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  1. NTU Theses and Dissertations Repository
  2. 管理學院
  3. 國際企業學系
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/21601
完整後設資料紀錄
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dc.contributor.advisor任立中
dc.contributor.authorChia-Ni Linen
dc.contributor.author林佳霓zh_TW
dc.date.accessioned2021-06-08T03:39:22Z-
dc.date.copyright2019-07-17
dc.date.issued2019
dc.date.submitted2019-07-10
dc.identifier.citation一、 中文部分
[1] 任立中、周建亨、陳靜怡、周文賢,2012,統計學:管理者必備的修鍊,新北市:前程。
[2] 江明晏,2018,台灣手機市場吹冷風 銷量不振補貼降,經濟日報,取自: https://money.udn.com/money/story/5641/3074405 [Accessed 17 Jun. 2018]。
[3] 呂俊德、黃郁琮,2007,3C 事業運籌體系再造及其電子化環境建置之個案研究,電子商務學報, 9卷3期:頁529-553。
[4] 李俊德,2011,兩岸 3C 產品深化程度之比較研究,國立交通大學經營管理學程未出版之碩士論文。
[5] 李靚慧,2018,全力投入家電市場 奇美集團:力拚家電業績年增2成,自由時報,取自:http://news.ltn.com.tw/news/business/breakingnews/2367504 [Accessed 20 Jun. 2018]。
[6] 孟欣宏、吳春樺、林文德,2013,退休對心理健康之影響—以鎮定安眠藥之使用為指標,台灣公共衛生雜誌,32卷1期:頁52-61。
[7] 張文雙、楊永弘,2009,ATC/DDD 系統的建立及其在藥物利用研究中的應用,臨床藥物治療雜誌,7卷1期:頁32-37。
[8] 許俊卿、李志恆,1998,臺灣地區十年來阿片類止痛藥使用趨勢之探討,中華公共衛生雜誌, 17卷6期:頁495-503。
[9] 陳瑩山,2017,用眼過度 眼睛更年期提早報到,健康世界,485期:頁13-14。
[10] 蔡明樺、沈能元、邱俊吉,2013,3C螢幕太鮮豔 19歲男白內障,蘋果日報,取自:https://tw.appledaily.com/headline/daily/20130222/34844983 [Accessed 18 Jun. 2018]。
[11] 蔡秋帆、詹婉卿、劉名浚、湯念湖,2014,藥物學,新北市:新文京。
[12] 戴吉亮,2001,從3C產品的市場分佈特性探討專業物流公司之特質,國立東華大學企業管理研究所未出版之碩士論文。
[13] GfK,2017,GfK:2017年上半年台灣電腦市場銷額較去年同期小幅成長2%.,取自:https://www.gfk.com/zh-tw/insights/press-release/gfk20172/ [Accessed 18 Jun. 2018]。
二、 英文部分
[1] American Optometric Association. (n.d.). Computer Vision Syndrome. [online] Available at: https://www.aoa.org/patients-and-public/caring-for-your-vision/protecting-your-vision/computer-vision-syndrome [Accessed 18 Jun. 2018].
[2] Bergman, U., Elmes, P., Halse, M., Halvorsen, T., Hood, H., Lunde, P. K. M., ... & Westerholm, B. (1975). The measurement of drug consumption. European journal of clinical pharmacology, 8(2), 83-89.
[3] Bergqvist, U. O., & Knave, B. G. (1994). Eye discomfort and work with visual display terminals. Scandinavian journal of work, environment & health, 27-33.
[4] Blehm, C., Vishnu, S., Khattak, A., Mitra, S., & Yee, R. W. (2005). Computer vision syndrome: a review. Survey of ophthalmology, 50(3), 253-262.
[5] Carneiro, H. A., & Mylonakis, E. (2009). Google trends: a web-based tool for real-time surveillance of disease outbreaks. Clinical infectious diseases, 49(10), 1557-1564.
[6] Chang, T. H., Fu, H. P., Lee, W. I., Lin, Y., & Hsueh, H. C. (2007). A study of an augmented CPFR model for the 3C retail industry. Supply Chain Management: An International Journal, 12(3), 200-209.
[7] Choi, H., & Varian, H. (2012). Predicting the present with Google Trends. Economic Record, 88(s1), 2-9.
[8] Cole, B. L., Maddocks, J. D., & Sharpe, K. (1996). Effect of VDUs on the eyes: report of a 6-year epidemiological study. Optometry and vision science: official publication of the American Academy of Optometry, 73(8), 512-528.
[9] Cooper, C., Mallon, K., Leadbetter, S., Pollack, L. and Peipins, L. (2005), Cancer internet search activity on a major search engine, United States 2001–2003, Journal of Medical Internet Research, 7(3), e36.
