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題名 網站使用者行為分析—以國立政治大學學術集成平台為例
Analysis of Website User Behavior: A Case Study of National Chengchi University Academic Hub作者 張思洋
Zhang, Si-Yang貢獻者 陳志銘
Chen, Chih-Ming
張思洋
Zhang, Si-Yang關鍵詞 機構典藏
學術集成平台
學者庫
行為分析
探索性資料分析
滯後序列分析
Institutional repository
Academic Hub
Scholar Hub
User behavior analysis
Exploratory data analysis
Lag sequence analysis日期 2021 上傳時間 1-Apr-2021 11:21:50 (UTC+8) 摘要 傳統的機構典藏平台存在內容建置較為局限、功能單一，以及不具作者視角的問題，致使其學術傳播效益受限。學者庫或學術集成平台為彌補機構典藏上述問題所轉型而成的新型平台。考慮到促進學術交流的發展趨勢，國立政治大學于2016年將原始的機構典藏系统改寫，將其發展為學術集成平台，使其建置內容具有更廣泛之研究者資訊、提供多元及視覺化功能，以及以作者視角呈現研究者資訊。為了解國立政治大學學術集成平台的使用情況，本研究針對此一平台之使用者操作歷程記錄進行分析，以評估其是否達到預期的學術傳播目的。本研究採用xAPI對網站使用者操作行為進行記錄，記錄時間範圍為2020年11月23日-2020年12月14日共計21天。共蒐集使用者操作行為歷程記錄19,019筆。本研究首先對所有資料進行敘述統計，從而了解整體的使用者特徵。根據使用者IP進行使用者分類，對不同地區的使用者進行卡方統計檢定，從而了解不同地區使用者的行為特徵。再根據下載論文平均次數，將使用者分為下載論文高低兩組，探究下載論文次數高低不同使用者的行為特徵與行為轉移模式。研究結果發現，了解研究者相關資訊與論文檢索下載相關之系統功能操作行為，為整體使用者在政大學術集成平台上最常使用的兩類操作行為。IP為台灣的使用者為政大學術集成平台的主要使用者。台灣的使用者中政治大學的使用者更關注研究者相關之資訊，較少使用論文瀏覽、檢索及下載之相關資訊。而其他地區的使用者則較關注論文瀏覽、檢索及下載之相關資訊，較少關注研究者相關之資訊。而透過對下載論文次數高低組的滯後序列分析則發現，政大學術集成平台在網頁設計與網站功能上的不足。最後基於研究結果，本研究提出政大學術集成平台優化建議，以及未來可以繼續發展的研究方向。整體而言，本研究透過使用者行為分析了解整體使用者、不同地區使用者，以及下載論文次數高低使用者的行為特徵及行為轉移模式，對於了解使用者如何操作政大學術集成平台及如何優化其平台網頁與功能設計具有貢獻。
The traditional institutional repository has the problems of relatively limited content establishment,single function, and lack of the author`s perspective, which limits its academic dissemination efficiency.The Scholar Hub or Academic Hub is a new type of platform developed to compensate for the above-mentioned problems in the institutional repository.Considering the development trend of promoting academic dissemination,National Chengchi University redesigned the original institutional repository system in 2016 and developed it into an Academic Hub,which provides with a wider range of researcher information, multiple and visual functions, and presenting researcher information from the author’s perspective. In order to find out the usage situation of the National Chengchi University Academic Hub, this research analyzed the users’ operation history of the Academic Hub to evaluate whether it achieves the expected academic dissemination purpose or not.In this research, xAPI was used to record the users’ operation behaviors from the National Chengchi University Academic Hub,and the recording time was ranged from November 23,2020 to December 14,2020,a total of 21 days. A total of 19,019 users’ behavioral records were collected.First of all,all the collected data were analyzed to find out the characteristics of overall users.Then,the IP of users were regarded as a classification standard to examine the differences in the behavior characteristics of users among different regions by chi-square test of independence.Next,according to the average number of the downloaded papers,the users were divided into two groups: high and low groups,to explore the user behavior characteristics and user behavior transfer mode based on lag sequential analysis .The analytical results show that the two most commonly used behaviors of the whole users were researchers related and papers related behaviors.The users in Taiwan were the main users of the National Chengchi University Academic Hub.And users in the National Chengchi University paid much more attention to researchers’ information,and paid less attention to information about