Identifying Quality Factors for Self-Tracking Solutions: A Systematic Literature Review

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dc.contributor.authorSchiller, Barbara
dc.contributor.authorBrogt, Tobias
dc.contributor.authorSchuler, J. Peter M.
dc.contributor.authorStrobel , Gero
dc.contributor.authorEicker, Stefan
dc.date.accessioned2020-01-04T07:55:25Z
dc.date.available2020-01-04T07:55:25Z
dc.date.issued2020-01-07
dc.description.abstractSelf-tracking solutions have become globally widespread, as they promise numerous advantages (e.g. improving health) to their users. Despite their benefits, such solutions are often abandoned due to quality issues. This phenomenon can also be observed for digitized products in general. As self-tracking solutions are hybrid products, combining digital and physical components, traditional domain-independent and abstract quality models like the prominent ISO 25000 standard seem to not cover quality in an appropriate way. We address these issues by answering the research question of which factors affect quality perceptions of different stakeholder groups when interacting in a wearable ecosystem. We use a systematic literature review based on a research protocol to identify and analyze 98 quality-influencing factors from 19 studies that we cluster in a map. The identified factors are compared to the ISO 25000 standard, showing that certain factors like hedonic motivation are unconsidered thoroughly in the existing standard.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2020.452
dc.identifier.isbn978-0-9981331-3-3
dc.identifier.urihttp://hdl.handle.net/10125/64194
dc.language.isoeng
dc.relation.ispartofProceedings of the 53rd Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectPersonal Health and Wellness Management with Technologies
dc.subjectinternet of things
dc.subjectiso 25000
dc.subjectquality
dc.subjectself-tracking
dc.subjectstructured literature review
dc.subjectwearable
dc.titleIdentifying Quality Factors for Self-Tracking Solutions: A Systematic Literature Review
dc.typeConference Paper
dc.type.dcmiText

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