[10] Dain, S. J., McCarthy, A. K., & Chan-Ling, T. (1988). Symptoms in VDU operators. American journal of optometry and physiological optics, 65(3), 162-167.
[11] Ettredge, M., Gerdes, J., & Karuga, G. (2005). Using web-based search data to predict macroeconomic statistics. Communications of the ACM, 48(11), 87-92.
[12] Ginsberg, J., Mohebbi, M. H., Patel, R. S., Brammer, L., Smolinski, M. S., & Brilliant, L. (2009). Detecting influenza epidemics using search engine query data. Nature, 457(7232), 1012.
[13] Goel, S., Hofman, J. M., Lahaie, S., Pennock, D. M., & Watts, D. J. (2010). Predicting consumer behavior with Web search. Proceedings of the National academy of sciences, 107(41), 17486-17490.
[14] Hassan, A., BVS, M. M. K., & FIACLE, M. (2017). Prevalence of Computer Vision Syndrome (CVS) amongst the students of Khyber Medical University, Peshawar. Islamabad Congress of Ophthalmology, 15(2), 59-64.
[15] Hultgren, G. V., & Knave, B. (1974). Discomfort glare and disturbances from light reflections in an office landscape with CRT display terminals. Applied Ergonomics, 5(1), 2-8.
[16] Lazer, D., Kennedy, R., King, G., & Vespignani, A. (2014). The parable of Google Flu: traps in big data analysis. Science, 343(6176), 1203-1205.
[17] Lie, I., & Watten, R. G. (1994). VDT work, oculomotor strain, and subjective complaints- an experimental and clinical study. Ergonomics, 37(8), 1419-1433.
[18] Margrain, T. H., Boulton, M., Marshall, J., & Sliney, D. H. (2004). Do blue light filters confer protection against age-related macular degeneration?. Progress in retinal and eye research, 23(5), 523-531.
[19] McLaren, N., & Shanbhogue, R. (2011). Using internet search data as economic indicators. Bank of England Quarterly Bulletin, 51(2), 134-140.
[20] Natsch, S., Hekster, Y. A., De Jong, R., Heerdink, E. R., Herings, R. M. C., & Van der Meer, J. W. M. (1998). Application of the ATC/DDD methodology to monitor antibiotic drug use. European journal of clinical microbiology and infectious diseases, 17(1), 20-24.
[21] Nishiyama, K. (1990). Ergonomic aspects of the health and safety of VDT work in Japan: a review. Ergonomics, 33(6), 659-685.
[22] Pelat, C., Turbelin, C., Bar-Hen, A., Flahault, A., & Valleron, A. J. (2009). More diseases tracked by using Google Trends. Emerging infectious diseases, 15(8), 1327.
[23] Rosenfield, M. (2011). Computer vision syndrome: a review of ocular causes and potential treatments. Ophthalmic and Physiological Optics, 31(5), 502-515.
[24] Rózanowska, M., Jarvis-Evans, J., Korytowski, W., Boulton, M. E., Burke, J. M., & Sarna, T. (1995). Blue light-induced reactivity of retinal age pigment in vitro generation of oxygen-reactive species. Journal of Biological Chemistry, 270(32), 18825-18830.
[25] Schuster, N. M., Rogers, M. A., & McMahon Jr, L. F. (2010). Using search engine query data to track pharmaceutical utilization: a study of statins. The American journal of managed care, 16(8), e215.
[26] Tatemichi, M., Nakano, T., Tanaka, K., Hayashi, T., Nawa, T., Miyamoto, T., ... & Sugita, M. (2004). Possible association between heavy computer users and glaucomatous visual field abnormalities: a cross sectional study in Japanese workers. Journal of Epidemiology & Community Health, 58(12), 1021-1027.
[27] Taylor, H. R., Munoz, B., West, S., Bressler, N. M., Bressler, S. B., & Rosenthal, F. S. (1990). Visible light and risk of age-related macular degeneration. Transactions of the American Ophthalmological Society, 88, 163.
[28] Thomson, W. D. (1998). Eye problems and visual display terminals—the facts and the fallacies. Ophthalmic and physiological optics, 18(2), 111-119.
[29] Vosen, S., & Schmidt, T. (2011). Forecasting private consumption- survey‐based indicators vs. Google trends. Journal of Forecasting, 30(6), 565-578.
[30] Willard, S. D., & Nguyen, M. M. (2013). Internet search trends analysis tools can provide real-time data on kidney stone disease in the United States. Urology, 81(1), 37-42.