browsing,searching,and downloading papers. However,users in other regions paid much more attention to the information related to browsing,searching,and downloading papers,and paid less attention to the information related to researchers.Through the lag sequential analysis of the two group users who downloaded papers that are higher and lower than the average number of papers downloaded,some deficiencies in the website design and system functions of the National Chengchi University Academic Hub were found.Finally,based on the research results, this study proposes several suggestions for the optimization of the National Chengchi University Academic Hub,as well as draws several research directions that can be further investigated in the future.Overall,this research used users’ behavior analysis scheme to understand the behavior characteristics and behavior transfer patterns of users in general,users in different regions,and users with high or low download times,which will contribute to understanding how users operate the National Chengchi University Academic Hub and how to optimize the National Chengchi University Academic Hub.參考文獻 國立政治大學圖書館(2019)。「Post-Print作者版本」大募集。檢自 http://www.lib.nccu.edu.tw/zh_tw/announcement/-Post-Print%E4%BD%9C%E8%80%85%E7%89%88%E6%9C%AC-%E5%A4%A7%E5%8B%9F%E9%9B%86-47784871陳志銘(2019)。學習微歷程大數據分析與應用。陳勇汀(2017)。行為順序檢定：滯後序列分析 / Behavior Analysis: Lag Sequential Analysis。檢自https://pulipulichen.github.io/HTML-Lag-Sequential-Analysis/黃婷婷、陳舜昌、高慧琴(2017)。大學圖書館OPAC系統用戶信息搜尋路徑的可視化分析。大學圖書館學報，35(1)，63-71。doi:10.16603/j.issn1002-1027.2017.01.009孫賢潔(2017)。行動政府網頁設計準則影響資訊尋求之研究(未出版之碩士論文)。國立政治大學，臺北市。Adeyemi, J. A., Appah, D., Akinlade, O., & Bribena, I. (2017). The Nigerian institutional repositories: Opportunities and barriers. Academia Journal of Educational Research, 5(10), 9.ADL Net.(2015).Experience xAPI Overview.Retrieved from https://adlnet.gov/projects/xapi/Asadi, S., Abdullah, R., Yah, Y., & Nazir, S. (2019). Understanding institutional repository in higher learning institutions: A systematic literature review and directions for future research. IEEE ACCESS, 7, 35242-35263. doi:10.1109/ACCESS.2019.2897729Aschenbrenner, A., Blanke, T., Flanders, D., Hedges, M. and O’Steen, B. (2008), “The future of repositories?”, D-Lib Magazine, Vol. 14 Nos 11/12, doi: 10.1045/november2008-aschenbrenner.Bakeman, R., & Gottman, J. M. (1997). Observing interaction: An introduction to sequential analysis, 2nd ed. New York: Cambridge University Press. doi:10.1017/CBO9780511527685Bankier, J.-G., & Perciali, I. (2008). The institutional repository rediscovered: What can a university do for open access publishing? Serials Review, 34(1), 21-26. http://doi.org/10.1016/j.serrev.2007.12.003Behrooz, O. T., Sihem, A. Y., & Termier, A. (2015). Interactive user group analysis. In Proceedings of the 24th ACM International on Conference on Information and Knowledge Management (pp. 403–412). New York, NY, USA: ACM. doi:10.1145/2806416.2806519Brusino, J.(2012).The Next Generation of SCORM: A Q&A; with Aaron Silvers.Retrieved from:https://web.archive.org/web/20140822192026/http://www.astd.org/Publications/Newsletters/Learning-Circuits/Learning-Circuits-Archives/2012/06/The-Next-Generation-of-SCORM-a-Q-and-a-with-Aaron-SilversChristian, G. E. (2009). Issues and challenges to the development of Open Access institutional repositories in academic and research institutions in nigeria. SSRN Electronic Journal. doi:10.2139/ssrn.1323387Croll.A., Power.C.