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dc.contributor.advisorErdelez, Sanda, 1960-eng
dc.contributor.authorPaul, Aninditaeng
dc.date.issued2009eng
dc.date.submitted2009 Falleng
dc.descriptionThe entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file.eng
dc.descriptionTitle from PDF of title page (University of Missouri--Columbia, viewed on January 27, 2011).eng
dc.descriptionThesis advisor: Dr. Sanda Erdelez.eng
dc.descriptionVita.eng
dc.descriptionPh. D. University of Missouri--Columbia 2009.eng
dc.description.abstractAcademic libraries need to evaluate their electronic services in order to ensure their users' satisfaction. Libraries have been using evidence based evaluation traditionally. These practices have their imitations as they are time consuming and rely on outdated literature. Human Information Behavior studies offer a rich literature of users' behavior that could provide evidence of usage; nevertheless HIB studies are centered on smaller sample and hence lack generalization. Web analytics can address the gap in library service evaluation and HIB studies by providing quick access to aggregate information on real users' data collected unobtrusively. This study was conducted in an academic library setting. Two topics on the use of analytics for library decision-making and generalizing in HIB studies were addressed. The Library's web usability group was interviewed and their Google Analytics data were reviewed. Qualitative analyses were conducted on data obtained from the interview and Google analytics. There were concrete findings on the use of web analytics for Library decision-making that indicated its utility for enhancing the Library's online services and for improving navigation. However, there were noteworthy factors that could affect decision-making indirectly - the respondents' curiosity of users' behavior, the Library management practices, could influence decision-making in the Library along the way. Visitor trending data in Google Analytics further provided important aspects of the online users' behavior. Graphs indicated irregular patterns in users' behavior over a period of a semester. Further instances illustrated the differences in users behavior were based on their choice of sources. Visitors' technology preferences indicated factors that could influence users' information seeking. Finally, analytics can provide information on the Library's primary resources used.eng
dc.description.bibrefIncludes bibliographical references.eng
dc.format.extentxiv, 208 pageseng
dc.identifier.oclc698485106eng
dc.identifier.urihttps://hdl.handle.net/10355/9860
dc.identifier.urihttps://doi.org/10.32469/10355/9860eng
dc.languageEnglisheng
dc.publisherUniversity of Missouri--Columbiaeng
dc.relation.ispartofcommunityUniversity of Missouri--Columbia. Graduate School. Theses and Dissertationseng
dc.rightsOpenAccess.eng
dc.rights.licenseThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License.
dc.subject.lcshGoogle Analyticseng
dc.subject.lcshWeb usage miningeng
dc.subject.lcshHuman-computer interactioneng
dc.subject.lcshLibraries -- User satisfactioneng
dc.subject.lcshAcademic libraries -- Computer network resourceseng
dc.subject.lcshInternet users -- Statistics -- Data processingeng
dc.subject.lcshLibrary users -- Statistics -- Dataprocessingeng
dc.titleThe use of web analytics on an academic library websiteeng
dc.typeThesiseng
thesis.degree.disciplineInformation science and learning technologies (MU)eng
thesis.degree.grantorUniversity of Missouri--Columbiaeng
thesis.degree.levelDoctoraleng
thesis.degree.namePh. D.eng


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