Staying true to the data : a visual and quantitative approach to showcase coding rigour and theoretical saturation

dc.contributor.authorDoyer, Ilse
dc.contributor.authorAyomoh, Michael Kweneojo
dc.contributor.emaililse.doyer@up.ac.za
dc.date.accessioned2026-03-13T12:11:55Z
dc.date.available2026-03-13T12:11:55Z
dc.date.issued2025-06
dc.description.abstractThis paper describes a data-based and transparent approach that was followed during classic grounded theory data analysis to ensure rigor and theoretical saturation. Firstly, a visual approach was followed to ensure that the theory discovery stayed as close to the story told by the data set as possible, thus ensuring both rigor and accuracy. Secondly, process data in the form of a coding rate time study and theoretical contribution rate, were tracked to monitor theoretical saturation objectively. The presented approach offers a novel approach to showcasing classic grounded theory rigor during the data coding process, as well as a way to prove that theoretical saturation was reached. The approach presented in this paper thus provides grounded theory researchers with a way in which to both ensure and defend the rigor and accuracy of their research.
dc.description.departmentIndustrial and Systems Engineering
dc.description.librarianam2026
dc.description.sdgSDG-09: Industry, innovation and infrastructure
dc.description.urihttps://groundedtheoryreview.org/index.php/gtr
dc.identifier.citationDoyer, I. & Ayomoh, M.K. 2025, 'Staying true to the data : a visual and quantitative approach to showcase coding rigour and theoretical saturation', Grounded Theory Review, vol. 24, no. 1, pp. 80-98.
dc.identifier.issn1556-1550
dc.identifier.urihttp://hdl.handle.net/2263/108970
dc.language.isoen
dc.publisherInstitute for Research and Theory Methodologies
dc.rights© Ilse Doyer, Michael K. Ayomoh, 2025.
dc.subjectClassic grounded theory
dc.subjectTheoretical saturation
dc.subjectSample size
dc.subjectTime study
dc.subjectData-based approach
dc.subjectData analysis
dc.titleStaying true to the data : a visual and quantitative approach to showcase coding rigour and theoretical saturation
dc.typeArticle

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