(2009).Complete web monitoring.O’Reilly Media Inc., Sebastopol .Cutroni, J. (2010). Google Analytics: Understanding Visitor Behavior.Davis, P.M. and Connolly, M.J.L. (2007), “Institutional repositories: evaluating the reasons for non-use of Cornell university’s installation of DSpace”, D-lib Magazine, Vol. 13 Nos 3/4, available at:www.dlib.org/dlib/march07/davis/03davis.htmlFarney, T. A. (2011). Click analytics: Visualizing website use data. Information Technology and Libraries, 30(3). doi:10.6017/ital.v30i3.1771Fenner M. (2014) Altmetrics and other novel measures for scientific impact. In: Bartling S., Friesike S. (eds) Opening Science. Springer, Cham.Giesecke, J. (2011). Institutional repositories: Keys to success. Journal of Library Administration, 51, 529-542. doi:10.1080/01930826.2011.589340Gvianishvili, G., Le Meur, J. Y., Šimko, T., Caffaro, J., Marian, L., Kaplun, S., et al. (2010). Capturing and analyzing user behavior in large digital libraries, (CERN-IT-2010-002), 8 p. doi:oai:cds.cern.ch:1295600Hagstrom, W. O. (1971). Inputs, Outputs, and the Prestige of University Science Department. Sociology of Education, 44(4), 375. doi:10.2307/2112029IBM(2013).Oh behave! How behavioral analytics fuels more personalized marketing.Enterprise Marketing Management.Jansen, B. J., & Spink, A. (2006). How are we searching the World Wide Web? A comparison of nine search engine transaction logs. Information Processing & Management, 42(1), 248-263. doi:10.1016/j.ipm.2004.10.007Jantz, R. C., & Wilson, M. C. (2008). Institutional repositories: Faculty deposits, marketing, and the reform of scholarly communication. The Journal of Academic Librarianship, 34(3), 186-195. doi:10.1016/j.acalib.2008.03.014Jiang, T., Chi, Y., & Gao, H. (2017). A clickstream data analysis of Chinese academic library OPAC users’ information behavior. Library & Information Science Research, 39(3), 213-223. doi:10.1016/j.lisr.2017.07.004Lim, K. C. (2015). Case studies of xAPI applications to E-Learning, 12.Lynch, C. (2003). Institutional repositories: Essential infrastructure for scholarship in the digital age. Portal Libraries and the Academy, 3, 327-336. doi:10.1353/pla.2003.0039Mödritscher, F., Neumann, G., & Brauer, C. (2012). Comparing LMS usage behavior of mobile and web users. In 2012 IEEE 12th International Conference on Advanced Learning Technologies (pp. 650-651). doi:10.1109/ICALT.2012.42Pakkala, H., Presser, K., & Christensen, T. (2012). Using Google Analytics to measure visitor statistics: The case of food composition websites. International Journal of Information Management, 32(6), 504-512. doi:10.1016/j.ijinfomgt.2012.04.008Palmer, D. T. (n.d.). The HKU Scholars Hub. Unlocking Collective Intelligence, 14.Palmer, D., & Liu, E. (2013). 從學術典藏庫(IR)到當前科研資訊系統(CRIS) – 如何和為何？ Retrieved from http://hdl.handle.net/10722/191176Palmer, D., & Liu, E. (2015). The HKU Scholars Hub - Beyond an institutional repository. Journal of Academic Libraries. Retrieved from http://hdl.handle.net/10722/219961Pinfield, S., Salter, J., Bath, P. A., Hubbard, B., Millington, P., Anders, J. H. S., et al. (2014). Open-access repositories worldwide, 2005-2012: Past growth, current characteristics, and future possibilities: Open-Access Repositories Worldwide, 2005-2012: Past Growth, Current Characteristics, and Future Possibilities. Journal of the