Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/6987
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dc.contributorDepartment of Management and Marketing-
dc.creatorEckhardt, A-
dc.creatorMaier, C-
dc.creatorHsieh, JJPA-
dc.creatorChuk, T-
dc.creatorChan, AB-
dc.creatorHsiao, JH-
dc.creatorBuettner, R-
dc.date.accessioned2014-12-11T08:29:17Z-
dc.date.available2014-12-11T08:29:17Z-
dc.identifier.isbn978-162993426-6-
dc.identifier.urihttp://hdl.handle.net/10397/6987-
dc.language.isoenen_US
dc.publisherAssociation for Information Systems (AIS)en_US
dc.rightsExcerpted from Proceedings of the 34th International Conference on Information Systems (ICIS) by Eckhardt, A., Maier, C., Hsieh, JJ, Chuk, T., Chan, A., Hsiao, J. & Buettner R., © 2013. Used with permission from Association for Information Systems, Atlanta, GA; 404-413-7444; www.aisnet.org. All rights reserved.en_US
dc.subjectIS useen_US
dc.subjectUser behavioren_US
dc.subjectLaboratory experimenten_US
dc.subjectExperienceen_US
dc.subjectPressure to performen_US
dc.subjectEye-trackingen_US
dc.subjectGaussian mixture modelen_US
dc.titleObjective measures of IS usage behavior under conditions of experience and pressure using eye fixation dataen_US
dc.typeConference Paperen_US
dc.identifier.spage2715-
dc.identifier.epage2731-
dcterms.abstractThe core objective of this study is to understand individuals IS usage by going beyond the traditional subjective self-reported and objective system-log measures to unveil the delicate process through which users interact with IS. In this study, we conducted a laboratory experiment to capture users’ eye movement and, more importantly, applied a novel methodology that uses the Gaussian mixture model (GMM) to analyze the gathered physiological data. We also examine how performance pressure and prior usage experience of the investigative system affect IS usage patterns. Our results suggest that experienced and pressured users demonstrate more efficient and focused usage patterns than inexperienced and non-pressured ones, respectively. Our findings constitute an important advancement in the IS use literature. The proposed statistical approach for analyzing eye-movement data is a critical methodological contribution to the emerging research that uses eye-tracking technology for investigation.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationProceedings of the 34th International Conference on Information Systems (ICIS), December 16-18, 2013, Milan, Italy, p. 2715-2731-
dcterms.issued2013-
dc.identifier.scopus2-s2.0-84897788214-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_IR/PIRAen_US
dc.description.pubStatusPublisheden_US
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