal of marketing, 49(4), 41-50.
Pathak, B., Garfinkel, R., Gopal, R. D., Venkatesan, R., & Yin, F. (2010). Empirical analysis of the impact of recommender systems on sales. Journal of Management Information Systems, 27(2), 159-188.
Peng, H., Cambria, E., & Hussain, A. (2017). A review of sentiment analysis research in Chinese language. Cognitive Computation, 9, 423-435.
Sproat, R., & Shih, C. (1990). A statistical method for finding word boundaries in Chinese text. Computer Processing of Chinese & Oriental Languages, 4(4), 336-351.
Rogers, E. M., & Beal, G. M. (1957). The importance of personal influence in the adoption of technological change. Soc. F., 36, 329.
Rui, H., Liu, Y., & Whinston, A. (2013). Whose and what chatter matters? The effect of tweets on movie sales. Decision support systems, 55(4), 863-870.
Salton, G. (1983). Introduction to modern information retrieval. McGraw-Hill.
Sullivan, D. (2001). Document warehousing and text mining: techniques for improving business operations, marketing, and sales. John Wiley & Sons, Inc..
Tirunillai, S., & Tellis, G. J. (2012). Does chatter really matter? Dynamics of user-generated content and stock performance. Marketing science, 31(2), 198-215.
Turney, P. D. (2002). Thumbs up or thumbs down? Semantic orientation applied to unsupervised classification of reviews. arXiv preprint cs/0212032.
Wang, J. H., & Lee, C. C. (2011, October). Unsupervised opinion phrase extraction and rating in Chinese blog posts. In 2011 IEEE Third International Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third International Conference on Social Computing (pp. 820-823). IEEE.
Wu, L., Shen, H., Fan, A., & Mattila, A. S. (2017). The impact of language style on consumers′ reactions to online reviews. Tourism Management, 59, 590-596.
Ye, Q., Law, R., Gu, B., & Chen, W. (2011). The influence of user-generated content on traveler behavior: An empirical investigation on the effects of e-word-of-mouth to hotel online bookings. Computers in Human behavior, 27(2), 634-639.
Yıldız, K., Polat, E., Sönmezoğlu, U., & Çokpartal, C. (2016). An Analysis on the determinants of service quality perceived by members of the fitness center. Niğde University Journal of Physical Education And Sport Sciences, 10(3), 453-464.
Yue, L., Chen, W., Li, X., Zuo, W., & Yin, M. (2019). A survey of sentiment analysis in social media. Knowledge and Information Systems, 60, 617-663.
Zhu, F., & Zhang, X. (2010). Impact of online consumer reviews on sales: The moderating role of product and consumer characteristics. Journal of marketing, 74(2), 133-148.

下載圖示
QR CODE