Association for Information Science and Technology, 65(12), 2404-2421. doi:10.1002/asi.23131Plaza, B. (2009). Monitoring web traffic source effectiveness with Google Analytics. Aslib Proceedings, 61(5), 474-482. doi:10.1108/00012530910989625Prabhakar, S., & Rani, S. V. (2018). Benefits and perspectives of institutional repositories in academic libraries. Scholarly Research Journal for Humanity Science & English Language, 5. doi:10.21922/srjhsel.v5i25.10948.Russell, R., & Day, M. (2010). Institutional repository interaction with research users: A Review of Current Practice. New Review of Academic Librarianship, 16(sup1), 116-131. doi:10.1080/13614533.2010.509996Rybinski, H., Skonieczny, L., Koperwas, J., Struk, W., Stepniak, J., & Kubrak, W. (2017). Integrating IR with CRIS – a novel researcher-centric approach. Program, 51(3), 298-321. doi:10.1108/PROG-04-2017-0026Salo, D. (2008), “Innkeeper at the roach motel”, Library Trends, Vol. 57 No. 2, pp. 98-123.Tabatha, A., Farney, Nina, & McHale. (2013). Introducing Google Analytics for libraries. Library Technology Reports.Tasy, M. Y., & Chen, C. M. (2017). Developing an Academic Hub with data synchronization, altmetrics display and added value information for promoting scholarly communication performance. In IFLA Conference Proceedings, IFLA. Retrieved from http://nccur.lib.nccu.edu.tw/handle/140.119/121176Thelwall, M., Haustein, S., Larivière, V., & Sugimoto, C. R. (2013). Do altmetrics work? Twitter and ten other social web services. PLoS ONE, 8(5), e64841. doi:10.1371/journal.pone.0064841Tukey, John W. (1977). Exploratory data analysis. Pearson. ISBN 978-0201076165.Velleman, P. F., & Hoaglin, D. C. (2012). Exploratory data analysis. In H. Cooper, P. M. Camic, D. L. Long, A. T. Panter, D. Rindskopf, & K. J. Sher (Eds.), APA handbooks in psychology®. APA handbook of research methods in psychology, Vol. 3. Data analysis and research publication (pp. 51-70). Washington, DC, US: American Psychological Association.W3Techs.(2019).Usage of traffic analysis tools for websites.Retrieved from https://w3techs.com/technologies/overview/traffic_analysisWong, E. Y. (2017). Association of college and research libraries scholarly communication toolkit.Technical Services Quarterly, 34(4), 430-431.doi:10.1080/07317131.2017.1355131Wu, Y. L., Tao, Y. H., & YangJ, P. C. (2008). Using UTAUT to explore the behavior of 3G mobile communication users. In IEEM 2007: 2007 IEEE International Conference on Industrial Engineering and Engineering Management (pp. 199-203). doi:10.1109/IEEM.2007.4419179Yu, C. H. (1977). Exploratory data analysis. Methods, 2, 131-160. 描述 碩士
國立政治大學
圖書資訊與檔案學研究所
107155024資料來源 http://thesis.lib.nccu.edu.tw/record/#G0107155024 資料類型 thesis dc.contributor.advisor 陳志銘 zh_TW dc.contributor.advisor Chen, Chih-Ming en_US dc.contributor.author (Authors) 張思洋 zh_TW dc.contributor.author (Authors) Zhang, Si-Yang en_US dc.creator (作者) 張思洋 zh_TW dc.creator (作者) Zhang, Si-Yang en_US dc.date (日期) 2021 en_US dc.date.accessioned 1-Apr-2021 11:21:50 (UTC+8) - dc.date.available 1-Apr-2021 11:21:50 (UTC+8) - dc.date.issued (上傳時間) 1-Apr-2021 11:21:50 (UTC+8) - dc.identifier (Other Identifiers) G0107155024 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/134434 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 圖書資訊與檔案學研究所 zh_TW dc.description (描述) 107155024 zh_TW dc.description.abstract (摘要) 傳統的機構典藏平台存在內容建置較為局限、功能單一，以及不具作者視角的問題，致使其學術傳播效益受限。