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/21601-
dc.description.abstract隨著智慧型手機等3C產品逐漸普及,民眾比以往花更多時間緊盯螢幕,導致許多眼睛不適的症狀,甚至可能會造成眼睛永久的損傷,所以近年來不少新聞報導民眾因為過度使用3C產品而引發眼睛不適,並前往就醫的例子。本研究欲以大數據的觀點,探討3C產品的產銷相關數據是否真的與醫療院所眼疾用藥量呈現正向關聯,並進一步研究眼疾相關網路討論聲量與3C產品數據、眼疾用藥量之間的相關性,以期能提供醫療院所與製藥公司一種低成本預測用藥量的參考指標,並給予其行銷、管理方面的建議。
本研究使用醫療機構的資料庫建立高雄某區每月總體用藥指標,並與政府單位公開的3C產品相關資料進行分析,發現用藥指標與某些項目確實有顯著的正向關聯存在,其中電視機進口量、可攜式電腦生產量、可攜式電腦進口值、液晶顯示器進口量的成長率可以合併為3C產品指標且作為預測用藥量的參考標的,醫院與製藥公司可依據上述產品的市場預測推估下期的用藥量,成為行銷、管理決策的參考依據。至於網路討論聲量的部分,本研究使用社群口碑資料庫建置每個月的眼疾網路討論聲量指標,並分別與3C產品資料、眼疾用藥指標進行分析,得知在本研究的架構下,若要使用網路討論聲量作為用藥量預測的參考指標,有實行上的困難。
zh_TW
dc.description.abstractThe goal of this study is to establish a low-cost and efficient method to predict the trends in ophthalmic drug utilization. With the improvement of technology, people spend more and more time on mobile devices. Although those products have brought great convenience to users, staring at digital screens for a long period of time may cause eye discomfort or vision problems. Therefore, ophthalmic medicines would be prescribed to treat the symptoms. The possibility of constructing a new business method by analyzing the connection between the data of digital products and ophthalmic medicine usage was tested in this paper. Moreover, the number of keywords in the posts discussing eye discomfort or vision problems online was calculated as an online discussion index. This index was constructed in order to check whether citizens complained about their symptoms on the Internet before seeing a doctor.
After a series of analyses, the correlation between the data of electronic products and the ophthalmic medication index was obvious while the role of online discussion index was not determined. Therefore, medical institutions and pharmaceutical companies could utilize the data of electronic devices to foresee the demand for ophthalmic medicines in the future.
en
dc.description.provenanceMade available in DSpace on 2021-06-08T03:39:22Z (GMT). No. of bitstreams: 1
ntu-108-R05724039-1.pdf: 2108237 bytes, checksum: f6a9ce0825a78c0e6019ed8b143cadc0 (MD5)
Previous issue date: 2019
en
dc.description.tableofcontents口試委員會審定書...I
誌謝...II
中文摘要...III
ABSTRACT...IV
圖目錄...VII
表目錄...IX
第一章 緒論...1
第一節 研究背景與動機...1
第二節 研究目的...2
第三節 研究流程...3
第二章 文獻回顧...4
第一節 藥物利用研究...4
第二節 3C產品市場現況...5
第三節 網路聲量研究...6
第四節 使用3C產品與眼睛不適的關聯...8
第三章 資料來源與研究方法...10
第一節 用藥指標資料...10
第二節 3C產品資料...22
第三節 網路聲量指標資料...26
第四節 研究方法...30
第四章 實證分析與結果...32
第一節 變數資料敘述...32
第二節 3C產品資料與用藥指標之關聯性...41
第三節 網路聲量指標與用藥指標之關聯性...52
第四節 3C產品資料與網路聲量指標之關聯性...53
第五章 結論...60
第一節 管理意涵...60
第二節 研究限制...64
第三節 未來研究建議...65
參考文獻...67
dc.language.isozh-TW
dc.title醫藥大數據—眼疾用藥指標的建立及其影響因素探討zh_TW
dc.titleThe Big Data in Medicine: A Study of Building an Ophthalmic Medication Index and Its Applicationsen
dc.typeThesis
dc.date.schoolyear107-2
dc.description.degree碩士
dc.contributor.oralexamcommittee周建亨,陳靜怡
dc.subject.keyword醫療產業,醫藥大數據,用藥指標,迴歸分析,網路聲量指標,3C產品指標,zh_TW
dc.subject.keywordBig Data Analysis,Ophthalmic Medication Index,Regression Analysis,Medical Industry,Computer Vision Syndrome,en
dc.relation.page71
dc.identifier.doi10.6342/NTU201901373
dc.rights.note未授權
dc.date.accepted2019-07-11
dc.contributor.author-college管理學院zh_TW
dc.contributor.author-dept國際企業學研究所zh_TW
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