學者庫或學術集成平台為彌補機構典藏上述問題所轉型而成的新型平台。考慮到促進學術交流的發展趨勢，國立政治大學于2016年將原始的機構典藏系统改寫，將其發展為學術集成平台，使其建置內容具有更廣泛之研究者資訊、提供多元及視覺化功能，以及以作者視角呈現研究者資訊。為了解國立政治大學學術集成平台的使用情況，本研究針對此一平台之使用者操作歷程記錄進行分析，以評估其是否達到預期的學術傳播目的。本研究採用xAPI對網站使用者操作行為進行記錄，記錄時間範圍為2020年11月23日-2020年12月14日共計21天。共蒐集使用者操作行為歷程記錄19,019筆。本研究首先對所有資料進行敘述統計，從而了解整體的使用者特徵。根據使用者IP進行使用者分類，對不同地區的使用者進行卡方統計檢定，從而了解不同地區使用者的行為特徵。再根據下載論文平均次數，將使用者分為下載論文高低兩組，探究下載論文次數高低不同使用者的行為特徵與行為轉移模式。研究結果發現，了解研究者相關資訊與論文檢索下載相關之系統功能操作行為，為整體使用者在政大學術集成平台上最常使用的兩類操作行為。IP為台灣的使用者為政大學術集成平台的主要使用者。台灣的使用者中政治大學的使用者更關注研究者相關之資訊，較少使用論文瀏覽、檢索及下載之相關資訊。而其他地區的使用者則較關注論文瀏覽、檢索及下載之相關資訊，較少關注研究者相關之資訊。而透過對下載論文次數高低組的滯後序列分析則發現，政大學術集成平台在網頁設計與網站功能上的不足。最後基於研究結果，本研究提出政大學術集成平台優化建議，以及未來可以繼續發展的研究方向。整體而言，本研究透過使用者行為分析了解整體使用者、不同地區使用者，以及下載論文次數高低使用者的行為特徵及行為轉移模式，對於了解使用者如何操作政大學術集成平台及如何優化其平台網頁與功能設計具有貢獻。 zh_TW dc.description.abstract (摘要) The traditional institutional repository has the problems of relatively limited content establishment,single function, and lack of the author`s perspective, which limits its academic dissemination efficiency.The Scholar Hub or Academic Hub is a new type of platform developed to compensate for the above-mentioned problems in the institutional repository.Considering the development trend of promoting academic dissemination,National Chengchi University redesigned the original institutional repository system in 2016 and developed it into an Academic Hub,which provides with a wider range of researcher information, multiple and visual functions, and presenting researcher information from the author’s perspective. In order to find out the usage situation of the National Chengchi University Academic Hub, this research analyzed the users’ operation history of the Academic Hub to evaluate whether it achieves the expected academic dissemination purpose or not.In this research, xAPI was used to record the users’ operation behaviors from the National Chengchi University Academic Hub,and the recording time was ranged from November 23,2020 to December 14,2020,a total of 21 days. A total of 19,019 users’ behavioral records were collected.First of all,all the collected data were analyzed to find out the characteristics of overall users.Then,the IP of users were regarded as a classification standard to examine the differences in the behavior characteristics of users among different regions by chi-square test of independence.Next,according to the average number of the downloaded papers,the users were divided into two groups: high and low groups,to explore the user behavior characteristics and user behavior transfer mode based on lag sequential analysis .The analytical results show that the two most commonly used behaviors of the whole users were researchers related and papers related behaviors.The users in Taiwan were the main users of the National Chengchi University Academic Hub.And users in the National Chengchi University paid much more attention to researchers’ information,and paid less attention to information about browsing,searching,and downloading papers. However,users in other regions paid much more attention to the information related to browsing,searching,and downloading papers,and paid less attention to the information related to researchers.Through the lag sequential analysis of the two group users who downloaded papers that are higher and lower than the average number of papers downloaded,some deficiencies in the website design and system functions of the National Chengchi University Academic Hub were found.Finally,based on the research results, this study proposes several suggestions for the optimization of the National Chengchi University Academic Hub,as well as draws several research directions that can be further investigated in the future.Overall,this research used users’ behavior analysis scheme to understand the behavior characteristics and behavior transfer patterns of users in general,users in different regions,and users with high or low download times,which will contribute to understanding how users operate the National Chengchi University Academic Hub and how to optimize the National Chengchi University Academic Hub. en_US dc.description.tableofcontents 目次 i表目次 iii圖目次 iv第一章 緒論 1第一節 研究背景與動機 1第二節 研究目的 6第三節 研究問題 6第四節 研究範圍與限制 7第五節 名詞解釋 8第二章 文獻探討 9第一節 機構典藏與學術集成平台 9第二節 使用者行為歷程記錄之常見工具 12第三節 網站使用者行為分析 14第三章 研究方法 16第一節 研究架構 16第二節 研究方法 18第三節 研究對象 19第四節 研究工具 20第五節 行為編碼 37第六節 資料蒐集、整理與分析 46第七節 研究實施步驟 49第四章 實驗結果與分析 51第一節 整體使用者行為特徵分析 51第二節 不同地區的使用者行為特徵分析 53第三節 下載論文次數高低使用者行為特徵和轉移模式分析 64第四節 綜合討論 78第五章 結論與建議 87第一節 結論 87第二節 政大學術集成平台平台之優化建議 89第三節 未來研究方向 92參考文獻 93 zh_TW dc.format.extent 2109941 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0107155024 en_US dc.subject (關鍵詞) 機構典藏 zh_TW dc.subject (關鍵詞) 學術集成平台 zh_TW dc.subject (關鍵詞) 學者庫 zh_TW dc.subject (關鍵詞) 行為分析 zh_TW dc.subject (關鍵詞) 探索性資料分析 zh_TW dc.subject (關鍵詞) 滯後序列分析 zh_TW dc.subject (關鍵詞) Institutional repository en_US dc.subject (關鍵詞) Academic Hub en_US dc.subject (關鍵詞) Scholar Hub en_US dc.subject (關鍵詞) User behavior analysis en_US dc.subject (關鍵詞) Exploratory data analysis en_US dc.subject (關鍵詞) Lag sequence analysis en_US dc.title (題名) 網站使用者行為分析—以國立政治大學學術集成平台為例 zh_TW dc.title (題名) Analysis of Website User Behavior: A Case Study of National Chengchi University Academic Hub en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 國立政治大學圖書館(2019)。「Post-Print作者版本」大募集。檢自 http://www.lib.nccu.edu.tw/zh_tw/announcement/-Post-Print%E4%BD%9C%E8%80%85%E7%89%88%E6%9C%AC-%E5%A4%A7%E5%8B%9F%E9%9B%86-47784871陳志銘(2019)。學習微歷程大數據分析與應用。陳勇汀(2017)。行為順序檢定：滯後序列分析 / Behavior Analysis: Lag Sequential Analysis。檢自https://pulipulichen.github.io/HTML-Lag-Sequential-Analysis/黃婷婷、陳舜昌、高慧琴(2017)。大學圖書館OPAC系統用戶信息搜尋路徑的可視化分析。大學圖書館學報，35(1)，63-71。doi:10.16603/j.issn1002-1027.2017.01.009孫賢潔(2017)。行動政府網頁設計準則影響資訊尋求之研究(未出版之碩士論文)。國立政治大學，臺北市。Adeyemi, J. A., Appah, D., Akinlade, O., & Bribena, I. (2017). The Nigerian institutional repositories: Opportunities and barriers. Academia Journal of Educational Research, 5(10), 9.ADL Net.(2015).Experience xAPI Overview.Retrieved from https://adlnet.gov/projects/xapi/Asadi, S., Abdullah, R., Yah, Y., & Nazir, S. (2019). Understanding institutional repository in higher learning institutions: A systematic literature review and directions for future research. IEEE ACCESS, 7, 35242-35263. doi:10.1109/ACCESS.2019.2897729Aschenbrenner, A., Blanke, T., Flanders, D., Hedges, M. and O’Steen, B. (2008), “The future of repositories?”, D-Lib Magazine, Vol. 14 Nos 11/12, doi: 10.1045/november2008-aschenbrenner.Bakeman, R., & Gottman, J. M. (1997). Observing interaction: An introduction to sequential analysis, 2nd ed. New York: Cambridge University Press. doi:10.1017/CBO9780511527685Bankier, J.-G., & Perciali, I. (2008). The institutional repository rediscovered: What can a university do for open access publishing? Serials Review, 34(1), 21-26. http://doi.org/10.1016/j.serrev.2007.12.003Behrooz, O. T., Sihem, A. Y., & Termier, A. (2015). Interactive user group analysis. In Proceedings of the 24th ACM International on Conference on Information and Knowledge Management (pp. 403–412). New York, NY, USA: ACM. doi:10.1145/2806416.2806519Brusino, J.(2012).The Next Generation of SCORM: A Q&A; with Aaron Silvers.Retrieved from:https://web.archive.org/web/20140822192026/http://www.astd.org/Publications/Newsletters/Learning-Circuits/Learning-Circuits-Archives/2012/06/The-Next-Generation-of-SCORM-a-Q-and-a-with-Aaron-SilversChristian, G. E. (2009). Issues and challenges to the development of Open Access institutional repositories in academic and research institutions in nigeria. SSRN Electronic Journal. doi:10.2139/ssrn.1323387Croll.A., Power.C.(2009).Complete web monitoring.O’Reilly Media Inc., Sebastopol .Cutroni, J. (2010). Google Analytics: Understanding Visitor Behavior.Davis, P.M. and Connolly, M.J.L. (2007), “Institutional repositories: evaluating the reasons for non-use of Cornell university’s installation of DSpace”, D-lib Magazine, Vol. 13 Nos 3/4, available at:www.dlib.org/dlib/march07/davis/03davis.htmlFarney, T. A. (2011). Click analytics: Visualizing website use data. Information Technology and Libraries, 30(3). doi:10.6017/ital.v30i3.1771Fenner M. (2014) Altmetrics and other novel measures for scientific impact. In: Bartling S., Friesike S. (eds) Opening Science. Springer, Cham.Giesecke, J. (2011). Institutional repositories: Keys to success. Journal of Library Administration, 51, 529-542. doi:10.1080/01930826.2011.589340Gvianishvili, G., Le Meur, J. Y., Šimko, T., Caffaro, J., Marian, L., Kaplun, S., et al. (2010). Capturing and analyzing user behavior in large digital libraries, (CERN-IT-2010-002), 8 p. doi:oai:cds.cern.ch:1295600Hagstrom, W. O. (1971). Inputs, Outputs, and the Prestige of University Science Department. Sociology of Education, 44(4), 375. doi:10.2307/2112029IBM(2013).Oh behave! How behavioral analytics fuels more personalized marketing.Enterprise Marketing Management.Jansen, B. J., & Spink, A. (2006). How are we searching the World Wide Web? A comparison of nine search engine transaction logs. Information Processing & Management, 42(1), 248-263. doi:10.1016/j.ipm.2004.10.007Jantz, R. C., & Wilson, M. C. (2008). Institutional repositories: Faculty deposits, marketing, and the reform of scholarly communication. The Journal of Academic Librarianship, 34(3), 186-195. doi:10.1016/j.acalib.2008.03.014Jiang, T., Chi, Y., & Gao, H. (2017). A clickstream data analysis of Chinese academic library OPAC users’ information behavior. Library & Information Science Research, 39(3), 213-223. doi:10.1016/j.lisr.2017.07.004Lim, K. C. (2015). Case studies of xAPI applications to E-Learning, 12.Lynch, C. (2003). Institutional repositories: Essential infrastructure for scholarship in the digital age. Portal Libraries and the Academy, 3, 327-336. doi:10.1353/pla.2003.0039Mödritscher, F., Neumann, G., & Brauer, C. (2012). Comparing LMS usage behavior of mobile and web users. In 2012 IEEE 12th International Conference on Advanced Learning Technologies (pp. 650-651). doi:10.1109/ICALT.2012.42Pakkala, H., Presser, K., & Christensen, T. (2012). Using Google Analytics to measure visitor statistics: The case of food composition websites. International Journal of Information Management, 32(6), 504-512. doi:10.1016/j.ijinfomgt.2012.04.008Palmer, D. T. (n.d.). The HKU Scholars Hub. Unlocking Collective Intelligence, 14.Palmer, D., & Liu, E. (2013). 從學術典藏庫(IR)到當前科研資訊系統(CRIS) – 如何和為何？ Retrieved from http://hdl.handle.net/10722/191176Palmer, D., & Liu, E. (2015). The HKU Scholars Hub - Beyond an institutional repository. Journal of Academic Libraries. Retrieved from http://hdl.handle.net/10722/219961Pinfield, S., Salter, J., Bath, P. A., Hubbard, B., Millington, P., Anders, J. H. S., et al. (2014). Open-access repositories worldwide, 2005-2012: Past growth, current characteristics, and future possibilities: Open-Access Repositories Worldwide, 2005-2012: Past Growth, Current Characteristics, and Future Possibilities. Journal of the Association for Information Science and Technology, 65(12), 2404-2421. doi:10.1002/asi.23131Plaza, B. (2009). Monitoring web traffic source effectiveness with Google Analytics. Aslib Proceedings, 61(5), 474-482. doi:10.1108/00012530910989625Prabhakar, S., & Rani, S. V. (2018). Benefits and perspectives of institutional repositories in academic libraries. Scholarly Research Journal for Humanity Science & English Language, 5. doi:10.21922/srjhsel.v5i25.10948.Russell, R., & Day, M. (2010). Institutional repository interaction with research users: A Review of Current Practice. New Review of Academic Librarianship, 16(sup1), 116-131. doi:10.1080/13614533.2010.509996Rybinski, H., Skonieczny, L., Koperwas, J., Struk, W., Stepniak, J., & Kubrak, W. (2017). Integrating IR with CRIS – a novel researcher-centric approach. Program, 51(3), 298-321. doi:10.1108/PROG-04-2017-0026Salo, D. (2008), “Innkeeper at the roach motel”, Library Trends, Vol. 57 No. 2, pp. 98-123.Tabatha, A., Farney, Nina, & McHale. (2013). Introducing Google Analytics for libraries. Library Technology Reports.Tasy, M. Y., & Chen, C. M. (2017). Developing an Academic Hub with data synchronization, altmetrics display and added value information for promoting scholarly communication performance. In IFLA Conference Proceedings, IFLA. Retrieved from http://nccur.lib.nccu.edu.tw/handle/140.119/121176Thelwall, M., Haustein, S., Larivière, V., & Sugimoto, C. R. (2013). Do altmetrics work? Twitter and ten other social web services. PLoS ONE, 8(5), e64841. doi:10.1371/journal.pone.0064841Tukey, John W. (1977). Exploratory data analysis. Pearson. ISBN 978-0201076165.Velleman, P. F., & Hoaglin, D. C. (2012). Exploratory data analysis. In H. Cooper, P. M. Camic, D. L. Long, A. T. Panter, D. Rindskopf, & K. J. Sher (Eds.), APA handbooks in psychology®. APA handbook of research methods in psychology, Vol. 3. Data analysis and research publication (pp. 51-70). Washington, DC, US: American Psychological Association.W3Techs.(2019).Usage of traffic analysis tools for websites.Retrieved from https://w3techs.com/technologies/overview/traffic_analysisWong, E. Y. (2017). Association of college and research libraries scholarly communication toolkit.Technical Services Quarterly, 34(4), 430-431.doi:10.1080/07317131.2017.1355131Wu, Y. L., Tao, Y. H., & YangJ, P. C. (2008). Using UTAUT to explore the behavior of 3G mobile communication users. In IEEM 2007: 2007 IEEE International Conference on Industrial Engineering and Engineering Management (pp. 199-203). doi:10.1109/IEEM.2007.4419179Yu, C. H. (1977). Exploratory data analysis. Methods, 2, 131-160. zh_TW dc.identifier.doi (DOI) 10.6814/NCCU202100412 en_US
